The share of the remaining risk factors in the discount rate is slight: the component of operating expenses approximates 0.55% and the project lifetime is at 0.2%. When it comes to nominal values, the column would have to be increased by the rate of inflation, which would offer a nominal rate of 10.03%; a foreign investor would also increase such rate by the portion of the country risk (here: 1.2% [28]), which would eventually result in a nominal rate of 11.3%.

#### **4. Discussion**

The paper gives the answer as to what is the composition of risk within a 7.65% real discount rate of portions for Polish onshore wind projects at the feasibility stage. Crucial risk components are capital costs, capacity factor, and electricity price.

The obtained results provide useful information for decision-makers with respect to making decisions in the area of wind power: the greatest attention should be paid to the thought-through participation in the RES auctions and careful assessments of capital expenditures. It also implies that reducing CAPEX uncertainty investors might significantly change RADR structure, reducing risk within a discount rate mainly to combination of energy price and capacity factor risks.

As we mentioned above, risk-adjusted discount rate of 7.65% (real) is selected only as a base—it will vary over time, with risk-free rates and beta updates. It can be served, however, as a guide to make a ranking of different investment alternatives.

The concept that has been developed for the risk components analysis of a cost of equity at the feasibility study stage can be used for the evaluation of projects at other development stages—e.g., in reference to the results obtained, the analysis of the scope of the discount rate at the project's operating stage (5.5%) can be performed.

Discount rate in amount of 5.5% has been selected arbitrarily, taking into account discussion with energy companies—at this stage of the project development risk is significantly lower than at the feasibility stage. It can be assumed that at this level of project development the risk of capital expenses will resolve, whereas the assessment accuracy (*UnCrnty*) of the capacity factor, the price of electricity, the operating expenses, and the project lifetime will improve by half—the risk portions of these components will be reduced then as follows (Figure 4):

1. capacity factor—1.28%;

altogether, with the risk-free rate, it amounts to 5.5%.

Then, the nominal rate will be 7.88% or, including the country risk—9.1%.

Similar analysis can be made for projects in scoping and pre-feasibility studies. In reference to the analogous analyses carried out for traditional coal projects [23], it becomes clear that the risk factors within a similar CoE/RADR are distributed differently in the case of traditional coal technology, the dominant component of specific risk within cost of equity was the electricity price (2.97%), which results from the fact that it is subject to market competition. Another significant portion is the price of CO2 emission allowances (0.92%): the factor which does not occur in wind energy. The disparity of components of capital expenses is interesting: the risk portion (0.22%) related to this factor in reference to its weight in wind energy (1.71%) is slight, which is related to the amount, the technological advancement of capital assets and their significance for the efficiency of wind technology. Future research might involve gathering data that could help companies to estimate in detail the risk level of an individual project at various stages of a project. A very interesting challenge is also conducting similar studies for other renewable energy technologies.

#### **5. Conclusions**

Wind energy in Poland, in spite of the temporary inhibition of its development, has a significant growth potential, which may turn out to be invaluable when taking actions aimed at the transition to the modern low-carbon economy into account. One of the key issues that the investors have to face is the risk of the technology. Investors who put money into energy projects are expecting an adequately high interest rate, which would allow them to compensate for the minimum acceptable real rate of return from the market and the project's specific risk. That is reflected in the adopted discount rate, where the range of specific risk related to the technology used. The paper identifies key risk components within the cost of equity of onshore wind projects at the feasibility level.

In answering these questions, a decision was made to estimate the value of such a rate, and subsequently to present it in a form accessible for further research. It was decided that the analysis of the components of the discount rate is facilitated by the approach focusing exclusively on the cost of equity (risk-adjusted discount rate, RADR) after-tax. This rate reflects the real expectations of investors with respect to the project risk. It accounts for the risk-free discount rate, the project-specific risk and—depending on the purposes of the research—the inflation rate and the country risk. The analysis—assuming 100% equity in

project financing—allows for concluding that the assessment refers to the inherent value of an energy project, not contaminated with the effects of benefits related to external financing.

To find out which onshore wind project parameters were the major factors of such risk, a relevant analysis of causes and effects was carried out, starting with the definition of risk understood as the product of uncertainty and consequences. Uncertainty was expressed as the assessment accuracy of key inputs, whereas consequence as the tangent of the slope of sensitivity curves of such variables (impact on changes in the IRR) on a spider diagram. Consequently, it was shown that the risk portions (real) in the cost of equity of onshore wind projects at the feasibility stage, in the amount of 7.65%, are as follows:

The analysis is supplemented by the assessment of risk portions within the rate characteristic for project's operating stage in the amount of 5.5%.

The research has some limits:

Further work in this respect is of significant utility value—more extensive knowledge about the structure of cost of equity will allow for adequate commencement and more rational management of projects, as well as better understanding of cash flow evaluations and efficient risk control.

**Author Contributions:** Conceptualization, P.W.S., K.Z., Z.D.-P., K.S.-W. and M.M.; Methodology, P.W.S. and K.Z.; Software, P.W.S. and K.Z.; Validation, P.W.S., K.Z., Z.D.-P., K.S.-W. and M.M.; Investigation, P.W.S., K.Z., Z.D.-P., K.S.-W. and M.M.; Resources, P.W.S. and M.M.; Data curation, P.W.S. and M.M.; Writing—original draft preparation, P.W.S., Z.D.-P. and K.S.-W.; Writing—review and editing, P.W.S., K.Z. and M.M.; Visualization, P.W.S. and M.M.; Supervision, P.W.S., K.Z., Z.D.-P. and K.S.-W. All authors have read and agreed to the published version of the manuscript.

**Funding:** The project is funded under the program of the Minister of Science and Higher Education titled "Regional Initiative of Excellence" in 2019-2022, project number 018/RID/2018/19, the amount of funding PLN 10 788 423,16.

**Acknowledgments:** The work was carried out as part of the statutory activity of the Mineral and Energy Economy Research Institute, Polish Academy of Sciences and WSB University.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

### *Article* **The Impact of Fleet Electrification on Carbon Emissions: A Case Study from Poland**

**Krzysztof Zamasz 1,2, Jakub St ˛echły 1,3, Aleksandra Komorowska 4 and Przemysław Kaszy ´nski 4,\***

**Abstract:** Fleet electrification is one of the measures proposed for achieving climate neutrality in the coming years. The replacement of internal combustion engine vehicles with electric vehicles has a positive impact on carbon emission reduction in some countries. However, in countries highly dependent on fossil fuels, such a possibility requires examination with respect to the means of electricity generation and fuel mix used in their power systems. One such country is Poland, selected as an example of an economy strongly dependent on fossil fuels. The main objective of this paper is to investigate the impact of fleet electrification of an individual company located in Poland on the reduction of carbon emissions. The concept and calculations are based on historical data on the single-year mileage and fuel consumption of 619 cars used by this company. Even though the Polish power system is based on fossil fuels, fleet electrification could contribute to a reduction in carbon emissions of 24%. The decrease in operational costs by EUR 370 thousand/year is also significant. Apart from environmental and economic impacts, this paper provides valuable findings on the difference between catalogue and real-driving data application in the various analyses. With respect to Polish fuel mix in 2019, the application of data published by car producers shows that fleet electrification would increase carbon emissions by 14% in this company. This means that depending on the initial assumptions, different conclusions can be drawn by policymakers, regulatory bodies, academics, or other groups of interest.

**Keywords:** electromobility; electric vehicle; carbon emissions; fleet electrification; sustainable mobility; sustainable development; fleet management; energy mix

#### **1. Introduction**

Electrification of transport is one of the key pathways towards energy transition [1]. Electromobility is also indicated as one of the solutions to achieving carbon neutrality in the European Union by 2050 [2]. However, the real impact of the electrification of transport on carbon emissions reduction is strongly dependent on the fuel mix of a given power system. Consequently, in countries where electricity is still mainly produced in coal-fired power plants, the impact of electrification is difficult to assess.

In the year 2019 in Poland, the total installed capacity in the power system was 46.8 GW, out of which, coal or gas-fired generation units stood for 74.3% (23.2 GW of hard coal-fired power plants, 8.4 GW of lignite-fired power plants, and 2.8 GW of natural gas-fired units). Electricity produced in these power plants amounted to 131.8 TWh (83.0% of total electricity production in 2019), of which 78.2 TWh was produced in hard coal-fired power plants, 41.5 TWh in lignite-fired power plants, and 12.1 TWh in natural gas-fired units [3]. The structure of electricity production in 2019 is shown in Figure 1. Additionally, because of

**Citation:** Zamasz, K.; St ˛echły, J.; Komorowska, A.; Kaszy ´nski, P. The Impact of Fleet Electrification on Carbon Emissions: A Case Study from Poland. *Energies* **2021**, *14*, 6595. https://doi.org/10.3390/en14206595

Academic Editor: Grzegorz Karo ´n

Received: 14 September 2021 Accepted: 11 October 2021 Published: 13 October 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

the introduction of the capacity market, changes in electricity production structure are not expected to happen in the coming years [4–6].

**Figure 1.** Electricity production in Poland in 2019.

#### *1.1. Literature Review*

Ref. [7] indicates that growth in electric vehicles leads to increased carbon emissions if electricity comes from hard coal-fired power plants. Studies conducted on the Chinese power system show that the indirect carbon emissions from BEVs are higher than from ICEVs (internal combustion engine vehicles) [8,9]. This issue is also presented in Ref. [10], where authors pointed out that indirect emissions from BEVs can be higher by 2.55–5.64 kg CO2/day when compared to ICEVs in Poland. Ref. [11] provides the results of carbon emission reduction at the national scale as a function of fuel and electricity consumption under various scenarios of carbon emission factors in Poland.

The existing literature refers to large-scale issues and presents calculations for catalogue data only. The literature review indicates no studies based on actual data on fuel consumption and carbon emissions conducted for an individual company undergoing decarbonisation. Ref. [12] presents a fleet electrification example of a Brazilian taxi company, but is irrelevant for countries with a high share of fossil fuels in power systems.

Electromobility in Poland is a subject analysed in several papers and reports, and the number of studies is growing. None of these papers provides findings on carbon emissions reduction from the perspective of an individual company. Ref. [13] presents multiple aspects of electromobility introduction for one company located in Poland. Ref. [14] provides a general framework for the electrification of public transport and its environmental impact; they mainly focus on the current status of ICEV replacement instead of the quantitative reduction of carbon emissions. Ref. [15] presents only the economic consequences of public fleet electrification.

#### *1.2. Study Contributions*

This paper was inspired by the study conducted in Ref. [10], which presents an analysis of the replacement of nine ICEVs—the findings indicating that BEVs can provide even higher carbon emissions than petrol and diesel vehicles in countries with a high share of electricity produced in coal-fired power plants. The main objective of this study is to develop a method that could be applied to a company located in Poland and simulate the replacement of 619 ICEVs; it compares direct emissions from ICEVs and indirect emissions from BEVs. Emissions calculations for BEVs reflect the fuel mix of the Polish power system. We believe that this subject requires attention because company fleets are a substantial part of each country's vehicle base. Currently, companies often make decisions to try to improve their image as being environmentally friendly. We also believe that these findings will support decision makers in similar companies in their ICEV replacement process. If a

positive net impact of fleet electrification on emissions is confirmed, the question of fleet conversion to BEVs (battery electric vehicles) comes down to the total cost of ownership only.

This paper also contributes to the existing literature by depicting the differences between fuel consumption and carbon emissions under real-world conditions, compared to the information provided by car producers.

Section 1 of this paper introduces the subject and explains how this paper contributes to the field. In Section 2 the methods and formulas for calculations are described. Section 3 of this paper presents the input data and numerical simulations; it also involves a discussion of the results of the study. Conclusions are presented in Section 4.

#### **2. Materials and Methods**

This paper aims to investigate the impact of fleet electrification on carbon emissions reduction in one company running its business in Poland. This company has 19 subsidiaries, and it operates mainly in the service and utility industry with diverse business profiles (among others, waste management, electricity, and heat production). To investigate the impact of fleet electrification, data from these subsidiaries (that altogether operated 619 cars fuelled by petrol or diesel) were collected and analysed.

The vehicles, which are used by the company, have been divided into six main categories (Table 1) representing the entire fleet, taking into consideration the variety of their applications. These categories include small (class A), medium (class B), and large (class C) passenger cars and SUVs. The remaining categories are cargo vans and commercial medium vehicles. The vehicles from the cargo vans category are intended for service activities, mostly within urban areas. The commercial medium vehicles are also intended for use predominantly in urban areas. Type of fuel is also provided as another distinguishing factor, namely petrol or diesel. The most numerous categories are the cargo vans—197 vehicles (of which 163 are diesel and 34 petrol), commercial medium cars—139 vehicles (all diesel), and B class passenger cars—98 vehicles (of which 35 are diesel and 63 petrol).

**Table 1.** Specification of ICE vehicles.

1 According to information published by producers. Based on: [16,17].

Table 1 shows the summary of specifications of ICE vehicles used in the company. Three hundred and twenty-one cars are chosen as representative cars, for which complete data on the total volume of fuel purchased were available over the analysed period. Based

on the catalogue data of these vehicles, fuel consumption and carbon emissions per km were calculated. The ranges of results are also presented in this table.

#### *2.1. Internal Combustion Engine Vehicles*

In order to calculate the carbon emissions of each category of cars *g* with internal combustion engines, the average fuel consumption for each representative car per 100 km is required. Fuel consumption *FCg*, *rg*, *f* of representative car *rg* of group *g* and fuel *f* per 100 km in a period analysed is determined by Equation (1):

$$\bigwedge\_{\mathfrak{g}\in\mathcal{G}}\bigwedge\_{r\mathfrak{g}\in RG}\bigwedge\_{f\in F}\textup{FC}\_{\mathfrak{g},r\mathfrak{g},f} = \frac{\textup{Fuel}\textup{Purchase}\_{\mathfrak{g},r\mathfrak{g},f}}{\textup{CM}\_{\mathfrak{g},r\mathfrak{g},f}} \cdot 100\tag{1}$$

where *FuelPurchaseg*,*rg*, *f* means the total volume of fuel *f* purchased for representative car *rg* of group *g*, and *CMg*,*rg*, *f* is the total mileage of each representative vehicle considered.

Fuel consumption of a representative car of a group *g* is applied to Equation (2) to calculate the weighted average fuel consumption of each group *AFCg*, *f* . To this end, the sum of the products of fuel consumption *FCg*, *rg*, *f* for representative car *rg* of a group *g* and fuel *f* per 100 km and weight factors *wg*,*rg*, *f* , are divided by the total number of vehicles in the group *g* and fuel *f* of the same type as the representatives *TRGNg*, *f* = ∑ *rg wg*,*rg*, *f* :

$$\bigwedge\_{\mathfrak{g}\in G} \bigwedge\_{f\in F} AF\mathbb{C}\_{\mathfrak{g},f} = \frac{\sum\_{\mathfrak{r}\mathfrak{g}} \left( FC\_{\mathfrak{g},r\mathfrak{g},f} \cdot w\_{\mathfrak{g},r\mathfrak{g},f} \right)}{TRGN\_{\mathfrak{g},f}} \tag{2}$$

where *wg*,*rg*, *f* , means the number of vehicles in a group *g* with fuel *f* of the same type as the representative car model selected for each group *g* and fuel *f* .

Carbon emissions for representative car *rg* of a group *g* with fuel *f* over an analysed period is given in Equation (3). The average carbon emission factor in a group *g* with fuel *f* is calculated as given in Equation (4). The sum of the products of carbon emission factor *CO*2*ICEg*,*rg*, *f* for a representative car *rg* of a group *g* with fuel *f* and weight factors *wg*,*rg*, *f* , is divided by the total number of vehicles in the group *g* with fuel *f* of the same type as the representatives *TRGNg*, *f* = ∑ *rg wg*,*rg*, *f* :

$$\bigwedge\_{\mathfrak{g}\in\mathcal{G}} \bigwedge\_{r\mathfrak{g}\in RG} \bigwedge\_{f\in F} \text{CO2}\,\text{ICE}\_{\mathfrak{g}\,\,r\mathfrak{g},f} = \text{FC}\_{\mathfrak{g}\,\,r\mathfrak{g},f} \cdot \text{CO2}\,\text{EF}\_f \cdot 10 \tag{3}$$

$$\bigwedge\_{\mathfrak{g}\in\mathcal{G}}\bigwedge\_{f\in F}A\,\mathrm{CO2}\,\mathrm{ICE}\_{\mathfrak{g},f} = \frac{\sum\_{\mathbf{r}\mathfrak{g}}\left(\mathrm{CO2}\,\mathrm{ICE}\_{\mathfrak{g},\mathbf{r}\mathfrak{g},f} \cdot w\_{\mathfrak{g},\mathbf{r}\mathfrak{g},f}\right)}{\mathrm{TRGN}\_{\mathfrak{g},f}}\tag{4}$$

where *CO*2*EFf* means carbon emission factor of fuel *f* .

Total average mileage *ACMTotg*, *f* for each group of cars *g* and fuel *f* is calculated as is shown in Equation (5):

$$\bigwedge\_{\mathfrak{g}\in\mathcal{G}}\bigwedge\_{f\in F} \text{ACMTot}\_{\mathfrak{g},f} = \text{FuelPur clause} \text{Tot}\_{\mathfrak{g},f} \cdot \frac{100}{\text{AFC}\_{\mathfrak{g},f}} \tag{5}$$

where *FuelPurchaseTotg*, *f* is the total volume of fuel *f* purchased by all cars in a group *g* over an analysed period.

Total carbon emission for a group *g* with fuel *f* over an analysed period is given in Equation (6). It is a product of the total average mileage for a group of cars *g* with fuel *f* and average carbon emissions in a group of cars *g* with fuel *f* [18]. Consequently, the total emissions *CO*2*ICETot* in the entire fleet with internal combustion engines are determined by Equation (7):

$$\bigwedge\_{\mathfrak{g}\in\mathbb{G}} \bigwedge\_{f\in\mathcal{F}} \mathrm{CO2ICEot}\_{\mathbb{g},f} = A \mathrm{CMTot}\_{\mathbb{g},f} \cdot A \mathrm{CO2ICE}\_{\mathbb{g},f} \cdot 10^{-6} \tag{6}$$

$$CO2ICE\text{ot} = \sum\_{\mathbb{g},f} CO2ICE\text{ot}\_{\mathbb{g},f} \tag{7}$$

#### *2.2. Battery Electric Vehicles*

In this paper, the authors assume that each car with an internal combustion engine is replaced with a battery electric vehicle. As a result, to calculate the carbon emission factor of the assigned electric vehicle to each group of cars *g* with fuel *f* , the electricity consumption and CO2 emission intensity of electricity generation at the national level are considered. The formula is presented in Equation (8):

$$\bigwedge\_{\mathfrak{g}\in\mathcal{G}}\bigwedge\_{f\in F}\mathcal{CO}2BEV\_{\mathfrak{g},f} = \frac{\mathcal{CO}2EmIntensity \cdot EC\_{\mathfrak{g},f}}{100} \tag{8}$$

where *CO*2*EmIntensity* means carbon emission intensity of electricity generation, and *ECg*, *f* is the electricity consumption of the assigned battery electric vehicle of a group of cars *g* with fuel *f* per 100 km.

Total carbon emissions for a group *g* with fuel *f* in an analysed period is given in Equation (9). The carbon emission factor of the assigned battery electric vehicle of each group of cars and the total average mileage for a group of cars *g* with fuel *f* in the analysed period are taken into account. Consequently, the total emissions in BEVs are determined by Equation (10):

$$\bigwedge\_{\emptyset \in \mathcal{G}} \bigwedge\_{f \in F} \text{TotCO2BEV}\_{\mathcal{g},f} = \text{CO2BEV}\_{\mathcal{g},f} \cdot \text{ACMTot}\_{\mathcal{g},f} \cdot 10^{-6} \tag{9}$$

$$\text{TotCO2BEV} = \sum\_{\mathbb{S},f} \text{TotCO2BEV}\_{\mathbb{S},f} \tag{10}$$

Electricity consumption in BEVs corresponding to each group of cars *g* with fuel f is also used to calculate total electricity consumption depending on the average mileage for each group *g* and fuel *f* , as is given in Equation (11). The study assumes fleet electrification at the level of 100%:

$$\bigwedge\_{\emptyset \in G} \bigwedge\_{f \in F} \text{TotEC}\_{\emptyset, f} = \frac{\text{ACMTot}\_{\emptyset, f} \cdot \text{EC}\_{\emptyset, f}}{100} \tag{11}$$

The total electricity consumption is used to calculate the total charging cost of electric vehicles corresponding to each group of cars *g* and fuel *f* , as is given in Equation (12):

$$\text{TotalChargingCost}\_{\%f} = 0.8 \cdot \text{TotEC}\_{\%f} \cdot \left(1 + \frac{\text{ACLoss}}{100}\right) \cdot \text{ACCcost} + 0.2 \cdot \text{TotEC}\_{\%f} \cdot \text{DCCost} \tag{12}$$

where *ACLoss* is the losses from AC charging, *ACCost* means the cost of electricity (for the AC charging), and *DCCost* is the charging service cost (for the DC charging).

Total cost of ownership (TCO) analysis has been conducted and compared between ICE vehicles and BEVs for two categories of cars (SUVs and B class). To this end, the following cost components were used in the analysis: cost of fuel or electricity, financial rate, and service rate.

#### *2.3. Case Study Assumptions*

The formulas presented in Section 2.2 were applied to the case study of a fleet of 619 ICE vehicles that were considered for replacement with battery electric cars in the coming years. Apart from economic reasons, the companies intended to reduce the carbon footprint of their business. That is why the impact of mobility on the group's carbon footprint and its potential reduction was of the utmost importance.

For the sake of representativeness of the results, a pre-covid period of one year between March 2019 and February 2020 was chosen. The analysis was conducted based on data on fuel consumption gathered from petrol retailers (fuel cards are the only form of fuel payments in the company). Additionally, since each employee is obliged to provide data on current mileage to the company's system with every fuel purchase, these data were also used in the study. The whole database constitutes fifty-nine thousand entries.

Due to the heterogeneity of the input data and their poor quality in some cases, concerning the number of kilometres travelled for business purposes, the data set was cleansed from obvious errors in the mileage reported by employees, non-fuel-related purchases at petrol stations, and empty entries. As previously mentioned, representative vehicles were chosen for each category, based on the number of vehicles of a given model in the category, the mileage, and continuity of usage over the analysed period. As a result, the analysis includes 22 vehicle models (two for each category), represented by 321 individual vehicles.

For each representative vehicle, average fuel consumption was calculated. The calculation was based on all available data for each representative car (not limited to the analysis period only). In order to estimate the real carbon emissions (g/km) for the representative cars, the tailpipe carbon emission factor for combustion of 1 dm3 petrol and diesel was used, at the level of 2.3 and 2.6, respectively [19]. In order to compare real carbon emissions, adequate for Polish weather conditions, an average of combined real data for cold weather (worst case based on −10 ◦C and use of heating) and mild weather (23 ◦C and no use of air conditioning) was considered.

The analysis assumed that each vehicle from the categories listed in Table 1 could be replaced with a specific electric car model. The parameters of these BEVs, primarily in terms of size and possible applications, were similar to ICE vehicles from the corresponding categories. Data for these electric vehicles, including their engine power, electricity consumption per 100 km, and driving range with a fully charged battery, are presented in Table 2.

**Table 2.** Specification of battery electric vehicles.

According to real-world data—except for cargo van and commercial medium categories for which no reliable real-world data was available, for which information published by the producer was used in this study. Based on: [20–25].

> One of the main assumptions regarding the impact analysis of fleet electrification on carbon emissions was the CO2 emission factor per unit of electricity production. Poland is an example of a country heavily dependent on fossil fuels—mainly hard coal and lignite. As a result, the CO2 emission factor for electricity available for the end-user (i.e., produced in thermal power plants, including electricity supplied by RES units and including transmission losses and balance differences) amounted to 719 kg CO2 per MWh in 2019 [26]. It was also one of the highest rates in the entire EU (Figure 2), which significantly influenced the final calculations of the possible fleet conversion effect.

> However, Poland is undergoing a transition process towards a low-emission economy and decarbonisation of the power system [27]. According to the new Energy Policy of

Poland until 2040 (EPP2040), in 2040, the assumed fuel mix of electricity generation (i.e., 27.9% coal, 17.0% gas, 13.6% nuclear, 39.5% renewables, and 2.0% others [28]) might result in a reduction in the carbon intensity of electricity generation, to the level of 378 kg CO2/MWh (own estimations).

**Figure 2.** Greenhouse gas emission intensity of electricity generation (as a CO2 equivalent) in EU countries in 2019. Source: own elaboration based on [29].

Another key assumption was that the entire fleet of ICE cars would be replaced with battery electric vehicles at the same time (100% conversion). Although the replacement of vehicles would be phased and spread over time, such an assumption allows one to calculate the maximum effects of fleet electrification. These findings are valuable from the perspective of company management because they provide the information needed to define or verify strategic goals.

As previously mentioned, in addition to investigating the impact of fleet electrification on CO2 emissions, the work also provides the results of potential savings related to the purchase of petrol or diesel (for ICE cars) and battery-charging costs (for BEVs). Information on fuel consumption costs for each ICE category was assumed based on historical data from petrol retailers and fuel cards of the company's employees. In the case of BEVs, a model for charging electric vehicles was defined as follows: 80% of total electricity consumption is covered from AC chargers and 20% from high-power DC chargers [30,31]. Electricity costs for AC chargers and total fees related to charging the vehicle at stations equipped with DC chargers are given in Table 3. It is also worth noting that the process of charging electric vehicle batteries is not without losses. Therefore, based on the data presented in Ref. [31], charging losses were assumed at the level of 10% to reflect losses between electric vehicle supply equipment (EVSE) and transformers. Taking into account the current policy of car dealers in Poland of providing mobile AC chargers (usually 3.7 kW or 11 kW) free of charge or for a symbolic fee, the focus was on carbon emissions rather than TCO, and considering the negligible cost of such a charger compared to the TCO of a vehicle, authors decided to exclude AC charger capital expenditure from the analysis.

**Table 3.** Charging cost of electric vehicles.

1 For DC chargers, total unit cost includes costs and margin of the charging station owner. Based on: [31,32].

#### **3. Results and Discussion**

This section presents and discusses the results obtained from the employment of the mathematical formulas to the case study of an individual company. The average total monthly fuel consumption is shown in Figure 3. The analysis indicates that the fleet consumes more than 52 thous. dm3 of fuel (18 thous. dm3 of petrol and 34 thous. dm3 of diesel) per month, corresponding to 135.7 Mg of CO2. What is also noticeable, is that the largest share in the total monthly fuel consumption (and consequently in the carbon emission) was from the diesel-fuelled cars: cargo vans (20.7%), commercial medium vehicles (18.2%), and passenger C class vehicles (13.2%). These categories were the most significant in the electrification of the company's fleet. Replacing these ICEV groups with BEVs would give the best results for decreasing emissions from fuel combustion (NOx, SOx, VOC, CO, and PM), which are responsible for the phenomenon of low-stack emissions.

**Figure 3.** Average monthly fuel consumption for each category of ICE fleet, thous. dm3.

#### *3.1. Fuel Consumption and Carbon Emissions*

As previously mentioned, two representative vehicles were chosen for each category (Table 1), taking into account the number of a given car model in each category. Then, vehicles were reviewed based on their mileage and continuity of mileage to find the most representative vehicles for a given category. Consequently, the fuel consumption of each group and level of carbon emissions was calculated and compared with the catalogue data published by the producers of the representatives considered. The results are presented in Figures 4 and 5, respectively.

**Figure 4.** Comparison of fuel consumption (dm3 per 100 km) of ICE cars—producers' data and fleet-specific measurements.

**Figure 5.** Comparison of carbon emissions (g CO2/km) of ICE and BEV cars—producers' data, fleet-specific measurements and real usage data.

> It can be noticed that real fuel consumption and carbon emission levels were higher across all categories in the case of ICE cars. Particularly:

#### *3.2. Carbon Emissions from BEVs in 2019 and 2040*

For each category (regardless of fuel type), a BEV analogue was assigned, chosen from car models currently available on the market. Due to the lack of reliable true usage data for commercial medium category emissions declared by producers, an increase of 20% was assumed.

As presented in Figure 5, for all categories, indirect BEV emission levels for the Polish energy mix of 2019 were higher than those declared by car producers and lower than actual emissions calculated for the category representatives. This is a significant finding, showing that for a power system which largely depends on fossil fuels, such as the Polish one, operational carbon emission levels for this particular fleet were in favour of BEVs back in 2019. A much greater effect could be obtained if the carbon intensity of the Polish power generation system was at the projected level for 2040 (47% reduction from 719 kg CO2/MWh as in 2019 to 378 kg CO2/MWh). Comparison of real data on carbon emission levels (in g CO2 per one kilometre) for BEV cars between the energy mixes in 2019 and 2040 is presented in Figure 6.

For each category, total carbon emission levels were calculated for the current ICE and the purely BEV fleet under two scenarios: First, the structure of electricity generation in 2019 was considered (Figure 1). Second, the assumptions published in the Energy Policy of Poland (EPP2040) regarding the energy mix for the year 2040 were taken into account [28].

**Figure 6.** Emission levels for BEVs for each category—comparison based on the carbon intensity of the Polish power sector: fuel mix in 2019 vs. fuel mix in 2040 (EPP2040).

The carbon intensity of each group of ICE vehicles and BEVs is presented in Figure 7. The total emissions from ICE vehicles amounted to 1628 Mg. Their replacement with battery electric vehicles caused a reduction by 24% (to the level of 1231 Mg). The results also indicated that the carbon emissions calculated for the energy mix of 2040 were lower by as much as 47.4% in comparison to 2019. Therefore, charging cars with electricity using a structure similar to 2040 would cause a carbon emission reduction of 60% (even with a 44.9% share of fossil fuels).

**Figure 7.** Comparison of total emission levels for ICE and BEV vehicle categories (Mg).

In Figures 8 and 9, a reduction in carbon emissions across categories is presented, along with emission reductions under the 2019 and 2040 Polish energy mix scenarios. It is perfectly justified to rely on a country's energy mix while looking at fleet electrification at the national scale. However, in the case of a given company or single BEV user, the individual structure of electricity consumption should be considered. Supposing that the company considers using solely renewable electricity to charge its cars at their premises, offsetting carbon emissions for home charging by employees and purchasing electricity and charging services from companies using renewable sources. In this case, the mobility decarbonisation goals could be achieved much earlier than presented in national commitments.

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**Figure 8.** Breakdown of total carbon emissions (Mg) across vehicle categories of the Polish carbon intensity of electricity generation as of 2019 and in 2040 (EPP2040).

**Figure 9.** Breakdown of emission reductions (%) for the Polish carbon intensity of electricity generation as of 2019 and in 2040 (EPP2040).

#### *3.3. Operational Costs and Savings*

Apart from the comparison of carbon emissions in ICE vehicles and BEVs, a simplified analysis of fuel/charging costs was conducted. The main findings for all vehicle groups are presented in Table 4. The results indicate that total fleet electrification would result in reduction of fuel costs by 50%, allowing the company to generate monthly savings, which could contribute to an increase in lease fees.

In addition to analysis of the savings from the perspective of groups, a rudimentary total cost of ownership (TCO) analysis was conducted. The TCO for two pairs of car categories (SUV and B class) were calculated in two scenarios: an average monthly mileage of 2000 km and the mileage for which break-even is reached. The cost of vehicle insurance was excluded from the analysis due to a lack of complete data. Therefore, it should be noted that due to the higher BEV value, insurance premiums are higher, and, consequently, the presented values are slightly biased in favour of BEVs. The same assumptions regarding charging structure and cost were made for emission level calculations. It is clearly

visible that the higher the monthly mileage is, the greater the use of the public charging infrastructure. Consequently, the generated savings will not be linear. For shorter ranges, almost all trips can be made using solely AC charging, limiting the cost. For the SUV category with a monthly mileage of 2000 km, electric vehicles were an economically viable solution, as presented in Table 5. Only below 600 km per month was the combustion model more profitable. In the case of B class vehicles, the situation was opposite—with a monthly mileage of 2000 km, the diesel representative was more economical, and the breakpoint occurred at a mileage of 3770 km per month, which is difficult to achieve in the majority of cases; this is depicted in Table 6.

**Table 4.** Operational costs and savings analysis for ICE to BEV conversion.

**Table 5.** TCO comparison for the SUV category.

**Table 6.** TCO comparison for the B segment category.

It can be noticed that TCO is highly dependent on average monthly mileage. Taking into account that the scope of this article is on CO2 emissions, it can be concluded that while planning a fleet transformation, a priority should be given to high-mileage cases within each category, which should provide benefits of both an environmental and economic nature.

#### *3.4. Catalogue Data vs. Real-World Driving Data*

The results of this study point out that there is a divergence in fuel consumption between (a) the catalogue data and (b) data collected from real-world driving (see Figure 10). The analysis conducted using producers' data indicated an increase in carbon emissions by 14% for the current fuel structure of the Polish power system. However, considering the data describing the historical mileage and fuel consumption of 619 cars, the results presented a reduction in carbon emission at the level of 24% for the same energy mix in the power system. Consequently, this paper confirms the existence of the fuel consumption gap that is discussed in detail in Ref. [33].

**Figure 10.** Differences between the impact of fleet electrification on carbon emissions using producers' data and case study results.

In the context of fuel/charging costs, as previously mentioned, fleet conversion resulted in a 50% reduction in fuel costs when real consumptions were compared to reference ICEVs and their BEV counterparts. As far as catalogue data are concerned, the difference was still in favour of BEVs, but it decreased to 30%. In case of no conversion of the fleet, the calculated savings achieved if ICE cars had consumed as producers had declared, reached 38% across all categories.

As a result, apart from the outcomes concerning carbon emission reduction and operational costs stemming from fleet electrification in an individual company, this work provides valuable findings on the divergence of the results depending on the method adopted. The selection of the different input data assumptions can cause different conclusions to be drawn. For instance, interest groups or lobbyists of ICE cars may use catalogue data in their analyses and provide completely different outcomes and findings than those presented here. Based on such analyses, fleet electrification in the company would cause an increase in carbon emissions. Therefore, the replacement of ICE vehicles with electric vehicles would be considered in the future with respect to forecasts of the fuel mix of the power system.

This is why decision-makers, and even policymakers or regulatory bodies, should rely on analysis based on real-driving data instead of catalogue data published on producers' websites.

#### **4. Conclusions**

The main aim of this paper was to investigate the potential of CO2 emission reduction related to company fleet electrification in Poland, a European Union country, which is

heavily dependent on fossil fuels for electricity generation. This paper also presents the results of the study of ICEV replacement with BEVs in a large international company. It provides valuable insights into the effects of this replacement on researchers, managers, and policymakers. These insights are valid not only in Poland but also in other countries with similar structures of power systems.

This paper also fills a research gap in the context of fleet electrification on a small scale using real-world data from a fleet of 619 vehicles operated across 19 subsidiaries of a resource management company located in Poland. The main conclusion is that even for a highly fossil fuel-dependant energy mix, indirect emissions for BEVs are lower than tailpipe emissions from ICE vehicles. The case study analysis shows that fleet electrification in the current fuel mix of the Polish power system (75% of electricity is still produced in coal-fired generation units, and 8% in natural gas-fired units) would decrease carbon emissions by 24%. These findings may support decision-making processes in companies when considering the replacement of ICE cars with electric vehicles due to environmental policies.

Case study analysis shows that fleet electrification also results in a decrease in operational costs; the annual expenditure on the purchase of electricity was EUR 370 thousand lower than on conventional fuel. Therefore, the replacement of combustion cars with electric ones may also generate financial savings. However, if the total cost of ownership (TCO) is analysed, the economic viability of electric vehicles is dependent on mileage. The TCO of SUVs is significantly lower for 2000 km per month but higher for mileage below 600 km. This is a consequence of the higher fraction of fixed costs. In the case of B class cars, the results are the opposite; the TCO of BEVs is lower at mileages over 3700 km when compared to ICEVs.

This study also provides a valuable insight into the implications of the methodological approaches used for similar analyses. Using the producers' data instead of real-world data produces entirely different results and different conclusions. The results indicate that using data published by producers gives an increase in carbon emissions of 14% instead of a decrease of 24%. This is why an appropriate method and input data assumptions are of the utmost importance in obtaining reliable outcomes.

Global companies perceive either moral obligation or economic value in becoming independent of energy utilities and their carbon footprint. Technological progress and increasing adoption of renewable sources, battery storage solutions and BEVs are constantly fuelling this trend towards economic break-even and resulting mass adoption.

The transition from ICE vehicles to BEVs is subject to heated public debate, misinformation and contradictory research results. In this context, this study provides valuable insight into the national and global debate as to whether fleet electrification in countries heavily dependent on fossil fuels is justified.

Although this article focuses on emissions reduction and associated fuel/charging costs, a transition towards BEV-based fleets constitutes a significant organisational, managerial and cultural challenge as habits and preferences are strong across all societies [34]. The authors plan to extend the concept and methods adopted here for future research. Firstly, the authors plan to prepare new business models for BEV fleet management as a tool for further reduction of emissions [35]. Secondly, the authors' aim is to expand the analysis of the total cost of ownership components [36], such as maintenance and failure costs [37]. Thirdly, the authors plan to compare the energy consumption of BEVs gradually introduced into company fleets with results published by OEMs and other BEV users. Finally, further research is needed to provide policy recommendations to assure a consistent regulatory framework. Current regulations in Poland tend to concentrate on individual users and public transport, with a relatively lower focus on company car fleets, which constituted more than 70% of new cars purchased in Poland in 2020 [38].

**Author Contributions:** Conceptualisation, K.Z., J.S., A.K. and P.K.; methodology, K.Z., J.S., A.K. and P.K.; software, J.S.; validation, K.Z., A.K. and P.K.; formal analysis, J.S., A.K. and P.K.; investigation, K.Z., J.S., A.K. and P.K.; resources, K.Z., J.S., A.K. and P.K.; data curation, K.Z. and J.S.; writingoriginal draft preparation, J.S., A.K. and P.K.; writing—review and editing, K.Z., J.S., A.K. and P.K.; visualisation, J.S., A.K. and P.K.; supervision, K.Z. All authors have read and agreed to the published version of the manuscript.

**Funding:** The project is funded under the program of the Minister of Science and Higher Education titled "Regional Initiative of Excellence" in 2019–2022, project number 018/RID/2018/19, the amount of funding PLN10788423.16.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Acknowledgments:** The author would like to thank Adrian Sienicki for his insightful comments and suggestions.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **Nomenclature**

#### **Abbreviations**

#### **References**

### *Article* **The Future of the Polish Energy Mix in the Context of Social Expectations**

**Wojciech Drozd˙ z \*, Oliwia Mr ˙ óz-Malik \* and Marcin Kopiczko**

Research Center on Management in Energy Sector, Department of Logistics, Institute of Management, University of Szczecin, Cukrowa Street 8, 71-004 Szczecin, Poland<EMAIL_ADDRESS>
**\*** Correspondence<EMAIL_ADDRESS>(W.D<EMAIL_ADDRESS>(O.M.-M.)

**Abstract:** Currently, Poland has been facing a process of intensive changes in the energy sector, motivated by the strengthening of the goals of the climate and energy policy at the European level. A key challenge for energy transition in Poland is to build an energy system that corresponds with social needs not only in terms of energy demand, but also environmental protection, with a strong role of local initiatives. The aim of this study is to present the expectations of the Poles regarding the optimal energy mix, especially representatives of local governments, and their awareness of the needs and expectations of their local communities. According to the authors, local governments are extremely important links, responsible for the development of the energy economy and energy security at the local level. The authors set themselves the task of verifying whether local authorities are prepared to create a substantive energy policy at the local level in accordance with the directions of the Polish energy policy and on the basis of local conditions, including the opinions of the inhabitants of a given region. The objective of this work was achieved by reviewing the available sources and the adopted survey method. A review of the literature, in particular in terms of the conducted research on the social acceptance in terms of energy policy, showed that there are no comprehensive surveys of the opinions of local government representatives. The results of study conducted by the authors showed that although the vast majority of respondents know the assumptions of the Polish energy policy until 2030, almost a quarter did not realize that the energy policy will be changed in the near future. At the same time, the vast majority of respondents believe that the Polish government should prepare a social campaign related to the energy policy. According to the authors, this proves the need to improve the awareness of this research group, which may bring benefits in the process of shaping the energy economy of the regions. The survey also showed preferences of the representatives of local governments for the optimal energy mix in Poland and their subjective assessment of the knowledge of public opinion in the region on the expected shape of the energy policy. From the findings, it can be concluded that more in-depth research is needed on the preparation of local governments to shape energy policy at the local level, including more detailed research on how opinions of the inhabitants of a given region and the specificity of a given region are taken into account while shaping local energy policy.

**Keywords:** Polish energy mix; energy transition in Poland; social acceptance; energy policy

#### **1. Introduction**

The transformation of the Polish energy sector has become a reality not only due to the need to keep pace with the path set out by the European Union's climate and energy policy, but also through support of society, which has created an impulse of initiatives and measures aimed primarily at increasing energy security at the local level and reducing the environmental pressures of the energy sector. An important reason for the growing interest of local communities in the energy sector is the increasing environmental awareness. The European Commission's 2014 study showed that most respondents associate the quality of their lives with the state of the environment and believe that environmental problems have

O.; Kopiczko, M. The Future of the Polish Energy Mix in the Context of Social Expectations. *Energies* **2021**, *14*, 5341. https://doi.org/10.3390/ en14175341

**Citation:** Drozd˙ z, W.; Mróz-Malik, ˙

Academic Editors: Miguel-Angel Tarancon and Victor Manuel Ferreira Moutinho

Received: 9 June 2021 Accepted: 19 August 2021 Published: 27 August 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

a direct impact on their lives. People watch their governments more closely as regards their actions related to the energy sector, expressing their opinion and taking action in support of central action [1]. Despite income disparities between Poland and Western Europe, Poles also try to take action; hence, there is a growing number of prosumers as well as micro and small installations and community energy cooperatives in this country.

By 2040, Poland's electricity demand is expected to increase by up to 50%, to 240 TWh [2], which is a huge challenge for the energy sector. Achieving the objectives of the new energy policy, including the development of the renewable energy sector and reduction of the share of coal in power generation, will require effective measures, including those initiated at the local level. By 2032, approximately 12 GW of generation capacity is to be decommissioned in Poland, to be replaced by a similar new capacity in the energy system, approximately 32% of which is expected to come from wind sources [3]. Poland faces the risk of missing capacity, which may result in capacity shortages and difficulties in meeting a growing demand for energy [4].

The crisis caused by the COVID-19 pandemic will have an impact on the energy sector, and experts stress that the economy should recover in a sustainable manner, with as little impact as possible on the environment and natural resources. Recent IEA studies show that global energy demand will decrease by about 5% in 2020, which is directly linked to recent developments. However, economic recovery is likely to lead to considerable increases in energy demand, which needs proper preparation [5]. The European Green Deal climate actions and in particular the climate target plan's 55% net reduction target presented under the Fit for 55 package set the direction for the development of the European energy sector with its ambitious new goals: increasing the emission reduction target to 55% (compared to 1990 level), setting a target of spending 37% of the €750 billion NextGenerationEU recovery fund on Green Deal objectives, and increasing the RES share up to 38–40%.

On July 14, the European Commission announced the climate and energy legislative package—Fit for 55. In line with the EU's climate ambitions, greenhouse gas emissions are to be reduced by 55% by 2030 (compared to 1990). By 2050, the European Union aims to achieve zero net emissions. Such ambitious plans require changes in all areas of social and economic life. The European Green Deal sets out a detailed vision to make Europe the first climate neutral continent by 2050. The new climate target, along with the Fit for 55 package, are part of the European Green Deal adopted in December 2019. The European Commission's proposals must be approved by EU governments and the European Parliament. The package consists of 13 legislative proposals, some of which are new, others presenting changes to existing legislation. The current EU regulations are updated: revision of the EU Emissions Trading System (EU ETS), reform of the LULUCF regulation ( Land Use, Land Use Change and Forestry), review of the Effort Sharing Regulation(ESR), amendment to the renewable energy directive (RED), amendment of the Energy Efficiency Directive (EED), revision of the Alternative Fuels Infrastructure Directive (AFID), amendment of the regulation defining CO2 emission standards for passenger cars and vans, and revision of the Directive on energy taxation. The new legislative proposals include the EU's new forest strategy, the Carbon Dioxide Limit Regulating Mechanism (CBAM), the Social Instrument for Climate Action, ReFuelEU Aviation (for sustainable aviation fuels), and FuelEU Maritim (for greening the European maritime space). The EU's goal of achieving net zero emissions by mid-century will require a massive increase in Europe's renewable energy generation capacity. The main aim of the reform will be to raise the RES targets for the EU. The current target for the share of renewable energy in the EU energy mix will be increased from 32 to 40 percent thanks to Fit for 55. All Member States will have to contribute to achieving this goal, which is an ambitious task for Poland and for the implementation of Polish energy policy. In addition, the directive will raise specific objectives, e.g., concerning the share of renewable energy sources in transport, heating, as well as the share of advanced biofuels. The issue of reducing emissions from the energy sector is one of the key problems of the Polish energy sector. The implementation of the fit

for 55 package in Polish conditions will be difficult; however, the authors believe that the vision presented in the updated energy policy will support the ambitious European goals.

Therefore, the potential of local communities and special role of cities in the process of Poland's energy transition should not be overlooked [6]. The European Commission points to the phenomenon of 'community energy initiatives'. The Joint Research Centre (JRC) of the European Commission has examined the activities undertaken by "community energy initiatives" within the European Union. Research has shown that, owing to legislative support to community action, they undertake a number of initiatives—from power generation (mainly with RES) to energy saving and storage and electromobility [7]. This shows not only huge ambitions of communities for their place in the energy sector, but also how much support the EU and the governments of individual Member States should offer for this type of action. Local communities can play a significant role in the process of transformation of the energy sector in Poland; they can also actively participate in the EU energy market by generating electricity at the local level, using it or reselling it to the market. Furthermore, one of the tasks of the internal energy market is to strengthen the rights of consumers and citizen energy communities [8]. It is also important that regional energy planning is balanced and based on the available renewable raw materials, so as to take into account the constraints imposed by environmental requirements and natural conditions at the lowest cost [9].

A study conducted by the European Commission shows that, by 2030, energy communities could own about 17% of installed wind energy and 21% of solar capacity [10]. By 2050, almost half of EU households are expected to be producing renewable energy [11]. This shows that the potential of citizens is substantial, which, combined with increasing awareness and willingness to act and support from the government, can yield spectacular results, supporting the European and Polish climate and energy objectives.

Local governments are an important element of the complex system of shaping the energy policy in Poland, with their competencies in the field of:

The available research on public opinion about the expected shape of energy policy, conducted in Poland, lacks references to the perspective of local governments. The authors attempted to fill this gap by showing preferences of representatives of local governments for the optimal energy mix in Poland and assessing their preparation to create an energy policy at the local level. According to the authors, this preparation should take into account the knowledge of the preferences of the inhabitants of a given region, as well as an in-depth analysis of the implemented local initiatives (energy cooperatives, prosumers) and local energy resources. There are no in-depth analyses in this area in Poland. The authors emphasize the importance of shaping conscious attitudes in the local government environment, as well as building knowledge and skills and constantly improving the competences of local government employees in the field of energy policy and sustainable development.

#### **2. Literature Review**

#### *2.1. Energy System in Poland in Figures*

The specific nature of the Polish power system stems mainly from a high share of conventional, coal-based energy sources. In 2019, the installed capacity in the Polish Power System (PPS) amounted to 46,799 MW, while the generating capacity amounted to 46,991 MW, an increase by 1.9% and 2.9%, respectively, compared to 2018. The average annual demand for capacity was 23,082 MW, with a maximum demand of 26,504.4 MW (an increase by 1% and 0.2%, respectively, compared to 2018). The ratio of available generating capacity was 64.5%—a decrease by 1.6% compared to 2018 [3].

Figure 1 presents the structure of PPS's installed capacity in 2017–2019. In the last 3 years, there was a small increase in RES, which in 2019 accounted for approx. 16% of the entire capacity installed in the PPS. In total, approx. 47 GW of the capacity was installed in the PPS at the end of 2019 [12].

In 2019, the average annual demand for capacity amounted to approx. 23.082 GW, while the maximum demand for capacity amounted to—approx. 26.5 GW [12]. Despite the fact that the highest historical level of the maximum demand for capacity was in 2019, the average annual demand for capacity in that year saw a slight decrease (by 0.9% compared to 2018). Due to the COVID-19 pandemic and the reduction in activity in certain sectors, the average annual demand for capacity is likely to follow the downward trend in 2020.

At the end of 2019, 9.5 GW was installed in RES, of which 1.5 GW in PV installations. Over the last two years, the development of RES has been supported by the development of prosumer installations. Wind energy clearly stands out among all RES—it has been developing dynamically from 2005, following the introduction of the support system (green certificates), until 2016, which is when the so-called a 'Distance Act' came into force (The Act of 20 May 2016 on wind farm investments) and the sector faced a major problem resulting from the oversupply of green certificates. This all led to the largest crisis in the history of the development of this sector in Poland, faced by both well-established companies and smaller investors [13]. At the end of 2019 the total installed capacity in onshore wind farms amounted to approx. 6 GW (Figure 2), which ranked Poland on the very high, 9th place in the European Union (Europe now has around 195 GW of onshore wind energy capacity installed) [14].

**Figure 2.** Renewable energy capacity installed in Poland in 2005–2019 [MW]. Source: developed by the authors, based on Reference [15].

Despite the increasing share of electricity generated from RES, this type of energy still accounts for only about 9% of Poland's electricity generation and covers approx. 8.5% of domestic electricity consumption (see Figure 3). According to the Polish National Renewable Energy Action Plan, prepared and submitted to the European Commission in 2010, by 2020, Poland is obligated to increase share of renewable energy in gross final consumption to 15%, but experts have pointed to the possible difficulties in achieving this target due to the specific nature of the Polish energy sector and the significant share of coal in energy production since its very adoption. In the last decade, the RES sector in Poland initially developed dynamically, increasing its share in the energy mix (mainly due to legislative changes and the introduction of the aforementioned support system in the form of green certificates). However, starting from 2012, large energy utilities have lobbied against RES, pointing to difficulties in balancing the power system and high costs of energy production, which resulted in annual RES capacity increases far from spectacular. The government's policies since 2015 have halted new investments, which threatened the achievement of the 2020 target [16].

Pursuant to Article 6a of the Act of 20 February 2015 on Renewable Sources, the President of the Energy Regulatory Office (hereinafter: ERO) shall prepare a report on the electricity fed into the grid by renewable energy prosumers and sold to the obligated seller referred to in Article 40(1) of the Act, which was generated from renewable energy sources in micro-installations and fed into the distribution grid, as well as informing about the type of micro-installations and their installed capacity [17]. This obligation has been in place for two years. The report prepared by the ERO President in 2020 [18] shows that there were 149,309 prosumers in Poland in 2019 (Table 1), and the total electricity fed into the grid by the prosumers amounted to 324,333.174 MWh, while the total amount of electricity fed into the grid by micro-installations was 47,896.048 MWh. In 2018 [19], the number of prosumers was 51,163 (the total electricity fed into the grid by prosumers in 2018 was 130,370.162 MWh), which means an increase by nearly 300%.

**Figure 3.** Domestic electricity production and consumption in Poland in 2006–2019 [GWh]. Source: developed by the authors, based on Reference [15].

**Table 1.** Number of micro-installations and total installed capacity in 2018–2019.

Source: Developed by the Authors, Based on References [19,20].

The number of small installations has also been steadily increasing in Poland. In 2019, small energy producers generated energy in a total of 817 installations (one energy producer may hold several installations). Their total installed capacity was nearly 163 MW. In terms of the number (341) and installed capacity (51.5 MW), small hydropower plants were the most prevalent in Poland. They were followed by photovoltaic installations both in terms of the number of installations (247) and installed capacity (47.5 MW). The least popular, on the other hand, were small biomass power plants. At the end of 2019, there were only two such sources in Poland. Owners of small installations (697 entities) generated more than 342 GWh of energy in the previous year, of which 70% (238 GWh) was sold to the obliged sellers and 30% was used for own purposes or sold to other sellers. One year earlier, such installations generated 208 GWh of electricity, selling 142 GWh (more than 68% of the energy generated) to the obliged sellers to the distribution grid. The largest amount of energy—over 158 GWh—was produced by small hydropower plants—almost 46% of energy produced by all small RES installations came from this source. Biogas plants using non-agricultural biogas generated more than 102 GWh of energy, of which only 29 GWh were sold to the obliged sellers. Ranking third were small wind power plants, which generated more than 51 GWh of energy [21].

#### *2.2. Energy Policy in Poland*

The Energy Policy of Poland presents the government's long-term strategy for the energy and fuels sector. Such a document is required by Articles 13–15a of the Energy Law. The document currently in force in Poland was adopted by the Council of Ministers in 2009 and covers the perspective until 2030. Due to the fact that the conditions affecting strategic decisions in the energy sector have changed in the last decade, and the document currently in force takes into account neither European trends nor public expectations, the Ministry of Climate and Environment has developed a project titled 'Energy Policy of Poland until 2040 . As the Ministry stresses, the European Union's climate and energy policy, including regulations under the 'Clean energy for all Europeans' package, is important in the context of work on the new draft [22]. On 2 February 2021, 12 years following the adoption of the previous Policy, the Council of Ministers adopted the Draft. The experts pointed out that, given the current trends and directions of development, without updating the 2009 policy, it would be very difficult to anticipate the future shape of the energy mix in Poland, which is why the new draft energy policy was a long-awaited document [23].

On 10 November 2009, the Council of Ministers adopted the Energy Policy of Poland until 2030, a document which was supposed to address serious challenges faced by the Polish energy sector at that time. These challenges were mainly related to high energy demand, inadequate level of development of fuel and energy generation and transport infrastructure, significant dependence on external supplies of natural gas and nearly complete dependence on external oil supplies, as well as environmental commitments, including climate commitments [24].

For the purposes of developing the energy strategy for Poland, a forecast of fuel and energy demand until 2030 [25] was prepared. Following an analysis, it was concluded that the projected increase in the final energy consumption in 2030 would grow by around 29% compared to 2006, with the largest increase, i.e., by as much as 90%, expected in the services sector. A 15% increase was projected for the industry sector and a 64% increase for the transport sector [25].

Regarding the final energy demand by carrier, by 2030, the final electricity consumption is expected to increase by 55%, gas by 29%, district heating by 50%, petroleum products by 27%, and renewable energy by 60%. Particularly evident against this backdrop is the expected increase in the consumption of renewable energy, which, according to the authors of the forecast, will result from the fulfilment by Poland of its obligations under the European Climate and Energy Package [25].

Since 2005, there has been a steady increase in the generation of energy from renewable sources. The climate and energy package until 2020 assumed a 20% reduction in greenhouse gas emissions (from 1990 levels), a 20% share of renewable energy in total energy consumption in the EU, and a 20% increase in energy efficiency [26]. In 2007, targets were set for Member States, including the target of a 15% share of RES in gross final energy consumption for Poland. In 2014, the European Council approved new targets for the whole EU until 2030, which were then revised in 2018 [26]:

One of the main prerequisites for decision-making on energy policy is a forecast of national power supply. The government anticipates that gross domestic electricity demand in 2030 will be 217.4 TWh. By comparison, in 2006 it was 150.7 TWh. Due to EU requirements, a growing share of renewable energy is expected (see Figure 4). In this respect, the forecast net generation of power from renewable sources is set at 38 TWh, which accounts for 18.8% of the total forecast net power generation [25].

**Figure 4.** Net power generation by fuel in 2021–2030 [TWh]. Source: developed by the authors, based on Reference [25].

Among all renewable energy sources, wind sources play a dominant role, with an expected increase in capacity to almost 8 GW in 2030 [25].

Poland's specific and characteristic energy system has been the reason for adopting the following six interdependent directions in the Energy Policy until 2030: improving energy efficiency, increasing the security of fuel and energy supply, diversification of the energy generation structures by introduction of nuclear power, developing the use of renewable energy sources, including biofuels, developing competitive fuel and energy markets, and reduction of environmental impacts of the energy sector [24].

The development of renewable energy is vital in the context of achieving climate and energy targets, as well as improving energy security and reducing adverse environmental impacts of the energy sector. Bearing in mind the finiteness of fossil sources and their specific nature, renewable sources are an excellent alternative in the energy transition process of Poland. In addition, the development of distributed renewable energy sources reduces transmission losses and improves local energy security. Positive environmental effects associated with the production of energy from RES and socio-economic benefits that accompany their development are also important in this context. They lead to a steady increase in the support for RES, with growing popularity of local community initiatives aimed at growing the benefits of the local use of small renewable sources (energy cooperatives, development of prosumer energy generation) [24].

On 30 December 2019, the Minister of State Assets submitted to the European Commission the National Energy and Climate Plan for the years 2021–2030, thus fulfilling the obligation imposed on Poland by Regulation (EU) 2018/1999 of the European Parliament and of the Council of 11 December 2018, which sets out new climate and energy targets for Poland for 2030. These targets are presented in Figure 5.

The primary objective of the National Energy and Climate Plan for the years 2021–2030 is to act in five dimensions: improve energy security, create and operate the internal energy market, improve energy efficiency, reduce sectoral carbon footprint, and support research, innovation, and competitiveness [27].

**Figure 5.** 2030 goals of the National Energy and Climate Plan for the years 2021–2030 for Poland. Source: developed by the authors, based on Reference [27].

The draft of the Energy Policy of Poland until 2040, adopted on the eve of the publication of this article [28], will define the long-term vision of the government for the energy sector. According to the Government's communication, the document will present a path towards the just transition of the energy sector, energy security, a stable labor market, sustainable development of the economy and strengthening its competitiveness, and recovery from the COVID-19 pandemic. Changes in the international context (Paris Agreement, so-called Katowice Climate Package, adoption by the EC of the 'Clean energy for all Europeans' package, and adoption of the European Green Deal) and global trends in climate and energy have forced Poland to revise the provisions of the already obsolete Energy Policy of Poland until 2030. These trends led to the revision of the objectives for the energy sector in Poland to support the European path to achieving climate neutrality by 2050 and to reduce adverse environmental impacts of the energy sector. The specific Polish energy sector, which is largely based on conventional, coal sources, requires continuous modernization of generation capacity and diversification of the energy generation structure, in particular while respecting the principle of just transition, which also takes into account its social context. The Polish government intends to allocate approx. PLN 200 billion from the EU and national funds under various mechanisms—such as the Cohesion Policy, the Recovery and Resilience Facility, the Just Transition Fund, and the Modernisation Fund or the Energy Transformation Fund—for the country's energy and climate transition by 2030 [28].

The new EPP 2040 is supposed to provide a foundation for the creation of a modern, sustainable, low-carbon energy system in Poland and is based on three pillars [28]:

The specific objectives of EPP 2040 cover the entire energy supply chain, from raw material acquisition to energy generation and supply (transmission and distribution) to its use and sale.

For environmental reasons, the cost-optimal structure of power sources presented in EPP 2040, in line with the government's analysis, includes nuclear power plants, whose development is limited due to organizational and technical constraints. The Energy Policy of Poland until 2030 envisages that there will be three nuclear units with a total net power of 4.5 GW (4.8 GW gross) in operation by 2030 [29]. Today, we already know that this objective will not be achieved, although work on the implementation of the Polish Nuclear Power Programme is underway. Currently, the government maintains that in 2033, the first unit of the first nuclear power plant with a capacity of approx. 1–1.6 GW will be commissioned in Poland, with six nuclear reactors with a total capacity of approx. 6.6 GW operating in Poland by 2045. The share of nuclear power plants in electricity production is set to be 9% in 2035, increasing to 16% in 2040 and to 23% in 2045 [30].

The new scenario for the energy sector until 2040, presented as part of the update of the Energy Policy of Poland, assumes the development of offshore wind farms at approx. 1 GW per year starting from 2025, with the achievement of 8–11 GW in 2040 (a 19% share in the structure of power generation in 2040). The inclusion of the offshore wind energy sector in the draft EPP 2040 and the adoption of the Act on offshore wind energy generation are an important signal for enterprises from the industry (investors and suppliers), confirming the importance of this sector for the country's energy strategy. Offshore wind energy has a huge potential for shaping social and economic benefits for the countries that support it [31]. In addition, it has been assumed that energy generated using photovoltaics would grow to 10–16 GW (at least 5% share in power generation) and the amount of energy generated by onshore wind farms to at least 6.9 GW (at least 11% share in power generation) by 2040 [22].

The draft version of the Poland's new energy strategy also provides for the development of energy storage technologies, smart metering, and energy management systems, and the development of electromobility and alternative fuels and hydrogen-based technology. Electromobility in Poland is currently on the rise, as can be seen both in the development of charging infrastructure for electric vehicles and in the number of these vehicles on Polish roads (year-to-year increase in the number of vehicles is between 1.56 and 2.50) [11,29].

The Energy Policy of Poland until 2040 adopted the following indicators as a measure of achievement of the objective [18]:

#### *2.3. The Energy System of the Future—Analysis of Social Expectations Based on Secondary Data*

The results indicate massive public support for the growth of renewable energy production, a strong policy supporting renewable energy, increasing energy efficiency, and greater active involvement of the Polish government in the efforts to reduce emissions in order to avoid dangerous changes. At the same time, support for coal, nuclear power, and other fossil fuels is much lower (Figure 6).

**Figure 6.** Type of energy that respondents believe should be developed in Poland in the near future (respondents could indicate two answers). Source: developed by the authors, based on Reference [32].

According to public opinion polls on RES carried out in Poland in 2015, one-third of the Poles knew about the existence of the RES Act, but only 7% were aware of what it addressed. A total of 11% of respondents were familiar with the term 'prosumer', but only 3% declared that they knew what exactly this term meant. The research also identified the investment potential of the Poles with regard to small RES installations. In 2015, 35% of respondents declared not only their support for the idea, but also their willingness to directly invest in RES, with 13% of respondents reporting willing to start using this technology within 2 years. At the same time, the percentage of those interested in the investment was significantly higher among those familiar with the RES Act (52%) and among those who felt informed about the possibilities of RES financing support (58%). Among those wishing to purchase RES installations, the main reason for such an investment was the willingness to reduce energy bills (over half of the respondents) and the possibility of enjoying cleaner air, as well as the convenience of using RES installations. Other reasons included the current opportunity of benefiting from subsidies, promotion of innovation or prestige, and improvement of one's image due to the construction of such an installation [33].

Figure 7 summarizes the results of a survey of the opinions of Poles on various energy sources [32,34]. Solar and wind energy are definitely at the forefront of this summary nearly 80% of respondents see their positive aspects. In that survey, conventional energy based on coal and nuclear sources enjoys the smallest support. The same study shows that in 2020, 75% of all respondents agree that the development of RES supports environmental protection and counteracts climate change. Slightly fewer, i.e., 70%, point to reduced dependence on energy imports and 68% of respondents say that it contributes to the creation of new jobs [34].

**Figure 7.** Comparative assessment of the different methods of power generation. Source: developed by the authors, based on References [32,34].

Despite the ambiguous dynamics of public support for RES initiatives, the declared level of support for pro-climate actions is relatively high and growing (Figure 8). In the 2018 social opinion polls [35], more than 80% of respondents agreed that Poland should support the European Union in its efforts to reduce carbon dioxide emissions. This percentage in 2018 was higher than in previous years. The results were similar for the question of whether Poland should support actions to help countries affected by the effects of climate change. At the same time, however, a significant number of people are concerned that Poland is too poor to afford special programs to combat climate change. In 2016, 48.9% of respondents thought so, while in 2018—37.3%. A significant proportion of respondents were also convinced that Poland's contribution to climate change was so low that its reduction would not significantly translate into global change. In 2016, 43.6% of respondents thought so, whereas in 2018 this percentage was lower, with only 37.3% of respondents saying 'yes'.

**Figure 8.** Support for the climate policy in Poland: Opinion 1: Poland should support the European Union in its efforts to reduce carbon dioxide emissions. Opinion 2: Poland should support actions to help countries that have been victims of climate change. Opinion 3: Poland is too poor to afford special programs aimed at combating climate change.  Source: developed by the authors, based on Reference [35].

#### **3. Methods**

The authors have used the diagnostic survey method and a critical literature review. This paper has been prepared based on the analysis of source materials such as documents and national and international regulations (in particular EU law), as well as secondary source data made available in reports prepared by energy sector entities, advisory companies, and research centers. To verify the results of the public opinion polls carried out in recent years, the available outcomes of these studies, conducted by renowned public opinion poll centers, were analyzed. The analysis seeks to answer the question of whether the energy policy implemented in Poland has met the expectations and how it has been received by the public, and to verify whether the research took into account opinions of local governments as the entities responsible for long-term anticipation of trends in the demand of the local community for fuels and energy.

The article analyzes the assumptions of the Energy Policy of Poland and changes in the Polish energy sector in recent years, in particular changes in the structure of power generation, based on reports published by Polskie Sieci Elektroenergetyczne S.A., a Stateowned company, and then assesses the dynamics of these changes. Public expectations and opinions on energy policy are also analyzed using secondary data (reports on surveys conducted by leading marketing research agencies).

Due to the lack of information on the opinions of local governments in the available secondary data, which the authors deem a group of particular importance due to their contribution to the development of the energy policy—and energy security—at the local level, a survey was conducted in December 2020 involving a group of 274 respondents. The survey addressed current and general knowledge about the Energy Policy of Poland and the respondents' opinion on actions implemented by the local government, as well as the awareness of the needs and expectations of the local community. The respondents answered the questions in person (personal interview) or online.

#### **4. Results**

The study of the opinions of representatives of local government units was carried out in December 2020 in the form of a personal interview and an online survey. Answers were received from 274 respondents aged 28 to 62, most of whom were women (154, 56.30%). The age of the vast majority of respondents falls within the range of 36–45 years (111, 40.51%), followed by the range of 46–55 (84, 30.66%) and 23–35 years (68, 24.82%), with respondents aged 56–65 being the smallest group (11, 4.01%). No response was received from anyone aged over 65. The largest number of respondents represent urban municipalities [gmina miejska] (143, 52.19%), cities or towns with county rights [miasto na prawach powiatu] (60, 21.9%), or urban and rural municipalities [gmina miejsko-wiejska] (48, 17.52%), with rural municipalities being the least represented (23, 8.39%). Currently (as of 1 January 2021), Poland is divided into 16 voivodships, 314 poviats, and 2477 municipalities (302 urban municipalities, including 66 in cities or towns with county rights, 652 urban and rural municipalities, and 1523 rural municipalities) [36]. The feedback received covers 11% of all municipalities in Poland, including 47.35% urban municipalities, over 90% cities or towns with county rights, only 7.36% of urban and rural municipalities, and about 2% of rural municipalities.

Respondents were asked about their awareness of the Energy Policy of Poland until 2030. A total of 230 respondents said 'yes' (83.21%, of which 58.26% were residents from urban municipalities, 22.17% were from cities with country rights, 16.09% were from urban and rural municipalities, and 3.48% were from rural municipalities), while 44 responded said 'no' (16.06%, of which 20.45% were residents from urban municipalities, 20.45% were from cities with country rights, 25.00% were from urban and rural municipalities, and 34.09% were from rural municipalities). For the question for their knowledge of the EU climate and energy policy assumptions, 73 (26.64%) of respondents assessed their knowledge as very good, 43 (15.69%) as good, 87 (31.75%) as moderate, and 71 (25.91%) as poor (see Table 2 and Figure 9).

**Table 2.** Residents' knowledge of the EU climate and energy policy assumptions.

Source: Own Study.

**Figure 9.** Knowledge of the EU climate and energy policy assumptions. Respondents could select only one answer. Source: own study.

Afterwards, respondents were also asked to assess their knowledge of the assumptions of the draft Energy Policy of Poland until 2040 (still in the project phase at the time of the survey). 63 respondents (22.99%) assessed their knowledge as very good, 85 (31.02%) moderate, and 71 (25.91%) poor. 55 (20.07%) respondents were not aware that the Energy Policy of Poland has been changing (see Table 3 and Figure 10).

Source: Own Study.

**Figure 10.** Knowledge of the assumptions of the Energy Policy of Poland until 2040. Respondents could select only one answer. Source: own study.

The respondents were also asked whether they knew what Poland's energy mix currently looks like, and their task was to tick the energy sources currently used in Poland (each respondent could select more than one answer). All respondents ticked hard coal (274, 100%) and almost all respondents (273, 99.64%) ticked lignite. A vast majority also ticked onshore wind energy (270, 98.54%), biogas (211, 77.01%), and biomass (194, 70.80%). A total of 150 (54.74%) respondents ticked gas and hydropower. Only 87 (31.75%) respondents selected photovoltaics and 67 (24.45%) ticked RES micro installations. Furthermore, 4 (1.46%) respondents ticked nuclear power, while 2 (0.73%) ticked offshore wind energy (see Figure 11).

**Figure 11.** Energy sources currently used in Poland. Respondents could select more than one answer. Source: own study.

Respondents were also asked to express their opinion on what the optimal energy mix for Poland should look like, by indicating the relevant scenario (see Table 4 and Figure 12). Respondents could select only one answer. A total of 47 (18.29%) respondents indicated the scenario with a dominant role of RES, 45 (17%) respondents selected the scenario based mainly on coal, 15 (5.84%) opted for the scenario in which prosumers predominate, 10 (3.89%) indicated that the focus should be primarily on energy efficiency, and 5 (1.95%) selected the scenario based on nuclear power. A total of 118 (43%) respondents indicated that the optimal mix should be based on all previously indicated sources apart from nuclear power, while 34 (13.23%) were in favor of all previously indicated sources apart from RES.

Source: Own Study.

**Figure 12.** Opinion on the optimal energy mix for Poland. Respondents could select only one answer. Source: own study.

The respondents were also asked whether they knew what opinions the local community in their city/municipality had on the optimal energy mix (Figure 13). A total of 160 (58.39%, of which 41.25% were residents from urban municipalities, 25.63% were from cities with country rights, 23.75% were from urban and rural municipalities, and 9.38% were from rural municipalities) said yes, while 114 (41.61%, of which 67.54% were residents from urban municipalities, 16.67% were from cities with country rights, 8.77% were from urban and rural municipalities, and 7.02% were from rural municipalities) said no. Another question concerned the knowledge of the number of prosumers registered in the respondents' city/municipality (Figure 14). The vast majority (240, i.e., 87.59%, of which 59.17% were residents from urban municipalities, 24.17% were from cities with country rights, 15.42% were from urban and rural municipalities, and 1.25% were from rural municipalities) responded in the negative, while 34 respondents (12.41%, of which 2.94% were residents from urban municipalities, 5.88% were from cities with country rights, 32.35% were from urban and rural municipalities, and 58.82% were from rural municipalities) had knowledge on this figure. The respondents were also asked to say whether they had ever heard of energy cooperatives (Figure 15). A total of 150 respondents (54.74%, of which 42.67% were residents from urban municipalities, 27.33% were from cities with country rights, 20.00% were from urban and rural municipalities, and 10.00% were from rural municipalities) affirmed, while 124 (45.26%, of which 63.71% were residents from urban municipalities, 15.32% were from cities with country rights, 14.52% were from urban and rural municipalities, and 6.45% were from rural municipalities) had never heard of them.

**Figure 13.** Knowledge of concepts and phenomena. Respondents could select only one answer—'yes' or 'no'. Source: own study.

**Figure 14.** Knowledge of concepts and phenomena. Respondents could select only one answer—'yes' or 'no'. Source: own study.

Most respondents (112, 40.88%) had no concerns related to the implementation of EU climate and energy requirements in Poland (see Table 5 and Figure 16). A marginally smaller number of them (106, 38.69%) did have such concerns. A total of 56 respondents (20.44%) had no opinion on this.

**Figure 15.** Knowledge of concepts and phenomena. Respondents could select only one answer—'yes' or 'no'. a—do you know the opinions of your local community on the optimal energy mix, b—do you know how many prosumers are registered in your city/municipality, c—have you heard the term 'energy cooperative'. Source: own study.

**Table 5.** Residents' concerns related to the implementation of EU climate and energy requirements in Poland.

Source: Own Study.

**Figure 16.** Concerns related to the implementation of EU climate and energy requirements in Poland. Respondents could select only one answer. Source: own study.

#### **5. Discussion and Conclusions**

Transformation of the energy sector in Poland is a current topic that has been developing before our very eyes. Both the Polish government and its citizens recognize the need to change the structure of power generation in Poland, and the path taken by the recently adopted draft Energy Policy of Poland until 2040 coincides with the expectations of Poles.

The authors made an attempt to check the development of the energy sector in Poland and verify the public opinion on the energy policy implemented in Poland. The authors also decided to check whether the available public opinion research include the expectations and knowledge of representatives of local governments, as a group particularly relevant from the point of view of their role in shaping energy policy and energy security at the local level.

The analysis of secondary data shows that the support for the European climate and energy policy among Poles is on the rise, as is the support for clean power such as solar and wind energy. There has been a slight decrease in the support for nuclear power, which may be due to the lack of a clear and consistent action plan and results. Social expectations are in line with the shape of the updated energy policy. As shown in [32–34], renewable energy sources, mainly wind and photovoltaics, are seen as the best ways of generating energy. Additionally, our own research showed that the optimal energy mix for Poland is expected to be based on RES or on RES together with prosumer initiatives and energy efficiency actions. This corresponds with the new goals of the energy policy in Poland, assuming no more than 56% of coal in power generation in 2030, at least 23% of RES in gross final energy consumption in 2030 a 30% reduction in GHG emissions by 2030 (compared to 1990).

Taking into account the information obtained in the survey, a majority of respondents have a moderate or low level of knowledge of the EU climate and energy package or the assumptions of the Energy Policy of Poland until 2040. At the same time, the vast majority of respondents know the assumptions of the Polish energy policy until 2030, but almost a quarter did not realize that the energy policy will be changed in the near future. According to the authors, the vast majority of respondents from this group come from rural areas, which may constitute a major barrier to initiatives taken by local governments or to the shaping of the local strategy for sustainable development due to the lack of knowledge of strategic paths for the development of the energy sector. The vast majority of respondents believe that the Polish government should prepare an awareness-raising campaign related to its energy policy and train local governments in this regard. The majority of respondents declare knowledge of the opinion of the local communities they represent—nearly 60% of them know their community's views on the optimal energy mix. It is worth emphasizing that 65% of the respondents from rural areas know the views of local communities. This shows that local governments in urban areas should take measures to better understand local communities and learn about their views on the preferred shape of energy policy. Given the current trends in the development of prosumer energy and support of the Polish government for the creation of energy cooperatives, it is also positive that a vast majority of respondents have heard of energy cooperatives. However, the lack of knowledge about the number of micro installations operating in a given city/municipality is unfavorable. The survey also showed preferences of representatives of local governments for the optimal energy mix in Poland and their subjective assessment of the knowledge of public opinion in the region on the expected shape of the energy policy. From the findings, it can be concluded that more in-depth research is needed on the preparation of local governments to shape energy policy at the local level, including more detailed research on how opinions of the inhabitants of a given region and the specificity of a given region are taking into account while shaping local energy policy.

Many local governments see RES as an opportunity for the development of their own region. The analysis of sectoral statistical data shows that both the share of renewable energy sources in the structure of power generation and the number of micro installations or prosumers have been gradually increasing, in line with the expectations of the public, as confirmed by the mentioned secondary research and the survey carried out by the authors. This has a positive impact on energy security, also at the local level, and in the long term, it will reduce the adverse environmental impacts of the energy sector. It is known that caring for the natural environment is gaining importance because ecological products are available, the consumption and processing of plastic is reduced, and the waste segregation process is implemented. To help nature, the use of renewable energy sources is also being developed, i.e., those based on natural and inexhaustible resources. The developed methods of obtaining them guarantee not only emission-free electricity production, but also endless possibilities of its use. However, it should be noted that it will be very difficult to achieve a dominant role of RES in the power generation structure in Poland—not only due to the persisting belief of some citizens in the infinity of conventional resources, but mainly due to major technological, financial, or legal barriers. With growing adoption of RES technology in Poland, legal barriers are gradually reduced by the government, an example of which is the adoption of the Act on offshore wind energy generation in early 2021, which is expected to give impetus to the Polish renewable energy industry and form a part of Poland's energy security system.

A review of the literature, in particular of the conducted research on social acceptance in terms of energy policy, showed that there are no comprehensive surveys of the opinions of local government representatives. The authors point to the great role and responsibility of the local government in the context of building local energy strategies based on locally available energy resources, knowledge resources, and the level of activity of local communities. There is no in-depth research in Poland that would show not only the opinion of local government representatives, but also the existence and main assumptions of local energy strategies, as well as the way of creating these strategies. The survey showed that representatives of local governments, who mostly assess their knowledge of the EU's energy and climate policies as moderate or poor (the vast majority of respondents with poor knowledge come from rural areas), are not fully prepared to create energy plans for their regions. The authors emphasize, however, that for a thorough examination of this issue, a study covering a much larger research group and a wider range of issues is necessary. The authors also emphasize the importance of shaping conscious attitudes in the local government environment, as well as building knowledge and skills and constantly improving the competences of local government employees in the field of energy policy and sustainable development.

**Author Contributions:** Conceptualization, methodology, validation, formal analysis, investigation, and writing, W.D. and O.M.-M.; resources and data curation, O.M.-M. and M.K.; writing—original draft preparation and visualization, O.M.-M.; writing—review and editing, W.D., O.M.-M., and M.K.; supervision, W.D. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research is funded by the University of Szczecin; Research Center on Management in Energy Sector, Institute of Management, Cukrowa Street 8, 71-004 Szczecin, Poland.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

### *Article* **The Impact of COVID-19 on Electricity Demand Profiles: A Case Study of Selected Business Clients in Poland**

**Marcin Malec 1,\*, Grzegorz Kinelski 2 and Marzena Czarnecka 3**

**Abstract:** The COVID-19 pandemic has caused changes in electricity demand and, consequently, electricity consumption profiles. Given the rapid changes in energy prices, it is significant from the perspective of energy companies, and forecasting consumed energy volume. A necessity for accurate energy volume planning forces the need for analyzing consumers' behaviors during the pandemic, especially under lockdowns, to prepare for the possibility of another pandemic wave. Many business clients analyzed in the paper are economic entities functioning in sectors under restrictions. That is why analyzing the pandemic's impact on the change in energy consumption profiles and volume of these entities is particularly meaningful. The article analyzes the pandemic and restrictions' impact on the total change of energy consumption volume and demand profiles. The analysis was conducted basing on data collected from a Polish energy trading and sales company. It focused on the energy consumption of its corporate clients. Analyzed data included aggregated energy consumption volumes for all company's customers and key groups of economic entities under restrictions. The analysis demonstrates the influence of pandemic restrictions on energy consumption in the group of business clients. Significant differences are observable among various sectors of the economy. The research proves that the largest drops in energy consumption are related to shopping centers and offices. Altogether, the restrictions have caused a 15–23% energy consumption drop during the first lockdown and a maximum 11% during the second against expected values.

**Keywords:** COVID-19 pandemic; lockdown; electricity demand profiles; energy consumption

### **1. Introduction**

The outbreak of the COVID-19 pandemic in 2020 was unexpected and began many new challenges for the global and national economies [1]. The situation has significantly impacted numerous industries, including production, agriculture, transport, financial services, education, and healthcare [2]. Some of its consequences were changes in the electricity demand profiles of consumers representing various branches of the economy. Has the situation significantly impacted the energy sector, in which the correct forecasting of electricity consumption is one of the key factors guaranteeing power plants' stability works and continuous financial income? It concerns energy production, transfer, and supply [3,4]. The International Energy Agency (IEA) indicates that the change in energy demand in 2020 was the largest in the last 70 years. In 2020, the pandemic decreased the global GDP by 4.4%. This value was significantly higher than the GDP decrease of 2009 (0.1%) that resulted from the global economic crisis. Forecasts indicate that in 2021, global production will recover to the level of 2019 due to an economic boom in large developing countries, particularly China and India. However, it is expected that developed economies will not recover to the levels they had before the pandemic [5]. During the

**Citation:** Malec, M.; Kinelski, G.; Czarnecka, M. The Impact of COVID-19 on Electricity Demand Profiles: A Case Study of Selected Business Clients in Poland. *Energies* **2021**, *14*, 5332. https://doi.org/ 10.3390/en14175332

Academic Editor: Susan Krumdieck

Received: 26 July 2021 Accepted: 24 August 2021 Published: 27 August 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

pandemic, in most countries, demand for electricity supply decreased significantly. It results in large uncertainty for all energy companies in the world. The pandemic makes predicting the situation's development impossible. Because of the lockdowns, limiting many life, economy, construction, and production activities decreased global demand for energy. Undeniably, the decrease has caused damage to the energy industry, which, in consequence, led at least nineteen American energy companies to bankruptcy [6].

Because of how the virus spreads, the main way to fight against it was to limit human interactions locally and globally. Depending on the country, the level of restrictions was related to an adopted strategy of fight against the pandemic and infection numbers [7]. One should pay attention to governments introducing restrictions undoubtedly influencing electricity consumption by consumers in many sectors. Unquestionably, politicians making decisions had taken energy security and the necessity for maintaining some economic sectors into account before restrictions were implemented. However, they did not know forecasts of possible consequences. Introducing restrictions usually had far-reaching consequences for energy companies. The lack of scenarios of restrictions' influence on energy consumption was significant in production planning and energy transfer organizing. However, the most severe consequences were observable in the electricity trade.

Introducing the first lockdown in March 2020 to respond to the SARS-CoV-2 spread was an entirely new situation for individual and business electricity consumers. In consequence, freezing many branches of the economy has led to considerable decreases in the first half of 2020 energy consumption. Compared to May 2019, energy consumption in 2020 was 8% lower [8].

Gradual unfreezing of the economy in the second half of 2020 caused successive equalization of energy consumption levels compared with the previous year. Sometimes, it was even higher than the year before. The rapid increase in 2020 energy consumption occurred in September. New restrictions of October–November 2020 did not change the increasing trend. At the beginning of December 2020, the electricity consumption level was circa (ca.) 14.5 TWh, 200 GWh more than in December 2019 [9,10].

In this context, it is essential to learn how to operate in case of a crisis. It is necessary to consider and adjust to aspects of a crisis and restrictions imposed by law. More than that, there is a need to be aware that a similar situation may happen again. It may refer to possible waves of the pandemic as well as other crises potentially impacting energy consumption for different hours, situations, and various branches of the economy. The energy sector has to be prepared for such situations. That is why an analysis of electricity consumption profiles is an absolute necessity. Uncertainty also impacts investment decisions in the energy sector, which is another reason behind the need for analysis [11,12].

As mentioned, the energy sector situation was disturbing for energy trading companies that carry out transactions on the stock exchange [13,14]. Electricity prices on the commodity market are conditioned mostly by production and environmental costs [15]. They are also strongly related to fuel prices, in Poland, it still is coal [16].

Given the energy prices fluctuation on the wholesale market, an accurate forecast is essential for energy trading and sales companies [17,18]. An adequate assessment of energy demand in particular hours of the day allows for correcting a contract position at the right time, maximizing the company's benefits, and minimizing its losses [19]. A key challenge from the perspective of energy trading companies was the changes in the consumption schedules and deviations in consumers' profiles. That is why the analysis of consumed energy volumes may enable an appropriate reaction to adopt accurate coefficients correcting consumption schedules, dependent on imposed restrictions.

The article analyzes energy consumption by a particular group of customers of a national energy trading and sales company. The research is focused on the restrictions' impact on the changes in electricity consumption volumes. Results were obtained through measurements taken during the lockdowns (the periods of limited mobility and activity of society) and compared with values obtained in the comparable period in 2019 and before the pandemic. The analysis concerns the total electricity consumption volumes and energy

consumption profiles of clients from the key sectors. Besides the comparative analysis of energy consumption in 2019 and 2020, the article employs basic statistical measurements for the volatility analysis. Furthermore, the study includes the assessment of the ratio of expected to actual energy consumption based on trends from before the pandemic.

The remainder is organized as follows. Section 2 presents a review of current research on the influence of the COVID-19 pandemic on the energetic sector. Section 3 presents the schedule of introducing and lifting restrictions by the Polish government in 2020. Section 4 includes computing methodology. Section 5 includes results. Section 6 presents a discussion and the most important conclusions.

#### **2. Literature Review**

Undoubtedly, demand for electricity radically decreased during the lockdowns because governments have forced isolation and implemented numerous limitations on movement and transport. Consequently, the load structure and its daily profile have also changed, which was incredibly difficult for energy producers and sellers to balance. Changes have also been visible in national energy mixes. The share of energy produced from renewable resources has increased, while the total production of electricity has decreased [20]. The new situation in the balance of power and the increased uncertainty of demand have put pressure on system operators and caused problems with maintaining voltage in the power grid and other challenges for system management [21]. Thus, the pandemic has generated unprecedented distortions in almost every element of the energy market. In [22], it was proven that data on electricity markets with high granularity and frequency might be used for the causal estimation of the COVID-19 pandemic's shortterm influence on the economy by delivering information important for future lockdown politics [22].

The pandemic's impact on the European electricity markets has been immense, especially in countries with rich energy supplies and nearly non-existent marginal production costs, such as France. The author of [23] presented the quantitative assessment of the crisis's influence on the French electro-energetic sector. During the lockdown, France experienced an unprecedented decrease in demand (−11.5%) and energy prices decline (−40%), which caused losses for the market participants estimated at 1.2 bln € (−45%) [23]. The COVID-19 pandemic's impact was also visible in decreasing GDP. For example, in Italy, it decreased about 30% [22]. The change in primary energy consumption in 20 European countries with the highest GDP was also discussed in [24].

In 2020, the only huge economy with a higher demand for electricity was China. However, the 2% increase was much lower than the values from previous years of about 6.5%. The other main electricity consumers, including the United States, India, Europe, Japan, South Korea, and South-Eastern Asia, noted a decrease in the scale of the whole year [1].

Nearly 42% of global demand for electricity is generated by industry and 22% by commercial and public services. That is why economic activity and electricity consumption are tightly related. In developed economies, the share of these sectors is more or less equal, about 32%. In developing countries dominated by industry, this sector needs about half of the final demand, while services use about 14% [5].

An accurate assessment of energy demand fluctuation based on constantly updated data is urgently required to analyze changes in the energy sector, production planning, and energy transportation. It is because investments and global energy supply chains have been distorted [25]. Load curves, especially electricity consumption peaks, have also changed. Noticeable changes in demand (consumption) in the macro- and microeconomic levels presented in the body of literature include:

1. Short-term demand decreases when the restrictions are introduced [26], but it is expected that demand will gradually recover after lifting them [27].

In the body of literature, there are studies of the impact of the pandemic on electricity consumption in various groups of end-consumers based on real measurements. Such research was conducted among households' inhabitants, an important group of consumers, who have changed electricity demand during the pandemic [31]. Other similar works present studies of the COVID-19 pandemic's influence on household electricity consumption in China [32], Spain [33], and Canada [34].

The other analyzed sector was healthcare. In these studies, authors review various changes in healthcare in different countries and their impact on the energy sector and environment. They present conclusions on the impact of the COVID-19 pandemic on these three sectors regarding climate change and the change in environmental emissions to which also healthcare has contributed [35].

Undoubtedly, new practices and social behaviors acquired during the pandemic influenced the need for electricity and its consumption. It has been proven that even though general demand for electricity during the pandemic decreases, quantitative and time differences are complex, and the return to usual consumption in various regions is not equivalent [36].

Studies demonstrate that the pandemic has had a particular effect on commerce. Analyses of the retail trade indicate that in March and April 2020, the highest decreases in the European Union countries were noted for gasoline and commodities bought in department stores and shopping malls. The situation stabilized in June 2020. The second period of decrease was observed from November 2020 to January 2021 [37].

Studies [5,27] indicate that changes in electricity consumption were independent of the region and the highest in commerce and services. The only difference was a period in which they occurred: the first quarter of 2020—China; the second quarter of 2020— Argentina (South America), Spain, and the United Kingdom (Europe); the second and the third quarter of 2020—the US (North America). Only in South America, the changes were also observed in the industry. Studies demonstrate that in the sector of households, significant changes in energy consumption were not noted in the analyzed regions.

Data presented in the European Parliament's report indicate that differences in the functioning of various industries were significant, which was another reason behind the change in their energy consumption. In EU countries, the results of the pandemic were primarily felt in the digital and healthcare sectors. The chemical industry, construction, and food production now go out of the crisis, which is best represented by the "V" curve, they recover to the production level before the pandemic. The automotive and textile industries are in a similar situation. Despite decreases, they are now recovering their positions before the first lockdowns. Sectors dependent on direct contact and human interactions, such as culture, environment, and air transport, have suffered from the crisis the most. They will be coping with its consequences for a long time. However, it has been proved that the pandemic increased the awareness of the benefits of digital and ecological transformation, which have to be associated with respective political investments and motivations [38].

Studies also indicate that from the perspective of the energy sector, the most direct consequences concerned the levels of power consumption, production mix structure, and electricity market price. Electricity consumption decreased by 15% in relation to previous years, and one could observe changing energy demand profiles in the states that introduced more rigorous restrictions than others, e.g., Italy, France, and Germany. In the states with less rigorous limitations (e.g., Sweden), significant changes in energy consumption were not noted [39]. In the context of the pandemic's influence on energy companies' functioning, particular attention deserves studies concerning the companies' financial outcomes [40]. Authors in [41] demonstrated that even though the lockdowns decreased mean energy prices in Italy by 45%, the transmission costs increased by 73% for the analogous period from the previous years. Thus, investments in power grids and the development of demand management technology are indispensable. Simultaneously, the growing share of renewable energy sources may increase the costs of maintaining a reliable power grid [42]. The COVID-19 pandemic has negatively influenced energy production, causing a rapid drop in income. Companies did not regulate fixed costs and expenses, which led them to lose value [43]. As mentioned in the introduction, some were even forced to declare bankruptcy [6].

The number of works evaluating the impact of restrictions on energy consumption from the perspective of an energy trading and sales company, which produces, distributes, and sells energy, is still very low. Such studies were conducted in the context of the possibility of implementing additional enhancements to energy consumption forecasting tools [44,45]. Understanding the changes in electricity demand and their influence on forecasting consumption is essential for maintaining reliable power grid operation and realizing tasks of energy trading companies with the best possible financial outcome. The change of consumers' behavior during the pandemic negatively impacts the predictability of demand schedules, which is critical for energy trading companies.

#### **3. The Pandemic in Poland—A Course (Chronology)**

In Poland, the first restrictions resulting from the COVID-19 pandemic were introduced by the Regulation of the Minister of Health on the Announcement of the State of Epidemic Emergency on the Territory of the Republic of Poland dated 13 March 2020. In practice, the state of the epidemic has been functional in Poland since 20 March 2020, after amending the announcement [46].

The regulation issued on 13 March introduced restrictions related to the functioning of many activities. The list of restricted entities was provided in the regulation following the Polish Classification of Activity. The restrictions introduced in the first period were gradually tightened. Since 25 March, there was a ban on movement except for strictly defined cases. April 1 introduced a ban on the operation of cosmetic and hairdressing salons and additional limitations to commerce. Lifting them began on 20 April, though their first effects were visible on 4 May. Eventually, the first stage of restrictions ended on 6 June. Since then, some recommendations on personal protection have been maintained. The limitations from March and April were called a "hard lockdown."

Since 8 August, in the country, there were regional restrictions. The state was divided into "yellow" and "red" zones. Districts were classified into them based on the number of confirmed infections. The second period of significant restrictions began on 24 October, though more limitations were added two weeks later. Some of them were lifted on 27 November 2020. The third state of restrictions was called a "national quarantine" and began on 28 December 2020 (Figure 1). The authors analyzed the impact of the pandemic on the change of energy demand profiles in 2019 and 2020. That is why "national quarantine" restrictions implemented in 2021 are not discussed in this article.

**Figure 1.** Graphical representation of COVID-19's restrictions from 2020 [46].

#### **4. Methodology and Data**

#### *4.1. Data Characteristics*

The analyzed dataset included the electricity consumption volumes of the customers of one of the national trading companies. The data were collected in hourly resolution for each hour in 2019 and 2020. The data were delivered in a day *n* + 2 by the Balance Responsible Party (Administrator) based on data coming from the Distribution System Operator. In case of detecting measurement errors, the Balance Party and the Operator revised them within 2 following days (Figure 2).

**Figure 2.** Collection and verification of measurement data—diagram.

Consumers belonging to the analyzed set represented various economic entities, e.g., production, service, and commercial companies operating in the territory of the whole country. The biggest clients were, among others, companies producing and distributing electricity, gas, and steam, ca. 35%, industrial consumers (food processing, electromechanical, and wood industries), ca. 30%, real-estate market companies (e.g., shopping malls), ca. 15%, and agriculture, ca. 7%. The total volume of energy consumed in 2019 was ca. 1.65 GWh. The Balance Responsible Party was obliged to create aggregates, including measurement points indicated by the Trading and Sales Company. The balancing positions of clients or shopping groups were appointed based on these points, but after an energy trading and sales company creates an energy consumption schedule. Such a plan must include all situations that may affect energy consumption (a day of the week, days off, unusual days, and nontypical phenomena). Parallelly, a considerable hardship for trading companies was verification and possible plan corrections due to an inertia period lasting 3 days. Actual consumption data were published on day *n* + 2 after 10:00, and SPOT trading on the Day-Ahead Market had to be submitted on the current day until 10:00 to the Polish Power Exchange.

The aim of the paper is to analyze the impact of the COVID-19 pandemic on the total electricity consumption and consumption profiles of clients representing key economic sectors. However, the authors are aware of certain limitations that may have an additional impact on energy consumption, such as the temperature difference occurring in the analyzed years or the difference in the level of companies' production. Due to measurement points' dispersion (several hundred recipients located in places of various longitude and latitude of Poland) and the lack of information about the production levels, introducing additional assumptions would adversely affect the presentation of the results, which could ultimately lead to a misinterpretation of the impact of lockdowns on the electricity consumption.

#### *4.2. Methodology*

#### 4.2.1. Comparative Analysis

As mentioned, the data were collected in hourly resolution for each hour in 2019 and 2020. For the sake of other analyses, the dataset was arranged into daily, weekly, and monthly values. In the comparative analyses, it was decided to adjust the values of 2020 for one day. Thus, working days and days off overlapped to enable the comparison of daily differences in consumption volumes. The conducted analysis focused on differences in consumed energy volumes in hourly, daily, weekly, and monthly intervals in 2 subsequent years: in 2019, without restrictions associated with the COVID-19 pandemic; and 2020, during the pandemic.

Furthermore, the article analyzed energy demand profiles in 3 key groups of consumers. They were consistent with the Polish Classification of Activity, i.e., the set of the types of socio-economic activities undertaken by economic entities. The analyzed sections included: manufacturing (Section C), electricity, gas, steam, and air conditioning supply (Section D), and real estate activities, including the operation of shopping malls (Section L) [47].

#### 4.2.2. Coefficient of Variation

This part analyzed the daily and weekly values of consumed energy. Volatility analysis was employed for investigating total consumption values. The analyses used weekly intervals (the subsequent weeks of the analyzed years), a selected working day (Tuesday), and one of the days off (Saturday). In the subsequent weeks, after computing mean and standard deviation values, total volatility was estimated for the selected variables in 2019 and 2020.

The measure of volatility was the coefficient of variation defined as the ratio of volatility absolute measure to mean values. Most often, it is the ratio of a mean analyzed value to the value of mean standard deviation [48].

$$V = \frac{S}{M} \cdot 100\% \tag{1}$$

where *V*—coefficient of variation, *S*—standard deviation (from the sample), *M*—mean (from the sample).

The coefficient of variation indicates a degree of differentiation of the analyzed sample (sample's features). Depending on the results, one can conclude about the level of volatility, but this coefficient is a relative measure. It is commonly recognized that a coefficient of variation lower than 10% indicates the statistical insignificance of the tested relation [49].

#### 4.2.3. Forecast (Trend) and Difference Calculation

The last stage of the analysis was to compute a difference between energy consumed in subsequent weeks and the expected values of consumption. The latter was estimated using simple regression (linear regression) based on weekly values of consumption in the 4 weeks before introducing the first and second waves of restrictions. The analyzed period included both lockdowns.

#### **5. Results**

This section presents the results of the analysis of energy consumption by the business clients of the studied trading and sales companies in 2019 and 2020. Tables and charts highlight differences in the values of consumed energy in the annual perspective and in detail for the lockdowns. Additionally, the consumption volumes in three sections representing the key groups of consumers were analyzed. The following parts present the volatility analysis' results with the coefficients of variation estimated in the quarterly and yearly scales. Finally, after employing linear regression, there was estimated a trend of weekly energy consumption volume during the lockdowns based on the collected data.

Figure 3 presents the comparison of electricity consumption volumes in 2019 and 2020. The blue line marked consumption volumes in the hourly resolution in 2019; the red line represents values for 2020. The differences (only positive values, indicating lower energy consumption volumes in 2020) between volumes for 2019 and 2020 were presented as a black line. The mean hourly consumption volume for the whole of 2020 was 2 MWh higher, but during the lockdowns, the mean consumption was 14 MWh and 1 MWh lower in the first and second lockdown, respectively (Figures 4 and 5).

The confirmation of a significant decrease in the volume of energy consumption in the first lockdown is also visible in the analysis of total consumption for individual months (Figure 6). The first restrictions announced on 14 March 2020, caused a change of the expected increase in the energy consumption trend, observed before, e.g., in February. The following months of the first lockdown have brought additional declines. Compared with 2019, they were 13% in April and 4% in May when the strictest limitations were lifted. In June, the consumption volume was similar to the previous year. A significant increase in the consumption volume could be observed in the third quarter in the absolute values and relation to the same period in 2019. Another drop overlaps with the second wave of introducing severe restrictions. In October, the year-on-year value was even higher, even though the increasing energy consumption trend of 2019 was not maintained. In November 2020, the energy consumption was 1% lower than in the previous year, and the downward trend became clearly visible. The lifting of Another restriction (27 November) definitely impacted the consumption increase in December.

**Figure 3.** Comparative analysis of energy consumption in 2019–2020.

**Figure 4.** Comparative analysis of energy consumption 14 March–3 May (the first lockdown).

**Figure 5.** Comparative analysis of energy consumption 24 October–27 November (the second lockdown).

**Figure 6.** Comparison of energy consumption in 2019 and 2020 (difference 2019–2020).