This is the first part of a 3-part series on energy analytics and the opportunities for startups in this area.
Energy is the source of life on earth and in today’s global scenario, holds more strategic value than any other commodity. While the ongoing search for alternative fuels has gained a lot of momentum in the past few years, the ever-growing rate of depletion of conventional sources of energy is a cause of concern for all of us. Even as governments worldwide have been fretting over ways to manage these resources and the inflation attached to it, startups are coming up with solutions that are helping individuals and organisations manage their energy usage in the most effective ways by using the power of “big data” as a tool.
Energy wastage has bothered mankind since time immemorial. Let us look at a few stats:
- Power plants typically only turn about 30% of the energy input into usable electricity. Up to 75 % of the energy in the fuel is lost at the start of the process. (Source)
- The amount of energy wasted by the US economy in 2012 can power the UK for seven years. (Source)
- In India, 23.65% of the energy generated is lost in transmission. (Source)
- Power shortages (primarily owing to transmission and distributions losses) currently cost India 0.4% of its GDP. A large number of Indian businesses use backup energy sources and schedule production activities based on power shortages in their region; however this is not a long-term solution. (Source)
What is energy analytics?
Energy data analytics, as a field, is an amalgamation of the distinct yet interrelated processes of monitoring energy usage, gathering data, drawing meaningful inferences and taking subsequent corrective measures which eventually bring about significant improvements in energy efficiency, and in turn, cost savings. Additionally, analytics-led decision making can also improve productivity and reliability. The key questions that the process addresses are:
- How much energy is being consumed by the entity (individual/organisation)?
- How much of this energy is being wasted? Where are the points/sources of such wastage?
- Which appliances/machines/devices/processes consume the highest amount of energy?
- When does the energy consumption reach its peak?
- What is the state of appliances, machines or equipment that use energy?
- What are the key energy-related costs being currently incurred?
- How can the energy efficiency be improved?
The global energy efficiency market was worth at least USD 310 billion in 2014 and continues to grow at an astounding pace, according to a new report from the International Energy Agency. IEA predicts that energy efficiency will become the world’s “first fuel” in the years to come. While energy efficiency is a broad term that encompasses a lot of practices and techniques, energy analytics forms an important part of energy efficiency. The energy analytics market itself is expected to be worth USD 3.8 billion globally by 2020.
According to a 2013 study from Tata Consultancy Services titled “The Emerging Big Returns on Big Data,” companies in the utilities and energy/resources industries have the highest expectations for generating returns on their big data investments than firms in any other industry (see graph below).
Another very important point that makes the case for energy analytics is that companies and individuals are making a dedicated and conscious effort towards reducing their carbon footprint and their energy-related expenses. In addition, in hardware-intensive industries, even the cost of maintenance can be quite high. In light of these opportunities, energy analytics startups offer customised solutions to their clients and help them in cost-reduction, monitoring and control.
Energy analytics as a startup opportunity
Energy analytics is a very demanding process as it involves the use of sophisticated software engines to track energy consumption and extraction of meaningful inferences from the data. To get into the energy analytics game, a company needs large quantities of information in a format allowing for easy access and analysis (this comes from the client; the startups need to build hardware for recording this data); advanced analytical tools such as Hadoop and NoSQL and a team with varying (complementary) skills.
In part 2 of this series, we will explore some of the most prominent energy analytics startups and their business models.
Written by Rakshit Ranjan (Summer Intern, CIIE) & edited by Mohsin Bin Latheef (Program Manager, CIIE)