**Atherosclerosis and Current Anti-Oxidant Strategies for Atheroprotection**

Luigi Fabrizio Rodella and Gaia Favero

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/53035


**13.1 Intrinsic therapeutic effect**

The selection of antigen is most important for targeting. The target antigen is highly expressed in cancer cells but not on a normal cell. Single, as well as multiple targeting, can be achieved through the use of an engineered antibody. Multivalent antibodies not only block signaling but also overcome resistance through multiple targets [57].


**1. Introduction**

The chapter summarizes the main concept in Volcanology with an overview that will help to understand other chapters presented in this Volcanology Book. This chapter has been chosen, in particular, for under-graduate people who want to deepen their knowledge in Volcanology, producing several avenues that can help them to develop their own research interests—from volcanic geology to forecast volcanic eruption [1–13]. Some concepts about the constitution of the Earth must be described to better understand the volcanology base. We know that the Earth, broadly speaking, is stratified with a temperature around 6000°C at its center, as at the surface of the sun. The stratification gives some cloud on the production and genesis of the magma. The issue is very much complex but worth to investigate for the sake of clarity about magma generation. The Earth is stratified not only for temperature but also for density, minerals, and physics state as liquid versus solid. In fact, it is the fluid zone of the Earth (asthenosphere versus outer core), the areas much advocated for partial melting: The asthenosphere is the denser, weaker layer beneath the lithospheric mantle. It lies between about 100 and 410 km beneath the earth's surface. The temperature and pressure of the asthenosphere are so high that rocks soften and partly melt, becoming semi-molten. Earth's outer core is a liquid layer about 2400 km thick and composed of mostly iron and nickel that lies above the earth's solid inner core and below its mantle. Its outer boundary lies 2890 km beneath Earth's surface. Unlike the inner (or solid) core, the outer core is liquid (**Figure 1**). Hence, the Earth is made of several layers—(a) crust, mantle, inner and outer core. (b) Lithosphere, asthenosphere, mesosphere to core (**Figure 2**). The asthenosphere must be the most productive melt layer within the mantle structure.

**Figure 1.** *Earth with a window inside the planet (author's collection).*

#### **Figure 2.**

*Plot of the P and S wave velocity, and density versus depth from the surface to the core. Upper mantle with a profile of S wave velocity (Vs) and the seismic discontinuity (redrawn after Schmincke [14]).*


**5. Conclusion**

In this chapter, we have presented closed-form solutions for computing and updating the principal components of (dynamic) discrete and continuous point sets. The new principal components can be computed in constant time, when a constant number of points are added or deleted from the point set. This is a significant improvement of the commonly used approach, when the new principal components are computed from scratch, which takes linear time. The advantages of some of the theoretical results were verified and presented in the context of computing dynamic PCA bounding boxes in Dimitrov, Holst, Knauer & Kriegel (2009); Dimitrov et al. (2011).

An interesting open problem is to find a closed-form solutions for dynamical point sets different from convex polyhedra, for example, implicit surfaces or B-splines. An implementation of computing principal components in a dynamic, continuous setting could be a useful practical extension of the results presented here regarding continuous point sets. Applications of the results presented here in other fields, like computer vision or visualization, are of high interest.


*2.2. CFD Modeling*

The mesh was constructed for the boiler using 3,529,358 cells. This mesh was selected after assessing the sensitivity by comparing the degree of numerical di ffusion between coarser (1.23 million cells) and finer (5.47 million cells) meshes. In these meshes, the cell fineness was varied only in the burner zone to have a respective average volume of 0.0114, 0.0034, and 0.0022 m3/cell. Compared to the finer mesh, the selected one exhibited very small deviations in the key performance parameters (0.12% in carbon conversion, 1.9% in the exit NO concentration, and 0.2% in the heat absorption on the furnace wall). In the detailed comparison for the flow pattern along the vertical centerline, the deviations from the results of the finer mesh were 4.7% in the velocity profile and 0.71% in the temperature profile. By contrast, the coarser mesh had deviations of 17.58% and 1.11%, respectively. The computation time for the selected mesh to reach a converged solution was 69% of that for the finer mesh. The details of the mesh sensitivity test together with the iteration strategy have been reported elsewhere [19].

The CFD simulations were performed using ANSYS Fluent (version 17.2) [20] with submodels for reactions, turbulence, and radiation, most of which have been reviewed by Sankar et al. [5] as common models applied to a coal-fired boiler. The reaction submodels are summarized in Table 3. Coal particles were tracked using the discrete phase method for 10 size fractions ranging between 5.9 μm and 204 μm, with a total of 49,560 particles. FLASHCHAIN [21] was used to determine the input parameters for coal devolatilization in a drop tube furnace at 1200 ◦C which was close to the heat transfer condition of pulverized particles in the boiler. This code predicted the reaction dynamics based on the semi-empirical coal network mode to provide the product yields (tar, CO, CO2, H2O, CH4, C2H4, C2H6, C3H6, HCN, H2S, and solid char) and reaction kinetics as listed in the table. Because the heating rate was much faster than that in the proximate analysis, the total volatiles yield (58.56% daf) was larger than the volatile matter content (41.67% daf) in Table 1. Because of sharing the same mass source from devolatilization and having similar reaction rates, C2+ hydrocarbons were

simplified to an imaginary species of CxHy. The yield and composition of tar were modified to include the H and O fractions of char so that the char could be modelled as a pure carbon solid and ash. For simplicity, it also incorporated the two minor volatiles (HCN and H2S). Char conversion by O2, CO2, and H2O was solved using the unreacted core shrinking model (UCSM) [22] which is suitable for high-temperature reactions in the industrial-scale furnace and the release of the UBC in fly ash. This model considers the three competing rates of the heterogeneous reaction on the char core surface and the gas di ffusions onto the particle and through the ash layer. With the UCSM, the decrease in the reactivity toward the end of char conversion can be simulated, which was required to predict the UBC in fly ash. The multiple volatile products and the UCSM were implemented into the CFD code using user defined functions (UDF).

**Table 3.** Summary of submodels adopted for boiler simulation.

Gaseous reactions (R4)−(R10) were based on the global reaction scheme of Jones and Lindstedt [23] for hydrocarbon and the tar oxidation rate for (R4) was taken from Smoot and Smith [24]. In the reaction rate, the turbulence-chemistry interaction was considered using the kinetic rate/eddy dissipation rate model [25] with the realizable k-ε model employed for turbulence.

Regarding the heat transfer, radiation was solved using the discrete ordinate method with the weighted sum of the gray gases model for gas absorption [28]. In the boundary condition, the entire furnace wall (evaporator) was set to have the average water/steam temperature of 652.15 K with an overall heat transfer coe fficient of 250 W/m2K and inner wall emissivity of 0.7. The heat transfer coe fficient was taken as the average of measured values 3.51–4.37 m2K/kW of thermal resistance equivalent to 229–285 W/m2K depending on the coal types [29]. The tube bundles from primary SH to the economizer were simplified as porous zones, with local source terms calculated for flow resistance, convection, and radiation based on the detailed geometry and steam conditions [30]. In brief, the inertial resistance in the lateral and transverse directions was calculated using the Jakob correlation [31]:

$$
\Delta \mathbf{p} = \frac{2f' \mathbf{G}\_{\text{max}} \, ^2 \text{N}\_L}{\rho} \left(\frac{\mu\_s}{\mu}\right)^{0.14} \tag{1}
$$

$$f' = [0.044 + \frac{0.08\left(\frac{S\_L}{D}\right)}{\left(\frac{S\_T}{D} - 1\right)^{0.43 + 1.13D/S\_L}}]Re^{-0.15} \tag{2}$$

Similarly, the heat transfer rate in each cell was calculated as the sum of convection (.*qconv*) and radiation (.*qrad*) for the specific tube surface area per unit volume (*As*):

$$\dot{q}\_{\rm conv} = f\_{\rm conv} A\_s \frac{k \,\mathrm{Nu}}{D} (T\_{\rm gus} - T\_s) \left[ \mathrm{W/m^3} \right] \tag{3}$$

$$\dot{q}\_{rad} = f\_{rad} \varepsilon \sigma A\_s \left( T\_{\text{gas}}{}^4 - T\_s{}^4 \right) \left[ \text{W/} \text{m}^3 \right] \tag{4}$$

The Nusselt number (*Nu*) for convection was determined from the Zukauskas correlation [32]:

$$Nu = 0.40 Re\_D^{0.6} Pr^{0.36} \tag{5}$$

The above equations include two correction factors (*fconv* and *frad*) that were introduced to consider the slagging/fouling factors and tuned to match the design values. The formulations for the flow resistance and heat transfer rates were implemented using UDFs.

NO reactions were calculated by post-processing of the CFD results. Thermal NO reactions were based on the extended Zeldovich mechanism with the rate constants taken from Hanson and Salimian [26] and the radical concentrations acquired from the respective partial equilibrium assumptions. In the fuel NO mechanism [27], the partitioning of fuel-N between volatile-N and char-N was determined using FLASHCHAIN. The release of N intermediates during the devolatilization of the low rank coal was assumed to be HCN 5:NH3 1, whereas the char-N was converted directly to NO. The reduction of NO to N2 on the active char surface was considered with a microscopic surface area that was assumed to be 100 m2/g. Prompt NO was ignored because its concentration is known to be minor [3].


*2.2. Characterization*

The microstructure of the fibers without and with coatings was characterized by scanning electron microscope (SEM) equipped with energy dispersed spectroscopy (EDS) (HITACHI FEG S4800, HITACHI, Tokyo, Japan). The phase composition of the fibers without and with coatings was analyzed by XRD equipped with a D8 ADVANCE diffractometer using monochromatic Cu Kα radiation (Bruker, Hamburg, Germany). The chemical composition of the fibers without and with coatings was traced by XPS using Al Kα radiation of energy 1486.6 eV (Thermo ESCALAB 250, Thermo Scientific, Waltham, MA, USA). TEM analysis was carried out on Tecnai F20 operating at 200 kV, and the samples were prepared according to [16].

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

#### *3.1. Characteristics of the CVD SiC Coatings*

The surface of the fibers without and with SiC coatings was observed by SEM. As shown in Figure 2, the as-received fibers showed a smooth and homogeneous surface, except for a few white sheet alumina micro-grains. After depositing for 2 h with SiC coatings, the fiber surface was no longer smooth and a large number of micro-bulges with the largest diameter of about 1 μm appeared. The coatings were generally dense, without any micro-cracks or pores.

The phase composition of the fibers without and with SiC coatings was analyzed by XRD. As shown in Figure 3a, diffraction peaks of mullite and γ-Al2O3 were detected for the as-received fibers. After being coated with SiC coatings (Figure 3b), three accessional peaks (2θ = 35.60◦, 60.06◦ and 71.83◦) were observed, which respectively belonged to the (111), (220) and (311) crystal planes of β-SiC. It is clear that the coatings were mainly composed of β-SiC phase [17].

**Figure 2.** Surface morphology of the fibers without (**a**) and with (**b**) coatings.

**Figure 3.** XRD patterns of the fibers without (**a**) and with (**b**) SiC coatings.

The chemical composition of the fibers without and with SiC coatings was analyzed by XPS. As shown in the survey scan (Figure 4a), the peaks of Al 2*s* and Al 2*p* disappeared after depositing with SiC coatings. Element analysis of the coated fibers revealed that the content of C increased while the contents of Al, Si and O decreased greatly. Moreover, the Cl 2*p*3/2 (~198 eV) peak and Cl 2*s* (~271 eV) peak were detected [18], indicating the absorption of HCl. As shown in Figure 4b, the C 1s peak could be fitted into two sub peaks, C–Si bond (282.6 eV) and C–C bond (283.2 eV) [19], which was attributed to SiC and carbon, respectively. As shown in Figure 4c, the Si 2*p* peak positioned at 100.9 eV was also attributed to Si–C bonding. In conclusion, the coatings were composed of β-SiC and free carbon.

An HR-TEM image of SiC coatings deposited for 2 h on the fibers is displayed in Figure 5a. It could be found that the coatings consisted of large quantities of turbostratic carbon and some cubic β-SiC micro-grains oriented in the (111) crystal plane with 0.250 nm spacing. The result was coincident with XPS analysis and revealed that the coatings were rich in carbon. As shown in the SAED pattern (Figure 5b), the diffraction rings could be indexed as (111), (220) and (311) planes of cubic β-SiC [20].

**Figure 4.** XPS analysis of the fibers: (**a**) survey scan of as-received ones and those with coatings, (**b**) C 1s spectra and (**c**) Si 2p spectra of those with coatings.

**Figure 5.** TEM analysis of the fibers with coatings deposited for 2 h: (**a**) HR-TEM image and (**b**) SAED pattern of coatings.

#### *3.2. Thickness Control of the CVD SiC Coatings*

The cross-sectional morphology of the samples deposited for different amounts of time is shown in Figure 6. It is apparent that the fibers were surrounded closely by SiC coatings. The coating thickness was measured 10 times at different points to obtain the average value. As shown in Table 1, the coating thickness increased with the deposition time, and the value of about 1.5 μm was obtained after depositing for 4 h. Figure 7 shows the effect of the deposition time on the coating thickness. It could be found that the thickness of the coatings deposited for 1, 2 and 4 h increased exponentially with the deposition time. However, the exterior of the coatings became looser as the deposition time increased above 2 h, owing to the reduction of the adhesion force on the coating surface, thus leading to the deposition difficulty of new raw materials [21,22].

**Figure 6.** Cross-sectional morphology of the coatings deposited for: (**a**) 1 h, (**b**) 2 h and (**c**) 4 h.

**Table 1.** Measured thickness and theoretical thickness of the coatings.

**Figure 7.** Measured thickness and theoretical thickness of the coatings deposited for different amounts of time.

In this study, the coating thickness (*d*) was also calculated according to the corresponding relationship between volume and weight for the coatings and fibers, which was summarized by Y. Zheng et al. [23]:

$$d = r\_0 \left[ (1 + \eta c)^{\frac{1}{2}} - 1 \right] \tag{1}$$

where *r*0 is the original fiber radius; *c* = (*f*/*c*), where *c* and *f* are the density of the coatings and fibers, respectively; and η = (ω*c*/ω*f*)%, where ω*c* and ω*f* are the weight of the coatings and fibers.

The original fiber radius (*r*0) was about 10 μm. The density of the pure SiC was 3.20 g/cm3. As the coatings were rich in carbon, the coating density (*c*) was not constant, and should be calculated according to the volume mixing law, where the volume ratio of the carbon and SiC in the coatings can be obtained by element ratio from XPS analysis. Then, the parameter *c* can be expressed as:

$$
\mathfrak{p}\_c = 2.764 \ e^{-0.02t} \tag{2}
$$

Combining Equations (1) and (2), and adopting *f* = 3.0 g/cm3, the coating thickness could be obtained and the results are shown in Table 1:

$$d = r\_0 \left[ \left( 1 + 1.085 \eta e^{0.02t} \right)^{\frac{1}{2}} - 1 \right] \tag{3}$$

As shown in Figure 7, both the measured and calculated coating thickness increased exponentially with the deposition time. The results of both methods were quite consistent in general. The calculated thickness was a little larger than the measured one. There were two main reasons: one was that the volume ratio of the carbon in the coatings was not accurate due to the ladder-like decrease of the carbon with the deposition time; the other one was that the coatings were a little loose. As a result, the actual coating density was di fferent from the theoretical one. However, the calculated thickness could still reflect the actual one, and it was meaningful for the thickness control of CVD coatings.

#### *3.3. Deposition Mechanism Research*

The chemical reaction process of CVD SiC coatings using MTS as a raw material was investigated to explain the deposition mechanism for the coatings. As the bond energy for C–Si, C–H and Si–Cl are 314, 337 and 466 J/mol, respectively, the breakdown of the C–Si bond occurred first at high temperature. The reaction process can be summarized as follows [24,25]:

$$\text{CH}\_3\text{SiCl}\_3 \leftrightarrow \text{CH}\_3\cdot + \text{SiCl}\_3\cdot \tag{4}$$

$$\text{CH}\_3\text{-}\leftrightarrow \text{\textasciicircum}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\raisebox{0.5ex}{\text{ }}}\text{\frac{0.5ex}{\text{ }}}\text{\frac{0.5ex}{\text{ }}}\text{\frac{0.5ex}{\text{ }}}\text{\frac{0.5ex}{\text{ }}}\text{\frac{0.5ex}{\text{ }}}\text{\frac{0.5ex}{\text{ }}}\text{\frac{0.5ex}{\text{ }}}\text{\frac{0.5ex}{\text{ }}}\text{\frac{0.5ex}{\text{ }}}\text{\frac{0.5ex}{\text{ }}}\text{\frac{0.5ex}{\text{ }}}\text{\frac{0.5ex}{\text{ }}}\text{\$$

$$\text{SiCl}\_3\text{} + 3/2\text{H}\_2 \leftrightarrow \text{\textasciicircum} + 3\text{HCl} \tag{6}$$

$$
\langle \text{Si} \rangle + \langle \text{C} \rangle \to \text{SiC} \tag{7}
$$

$$
\langle \text{Si} \rangle \to \text{Si} \tag{8}
$$

$$
\langle \mathbf{C} \rangle \to \mathbf{C} \tag{9}
$$

where < Si > and < C > correspond to the intermediate states of Si and C, which can form SiC as shown in Equation (7). It can be concluded from Equations (5)–(7) that hydrogen has a great e ffect on the formation of silicon or free carbon during the CVD process. That is to say, pure SiC coatings can hardly be prepared via CVD process, and they will always be rich in silicon or free carbon. It is reported in the literature that coatings deposited on carbon plate, fibers or composites by CVD using MTS at temperatures above 1200 ◦C are usually composed of SiC, and Si impurities form at lower deposition temperature [25–27]. In this study, the coatings deposited on NextelTM440 fibers by CVD using MTS at 1100 ◦C were composed of SiC and free carbon.

In addition, the cross-sectional morphology of the coated fibers (Figure 6a–c) revealed that the coatings were loose. In order to investigate structure and composition of the interior of the coatings, the fibers with SiC coatings deposited for 2 h were ultrasonically treated to thin the coatings from 364.2 to 97.6 nm. As shown in Figure 8a,b, many hemispherical bulges with uniform diameter of about 4 μm with a disorderly distribution on the fiber surface. The magnified SEM image (Figure 8c) shows that the plane area of the coatings was dense and smooth, without any defects. Furthermore, the EDS analysis (Figure 8e–f) revealed that after ultrasonic treatment, the fibers were totally covered by thin carbon layers with few SiC bulges. Compared to the original coatings (Figure 4b), no Cl peak was detected, indicating a dense structure for the interior of the coatings, without any absorption of HCl.

**Figure 8.** Surface morphology and EDS analysis of the coatings deposited for 2 h after ultrasonic treatment: (**a**) overview image, (**b**) detailed image with marked areas for the EDS measurement, (**c**) detailed image for smooth area of the fiber surface, (**d**) detailed image for the fracture surface, (**e**) EDS measurement of smooth area and (**f**) EDS measurement of bulges.

As a result, the deposition mechanism can be described. As shown in Figure 2b and schematized in Figure 9a, there were a few white sheet alumina micro-grains with disorderly distribution on the original fibers. Theses micro-grains not only increased the specific surface area but also had high catalysis activity, which led to the < Si > and < C > attaching onto them and reacting to form spherical SiC particles rapidly. At the same time, MTS was decompounding and depositing on fibers per Equations (4)–(9) to form carbon-rich SiC coatings (as shown in Figure 9b). As the deposition process continued and the coating thickness increased, the growth rate of spherical SiC particles and deposition rate of SiC coatings gradually became close to each other, and a relatively smooth surface was finally obtained (Figure 9c). As mentioned previously, SiC coatings became looser as the coating thickness increased due to the reduction of adhesion force on the coating surface.

**Figure 9.** Schematic of the deposition mechanism for SiC coatings on NextelTM440 fibers: (**a**) the original fiber, (**b**) initial stage of deposition and (**c**) later stage of deposition.


**2. Model of Low Voltage grid**

The power electronics based low voltage network model is obtained using the SimPowerSystems Toolbox of Matlab/Simulink. The models include the Medium/Low voltage (MV/LV) transformer, the distribution lines, the most significant electrical loads and the microgenerators connected to the grid.

#### **2.1 Distribution transformer**

It is assumed that the distribution MV/LV transformer is ΔYN, with the secondary neutral directly connected to ground. The transformer used in the simulations is fed by a 30kV voltage on MV (medium voltage) and, in LV (Low Voltage) the line/phase voltage is 400V / 230V. The magnetization and the primary and secondary windings reactance and resistance are calculated from the transformer manufacturer no-load, short-circuit and nominal load tests [Elgerd, 1985].

Fig. 1. Equivalent single phase model of a distribution transformer

From the no-load test, applying the nominal voltage *Un* to the secondary side of the transformer, and leaving the primary side open, it is possible to obtain the transformer magnetizing current *Im*. As the series impedance is much lower than the magnetizing impedance, it is assumed that the iron losses are nearly equal to the no-load losses *P*0. Then, from the nominal voltage *Un*, the magnetizing current *Im* and the no load losses *P*0, it is possible to determine the transformer magnetizing reactance and resistance. The magnetizing conductance is given by (1).

$$\mathbf{G}\_m = \frac{P\_0}{\mathbf{U}\_n^2} \tag{1}$$

The magnetizing resistance *Rm* (2) is obtained from the magnetizing conductance *Gm* (1).

$$R\_{sv} = \frac{1}{G\_{sv}}\tag{2}$$

From the magnetizing current *Im* and the magnetizing conductance *Rm* it is possible to determine the magnetizing susceptance *Bm* (3):

From the obtained results, active μG have the capability to guarantee an overall Power Quality improvement (voltage THD decrease and Power Factor increase) allowing a voltage THD decrease when compared to voltage THD values obtained with conventional μG.

The power electronics based low voltage network model is obtained using the SimPowerSystems Toolbox of Matlab/Simulink. The models include the Medium/Low voltage (MV/LV) transformer, the distribution lines, the most significant electrical loads and

It is assumed that the distribution MV/LV transformer is ΔYN, with the secondary neutral directly connected to ground. The transformer used in the simulations is fed by a 30kV voltage on MV (medium voltage) and, in LV (Low Voltage) the line/phase voltage is 400V / 230V. The magnetization and the primary and secondary windings reactance and resistance are calculated from the transformer manufacturer no-load, short-circuit and nominal load

*R1 X1 R2 X2*

From the no-load test, applying the nominal voltage *Un* to the secondary side of the transformer, and leaving the primary side open, it is possible to obtain the transformer magnetizing current *Im*. As the series impedance is much lower than the magnetizing impedance, it is assumed that the iron losses are nearly equal to the no-load losses *P*0. Then, from the nominal voltage *Un*, the magnetizing current *Im* and the no load losses *P*0, it is possible to determine the transformer magnetizing reactance and resistance. The

> 0 *m* 2 *n*

> > 1

*m*

= (1)

*G*= (2)

*P G U*

The magnetizing resistance *Rm* (2) is obtained from the magnetizing conductance *Gm* (1).

*m*

From the magnetizing current *Im* and the magnetizing conductance *Rm* it is possible to

*R*

*Bm Gm*

Fig. 1. Equivalent single phase model of a distribution transformer

**2. Model of Low Voltage grid**

**2.1 Distribution transformer**

tests [Elgerd, 1985].

the microgenerators connected to the grid.

magnetizing conductance is given by (1).

determine the magnetizing susceptance *Bm* (3):

$$B\_m = -\sqrt{\left(\frac{I\_m}{\mathcal{U}\_n}\right)^2 - G\_m^2} \tag{3}$$

The magnetizing reactance *Xm* is given by (4):

$$X\_m = \frac{1}{B\_m} \tag{4}$$

The magnetizing impedance is much higher than the series branch impedances (Fig. 1). Then, from the short-circuit test, it is possible to obtain the short-circuit impedance *Zcc* (5) and the total resistance *Rt* (6) from the transformer primary and secondary windings, knowing the short-circuit voltage *Ucc*, necessary to guarantee the current nominal value *In* and the short-circuit losses *Pcc*.

$$Z\_{cc} = \frac{\mathcal{U}\_{cc}}{I\_n} \tag{5}$$

$$R\_t = \frac{P\_{cc}}{I\_n^2} \tag{6}$$

Then, from (5) and (6) it is possible to determine the leakage reactance *Xt* (7):

$$X\_t = \sqrt{Z\_{cc}^2 - R\_t^2} \tag{7}$$

The resistance and leakage reactance from the primary and secondary windings may be assumed to be equal. Then:

$$R\_1 = R\_2 = \frac{R\_t}{2} \tag{8}$$

$$X\_1 = X\_2 = \frac{X\_t}{2} \tag{9}$$

In this work a 400kVA 30kV/400V distribution transformer (base values *Sb*=400kVA, *Ub*=30kV, /( 3 ) *bb b IS U* = ) is used. From the no-load test a magnetizing current *Im*=2.9% and no-load losses of *P0*=1450W are considered. From the short-circuit test it is assumed *Ucc*=4.5%, with nominal current *In* (1 pu) and short-circuit losses *Pcc*=8.8 kW.

#### **2.2 Distribution cables**

The distribution cables models are based on the π model (Fig. 2) and their section is chosen according to the current nominal values. The series resistance and inductance and the shunt admittance may be obtained from the manufacturers values depending on the cables section and length.

In LV distribution networks four-wire cables are used (three phase conductors and a neutral conductor insulated separately), all enclosed by an outer polyethylene insulation mantle. Usually the conductors are sector shaped. The shunt and series impedance are determined by the physical construction of the cable.

Design of a Virtual Lab to Evaluate and Mitigate

Power Quality Problems Introduced by Microgeneration 189

a)

Fundamental (50Hz) = 1.883 , THD= 1.66%

0 5 10 15 20 25 0

Harmonic order

Nonlinear loads are assumed to be mainly represented as diode rectifiers and are divided in

The first group includes low power electronic equipment as TV sets, DVD players or computers. Usually, these electronic apparatus have isolated DC supplies connected to the grid through single phase rectifiers and they can be modelled as their first stage converter: a

D1

D2

*Co*

D4 D3

Fig. 4. Grid voltage and current waveform obtained for a refrigerator: a) Measured with a Fluke 435, THDi=10.8% and PF=0.57; b) Obtained with the simulated model, considering

0.5

THDv=5%; c) Simulated current harmonics, THDi=1.66% and PF=0.57

single phase rectifier feeding a DC *Ro*//*Co* load (Fig. 5) [Mohan et all, 1995].

*L*

Fig. 5. Single phase rectifier as a model for the majority of electronic apparatus

1

Mag (% of Fundamental)

three groups depending on their rated power.

Grid

**2.4 Nonlinear loads**

1.5

0.02 0.025 0.03 0.035 0.04 0.045 0.05 0.055 0.06

c)

*Ro*

*Vo*

b)

230V 10A

Fig. 2. π model of the distribution electrical network

Based on the single phase model of Fig.2, the model of a three phase distribution cable is obtained, Fig. 3 [Ciric et all 2003], [Ciric et all 2005].

Fig. 3. Modified π model of the distribution electrical network

The series resistance *R* (Ω/km) [Jensen et all, 2001] depends on the cable internal resistance, on the ground resistance (there is no screen and the current diverted to ground must be included in the model) and on the proximity effect resistance. The skin effect and the proximity effect result in the increase of the conductors resistance.

The cable apparent inductance *Ls* depends on the self inductance, on the mutual inductance and on the inductance due to non-ideal ground.

The cable shunt admittance depends on the capacitances between conductors and on the conductors to ground capacitances [Jensen et all, 2001].

In overhead lines only the series impedance is considered. The capacitance is usually negligible.

Both for underground cables and overhead lines, the length should be adequate to guarantee their protection, according to the manufacturer values, and to assure that despite the voltage drops, the compliance with RMS voltage standard values [EN 50160] is always guaranteed.

#### **2.3 Linear loads**

Linear loads are represented as simple resistances (R) and inductances (RL). Resistive loads may be used to simulate incandescent lamps or conventional heaters, whether inductive loads may be used to simulate refrigerators, according to the measurements performed with a FLUKE 435 and shown in figure 4.

*R L*

Fig. 2. π model of the distribution electrical network

obtained, Fig. 3 [Ciric et all 2003], [Ciric et all 2005].

*CA /2*

*A*

*B*

*C*

*N*

*G*

negligible.

guaranteed.

**2.3 Linear loads**

a FLUKE 435 and shown in figure 4.

*CB /2*

and on the inductance due to non-ideal ground.

conductors to ground capacitances [Jensen et all, 2001].

*CC /2*

*CN /2*

Fig. 3. Modified π model of the distribution electrical network

proximity effect result in the increase of the conductors resistance.

*CC /2 CC /2*

Based on the single phase model of Fig.2, the model of a three phase distribution cable is

*RA LA*

*RB LB*

*CA /2*

*CB /2*

*CC /2*

*CN /2*

*RC LC*

*RN LN*

The series resistance *R* (Ω/km) [Jensen et all, 2001] depends on the cable internal resistance, on the ground resistance (there is no screen and the current diverted to ground must be included in the model) and on the proximity effect resistance. The skin effect and the

The cable apparent inductance *Ls* depends on the self inductance, on the mutual inductance

The cable shunt admittance depends on the capacitances between conductors and on the

In overhead lines only the series impedance is considered. The capacitance is usually

Both for underground cables and overhead lines, the length should be adequate to guarantee their protection, according to the manufacturer values, and to assure that despite the voltage drops, the compliance with RMS voltage standard values [EN 50160] is always

Linear loads are represented as simple resistances (R) and inductances (RL). Resistive loads may be used to simulate incandescent lamps or conventional heaters, whether inductive loads may be used to simulate refrigerators, according to the measurements performed with

Fig. 4. Grid voltage and current waveform obtained for a refrigerator: a) Measured with a Fluke 435, THDi=10.8% and PF=0.57; b) Obtained with the simulated model, considering THDv=5%; c) Simulated current harmonics, THDi=1.66% and PF=0.57

#### **2.4 Nonlinear loads**

Nonlinear loads are assumed to be mainly represented as diode rectifiers and are divided in three groups depending on their rated power.

The first group includes low power electronic equipment as TV sets, DVD players or computers. Usually, these electronic apparatus have isolated DC supplies connected to the grid through single phase rectifiers and they can be modelled as their first stage converter: a single phase rectifier feeding a DC *Ro*//*Co* load (Fig. 5) [Mohan et all, 1995].

Fig. 5. Single phase rectifier as a model for the majority of electronic apparatus

Design of a Virtual Lab to Evaluate and Mitigate

0.6 0.605 0.61 0.615 0.62 0.625 0.63 0.635 0.64

230V 10A

0.6 0.605 0.61 0.615 0.62 0.625 0.63 0.635 0.64

lower power equipment as TV sets.

Simulated current harmonics, THDi=45% and PF=0.5

230V 10A

Power Quality Problems Introduced by Microgeneration 191

c)

e)

Fig. 7. Grid voltage and current waveform obtained for a washing machine; a) b) Measured with a Fluke 435, THDi=46.7%; c) Obtained with the simulated model, considering voltage THDv=5%; d) Simulated current harmonics, THDi=47.85% and PF=0.76; e) Obtained with the simulated model, considering voltage THDv=5% and a saturated inductance; f)

To smooth the current absorbed from the LV network, the rectifier is connected to the grid through a filtering inductance, which is calculated as a percentage of the output load impedance (3), where *f* represents the grid frequency and *k* is a constant, usually *k*=0.03 for

> 2 *o*

*R k R L f* = π

10 20

10

20

Mag (% of Fundamental)

30

40

30 40 50

Mag (% of Fundamental)

a) b)

Fundamental (50Hz) = 5.712 , THD= 47.85%

0 5 10 15 20 25 0

Harmonic order

Fundamental (50Hz) = 4.933 , THD= 45.00%

0 5 10 15 20 25 0

Harmonic order

(12)

d)

f)

Fig. 6 shows the voltage and current measurements obtained for a TV set and the equivalent simulated waveforms.

Fig. 6. Grid voltage and current waveform obtained for a TV set; a) b) Measured with a Fluke 435, THDi=65.6% and PF=0.75; c) Obtained with the simulated model, considering voltage THDv=5%; d) Simulated current harmonics, THDi=69.9% and PF=0.76

Fig. 7 shows the voltage and current measurements obtained for a washing machine and the equivalent simulated waveforms.

The virtual lab models of these non linear loads are sized based on their rated power. Then, assuming an adequate DC voltage *Vo av*, the value of the equivalent output resistance *Ro* is obtained from (10). For the TV set an output voltage average value *Vo av*=300V is assumed.

$$R\_o = \frac{V\_{o\_w}^2}{P} \tag{10}$$

The capacitor *Co* is designed to limit the output voltage ripple Δ*Vo*. Also, it depends on the output voltage average value *Vo av*, on the equivalent output resistance *Ro*, and on the time interval when all the diodes are OFF (approximately equal to one half of the grid period Δ*t*=10ms). In the simulations, the ripple is assumed to be lower than Δ*Vo*=50V.

$$\mathbf{C}\_o = \frac{V\_{o\_w}}{R\_o} \frac{\Delta t}{\Delta V\_o} \tag{11}$$

Fig. 6 shows the voltage and current measurements obtained for a TV set and the equivalent

c)

Fig. 6. Grid voltage and current waveform obtained for a TV set; a) b) Measured with a Fluke 435, THDi=65.6% and PF=0.75; c) Obtained with the simulated model, considering

Fig. 7 shows the voltage and current measurements obtained for a washing machine and the

The virtual lab models of these non linear loads are sized based on their rated power. Then,

*o V*

The capacitor *Co* is designed to limit the output voltage ripple Δ*Vo*. Also, it depends on the

interval when all the diodes are OFF (approximately equal to one half of the grid period

*av o*

*V t C R V*

*o o*

*R*

Δ*t*=10ms). In the simulations, the ripple is assumed to be lower than Δ*Vo*=50V.

*o*

2 *av o*

voltage THDv=5%; d) Simulated current harmonics, THDi=69.9% and PF=0.76

obtained from (10). For the TV set an output voltage average value *Vo*

Mag (% of Fundamental)

a) b)

Fundamental (50Hz) = 0.9027 , THD= 69.93%

0 5 10 15 20 25 0

Harmonic order

*av*, the value of the equivalent output resistance *Ro* is

*av*, on the equivalent output resistance *Ro*, and on the time

*P* ≈ (10)

Δ ≈ Δ (11)

*av*=300V is assumed.

d)

simulated waveforms.

0.06 0.065 0.07 0.075 0.08 0.085 0.09 0.095 0.1

equivalent simulated waveforms.

output voltage average value *Vo*

assuming an adequate DC voltage *Vo*

230V 5A

Fig. 7. Grid voltage and current waveform obtained for a washing machine; a) b) Measured with a Fluke 435, THDi=46.7%; c) Obtained with the simulated model, considering voltage THDv=5%; d) Simulated current harmonics, THDi=47.85% and PF=0.76; e) Obtained with the simulated model, considering voltage THDv=5% and a saturated inductance; f) Simulated current harmonics, THDi=45% and PF=0.5

To smooth the current absorbed from the LV network, the rectifier is connected to the grid through a filtering inductance, which is calculated as a percentage of the output load impedance (3), where *f* represents the grid frequency and *k* is a constant, usually *k*=0.03 for lower power equipment as TV sets.

$$L\_{\aleph} = \frac{k \, R\_{\circ}}{2 \pi \mathfrak{f}} \tag{12}$$

Design of a Virtual Lab to Evaluate and Mitigate

**2.5 Conventional single phase microgenerators**

 Boost stage + MPPT

Fig. 10. Block diagram of a conventional μG

a DC voltage source *UDC* (Fig. 11).

S1

S2

Fig. 11. Model of the single phase microgenerator

Photovoltaic Panel

UDC

unitary power factor.

*Vo*

Power Quality Problems Introduced by Microgeneration 193

In this model the equivalent output load may be calculated from (1) assuming *P*=6kW and

Microgenerators are connected to the LV grid through single phase VSI (voltage source inverters) (Fig. 10) [Pogaku et all, 2007] and they are designed to guarantee the compliance with international standards (as EN 50438) and to have characteristics similar to the authorized equipment (maximum rated power, current THD and input power factor).

For simplicity reasons and minimization of simulation times, the microgenerators are simulated considering only the grid connection stage, as current controlled inverters fed by

It is assumed that the VSI is connected to the grid through a filtering inductance designed to guarantee a current ripple lower than Δ*Igrid*. To minimize filtering, a three level PWM is used. Then, the inductance *LL* (Fig. 11) is calculated according to (13), where *UDC* is the DC

4

*U L*

*L*

S4

The VSI is controlled using a linear control approach, assuming that the maximum power is supplied to the grid and guaranteeing that the current injected in LV grid has a nearly

*v*PWM

S3

*DC*

*s grid*

*RL*

link voltage, *fs* is the switching frequency and Δ*Igrid* is the current ripple.

Voltage Source Inverter

UDC vPWM Vgrid

AC Filter

*f I* = Δ (13)

*LL*

*i grid* Grid

*Vgrid*

9 shows the voltage and current waveforms obtained with the designed model.

*av*=520V. The output filter capacitor is obtained from (2) considering Δ*t*=3.3ms (in a 6 pulse rectifier Δ*t=T*/6). The input filtering inductance is obtained from (3) considering *k*=0.03. Fig.

As an example, with the designed model it is possible to obtain current waveforms similar to those measured on a TV set (Fig. 6), using the previously calculated values of *Ro*, *Co* and *LR* and assuming *P*=150W.

For other higher power household appliances as modern washing or dishwashing machines, a similar model may be used but the average rated power *P* should be higher, as well as the input filtering inductance. The voltage and current measurements obtained for a washing machine are shown in Fig. 7 a) b) and the equivalent simulated waveforms are shown in figures 7 c) d) where *P*=1kW, and the filtering inductance is obtained from (12) assuming *k*=0.1. Comparing figures 7 b) and 7 d) the measured and simulated currents THD as well as the harmonic contents are similar. Still, the current waveforms of Fig. 7 a) c) present some differences. To obtain similar current waveforms, the saturation effect of the input inductance should be considered, as shown in Fig. 7 c) d).

Even though the majority of LV grid connected loads are single phase, there may be a few three phase loads, as welding machines or three phase drives in small industries. Again, this equipment may be represented as their first stage converter, usually a three phase diode rectifier feeding an equivalent *Ro3*//*Co3* load (Fig. 8).

Fig. 8. Three phase rectifier as a model for an electronic equipment of a small industry

Fig. 9. a) Grid voltage and current waveform obtained for a three phase rectifier obtained with the simulated model, considering voltage THDv=5%; b) Current harmonics and THDi=34.86%, PF=0.91

As an example, with the designed model it is possible to obtain current waveforms similar to those measured on a TV set (Fig. 6), using the previously calculated values of *Ro*, *Co* and

For other higher power household appliances as modern washing or dishwashing machines, a similar model may be used but the average rated power *P* should be higher, as well as the input filtering inductance. The voltage and current measurements obtained for a washing machine are shown in Fig. 7 a) b) and the equivalent simulated waveforms are shown in figures 7 c) d) where *P*=1kW, and the filtering inductance is obtained from (12) assuming *k*=0.1. Comparing figures 7 b) and 7 d) the measured and simulated currents THD as well as the harmonic contents are similar. Still, the current waveforms of Fig. 7 a) c) present some differences. To obtain similar current waveforms, the saturation effect of the input

Even though the majority of LV grid connected loads are single phase, there may be a few three phase loads, as welding machines or three phase drives in small industries. Again, this equipment may be represented as their first stage converter, usually a three phase diode

D3

D6

D1

D4

Fig. 8. Three phase rectifier as a model for an electronic equipment of a small industry

a)

Fig. 9. a) Grid voltage and current waveform obtained for a three phase rectifier obtained with the simulated model, considering voltage THDv=5%; b) Current harmonics and

Mag (% of Fundamental)

*Ro3*

0 5 10 15 20 25 0

Fundamental (50Hz) = 12.96 , THD= 34.86%

Harmonic order

b)

*Vo3*

*Co3*

D2

D5

*LR* and assuming *P*=150W.

inductance should be considered, as shown in Fig. 7 c) d).

*L*

*L*

*L*

rectifier feeding an equivalent *Ro3*//*Co3* load (Fig. 8).

*Vgrid1*

*Vgrid2*

*Vgrid3*

0.06 0.065 0.07 0.075 0.08 0.085 0.09 0.095 0.1

THDi=34.86%, PF=0.91

230V 20A

In this model the equivalent output load may be calculated from (1) assuming *P*=6kW and *Vo av*=520V. The output filter capacitor is obtained from (2) considering Δ*t*=3.3ms (in a 6 pulse rectifier Δ*t=T*/6). The input filtering inductance is obtained from (3) considering *k*=0.03. Fig. 9 shows the voltage and current waveforms obtained with the designed model.

#### **2.5 Conventional single phase microgenerators**

Microgenerators are connected to the LV grid through single phase VSI (voltage source inverters) (Fig. 10) [Pogaku et all, 2007] and they are designed to guarantee the compliance with international standards (as EN 50438) and to have characteristics similar to the authorized equipment (maximum rated power, current THD and input power factor).

Fig. 10. Block diagram of a conventional μG

For simplicity reasons and minimization of simulation times, the microgenerators are simulated considering only the grid connection stage, as current controlled inverters fed by a DC voltage source *UDC* (Fig. 11).

It is assumed that the VSI is connected to the grid through a filtering inductance designed to guarantee a current ripple lower than Δ*Igrid*. To minimize filtering, a three level PWM is used. Then, the inductance *LL* (Fig. 11) is calculated according to (13), where *UDC* is the DC link voltage, *fs* is the switching frequency and Δ*Igrid* is the current ripple.

$$L\_{\rm L} = \frac{\mathcal{U}\_{\rm DC}}{\mathbf{4} \, f\_s \, \Delta I\_{g\rm rld}} \tag{13}$$

Fig. 11. Model of the single phase microgenerator

The VSI is controlled using a linear control approach, assuming that the maximum power is supplied to the grid and guaranteeing that the current injected in LV grid has a nearly unitary power factor.

Generally, the association of the modulator and the power converter may be represented as a first order model (14), with a gain *KD* and a dominant pole dependent on the average delay time *Td* (usually one half of the switching period *Td*=*Ts*/2) [Rashid, 2007].

$$\mathbf{G}\_{\circ}(\mathbf{s}) = \frac{\upsilon\_{\text{PWM}\_{w}}(\mathbf{s})}{\mu\_{\text{c}}(\mathbf{s})} = \frac{K\_{\text{D}}}{sT\_{d} + 1} \tag{14}$$

The incremental gain *KD* (15) depends on *UDC* voltage and on the maximum value max *uc* of the triangular modulator voltage.

$$K\_D = \frac{\mathcal{U}\_{DC}}{\mu\_{c\_{\text{max}}}} \tag{15}$$

Design of a Virtual Lab to Evaluate and Mitigate

0.06 0.065 0.07 0.075 0.08 0.085 0.09 0.095 0.1

10kHz and Δ*Igrid*<0.1 *Igrid*.

a non-linear load.

model; b) Current harmonics and THDi=2.33%, PF=-0.999

guaranteeing the compliance with international standards.

μG

Fig. 14. Example of a small LV grid with a μG and a non-linear load

230V 25A

(18).

Power Quality Problems Introduced by Microgeneration 195

From (16) and (17), assuming a damping factor ξ = 2 2 , the value of *Tp* is obtained from

*K T T R*

*p*

a)

2 *D id*

0

Fig. 13. a) Current and voltage waveforms of a single phase VSI obtained with the simulated

Figure 13 shows the results obtained for the proposed μG model, assuming that the μG apparent power is *S*=3450VA, the DC voltage is *UDC*=400V, the switching frequency is near

The μG power factor is negative, even though nearly unitary as the displacement factor between the voltage and the current is 180º. The current THD is lower than 3%. However, considering only the first 50 harmonics, as in most power quality meters, the current THD decreases to THDi=0.35% These results are according to the manufacturers values,

Even though these microgenerators are designed to present high power quality parameters (high power factor and low current THD), still they are not usually exploited to their full extent as in general, they are sized and the controllers are designed only to minimize the

As an example, consider a small LV grid, as the one represented in figure 14, with a μG and

*i grid i* μ*G*

Vgrid

Grid

Inductive + Non-linear load

impact on the LV grid. The mitigation of Power Quality issues is not considered.

*i nl* 0.5

1

Mag (% of Fundamental)

1.5

2

α = (18)

Fundamental (50Hz) = 21.23 , THD= 2.32%

0 5000 10000 15000 20000

b)

Frequency (Hz)

To control the current injected in the LV grid it is usual to choose a PI compensator (to guarantee fast response times and zero steady-state error to the step response). The block diagram of the current controller is then represented in Fig. 12, where α*i* represents the gain of the current sensor.

Fig. 12. Block diagram of the current controlled VSI

To design the current controller it is then necessary to obtain the closed loop transfer function of the whole system. To guarantee some insensitivity to the disturbance introduced by the grid voltage *Vgrid*, it is assumed that the disturbance is known (is the grid voltage). For simplicity in the controller design, it is considered that the μG sees an equivalent resistance *R0*=*Vgrid*/*igrid* connected to its terminals. From the controller point of view, this results in *R*=*RL*+*R0*. Then, making the compensator zero *Tz* coincident with the pole introduced by the input filter *T LR Z L* = , the second order transfer function of the current controlled VSI is obtained from (16).

$$\mathbf{G}\_{cl}(\mathbf{s}) = \frac{i\_{grid}\{\mathbf{s}\}}{i\_{grid\_{sq}}\{\mathbf{s}\}} = \frac{\frac{K\_D \,\mathbf{\alpha}\_i}{T\_p T\_d R}}{\mathbf{s}^2 + \frac{1}{T\_d}\mathbf{s} + \frac{K\_D \,\mathbf{\alpha}\_i}{T\_p T\_d R}}\tag{16}$$

The transfer function (16) is then compared to the second order transfer function (17) written in the canonical form.

$$\text{G}\_2(\text{s}) = \frac{\text{\textdegree\text{\textdegree\text{\textdegree}}}{\text{\textdegree\text{\textdegree}}^2 + 2\text{\textdegree\text{\textdegree\text{\textdegree}}}\text{\text{\textdegree\text{\textdegree}}}\text{\text{\textdegree}} + \text{\text{\textdegree}}^2}{\text{\text{\textdegree}}^2 + 2\text{\text{\textdegree\text{\textdegree}}}\text{\text{\textdegree}}\text{\text{\textdegree}} + \text{\text{\textdegree}}^2} \tag{17}$$

Generally, the association of the modulator and the power converter may be represented as a first order model (14), with a gain *KD* and a dominant pole dependent on the average delay

> ( ) ( ) () 1 *PWMav D*

The incremental gain *KD* (15) depends on *UDC* voltage and on the maximum value max *uc* of

*v s K G s*

*D*

*c d*

max *DC*

Modulator+VSI

+1 *d D sT K*

> α*i*

To design the current controller it is then necessary to obtain the closed loop transfer function of the whole system. To guarantee some insensitivity to the disturbance introduced by the grid voltage *Vgrid*, it is assumed that the disturbance is known (is the grid voltage). For simplicity in the controller design, it is considered that the μG sees an equivalent resistance *R0*=*Vgrid*/*igrid* connected to its terminals. From the controller point of view, this results in *R*=*RL*+*R0*. Then, making the compensator zero *Tz* coincident with the pole introduced by the input filter *T LR Z L* = , the second order transfer function of the current

2

= = α

*i s K s s*

*D i grid*

2

*grid p d*

The transfer function (16) is then compared to the second order transfer function (17) written

2 2 2 ( ) 2 *n n n*

*s s*

*i s TTR*

*D i*

α

*K*

+ +

*d pd*

*T TTR*

ω = + ξω +ω (17)

( ) ( ) ( ) 1 *ref*

*cl*

*G s*

*G s*

*c U K*

To control the current injected in the LV grid it is usual to choose a PI compensator (to guarantee fast response times and zero steady-state error to the step response). The block

*u s sT* = ≈ + (14)

*u* = (15)

*Vgrid*

+

α

Input Filter *i grid*

(16)

*i* represents the gain

time *Td* (usually one half of the switching period *Td*=*Ts*/2) [Rashid, 2007].

*C*

diagram of the current controller is then represented in Fig. 12, where

*uc V I PWMav grid\_ ref*

*z sT* 1+ *sT*

+ -

Fig. 12. Block diagram of the current controlled VSI

*i p*

α

controlled VSI is obtained from (16).

in the canonical form.

the triangular modulator voltage.

of the current sensor.

From (16) and (17), assuming a damping factor ξ = 2 2 , the value of *Tp* is obtained from (18).

$$T\_p = \frac{2K\_D \,\alpha\_i \, T\_d}{R} \tag{18}$$

Fig. 13. a) Current and voltage waveforms of a single phase VSI obtained with the simulated model; b) Current harmonics and THDi=2.33%, PF=-0.999

Figure 13 shows the results obtained for the proposed μG model, assuming that the μG apparent power is *S*=3450VA, the DC voltage is *UDC*=400V, the switching frequency is near 10kHz and Δ*Igrid*<0.1 *Igrid*.

The μG power factor is negative, even though nearly unitary as the displacement factor between the voltage and the current is 180º. The current THD is lower than 3%. However, considering only the first 50 harmonics, as in most power quality meters, the current THD decreases to THDi=0.35% These results are according to the manufacturers values, guaranteeing the compliance with international standards.

Even though these microgenerators are designed to present high power quality parameters (high power factor and low current THD), still they are not usually exploited to their full extent as in general, they are sized and the controllers are designed only to minimize the impact on the LV grid. The mitigation of Power Quality issues is not considered.

As an example, consider a small LV grid, as the one represented in figure 14, with a μG and a non-linear load.

Fig. 14. Example of a small LV grid with a μG and a non-linear load

Design of a Virtual Lab to Evaluate and Mitigate

 Boost stage + MPPT

Fig. 17. Block diagram of an active μG

S1

*C*

*pv i*

*ic*

S2

Fig. 18. Model of the single phase active microgenerator

+ VSI + +

+ -

*i*μ*G ref*

*i pv i*

by the current *ipv* of the photovoltaic panel + boost stage.

unitary power factor).

Photovoltaic Panel

*i*

*Vc*

*Vcref*

+

*Vc*

Power Quality Problems Introduced by Microgeneration 197

power quality issues, as current THD, reducing the LV grid harmonic pollution (and near

VSI Active Power Filter

Based on the conventional μG model (Fig. 11), the proposed active μG is simulated according to Fig. 18, considering the DC link filtering stage and the disturbance introduced

S4

α*v*

*v*PWM

S3

VC vPWM Vgrid

AC Filter

*RL LL*

Non-linear load

*igrid*

Non-linear load

*i nl*

*VPWM av*

*ic*

+

*sC* 1

*i*

+ *i pv*

Filter

*i*μ*G*

+ +

 *inl*

*igrid*

Modulator

α*i*

*Cv*(*s*) *Ci* (*s*) Input

Fig. 19. Diagram block of the DC voltage controller and of the grid current controller to guarantee active filtering of the current harmonics introduced by the non-linear load

*i*μ*G*

*i nl*

*i grid i* μ*G*

Grid

*Vgrid*

Using the previously designed μG the current *i*μ*G* (Fig. 14) will be equal to the one obtained in Fig. 13. The non-linear load current *inl* is represented in Fig. 15 and is characterized by THDi=47.55%.

Fig. 15. a) Grid voltage *Vgrid* and current waveform *inl* obtained for the non-linear load; b) Current harmonics and THDi=47.55%, PF=0.15

The grid current *igrid* is represented in Fig. 16 and, as a result of the non-linear load THDi=18.79%.

Fig. 16. a) Waveforms of grid voltage *Vgrid* and current *igrid*; b) Current harmonics and THDi=18.79%

From this example it is possible to conclude that even though the μG injects nearly sinusoidal currents in the grid (Fig. 13), still it is not capable of guaranteeing sinusoidal currents when other nonlinear loads are connected to the grid.

#### **2.6 Active microgenerators**

To minimize some power quality problems as current and voltage THD, an active μG is included in this Lab (Fig. 17). Even though using the same power electronics converters as the conventional μG, with adequate control strategies and adequate filtering, it is possible to guarantee its operation as active power filter (APF), allowing the local mitigation of some

in Fig. 13. The non-linear load current *inl* is represented in Fig. 15 and is characterized by

a)

Fig. 15. a) Grid voltage *Vgrid* and current waveform *inl* obtained for the non-linear load;

a)

Fig. 16. a) Waveforms of grid voltage *Vgrid* and current *igrid*; b) Current harmonics and

currents when other nonlinear loads are connected to the grid.

0

From this example it is possible to conclude that even though the μG injects nearly sinusoidal currents in the grid (Fig. 13), still it is not capable of guaranteeing sinusoidal

To minimize some power quality problems as current and voltage THD, an active μG is included in this Lab (Fig. 17). Even though using the same power electronics converters as the conventional μG, with adequate control strategies and adequate filtering, it is possible to guarantee its operation as active power filter (APF), allowing the local mitigation of some

5

10

Mag (% of Fundamental)

15

The grid current *igrid* is represented in Fig. 16 and, as a result of the non-linear load

0

10

20

Mag (% of Fundamental)

30

40

μ

*G* (Fig. 14) will be equal to the one obtained

Fundamental (50Hz) = 6.072 , THD= 47.55%

0 500 1000 1500 2000

0 500 1000 1500 2000

Frequency (Hz)

b)

b)

Frequency (Hz)

Fundamental (50Hz) = 15.45 , THD= 18.79%

Using the previously designed μG the current *i*

1.9 1.905 1.91 1.915 1.92 1.925 1.93 1.935 1.94

1.9 1.905 1.91 1.915 1.92 1.925 1.93 1.935 1.94

**2.6 Active microgenerators**

230V 25A

b) Current harmonics and THDi=47.55%, PF=0.15

230V 25A

THDi=47.55%.

THDi=18.79%.

THDi=18.79%

power quality issues, as current THD, reducing the LV grid harmonic pollution (and near unitary power factor).

Fig. 17. Block diagram of an active μG

Based on the conventional μG model (Fig. 11), the proposed active μG is simulated according to Fig. 18, considering the DC link filtering stage and the disturbance introduced by the current *ipv* of the photovoltaic panel + boost stage.

Fig. 18. Model of the single phase active microgenerator

Fig. 19. Diagram block of the DC voltage controller and of the grid current controller to guarantee active filtering of the current harmonics introduced by the non-linear load

Assuming that the *Vc* voltage dynamics in the DC link is considerably slower than the dynamics of the microgenerator AC current *i*μ*G*, then the active μG current *i*μ*G* and the voltage *Vc* may be controlled according to the diagram block of Fig. 19.

The active μG current controller design is equal to the design of the controller used for the conventional μG. Then, neglecting the high frequency poles, the current controlled system may be represented according to (19), where the controller gain *Gi* (20) is obtained from the input/output power constraint, where *Vmax* represents the amplitude of the grid voltage.

$$\frac{\text{i}\,\text{(s)}}{\text{i}\_{\mu G \,\text{ref}}\,\text{(s)}} = \frac{\frac{\text{G}\_i}{\text{\textdegree{}} \,\text{\textdegree{}} \,\text{\textdegree{}}}}{T\_{dv} \,\text{s} + \text{1}} \tag{19}$$

Design of a Virtual Lab to Evaluate and Mitigate

disturbances.

Then:

order polynomial (24).

microgenerator AC current *i*

grid period.

Power Quality Problems Introduced by Microgeneration 199

( ) 1 1 1 1 *cref*

*s T s sC* = = +α + α +

*i*

α

α = α α ++ +

*s Ts*

*pv vip vii v*

From the final value theorem (23), the response to the disturbance introduced by *ipv* current is zero, meaning that in steady-state, the PI controller guarantees the minimization of the

> ( ) lim 0 ( ) *cref*

*pv v v s i s* →

To determine the PI controller parameters, the denominator of (22) is compared to the third

*c*

0

1 1.75

2 0

 α ω = α

> 3 0

 α ω = α

2.15

 ω =

Solving (25), the proportional gain *Kp* and the integral gain *Ki* are obtained:

*p*

*i*

μ

*i s G K G K ss s T TC TC* =

1

*i dv*

( )

+

*dv*

*dv dv i dv i*

0

=

3 2 23

*dv v i p dv i*

*G K T C G K T C*

( )

*i*

1.75

2

3 2

*G*, then the pole *Tdv* is assumed to be 2 *T T dv* ≈ , where T is the

( ) ( )

*i*

1.75

Assuming that the dynamics of *Vc* voltage is considerably slower than the dynamics of the

Figures 22 to 24 show the results obtained for the proposed active μG model, assuming that the μG apparent power is *S*=3450VA, the DC voltage is controlled to be *Vc*=400V, the semiconductors switching frequency is near 10kHz and Δ*Igrid*<0.1 *Igrid*. The DC link capacitor

*v i dv*

*G T*

*T*

*vii dv i*

2.15

*v i dv*

*C K G T*

α =

*C K*

α α = α

1

α α

3 0 00 *Ps s s s* ( ) 1.75 2.15 = + ω + ω +ω (24)

(21)

(22)

= (23)

(25)

(26)

0

( ) 1 *cref*

*pv i i v v p*

Simplifying (21) it is possible to obtain the transfer function in the canonical form (22).

*v s sC i s K G K*

3 2 0

0

*s*

*c dv i*

*v s T C*

( )

*c*

( )

$$\mathbf{G}\_i(\mathbf{s}) = \frac{V\_{\text{max}}}{\mathbf{2}V\_{\varepsilon}} \tag{20}$$

Then, the current controlled system may be represented as a current source (19), as shown in Fig. 20.

Fig. 20. Simplified block diagram used to design the voltage controller

From Fig. 20, the block diagram of the DC voltage controller is obtained and represented in figure 21.

Fig. 21. Block diagram of DC stage voltage controller

From Fig. 21, the voltage response to the disturbance introduced by the photovoltaic panel is given by (21):

$$\left. \frac{v\_c(s)}{i\_{pv}(s)} \right|\_{v\_{is\_p} = 0} = \frac{\frac{1}{sC}}{1 + \alpha\_v \left( K\_p + \frac{K\_i}{s} \right) \frac{G\_i}{\alpha\_i} \frac{1}{T\_{ds}s + 1} \frac{1}{sC}} \tag{21}$$

Simplifying (21) it is possible to obtain the transfer function in the canonical form (22).

$$\left. \frac{\upsilon\_c(s)}{i\_{\upsilon v}(s)} \right|\_{v\_{i\_{\upsilon f}}=0} = \frac{s \frac{\alpha\_i}{T\_{dv} \mathbb{C} \alpha\_i} (T\_{dv} s + 1)}{s^3 + \frac{1}{T\_{dv}} s^2 + \frac{\alpha\_v \mathbb{G}\_i \mathbb{K}\_p}{T\_{dv} \mathbb{C} \alpha\_i} s + \frac{\alpha\_v \mathbb{G}\_i \mathbb{K}\_i}{T\_{dv} \mathbb{C} \alpha\_i}} \tag{22}$$

From the final value theorem (23), the response to the disturbance introduced by *ipv* current is zero, meaning that in steady-state, the PI controller guarantees the minimization of the disturbances.

$$\left. \lim\_{s \to 0} \frac{v\_{\boldsymbol{c}}(\boldsymbol{s})}{\dot{\boldsymbol{i}}\_{\boldsymbol{p}\boldsymbol{v}}(\boldsymbol{s})} \right|\_{\boldsymbol{v}\_{\boldsymbol{v}\_{\boldsymbol{q}\boldsymbol{f}}}=0} = 0 \tag{23}$$

To determine the PI controller parameters, the denominator of (22) is compared to the third order polynomial (24).

$$P\_3(\text{s}) = \text{s}^3 + 1.75\,\text{\textdegree{o}\_0}\,\text{s}^2 + 2.15\,\text{\textdegree{o}\_0}\,\text{s} + \text{o}\_0^3\tag{24}$$

Then:

198 Electrical Generation and Distribution Systems and Power Quality Disturbances

Assuming that the *Vc* voltage dynamics in the DC link is considerably slower than the

The active μG current controller design is equal to the design of the controller used for the conventional μG. Then, neglecting the high frequency poles, the current controlled system may be represented according to (19), where the controller gain *Gi* (20) is obtained from the input/output power constraint, where *Vmax* represents the amplitude of the grid voltage.

( )

*i*

*C*

Fig. 20. Simplified block diagram used to design the voltage controller

*i* μ*G ref*

*s K K i p* +

Fig. 21. Block diagram of DC stage voltage controller

*i c*

*i s*

*Gref dv*

( ) 2 *max*

Then, the current controlled system may be represented as a current source (19), as shown in

*pv* **)(** *si* **)(** *sT*

From Fig. 20, the block diagram of the DC voltage controller is obtained and represented in

*Vc ref Vc*

+1 α *sT G dv ii*

α*v*

From Fig. 21, the voltage response to the disturbance introduced by the photovoltaic panel is

*i*

+

+

 *ipv*

> *sC* 1

*V G s*

*i s Ts* μ

voltage *Vc* may be controlled according to the diagram block of Fig. 19.

μ

() 1

*i i*

*G*

*c*

*G*, then the active μG current *i*

α ≈ + (19)

*V* ≈ (20)

*G si Gref i dv i* μ +α ≈ 1 1

μ

*G* and the

dynamics of the microgenerator AC current *i*

*VC i*

Fig. 20.

figure 21.

given by (21):

+ + -

$$\begin{cases} 1.75 \text{\color{red}{0}s\_0 = \frac{1}{T\_{\text{dv}}}}\\ 2.15 \text{\color{red}{0}s\_0^2 = \frac{\alpha\_v \text{ G}\_i \text{ K}\_p}{T\_{\text{dv}} \text{C} \alpha\_i}\\ \alpha\_0^3 = \frac{\alpha\_v \text{ G}\_i \text{ K}\_i}{T\_{\text{dv}} \text{C} \alpha\_i} \end{cases} \tag{25}$$

Solving (25), the proportional gain *Kp* and the integral gain *Ki* are obtained:

$$\begin{cases} K\_p = \frac{2.15 \text{ C} \,\alpha\_i}{\alpha\_v \text{ G}\_l \, T\_{dv} \left(1.75 \right)^2} \\ K\_i = \frac{\text{C} \,\alpha\_i}{\alpha\_v \text{ G}\_l \left(1.75 \right)^3 \left(T\_{dv} \right)^2} \end{cases} \tag{26}$$

Assuming that the dynamics of *Vc* voltage is considerably slower than the dynamics of the microgenerator AC current *i*μ*G*, then the pole *Tdv* is assumed to be 2 *T T dv* ≈ , where T is the grid period.

Figures 22 to 24 show the results obtained for the proposed active μG model, assuming that the μG apparent power is *S*=3450VA, the DC voltage is controlled to be *Vc*=400V, the semiconductors switching frequency is near 10kHz and Δ*Igrid*<0.1 *Igrid*. The DC link capacitor

Design of a Virtual Lab to Evaluate and Mitigate

Fig. 23.

THDi=13%

Power Quality Problems Introduced by Microgeneration 201

To guarantee nearly sinusoidal grid currents, the μG current will be the one presented in

230V 25A

1.9 1.905 1.91 1.915 1.92 1.925 1.93 1.935 1.94

Fundamental (50Hz) = 21.16 , THD= 13.00%

0 500 1000 1500 2000

Frequency (Hz)

1.9 1.91 1.92 1.93 1.94 1.95 1.96 1.97 1.98 1.99 2 0

Fig. 23. a) Waveforms of grid voltage and μG current; b) μG current harmonics and

The proposed models will be further tested in a low voltage grid.

Fig. 24. Waveform of the DC link capacitor voltage

Mag (% of Fundamental)

a)

b)

The average value of the capacitor voltage is *Vc*=400V, as shown in Fig. 24.

is C=2.7mF, guaranteeing a voltage ripple lower than 5%. The results obtained for the nonlinear load are those presented in figure 15.

From Fig. 22 it is possible to conclude that the proposed active μG acts as an active power filter, guaranteeing nearly sinusoidal grid currents. Comparing the results of Fig. 22 and Fig. 16, there is a clear reduction of the grid current THD. This reduction will become more obvious for more complex grids and highly non-linear loads.

Fig. 22. a) Waveforms of grid voltage and current; b) Grid current harmonics and THDi=3.56%, PF=0.9999.; c) Grid current harmonics and THDi50=1.55% (considering only till the 50th order harmonic)

is C=2.7mF, guaranteeing a voltage ripple lower than 5%. The results obtained for the non-

From Fig. 22 it is possible to conclude that the proposed active μG acts as an active power filter, guaranteeing nearly sinusoidal grid currents. Comparing the results of Fig. 22 and Fig. 16, there is a clear reduction of the grid current THD. This reduction will become more

230V 25A

1.9 1.905 1.91 1.915 1.92 1.925 1.93 1.935 1.94

Fundamental (50Hz) = 15.24 , THD= 3.56%

0 5000 10000 15000 20000

0 500 1000 1500 2000

Frequency (Hz)

THDi=3.56%, PF=0.9999.; c) Grid current harmonics and THDi50=1.55% (considering only till

Fig. 22. a) Waveforms of grid voltage and current; b) Grid current harmonics and

Frequency (Hz)

Fundamental (50Hz) = 15.12 , THD= 1.55%

a)

b)

c)

linear load are those presented in figure 15.

obvious for more complex grids and highly non-linear loads.

0 0.5 1 1.5 2 2.5

0

0.5

Mag (% of Fundamental)

the 50th order harmonic)

1

1.5

Mag (% of Fundamental)

To guarantee nearly sinusoidal grid currents, the μG current will be the one presented in Fig. 23.

The average value of the capacitor voltage is *Vc*=400V, as shown in Fig. 24.

Fig. 23. a) Waveforms of grid voltage and μG current; b) μG current harmonics and THDi=13%

Fig. 24. Waveform of the DC link capacitor voltage

The proposed models will be further tested in a low voltage grid.

Design of a Virtual Lab to Evaluate and Mitigate

LV L1 L2

LV L1

L2

L3

L4

load distance increases, the voltage drop increases as well.

L5

L3 L4

L5

L6 a)

**Power Factor Voltage RMS value**

L6 c) LV L1 L2

Fig. 26. Results obtained for 15 % and 85 % of the transformer rated power, without μG. Measurements carried out on the transformer LV side for each one of the groups of loads L1

Fig. 26 shows that the voltage THD increases more than 50% (as in load 6) from the no-load (15% SN) to the full load (85% SN) scenario. As the percentage of linear and non-linear loads is nearly equal for both scenarios, the current THD does not present significant changes (it even decreases slightly in the full load scenario). Also, the Power Factor results are similar for both scenarios, even though slightly lower for the no-load scenario. As for the load voltages RMS values, higher loads result in higher voltage drops. Also, as the transformer to

Figure 27 presents the results obtained with μG assuming that the transformer is at 15 % of its rated power SN (no load scenario). The measurements of phase voltages and currents are

carried out on the transformer LV side for each one of the groups of loads L1 to L6.

to L6: a) Voltage THD; b) Current THD; c) Power Factor; d) Value of RMS voltage

Power Quality Problems Introduced by Microgeneration 203

**Voltage THD Current THD**

LV L1 L2 L3 L4 L5 L6

L3 L4 L5

b)

L6 d)

No load scenario (15% SN) – phase A No load scenario (15% SN) – phase B No load scenario (15% SN) – phase C Full load scenario (85% SN) - phase A Full load scenario (85% SN) - phase B Full load scenario (85% SN) - phase C


**Author details**

58 Earthquake Engineering

which causes energy radiation of different fault parts in different times and seismic waves

Let's compare amplitude spectra of obtained design accelerograms with spectrum of real earthquake from considered fault. Data analysis (fig. 18 and fig. 19) shows that spectra of

It must be noted that spectrum of vertical component of real earthquake is closer to design spectra. The last fact is quite obvious and is explained by proximity to earthquake source. Indeed, close earthquakes in general are characterized by predomination of vertical component. Record of TEA station (located in theater) was selected due to its location on

Analysis of spectrum of weak earthquake shows that peaks are observed on 1.3 and 5.6 Hz (Fig. 18). In spectra of synthesize accelerograms mentioned amplitudes are also observed. At the same time medium response on strong earthquake, undoubtedly, differ from weak

**Figure 19.** Spectra of design accelerograms at different source locations of earthquake М=7,1: 1 –

**Figure 20.** Spectra of accelerograms of weak earthquake with epicenter in the zone of Vladikavkaz

western part of fault; 2 – middle part of fault; 3 – eastern part of fault

fault. (25.08.2005 10:25 GMT, H = 8 km M= 2.5).

are interference and causes directivity effects (Beresnev & Atkinson, 1997, 1998).

calculated and real earthquakes in a whole are similar in their main parameters.

dense gravel and has a minimal distortions caused by soil conditions.

earthquake response (Fig. 19) (Zaalishvili, 2000).

V. B. Zaalishvili *Center of Geophysical Investigations of RAS, Russian Federation*


**GREEN NANOTECHNOLOGY - OVERVIEW AND FURTHER PROSPECTS**

Edited by **Marcelo L. Larramendy** and **Sonia Soloneski**

#### **Green Nanotechnology - Overview and Further Prospects**

http://dx.doi.org/10.5772/61432 Edited by Marcelo L. Larramendy and Sonia Soloneski

#### **Contributors**

Seyed Mohsen Sadeghzadeh, Mehdi Mogharabi, Francesco Ruffino, Giuseppe Cacciato, Massimo Zimbone, Maria Grazia Grimaldi, Fahmina Zafar, Eram Sharmin, Nahid Nishat, Sharif Ahmad, André Decroly, Marc Debliquy, Arnaud Krumpmann, Driss Lahem, Man Singh, Xianfeng Chen, Jia Lin, Xiaolin Liu, Shu Zhu, Vladimir V. V. Kouznetsov, Carlos A. Andrés Martínez Bonilla, Ahmad Alshammari, V. Narayana Kalevaru, Andreas Martin, Guilin Chen, Shuiyuan Chen, Zhigao Huang, Jorge A.R. Salvador, Samuel Silvestre, Maria Manuel Silva

#### **© The Editor(s) and the Author(s) 2016**

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#### **Notice**

Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published chapters. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book.

First published in Croatia, 2016 by INTECH d.o.o. eBook (PDF) Published by IN TECH d.o.o. Place and year of publication of eBook (PDF): Rijeka, 2019. IntechOpen is the global imprint of IN TECH d.o.o. Printed in Croatia

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Green Nanotechnology - Overview and Further Prospects Edited by Marcelo L. Larramendy and Sonia Soloneski p. cm. Print ISBN 978-953-51-2409-2 Online ISBN 978-953-51-2410-8 eBook (PDF) ISBN 978-953-51-4199-0


*2.5.* ∆*RIL-*∆*RES-F508del-CFTR Levels at the Plasma Membrane are Equivalent to Those of wt-CFTR*

To determine the fraction of the above CFTR variants that localize to the PM, we used quantitative cell surface biotinylation. These data showed that PM levels of ∆RIL-∆RES-F508del-CFTR were equivalent to those of wt-CFTR, while those of ∆RIL-F508del-CFTR were significantly lower (Figure 4A, lanes 5,4; Figure 4B). Data also confirmed that ∆RES did not induce appearance of F508del-CFTR at the cell surface (data not shown). Corrector VX-809 further increased the PM expression of ∆RIL-∆RES-F508del-CFTR to levels that are significantly higher than those of wt-CFTR (Figure 4A, lanes 2,9, Figure 4B). This compound also significantly increased PM levels of ∆RIL-F508del-CFTR to similar levels of wt-CFTR (Figure 4A, lanes 2,8; Figure 4B).

**Figure 4.** Plasma membrane levels, efficiency of processing and turnover of immature CFTR without Regulatory Extension (RES). (**A**) BHK cells expressing ∆RIL-F508del and ∆RIL-∆RES-F508del-CFTR and treated with 3 µM VX-809 for 48 h (or DMSO control) were subjected to cell surface biotinylation. wt-CFTR samples not treated with biotin were the negative control (NC). After streptavidin pull-down, CFTR was detected by WB. CFTR and CNX are detected in the whole cell lysate (WCL) as controls. (**B**) Quantification of data in (a) for PM CFTR normalized to total protein and shown as fold change relatively to wt-CFTR cells treated with DMSO. "\*" and "#" indicate significantly different from wt-CFTR treated with DMSO and from respective variant without VX-809, respectively (*p* < 0.05). (**C**) BHK cells expressing wt-, F508del-CFTR alone or jointly with ∆RIL, ∆RES, and ∆RIL-∆RES were subjected to pulse-chase (see Materials and Methods) for the indicated times (0, 0.5, 1, 2, and 3h) before lysis and immunoprecipitation (IP) with the anti-CFTR 596 Ab. After electrophoresis and fluorography, images were analyzed by densitometry. (**D**) Turnover of immature (band B) CFTR for different CFTR variants is shown as the percentage of immature protein at a given time point of chase (P) relative to the amount at t = 0 (P0 ). (**E**) Efficiency of processing of band B into band C is shown as the percentage of band C at a given time of chase relative to the amount of band B at t = 0. "\*" and "#" indicate statistical significantly different (*p* < 0.05) from wt-CFTR and F508del-CFTR, respectively. Data represent mean ± SEM (*n* = 5).

Given the very significant stabilization of immature ∆RES-F508del-CFTR (Figure 1B), next, we determined how removal of RES affected the processing efficiency and the turnover of the F508deland ∆RIL-F508del-CFTR variants. To this end, we performed pulse-chase experiments (Figure 4C,D) and indeed our results revealed that ∆RES very significantly stabilized immature F508del-CFTR not just relatively to F508del-CFTR but to levels even significantly higher than those of wt-CFTR (Figure 4C,D). Indeed, our data show that although F508del-CFTR without RE did not traffic to the PM, it showed a dramatic stabilization of its immature form (evidencing a turnover rate ~2× lower than that of wt-CFTR. It should be noted that the turnover of F508del-CFTR itself is ~1.4×faster vs. wt-CFTR, thus this stabilization (of ~3× vs. F508del-CFTR) represents indeed a massive stabilization. Interestingly, this stabilizing effect was no longer significant for ∆RIL-∆RES-F508del-CFTR nor for ∆RIL-F508del-CFTR, the latter being equivalent to wt-CFTR (Figure 4C,D). Removal of RIS from F508del-CFTR did not stabilize its turnover (data not shown). As to removal of either RES or RIS from wt-CFTR, it did not affect the processing efficiency or the turnover vs. wt-CFTR (Figure S2).

In summary, levels of ∆RIL-∆RES-F508del-CFTR at the PM are equivalent to those of wt-CFTR.