CHAPTER 3 MAXIMUM POWER TRANSFER THEOREM BASED MPPT FOR STANDALONE PV SYSTEM

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1 60 CHAPTER 3 MAXIMUM POWER TRANSFER THEOREM BASED MPPT FOR STANDALONE PV SYSTEM 3.1 INTRODUCTION Literature reports voluminous research to improve the PV power system efficiency through material development, enhancing strategies for the efficient power point tracking and the development of efficient of DC-DC power converter topologies. Today s material technology assures only low to medium energy conversion efficiency PV cell. Hence, it is important to design high performance DC-DC converter and to propose efficient tracking algorithm. In which challenges arise on account of non-linear nature of I-V characteristics of PV system. The use of conventional power converters in PV system for MPPT, results in high ripple content in voltage and current. The problem gets worse because the output power of solar cells mainly depends on factors such as temperature and irradiance. Varying environmental conditions greatly affect the photovoltaic array output power. The nonlinear I V characteristics of the PV source make the MPPT complex. To overcome this problem, number of MPPT methods have been developed such as P&O, INC, ripple correlation control and lookup table method (Soon et al. 2013, Ishaque et al. 2014, Lin et al. 2011, Esram et al. 2006, Chung et al. 2003). Among these, the first two are the most commonly implemented methods in the existing PV systems. These methods vary in complexity, accuracy, speed, oscillation around the MPP, hardware implementation, and sensor requirement.

2 61 The artificial intelligence methods such as fuzzy logic and neural network are well adopted for handling nonlinearity in many applications. Though these methods are good in dealing with the nonlinear characteristics of the I V curves of PV panel, they require extensive computation and the versatility of these methods is limited (Messai et al. 2011, Femia et al. 2007, Faraji et al. 2013). The lookup table method needs a prior knowledge of the PV array characteristics, so that, a clear mathematical function relating the output characteristics has to be predetermined. However, PV array characteristics depend on many complex factors such as temperature, partial shading, aging and a possible breakdown of individual cells. So, it is difficult to predict and store all the possible system conditions. Modified algorithms have been introduced to improve the efficiency of MPPT algorithm in different aspects (Liu et al. 2008, Emad & Masahito 2010). INC algorithm with direct control method (Safari & Mekhile 2011, Liqun et al. 2013) eliminates additional control loop required for MPPT and shorten the computational time. In recent years implementation point of view, several MPPT algorithms such as Hill Climbing/P&O method, INC technique and artificial intelligence methods have been implemented using FPGA based controller because of its inherent features such as faster operation and optimized design of hardware architecture etc (Mellit et al. 2011, Khaehintung et al. 2006). 3.2 PROBLEM STATEMENT For maximum utilization of energy from the PV panel, MPPT is pivotal. It is important to simplify the tracking algorithm to increase response speed, reduce ripple and increase conversion efficiency in addition to costeffectiveness. With this view in sight, the limitations and advantages of the existing MPPT methods are considered in this section and a simplified Maximum Power Transfer Theorem (MPTT) based MPPT method is proposed.

3 62 It is implemented using elementary DC-DC LUO converter, as fundamental converters such as buck, boost, buck-boost are not suitable for applications which needs low ripple in current and voltage. The fourth order converters such as CUK, SEPIC and LUO converter are better, but CUK converter produces the output voltage with opposite polarity. LUO is similar to SEPIC converter, but most of the literature discusses the performance of SEPIC converter for PV system only. LUO converter coupled to PV panel is not much reported in literature. The inherent property of LUO converter overcomes the parasitic problems present in the classical DC-DC converter in addition to having reduced ripple content. The proposed MPTT based technique performs MPPT using simple control technique by fine-tuning the duty cycle of the converter so as to make the input resistance of converter equal to the load resistance of the solar panel. Hence, the need for proportional-integral (PI) control loop is eliminated. The performance analysis of the proposed MPPT algorithm is compared with an existing P&O algorithm through MATLAB simulations. Experiment results of the proposed MPPT are implemented through FPGA controller using LUO converter with 40W solar panel. From the results, it is proved that the response of the proposed method is faster than the existing P&O method under varying solar irradiation conditions for a given fixed step size (change in duty cycle). The voltage and current ripples are considerably low and also the proposed algorithm has higher efficiency and low implementation cost. 3.3 CIRCUIT DESCRIPTION OF LUO CONVERTER Among all the existing converter topologies, like the buck-boost converter topology, the LUO converter provides a regulated positive output voltage of any required level (higher or lower) from positive input source voltage. The benefits of LUO converter include lower output voltage ripple, easier

4 63 compensation and good performance characteristics in particular there is no parasitic problem. It causes the output voltage and power transfer efficiency to be restricted to low value. Thus, the novel attempt is made using LUO converter in the proposed PV system. The basic circuit diagram of the elementary LUO converter is shown in Figure 3.1 In this circuit, S is the switch and D 1 is the diode. The coupling capacitor C 1 acts as the primary means of storing and transferring energy from the input source to the output load via the inductor L 1 and a low-pass filter L 2 -C 2. Figure 3.1 Basic circuit diagram of elementary DC-DC LUO converter The LUO converter can operate either in Continuous Conduction Mode (CCM) or Discontinuous Conduction Mode (DCM) depending on the current flow through L 1. In the present work CCM mode of operation is considered Modes of Operation of LUO Converter To analyze the working principle of LUO converter, two modes (ON state and OFF state) of the switch are considered.

5 64 Figure 3.2 Equivalent circuit of LUO converter when switch S is in ON condition Mode1: The equivalent circuit of the LUO converter when the switch is in turned ON condition is shown in Figure 3.2. The diode D is in OFF condition. In this mode, the source current i in is equal to the sum of i L1 and i L2 and inductor L 1 is charged by the supply voltage. At that time, inductor L 2 absorbs energy from the source and capacitor C 1 and both currents i L1 and i L2 increase. Figure 3.3 Equivalent circuit of LUO converter when switch S is in OFF condition Mode 2: The current drawn from the source becomes zero, and current i L1 flows through the diode to charge capacitor C 1, when the switch S is in OFF. The equivalent circuit of the LUO converter when the switch is in turned OFF state is shown in Figure 3.3. In the meantime, current i L2 flows through (C 2 and R L ) circuit. Both currents i L1 and i L2 decrease. The variations of currents i L1 and i L2 are small so that, i L1 I L1 and i L2 I L2, where I L1 and I L2 are mean values of inductor current L 1 and L 2.

6 65 in equation (3.1) The charge on capacitor C 1 increases, during switch off period as given Q (1 D)I L1 (3.1) It decreases during switch-on period as given by equation (3.2) Q DI L2 (3.2) where D is the duty cycle of the switch S. T D T on In a whole period, Q Q and using this relation, the inductor current I L2 equation (3.3) is derived I L2 1 D IL1 (3.3) D Since the capacitor C 2 performs as a low-pass filter, the output current is given by equation (3.4) I L2 I 0 (3.4) During the switch-on period, the source current is i s = i in = i L1 + i L2, and i in = 0 during switch-off. Thus, the average source current I in is given by equation (3.5) I in D i in D i 1 D D L1 il2 D 1 IL1 IL1 (3.5) Now, the output current is I 1 D D 0 I in (3.6)

7 66 Therefore, the converter output voltage is given by, V D 1 D 0 V in (3.7) where V 0 is the output voltage of the LUO converter and I 0 is the output current of the converter. To analyze the variations of different circuit element currents and voltages, key waveforms and of operating stages are shown in Figure 3.4 during ON and OFF conditions. The instantaneous currents and voltages of the inductor and capacitor during switch ON and OFF condition are given in the Table 3.1. Table 3.1 Current and voltage in L and C during switch ON and OFF condition Voltage /Current of L&C During switch ON condition 0<t<DT During switch OFF condition DT<t<T V SW 0 V0 V in V L1 V in V L2 V in - VO - VO Vin V0 i i (0) t L1 L1 il1(dt) (t DT) L L 1 1 i L2 Vin V0 il2(0) t il2(dt) (t DT) L L 2 2 Vin V0 i i (0) t C1 L2 il1(dt) (t DT) L L V 2 in i i C2 L2(0) t I 0 0 il1(dt) (t DT) I L1 L1 0 VD in V0 V V 0 1

8 67 Figure 3.4 Key waveforms in elementary LUO circuit during ON and OFF states 3.4 PROPOSED MPTT BASED CONTROL STRATEGY The existing P&O algorithm has very less complexity but on reaching very close to MPP, it doesn t stop at MPP and keeps on perturbing on both the directions. To overcome the inability of P&O method to track the peak power under fast varying atmospheric condition, a new MPPT algorithm is proposed

9 68 which track peak power under varying atmospheric conditions with greatly reduced ripples in current and voltage of the PV panel and converter output. Figure 3.5 Block diagram of proposed PV system with LUO converter The proposed algorithm is applicable for the system with constant load. This algorithm works on the principle that at, P Pmax, where P is the power at any point of the PV curve, the ratio of V PV to I PV should be equal to R in, Where R in is the equivalent load resistance as seen from the PV panel side and it is also called as the input resistance of the converter. Figure 3.5 shows the block diagram of the proposed PV energy system with LUO converter. The R in of LUO converter is given by equation (3.8) R D V0 1 D in R L D I 0 D (3.8) where R L is the load resistance connected to the converter and D is the duty cycle.

10 69 At a given operating point, the ratio of PV panel voltage and current is R ref and is given by equation (3.9) V PV R ref (3.9) IPV From the initial value of duty cycle, R in is calculated by using equation (3.8).From the measured values of V PV and I PV, the R ref is calculated by using equation (3.9) for the same value of duty cycle. Now, the error value of the source and load resistance of the PV panel e is, e R ref R in (3.10) If the error e is greater or lesser than a specified tolerance, the duty cycle is decreased or increased by a discrete step D and again e is calculated as above till error e lies within the specified tolerance then, the final value of D is the duty cycle of the converter at which, maximum power is obtained from the PV panel. The variation of the R in with duty cycle for different values of D is shown in Figure 3.6. Hence, effective load line on the I-V curve of the PV module is moved to a point where maximum power can be extracted. Figure 3.6 Variation of R in with duty cycle

11 70 The proposed MPPT algorithm with direct control method is clearly explained by the flow chart shown in Figure 3.7 in which the duty cycle (D) is calculated directly. In the flow chart, V old, I old and D old denote the initial values of PV voltage, current and duty cycle, and are taken as 0.1V, 0.1A and 0.5, respectively. The step size of duty cycle ( D) is taken as 0.02 based on trial and error approach. Same initial value is taken for the existing P&O method for the comparison of two algorithms. Since the proposed algorithm involves only the measurement of the present values of V PV and I PV instead of calculating ΔP, the maximum power point approach is getting smoother. A small sampling time for measuring V PV and I PV of solar panel is necessary, Thus, the MPP s achieving time is reduced. Therefore, the proposed algorithm is faster with reduced oscillation. There are many algorithms implemented so far to track the MPP of a PV module. The choice of the algorithm depends on the response time, complexity of the algorithm to track the MPP, efficiency, implementation cost and the ease of implementation. It is observed that the proposed technique works like the existing P&O technique, but the fluctuations in the power of the PV module around the MPP are less compared to the existing P&O method. In the proposed method, proportional-integral (PI) control loop is eliminated and the duty cycle is controlled directly using the algorithm. So that the computational time for tuning the controller gains is reduced and the cost of the controller is eliminated.

12 71 Figure 3.7 Flow chart of the proposed MPPT with direct control method 3.5 DESIGN OF CIRCUIT ELEMENTS FOR THE LUO CONVERTER The solar PV energy generation system is designed to feed an average DC load of 35W/36V at 1000 W/m 2 and considering this load, the rating of selected solar-pv panel is 40W. The standard 40W panel is connected in the proposed configuration PV system. The designed LUO converter utilizes the solar power source using the ALEKO 40-W solar photovoltaic module. Its rated peak power is 40W, rated maximum voltage is 17.5 V and the rated maximum current is 2.29A.

13 72 The relationship between the input voltage and the output voltage of the LUO converter in terms of duty cycle is given by equation (3.7). The maximum (D max ) and minimum (D min ) duty cycles are calculated by using equations (3.11) and (3.12), D max V0 VD (3.11) V V V in min 0 D D min Vo VD V V V (3.12) in max o D It is assumed that the diode drop V D is 0.6V. The maximum duty cycle and the minimum duty cycle are obtained as D max =0.78 and D min =0.67 based on equation 3.11 and ( by considering V in min assumed as 10V at minimum irradiation and V in max taken as 17.5V at 1000 W/m 2 ). The limit of duty cycle is The duty cycle is not fixed due to the tracking process of MPP. The following design is done for the selection of inductor and capacitor present in the circuit Selection of Inductor The value of inductors L 1 and L 2 are selected based on the ripple value. A good inductor may have the peak to peak ripple current of approximately 10% of its maximum input current at minimum input voltage. The value of ripple current ΔI L1 can be calculated, from the equations (3.13) and (3.14). I L 1 I 0 V V 0 in min 10% (3.13) I I0 L 2 10% (3.14)

14 73 The value of inductors can be calculated by the equations (3.15) and (3.16). L L V (3.15) in,min 1 Dmax IL f 1 s V in,min 2 Dmax IL f 2 s where f s is the switching frequency of the LUO converter (3.16) Capacitor (C 1 ) Design The coupling capacitor (C 1 ) of the LUO converter is determined by equation (3.17) V C1 I0 D C f 1 max s (3.17) The peak to peak ripple value (ΔV C1 ) of capacitor voltage is considered as 4% of the output voltage. Now, the capacitor C 1 is calculated by using equation (3.17).The peak voltage across C 1 is close to the input voltage. The voltage rating of capacitor C 1 is selected larger than the maximum input voltage Output Capacitor Selection The output capacitor (C 2 ) can be calculated using the equation (3.18) C 2 D 8 V max in min 2 VC L2f 2 s (3.18) Where V C is the ripple voltage across capacitor C 2 2 The components specification of the LUO converter used in the simulation and experimental setup calculated by using the equations ( ) are given in Table 3.3.

15 74 Table 3.2 Specification of LUO converter Components Specifications Switch: MOSFET IRF 850 Inductor, L 1 & L 2 2mH &3mH Capacitor, C 1 &C 2 250µF & 200µF Load Resistance, R L 35 ohm Switching Frequency (f s ) 25 khz Input Voltage 10V-17.4V Output Voltage 36V at 1000 W/m ANALYSIS OF SIMULATION RESULTS The proposed solar-pv system is modeled in MATLAB/SIMULINK. It includes the PV module, the LUO converter, and the MPPT algorithm. The performance analysis of the proposed method is carried out for the different irradiation conditions. In order to ensure that the proper operation of the proposed MPPT algorithm, the irradiation is varied from one value to another value and the responses are observed. The following simulation results illustrate the effectiveness of the proposed algorithm Performance Evaluation of the Proposed PV System Under Steady State Condition Figure 3.8 shows the MPPT tracking features of the existing and the proposed algorithms at constant irradiation level of 1000 W/m 2. Further Figure 3.9 shows the MPPT tracking features of the proposed algorithm, when the irradiation level is changed from 1000 to 800 W/m 2 at 0.2 sec at constant temperature of 25 0 C. As the irradiation level varies, the proposed MPPT controller tracks the new MPP. The power output of the PV array is decreased to 30.6W from 40W at the time of 0.2 sec. The voltage of the PV module is decreased to 15.4V from 17.4V under the same condition. It is also observed that for the new MPPT, the LUO

16 75 converter provides a DC voltage of 36V for the load resistance of 35 ohms at the irradiation level of 1000 W/m 2. Form the obtained tracking feature results, it is clear that in the proposed technique, the perturbation at close to the MPP is very less compared to the existing P&O method.. Figure 3.8 MPPT tracking features of existing and the proposed algorithm at constant irradiation level of 1000 W/m 2 Figure 3.9 MPPT tracking features of the existing and the proposed MPPT method when irradiation level is varied from 1000 to 800W/m 2 (dynamic response)

17 76 Figure 3.10 PV panel output voltages for the existing and proposed MPPT method at 1000 W/m 2 Figure 3.11 PV panel output current for existing and proposed MPPT method at 1000 W/m 2 Figure 3.12 Converter output voltage for existing and proposed MPPT method at 1000 W/m 2

18 77 Figure 3.13 Converter output current for existing and proposed MPPT method at 1000 W/m 2 Figures 3.10 and 3.11 show the simulation results of PV module voltage and current at 1000 W/m 2. It is observed that the settling time of the exiting P&O MPPT algorithm is 0.14 sec but it is 0.07 sec in the proposed MPPT algorithm. It clearly states that the proposed algorithm is 50% faster than the existing P&O method. LUO converter output voltage and current for the existing and the proposed MPPT algorithm at 1000 W/m 2 are shown in Figures 3.12 and Performance Evaluation of the Proposed PV System Under Dynamic Condition Figures 3.14 to 3.17 illustrate the dynamic performance of the existing P&O and the proposed MPPT methods when the irradiation level is varied from 1000 to 800 W/m 2 at 0.2sec. The proposed algorithm tracks the MPP under changing in environmental condition.. Figure 3.18 provides particulars of tracking speed of the existing and the proposed MPPT algorithms for varying irradiation conditions.

19 78 Figure 3.14 PV panel output voltage for the existing and proposed method when irradiation level is varied from 1000 to 800 W/m 2 at 0.2 sec Figure 3.15 PV panel output current for existing and proposed method when irradiation level is varied from 1000 to 800 W/m 2 at 0.2 sec

20 79 Figure 3.16 Converter output voltage for existing and proposed method (irradiation level is varied from 1000 to 800 W/m 2 at 0.2 sec) Figure 3.17 Converter output current for the existing and proposed MPPT method (irradiation level is varied from 1000 to 800 W/m 2 at 0.2 sec) Figure 3.18 Comparison of MPPT tracking speed of existing and proposed MPPT algorithm for various irradiation levels

21 VOLTAGE AND CURRENT RIPPLE OF PV PANEL AND CONVERTER IN THE PROPOSED PV SYSTEM Figures 3.19 and 3.20 show the microscopic view of the PV panel voltage and current at 1000 W/m 2. It is observed that the ripple voltage of the existing P&O method is 2.4V and the proposed method is 6.5mV. Similarly, in the proposed MPTT method, PV panel ripple current is very low for all irradiation levels. The microscopic views of the converter output voltage and current ripple at 1000 W/m 2 are highlighted as shown in Figures 3.21 and (a) (b) Figure 3.19 Microscopic view of PV panel output voltage ripple at 1000 W/m 2 (a) For existing MPPT method (b) For proposed MPPT method

22 81 (a) (b) Figure 3.20 Microscopic view PV panel output current ripple at 1000 W/m 2 (a) For existing P&O method (b) For proposed MPPT method (a)

23 82 (b) Figure 3.21 Converter output voltage ripple at 1000 W/m 2 (a) For existing P&O method (b) For proposed MPPT method (a) (b) Figure 3.22 Converter output current ripples at 1000 W/m 2 (a) For existing MPPT method (b) For proposed MPPT method

24 83 From the simulation results, it is observed that compared to the existing P&O algorithm, the proposed method tracks the MPP quickly for the varying irradiations and reduces the ripple significantly. Table 3.3 shows the comparison of simulation results of the existing P&O and the proposed MPPT methods in terms of ripple content at various irradiation conditions. The significant ripple reduction is obtained through the proposed system, compared to the existing method under different operating conditions. Table 3.3 Ripple content of the existing P&O and the proposed MPPT technique for various irradiation conditions Existing P&O MPPT Method Proposed MPPT Method Irradiation Level (W/m 2 ) PV Panel Converter Output PV Panel Converter Output V PV (V) I PV (A) V O (V) I O (A) V PV (V) I PV (ma) V O (V) I O (A) EXPERIMENTAL RESULTS AND DISCUSSION To verify the functionality and the performance of the proposed method, a hardware prototype is built in the laboratory with the same specifications as in the simulation environment. The performance of the prototype model PV system is verified under different irradiation conditions. Figure 3.23 presents the experimental setup of the proposed solar PV system. The proposed MPPT algorithm is implemented using Field Programmable Gate Array (FPGA - SPATRAN-6XC6SLX9) controller to control the duty cycle of the LUO converter based on the proposed algorithm. The Xilinx software is used to develop the programs for Spartan 6 and is loaded in the FPGA.

25 84 Figure 3.23 Experimental set up of proposed solar PV system Figure 3.24 shows the experimental waveform of the gate signal applied to the switch (S) of the LUO converter at irradiation level of 1000 W/m 2 for the proposed MPPT technique. Figure 3.25 shows the corresponding changes in the PV module output terminal voltage for the existing and the proposed algorithms. It is clearly observed that the ripple is reduced in the proposed method. The tracking time is 0.15 sec for the existing method and 0.09 sec for the proposed method. Figures 3.26 and 3.27 show the voltage across inductors (L 1 and L 2 ) of the converter for the proposed MPPT at 1000 W/m 2. Figures 3.28 and 3.29 show the output voltage of LUO converter for the existing and the proposed MPPT systems with microscopic view of voltage ripple at 1000 W/m 2. Figure 3.30 shows the output voltage of LUO converter at steady state condition for the proposed MPPT at irradiation level of 1000 W/m 2. The hardware results are in close agreement with the simulated results. The ripple voltage and current are minimized in the proposed method when compared to the same obtained from the existing P&O method and also tracking is very fast. It is clear that for a fixed load and varying solar irradiation conditions, the duty ratio of the converter is adjusted by the FPGA such that the PV array terminal voltage tracks the MPP

26 85 voltage. Comparison of various parameters such as tracking speed, V MPP, I MPP,V O, I O and its ripple voltage and current values for the existing and proposed MPPT methods at 1000 W/m 2 are tabulated which is depicted in the Table 3.4. Figure 3.24 Generated gate pulse for the switch (S) for the LUO converter at 1000 W/m 2 Figure 3.25 Experimental results of the PV panel output voltage at 1000 W/m 2 (a) For existing P&O method (b) For proposed MPPT method

27 86 Figure 3.26 Voltage across inductor L 1 of LUO converter at 1000W/m 2 Figure 3.27 Voltage across inductor L 2 of LUO converter at 1000 W/m 2

28 87 Figure 3.28 Experimental results of the converter output voltage for existing MPPT method with microscopic view of voltage ripple at 1000 W/m 2 Figure 3.29 Experimental results of the converter output voltage for proposed MPPT with microscopic view of voltage ripple at 1000 W/m 2

29 88 Figure 3.30 Experimental results of the converter output voltage for proposed MPPT at steady state condition Figure 3.31 Experimental results of the converter output current (a) For the existing P&O method with microscopic view of ripple (b) For the proposed MPPT method with microscopic view of ripple Figure 3.31 shows the LUO converter output current ripples at 1000 W/m 2 for the existing P&O and proposed MPPT algorithm. It is observed that existing P&O MPPT gives 84mA output ripple current whereas the proposed MPPT gives only 3.1mA at 1000 W/m 2 which shows good results. Similarly for

30 89 other irradiation levels, PV panel current and voltage also converter output current and voltage ripple is very less in the proposed MPPT technique. Table 3.4 Comparisons of performance parameter for existing P&O and proposed MPTT algorithm at 1000 W/m 2 Parameters Existing Simulation Proposed Experimental Result of Proposed Method MPPT P&O MPTT Technique Implementation of MPTT MPP Tracking Time (sec) V MPP (V) I MPP (A) V PV 2.4V 6.5mV 12.5 mv I PV 0.135A 0.1mA 0.45mA V O (V) I O (A) V O 2V 20mV 24.5mV I O (ma) It is observed that the proposed MPTT based MPPT method has lot of merits compared to the existing P&O method such as fast tracking, reduced ripple and the complexity of implementing the MPPT algorithm is less. 3.9 SUMMARY In this work, a new MPTT based MPPT technique is proposed which effectively tracks the MPP of a solar panel using LUO converter under varying irradiation conditions. The simulation results demonstrate the capability of the proposed system to eliminate the undesirable ripples in the converter and PV module. The MPPT performance characteristics are predetermined by MATLAB/SIMULINK environment and compared with the existing P&O

31 90 technique. It is also verified experimentally with a FPGA controller based laboratory prototype using 40-W solar panel along with the proposed converter. The experimental results show that the proposed MPPT algorithm is accurate and has fast tracking response with low ripple. The algorithm is simple to implement and cost effective, since additional control loop is not required.

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