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MAXIMUM POWER POINT TRACKING CONTROLLER BASED ON SLIDING MODE APPROACH Maissa Farhat*, Oscar Barambones**, Jose A. Ramos**, Jose M. Gonzalez de Durana** *Research Unit of Photovoltaic, Wind and Geothermal Systems, National Engineering School of Gabes, University of Gabes, Rue Omar Ibn-Elkhattab, Zrig, Gabès, 6029, Tunisia. [email protected] **Advanced Control Group. Universidad del País Vasco, EUI, Nieves Cano 12, 01006 Vitoria, España. [email protected] Abstract Recently, the solar energy has become an alternative source of energy of great importance. Diverse researches and efforts have been concentrated on the photovoltaic (PV) systems efficiency improvement and the accessibility to this technology. This paper presents an intelligent approach for the improvement and optimization of the PV system efficiency. A PV system topology incorporating a maximum power point tracking controller (MPPT) is studied. In order to perform this goal a special interest was focused on the sliding mode control and the P&O algorithm. This paper presents a detailed study and design of a MPPT controller to ensure a high PV system performance which can be selected for practical implementation issue. A simulation examples shows that the MPPT is achieved using a DC/DC Boost converter between the PV system and the resistive load. Significant extracted results are given to prove the validity of the proposed overall PV system. Keywords: PV, Boost Converter, MPPT, SMC. 1 INTRODUCTION This work analyses the control of a stand-alone PV system. However the success of a PV application depends on whether conditions where the power electronics devices helped to extract a high power from the PV generator (PVG). The extraction of the maximum of power from the PVG is then indispensable. Therefore, maximum power point tracking (MPPT) controller accuracy becomes a key control in the device operation for successful PV applications. In general, the MPPT control is a challenging, because the sunshine condition that determines the amount of sun energy into the PVG may change at any time. Therefore, the PV system can be considered as a non-linear complex system. Numerous MPPT methods have been developed and implemented in previous studies, for instance, perturb and observe (P&O), fractional open-circuit voltage and fuzzy logic controller (FLC) approaches [7] etc. These techniques have high tracking accuracy under stable internal and external condition, but still reveal some trade-offs between tracking speed and tracking reliability when load values or weather conditions rapidly changes [6]. Sliding mode controller has recently attracted considerable attention of researchers, The main benefit of the sliding sector technique is that it can avoid chattering [1],[8], Its advantage among, is the simplicity of implementation, robustness, and great performance in different fields such as robotic, motor control, etc. In this paper the interest was focus in the use of SMC in the photovoltaic fields by maximizing the power generated from the PV panels. Moreover, the system stability is demonstrated [2]. The main role of this controller is to generate a command using a voltage reference (Vref) in order to force the system to work at the MPP. The Vref is generated online via a voltage reference generator that doesn’t require the irradiation measurement. In this paper, the SMC algorithm generates directly PWM signal. This last has the benefit to avoid the use of a PWM commutation signal (Saw signal). It permits to build directly a PWM output signal toward the converter IGBT gate. Contrariwise, other algorithm such as P&O [7] generates a duty cycle signal that will be used with a reference saw signal to generate a PWM IGBT drive signal. In general, a PV system is typically built around the following main components as shown in figure 1: 1) A PVG that converts solar energy to electric one, 2) A DC-DC converter that manipulates produced DC voltage by the PV arrays to a load voltage demand, 3) A digital controller that drives the converter operation with MPPT capability. 4) Resistive Load Actas de las XXXV Jornadas de Automática, 3-5 de septiembre de 2014, Valencia ISBN-13: 978-84-697-0589-6 © 2014 Comité Español de Automática de la IFAC (CEA-IFAC) q Vc RS I c I d I rs exp 1 kT I sh (3) 1 Vc RS I c Rp (4) The reverse saturation current at reference temperature can be approximately obtained as: I rs I rs _ ref (5) qVoc exp 1 ns .n. .Tc Finally the cell current Ic can be given by Figure 1: Synoptic diagram of PV system Ic I 2 PHOTOVOLTAIC CONVERSION ph I rs exp q Vc Rs I c kT 1 1 Rp Vc Rs Ic (6) ENERGY The modeling of a PVG depending on series and parallel number respectively Ns and Np as: 2.1 PVG MODEL I p N p I c V p N s n s V c One can substitute a PV cell to an equivalent electric circuit which includes a power supply and a diode. (7) Figure 2: Simplified PV Cell Equivalent Circuit The power source produces the Iph current, which depends on impinging irradiation. Through diode flows the current Id. The current Ic feeding the load is the difference between Iph and Id which is reduced by the resistance RS. This last represents resistances of cell and connection among cells [5]. By exploiting the node law Finally the PVG current (Ip) can be given by I c I ph I d I sh (1) The current Iph can be evaluated as: I ph G G ref I rs _ ref K SCT Tc Tc _ ref Figure 3: A PVG Group of modules; Ns numbers in series and Np in parallel. Rs I P q Vp N p I rs exp I p N pI ph kT ns N s Np N p Vp (2) Rs I P R p ns N s N p Actas de las XXXV Jornadas de Automática, 3-5 de septiembre de 2014, Valencia ISBN-13: 978-84-697-0589-6 © 2014 Comité Español de Automática de la IFAC (CEA-IFAC) 1 (8) The highly I-V nonlinear characteristics are shown in figure 4 for different irradiation values. 70 60 G=1200W/m² G=1000W/m² G=500W/m² G=300W/m² Ip(A) 50 40 30 20 10 0 0 2 4 6 8 10 12 14 16 18 20 Vp(v) Figure 5 shows the circuit diagram of a boost converter, and a load. 5 4 Ip(A) 3 2 1 0 Figure 5: Circuit diagram of the Boost converter 0 2 4 6 8 10 12 14 16 18 20 Vp(v) Figure 4: (a) P-V and (b) I-V characteristics at fixed temperature value of 25.3°C 2.2 BOOST CONVERTER DC-DC converters are electronic devices used whenever is needed to change DC electrical power efficiently from one voltage level to another. They’re necessary because unlike AC, DC can’t simply be stepped up or down using a transformer. In many ways, a DC-DC converter feeding the load is going through a regulated converter to hold its maximum. Hence, the efficiency of the photovoltaic system is performed. In order to step up the voltage, the operation consists of switching an IGBT shown in figure 5 at a high commutation frequency, with output voltage control by varying the switching duty cycle (D). When the IGBT is switched on, current flows from the input source through the inductor (L) and the IGBT, then the energy is stored in the inductor. After that there is no current through the Diode (D1), and the load current is supplied by the capacitance hold charge in(C). The IGBT is turned off; L opposes any drop in current by immediately reversing its emf. So, the inductor voltage adds to (i.e., .boosts.) the source voltage and current due to this boosted voltage now flows from the source through L, D1 and the load, recharging C as well. The output voltage is therefore higher than the input voltage, and it turns out that the voltage step-up ratio is equal to [4] The boost converter is assumed to operate in a continuous conduction mode with two states based on the status of the switch. 1 VO Vin 1 D (9) Based on the assumption where Pin=Pout it can be deduce that Rpv (1 D)2 Rout (10) Where Rpv is the equivalent resistance connected to the PV panel and 1-D is actually the proportion of the switching cycle that the IGBT is off, rather than on. 3 MPPT CONTROLLERS 3.1 P&O ALGORITHM Due to its simplicity, P&O algorithm presented in figure 6 is the most popular [10], The principle of this controller is to provoke perturbation by acting (decrease or increase) on the PWM duty cycle command and observe the output PV power reaction. If the actual power P (k) is greater than the previous computed one P (K-1), then the perturbation direction is maintained otherwise it is reversed [3]. The ∆D crisp value is chosen by trial and tests in simulation. The P&O diagram is: If the crisp value ∆D is very big or very small then we may lose information. Despite the P&O algorithm is easy to implement it has mainly the following problems The PV system will always operates in an oscillating mode. The PV system may fail to track the maximum power point and as result operate in current or voltage zones. Actas de las XXXV Jornadas de Automática, 3-5 de septiembre de 2014, Valencia ISBN-13: 978-84-697-0589-6 © 2014 Comité Español de Automática de la IFAC (CEA-IFAC) involves the maximum of extractable power, a number of such couples for different irradiation values have been collected and then interpolated to get the suitable function (VMPP= F(PMPP)). Ip (k ),V p ( k ) This function is created using Matlab Fitting Curve Toolbox. In this work several test has been done using diferent type of function such as, Fourier, gaussian, rational, and the polynomial function like the work of Abderrahim, [10]. Finely we deduce that the power function fits more the Atersa model. The constructed function is denoted as : P (k ) Ip (k ) V p ( k ) P 0 V p 0 D(k) D(k 1) D V p 0 D(k) D(k 1) D D(k) D(k 1) D F(x) = a xb +c D(k) D(k 1) D (11) Where the a, b, c coefficient as numerical values specific for the used PV panel. With: a=-8.638; b=0.1697; c=19.74; Figure 6: P&O Algorithm global structure Step 2 3.2 SLIDING MODE CONTROL The method of control is divided into two steps the first is determine the voltage value at which the system operates with its maximum of power, and then the second is to operate the system with this voltage value that gives the maximum power. After determined the Vref the implemented (SMC) algorithm calculate the difference between the acquired PV voltage and the Vref and then, via the boost converter force the PVG to operate at the reference voltage value (Vref) and therefore at the maximum power zone. S = e = V p V ref (12) Step 1 In this part of the work, the main objective is to construct a MPP voltage-reference generator that meets the MPP. Specifically, this generator is expected to compute on-line the optimal voltage value VMPP so that, if the voltage Vp is made equal to VMPP then, maximal power is captured. In fact this method does not require irradiation measurement u 1 1 S ig n ( S ) 2 1 u 0 S 0 S 0 (13) (14) Stability demonstration: The stability can be analyzed using the Lyapunov stability method. A positive definite function V is defined as: 18 17 reference Voltage (v) 16 V 15 14 1 2 S 0 2 (15) Whose time derivative is: dS V S = SS dt 13 12 11 10 0 10 20 30 40 50 60 70 80 Power(W) Considering Figure 7: Optimal power-voltage characteristic The figure 7 present the curve of optimal powervoltage characteristic obtained from the polynomial interpolation. It is easy to see from figure 4 that for any radiation G, there is a unique couple (Vp, P) that S e V p VMPP * S e Vp When S>0 The switch will be open, this imply that the duty cycle will increase. From the boost converter model Actas de las XXXV Jornadas de Automática, 3-5 de septiembre de 2014, Valencia ISBN-13: 978-84-697-0589-6 © 2014 Comité Español de Automática de la IFAC (CEA-IFAC) equation (10) we have, R pv (1 D)2 Rout and using this equation, we can observe that if the duty cycle D increases, then Rpv= (1 D) 2 Rout decreases so based on the PV dynamic given by the I-V characteristic shown in figure 8, the Ip will increase and Vp will decrease equivalently from eq (8), it can be deduced that, when the voltage (Vp) increase/decrees the current (Ip) decrease/increase, so, if the resistance connected to the PV panel decrease then (Ip) increases and (Vp) decreases 1 R pv 5 4.5 1 RMPP 4 I MPP3.5 Ip(A) 3 2.5 2 1.5 1 1 R pv 0.5 0 0 5 10 15 Vp(v) VMPP 20 25 Figure 8: I-V characteristics So as a consequence in this case, this imply that 0 and S 0 Vp 4 SIMULATION RESULTS In this section, the PV system global control shown in figures 1 is implemented The sliding-mode MPPT, with optimal voltage reference, is compared to P&O algorithm. The robustness of both controllers is tested over internal and external variation. The system is tested over a sudden step load variation and irradiation change. Figure 9 present the I-V and P-V characteristic at fixed temperature and different irradiation values (500 and 1000W/m²) Figures 10, 11 show respectively the irradiation and load variation. Figure 12 (a) shows the controllers output. The SMC build directly a PWM output Signal toward the converter IGBT gate, however the P&O algorithm generate a duty cycle signal that will be used with a reference saw signal (MLI) to generate a PWM IGBT drive signal. Figure 12(b) in a zoom of figure 12 (a) and shows the impact of the irradiation variation on the SMC frequency. Figures 13, 14, 15 show the PVG current, voltage and power respectively. These figures show that in spite of the load change: the operation point of the PV remains constant in the MPP due to the robustness of controllers. When the irradiation changes, the MPP also changes its position, so the controller act in order to track the new MPP. Figure 16 and 17 show the load voltage and current. SS 0 and finally 60 G=1000W/m² G=500W/m² 5 When S<0 , using the same method The switch will be close, this imply that the duty cycle will decrease. If the duty cycle D decreases, then Rpv= ( (1 D) 2 Rout ) increases so based on the PV dynamic given by the I-V characteristic shown in figure 8, the Ip will decrease and Vp increase equivalently from eq (8), it can be deduced that, when the voltage (Vp) decrease/increase the current (Ip) increase/decrease, so if the resistance connected to the PV panel increase then (Vp) increases and (Ip) decreases, and this imply that: Ip(A) 4 40 3 2 20 1 0 0 5 10 15 20 0 25 Vp(v) Figure 9: I-V and P-V characteristic under constant temperature (25°C) 1200 and then S 0 SS 0 G(W/m²) 1000 0 and Vp 800 600 400 200 0 0 0.5 1 Time(s) Finally, using the Lyapunov stability theory it can be concluded that S reaches the state S = 0 means that the system reaches the desired voltage value Vref and hence the convergence to the point of maximum power. Figure 10: irradiation Actas de las XXXV Jornadas de Automática, 3-5 de septiembre de 2014, Valencia ISBN-13: 978-84-697-0589-6 © 2014 Comité Español de Automática de la IFAC (CEA-IFAC) 1.5 60 1.5 50 1 IR(A) R() 40 30 20 0.5 10 0 0 0.5 1 1.5 0 0 0.5 Time(s) 1 1.5 Time(s) Figure 11: Load Value Figure 17: current Load (a) 1 The obtained simulation results show that both systems using different controller present a good maximum power tracking, however the SMC controller present less oscillations and fast tracking in the response. SMC P&O D 0.5 0 -0.5 0 0.5 1 1.5 Time(s) Figure 12 a: Controller output 5 CONCLUSION 1 0.8 0.6 0.4 0.2 0 0.998 0.999 1 1.001 1.002 1.003 1.004 1.005 Figure 12 b: Controller output 4 3 Ip(A) 3.55 3.5 2 In this work, a complete study of PV systems integrating an MPPT controller was studied. The proposed PV system is composed of a PV generator, a boost converter and a resistive load. In order to bring up the system efficiency a designed SMC MPPT controller was presented. This controller guarantees high dynamic system performances. Simulation results are given to highlight the obtained performances. This study is the foundation of a practical implementation follow-up this research work. 3.45 3.4 3.35 0.4 1 0.45 0.5 0.55 0.6 Agradecimientos 0 0 0.5 1 1.5 Time(s) Figure 13: PVG current 25 Este trabajo ha sido realizado parcialmente gracias al apoyo de la Universidad del País Vasco (GIU13/41 y UFI11/07) Vp(v) 20 15 17 10 16 5 0 APPENDIX A 16.5 15.5 0.45 0.5 0 0.55 0.5 1 1.5 Time(s) Figure 14: PVG Voltage 60 50 40 P(W) 30 30 29 28 20 27 1 10 0 G,Gref I p, Vp Rp, Rs n Eg Irs KSCT 0 1.05 1.1 1.15 0.5 1.2 1 1.5 Time(s) Figure 15: PVG Power 60 50 Tc, Tc_ref β D Ns, Np ns Global, Reference insulation (W /m2). Cell output current and voltage. Cell parallel and series resistance (Ω). Solar ideal factor Band gap energy (ev) Reverse diode saturation current (A) Short circuit current temperature (A/°K). Cell junction and Reference temperature (°C). Boltzmann constant (1. 38e-23) duty cycle Number of series and parallel modules. Number of series cells VR(v) 40 30 20 10 0 0 0.5 1 1.5 Time(s) Figure 16: The load voltage Actas de las XXXV Jornadas de Automática, 3-5 de septiembre de 2014, Valencia ISBN-13: 978-84-697-0589-6 © 2014 Comité Español de Automática de la IFAC (CEA-IFAC) Referencias [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] A. Alqahtani, V. Utkin in. (2012), SelfOptimization of Photovoltaic System Power Generation Based on Sliding Mode Control. Proceedings of IECON’12. A.Cid-Pastor. (2013), Synthesis of loss-free resistors based on sliding-mode control and its applications in power processing. Control Engineering Practice, vol. 21, pp.689-699. E.F. Abderrahim, G .Fouad., M.Abdel moinime (2013), Reference Voltage Optimizer for Maximum Power Tracking in Single-Phase Grid-Connected Photovoltaic Systems, Journal of Control and Systems Engineering vol.1, n. 2, pp.57-66 J.Park, S, Kim, (2012), Maximum Power Point Tracking Controller for Thermoelectric Generators with Peak Gain Control of Boost DC–DC Converters, ‘Journal of Electronic Materials, vol. 41, pp. 1242-1246. M. Farhat, and L. Sbita., (2012), Advanced ANFIS-MPPT Control Algorithm for Sunshine photovoltaic Pumping Systems," International Conference on Renewable Energies and Vehicular Technology. M. Veerachary,T. Senjyu., and K. Uezato, (2002). Feedforward maximum power point tracking of PV systems using fuzzy controller, IEEE Transactions on Aerospace and Electronic Systems 38, pp. 969-981. T. Esram, P. L. Chapman, (2007). Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques. IEEE transactions on energy conversion vol. 22. Y.Levron and D. Shmilovitz, (2013), Maximum power point tracking employing sliding –mode control. IEEE Trans. on Circuits and Systems vol. 60, pp.724-731. Z. Shiqiong., Longyun . K, Jing. S, Guifang .G, Bo Cheng,. B Cao, Yiping . T (2010), A novel maximum power point tracking algorithms for stand-alone photovoltaic, system, International Journal of Control, Automation and Systems, vol.8,n. 6, pp. 1364-1371. Z. Zaidi., F. Boudjema, (2010), Hybrid Control and Optimization of a Plus-EnergyHouse with DHWS, International Renewable Energy Congress IREC, Sousse, Tunisia. Actas de las XXXV Jornadas de Automática, 3-5 de septiembre de 2014, Valencia ISBN-13: 978-84-697-0589-6 © 2014 Comité Español de Automática de la IFAC (CEA-IFAC)