Power Control Approach for PV Panel System Based on PSO and INC Optimization Algorithms

With the development of the world, the search for renewable energy continued not only popular with companies, but with the advancement of technology, ordinary people began to use it. Currently, approximately 26% of the world is powered by renewable energy [1]. Solar energy is a most widely renewable energy source due to the absence of fuel costs, minimal maintenance needs, and environmental friendliness [2]. In  solar power system Photovoltaic (PV) model is used to convert the light and heat from the sun into electricity. PV model  has gained significant attention in the last decades as it has no moving part, a companion to its environment and produces less pollution of the environment [3]. Improvements  of PV solar cells have been continuing to increase their efficiency and accuracy and make them cheaper and more flexible. Development of power electronics and control approaches plays an essential role in the improvement of the PV solar power systems. The main electric parts of the PV solar energy system are power converters and inverters [4]. Power converters differ according to the principle of functioning, construction, energy efficiency, size, precision control, transitional state response, and price [5]. These  electronic devices are mainly classified: Buck-Boost, Boost, Buck, Zeta, Sepic, and Cuk converters [6]. The converters are more power-efficient devices due to  their high voltage conversion efficiency, which  reaches to 98%. In solar power systems, the power converters are used to regulate the PV output voltage and supply a suitable voltage to DC load. Type and number of power converters used in the solar energy system is governed by the system application. Maximum Power Point Tracking (MPPT) technology is used to extract maximum power from PV panel. MPPT is implemented using one of the optimization algorithms like Incremental Conductance (INC) and Practicles Swarm Optimization (PSO) algorithms and Perturb& Observe (P&O) which are adopted to tune the duty cycle of of the Pulse Width Modulation (PWM) command signal used to control the switching process of the power converter circuit. 

The second part of the PV power system, voltage inverters, are used to connect PV cells  by on-grid and off-grid system and provide the load by an AC voltage. It is worth considering that the converters and inverter circuits are non-linear systems. Generally,  claasic and optimal linear controllers like PID  and LQR controller respectively are used successfully to implement control action of more nonlinear systems within an acceptable operating space [7-10]. PID controller is highly recommended to implement the control action of various industrial applications due to its simplicity and easy to realize [11]. In this study, a linear PID contoller can be adopted to perform a voltage regulation process of the DC/DC converters and DC/AC inverter circuits in the proposed PV power system as the variation of the input voltage of these circuits is not huge. While for massive variation input voltage power systems, PID linear control system may not give an acceptable voltage regulation performance, for this type of systems a non-linear controller technique is recommended to control its output voltage.  

In order to improve the performance of the PV power system, the parameters of the MPPT control and the converter controller should be tuned properly. A classic tuning approach using trial and error method can be used to improve the performance of the voltage control system. However, this manual tuning approach consumes more time and effort [12]. Moreover, there is no guarantee that the system based on the tuned parameters can achieve best performance.To avoid the drawbacks of the manual tuning approach, many intelligent optimization methods; Genetic Algorithm (GA) [13], [14],  Fuzzy Logic (FL) [15], Big Bang-Big Crunch (BBBC) algorithm [16], Bacterial Foraging Optimization (BFO) algorithm algorithm [17], [18], Particle Swarm Optimization (PSO) algorithm [19], [20] and Artificial Bee Colony (ABC) [21], [22] are successfully used by many researchers to optimize the  PID controller in various control problems. In this application, a PSO tuning method is used to obtain best values for the system control parameters, as it has a simple procedure, a rapid convergence speed and  easy to implement. Furthermore its ability to find a global solution for the power system problem.During the past decades there is a considerable interest in development of the solar energy systems. In [23], Reshma S. Jadhav et al A hybrid renewable energy system based on PV and wind  with  battery  storage is presented for grid connection .A solar cell and wind turbine are employed to power on and off grid link and charging a battery bank. A Boost converter is used to match between PV-wind-battery system and grid connection. PI controller is adopted to regulate the output voltage of the DC-DC boost converter. In this study, the energy generated by solar array and wind turbine is managed by a control unit so that an effective power is supplied to battery bank, autonomous grid, off-grid and load. The proposed hybrid power system is simulated  using Matlab/Simulink environment and its output responses are analysed  to confirm the efficiency of the suggested power generation and management method.

The authors in [24] presented power system supplied by solar panels and batteries for stand-alone and on-grid connections. They introduced solar inverter which integrates  PV array, battery, grid and DC load using Fuzzy control approach.  The role of Fuzzy Logic (FL) controller is to determine the amount of power that each source should supply to DC-rail.  Based on the proposed FL control approach, the PV panel operates in ON/OFF MPPT, which help operate the inverter in stand-alone mode. A Boost converter is used to adjust the output voltage of solar panel that should supply to DC load and AC load  through inverter. The researchers proposed the MPPT  technique to get the maximum power supplied to loads based on FL method.. Based on the connection strategy  between panel, battery and grid, the performance of the proposed power system is tested and evaluated under  seven connection modes.  The simulation results proved that the proposed control system could manage an intelligent power flow between the sources.

Julio Seguel et al in [25] used Buck and Buck-Boost converter to convert energy from solar panels to load. The researchers compared the performance of three methods of MPPT to obtain maximum power from PV, using incremental conductance, perturb and observe, and constant voltage. The proposed method was confirmed by simulation using MATLAB/Simulink. Simulation results obtained from the PV system operating under temperature and various radiation conditions are compared and discussed. The INC--Buck combination had the highest steady-state efficiency while  the PV-Buck-Boost combination showed the best transient behavior.

In 2021, Rinku et al. in [26] proposed a renewable power system for resistive load based on a PV array using MPPT controller with Boost converter.  In this study, the MPPT controller is implemented using modern PSO  algorithm and the traditional  algorithms, INC and P&O, which are used to extract maximum power of the PV panel under constant solar insolation and temperature conditions.   The proposed system is simulated using Matlab/Simulink software to test the performance of the presented PSO/INC/P&O-MPPT controllers. The response of average power extracted  from PV panel and the output voltage across the load using PSO, INC and P&O algorithms are evaluated based on  rise  time,  settling time and overshoot, parameters.  The simulated results showed that the presented PSO-MPPT controller  can enhance the power efficiency  of the PV panel system and achieve more accurate and faster response compared with the standard algorithms.

In 2021, Koson et. al in [27] proposed a modified solar power system based on non-iterative MPPT control for single phase off-grid connection. The PV power is delivered to the grid system through a single-stage single-phase inverter circuit. The power converter circuit of the system is modified to implement open circuit voltage V_oc and short circuit current I_sc measurements of the PV array. The non-iterative MPPT is designed to realize the maximum power of the PV panel using the datasheet parameters of the PV panel  combined with the V_oc and Isc measurements. In the study, a double band hysteresis current controller is used to regulate the output current of the inverter circuit based on the current reference. The system based on non-iterative MPPT control algorithm is simulated using Matlab/Simulink tool. The simulation results in transient and steady state domains are analysed to evaluate the performance of the proposed system. The simulated test  confirmed that under changing irradiance working conditions the presented power system can transfer maximum power from the PV panel to the off-grid system  with 〖THD〗_i  of 2.9% and PF of 0.95. In this paper, an off-grid interface PV system based on a Boost converter is also presented.  Two control methods, PSO and INC, are adopted to implement the MPPT technique for the PV panel system. MPPT is based on the INC and PSO control method  is used to track maximum power generated from the photovoltaic array to the load system.  A bidirectional Buck-Boost converter is utilized to charge the battery by full power and discharge its power to DC loads to enhance the power delivered to the load system.The rest of the paper is organized as follows; the configuration and mathematical modelling of the proposed PV power system are given in section 2. Optimization algorithms are presented in Section 3. Section 4 introduces the theory of the PID controller technique of the system. In section 5, Simulation results PV power system., followed by concluding remarks in section 6.