scholarly journals Power Maximization in Standalone Photovoltaic System: An Adaptive PSO Approach

Author(s):  
Anbarasi MP ◽  
Kanthalakshmi S

Abstract A control strategy for power maximization which is an important mechanism to extract maximum power under changing environmental conditions using Adaptive Particle Swarm Optimization (APSO) is proposed in this paper. An Adaptive Inertia Weighting Factor (AIWF) is utilised in the velocity update equation of traditional PSO for the improvement in speed of convergence and precision in tracking Maximum Power Point (MPP) in standalone Photovoltaic system. Adaptation of weights based on the success rate of particles towards maximum power extraction is the most promising feature of AIWF. The inertia weight is kept constant in traditional PSO for the complete duration of optimization process. The MPPT in PV system poses a dynamic optimization problem and the proposed APSO approach paves way not only to track MPP under uniform irradiation conditions, but also to track MPP under non uniform irradiation conditions. Simulations are done in MATLAB/Simulink environment to verify the effectiveness of proposed technique in comparison with the existing PSO technique. With change in irradiation and temperature, the APSO technique is found to provide better results in terms of tracking speed and efficiency. Hardware utilizing dSPACE DS1104 controller board is developed in the laboratory to verify the effectiveness of APSO method in real time.

Author(s):  
Noureddine Boubekri ◽  
Sofiane Doudou ◽  
Dounia Saifia ◽  
Mohammed Chadli

This paper focuses on mixed [Formula: see text] fuzzy maximum power point tracking (MPPT) of photovoltaic (PV) system under asymmetric saturation and variations in climatic conditions. To maximize the power from the PV panel array, the DC–DC boost converter is controlled by its duty ratio which is practically saturated between 0 and 1. MPPT based on conventional control presents the problems of oscillations around maximum power point (MPP) and divergence under rapid climatic changes. In order to attenuate the effect of atmospheric condition variation and take into account asymmetric saturation of the duty ratio, we propose a novel robust saturated controller based on both [Formula: see text] performances and Takagi-Sugeno (T-S) representation of PV-boost nonlinear system. Within this approach, the nonlinear PV-boost system and its reference are first described by T-S fuzzy models. Second, the saturation effect is represented by a polytopic model. Then, a fuzzy integral state feedback controller is designed to achieve stable MPPT control. Based on Lyapunov function, the mixed [Formula: see text] stabilization conditions are derived in terms of linear matrix inequalities (LMIs). The optimization of the attraction domain of closed-loop system is solved as a convex optimization problem in LMI terms. Finally, the efficiency of the proposed controller under irradiance and temperature variations is demonstrated through the simulation results. The comparison with some existing controllers shows an improvement of MPPT control performance in terms of power extraction.


2019 ◽  
Vol 8 (2S8) ◽  
pp. 1140-1148

The extensive usage of solar has extended the opportunity of research to increase the efficiency of PV module. Maximum Power Point Tracking technique plays an important role. In P & O and Incremental conductance the power produced is less. In this paper a Fuzzy based P & O and Fuzzy based Incremental Conductance MPPT techniques are presented to extract the maximum power from the photovoltaic system by considering the dynamic variation in irradiations and temperature also. Here the 100 kW PV array is considered and it is connected to the utility grid via a DC-DC boost converter of 500volts with a 3 phase three level voltage source converter. The result is obtained by the MAT LAB Simulink and the same is appraised with the traditional P & O and Incremental conductance. The PV System produces the maximum power by the application of Fuzzy based incremental Technique compared to conventional methods.


2018 ◽  
Vol 7 (4.35) ◽  
pp. 457
Author(s):  
M. I. Iman ◽  
M. F. Roslan ◽  
Pin Jern Ker ◽  
M. A. Hannan

This work comprehensively demonstrates the performance analysis of Fuzzy Logic Controller (FLC) with Particle Swarm Optimization (PSO) Maximum Power Point Tracker (MPPT) algorithm on a stand-alone Photovoltaic (PV) applications systems. A PV panel, DC-DC Boost converter and resistive load was utilized as PV system. Three different MPPT algorithms were implemented in the converter. The result obtained from the converter was analyzed and compared to find the best algorithm to be used to identify the point in which maximum power can be achieve in a PV system. The objective is to reduce the time taken for the tracking of maximum power point of PV application system and minimize output power oscillation. The simulation was done by using MATLAB/Simulink with DC-DC Boost converter. The result shows that FLC method with PSO has achieved the fastest response time to track MPP and provide minimum oscillation compared to conventional P&O and FLC techniques.


2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
M. Abdulkadir ◽  
A. H. M. Yatim ◽  
S. T. Yusuf

This paper presents a control strategy proposed for power maximizing which is a critical mechanism to ensure power track is maximized. Many tracking algorithms have been proposed for this purpose. One of the more commonly used techniques is the incremental conductance method. In this paper, an improved particle swarm optimization- (IPSO-) based MPPT technique for photovoltaic system operating under varying environmental conditions is proposed. The approach of linearly decreasing scheme for weighting factor and cognitive and social parameter is modified. The proposed control scheme can overcome deficiency and accelerate convergence of the IPSO-based MPPT algorithm. The approach is not only capable of tracking the maximum power point under uniform insolation state, but also able to find the maximum power point under fast changing nonuniform insolation conditions. The photovoltaic systematic process with control schemes is created using MATLAB Simulink to verify the effectiveness with several simulations being carried out and then compared with the conventional incremental conductance technique. Lastly, the effectiveness of the intended techniques is proven using real data obtained form previous literature. With the change in insolation and temperature portrait, it produces exceptional MPPT maximization. This shows that optimum performance is achieved using the intended method compared to the typical method.


2011 ◽  
Vol 480-481 ◽  
pp. 739-744
Author(s):  
Kuei Hsiang Chao ◽  
Yu Hsu Lee

In this paper, a novel incremental conductance (INC) maximum power point tracking (MPPT) method based on extension theory is developed to make full use of photovoltaic (PV) array output power. The proposed method can adjust the step size to track the PV array’s maximum power point (MPP) automatically. Compared with the conventional fixed step size INC method, the presented approach is able to effectively improve the dynamic response and steady state performance of a PV system simultaneously. A theoretical analysis and the design principle of the proposed method are described in detail. Some simulation results are performed to verify the effectiveness of the proposed MPPT method.


2012 ◽  
Vol 263-266 ◽  
pp. 2131-2137
Author(s):  
Qing Fu ◽  
Guang Lei Cheng ◽  
Feng Jie Liu ◽  
Gui Long Ma

To utilize maximum solar energy, maximum power point tracking (MPPT) control is much important for PV system. The paper presents a new MPPT method based on adaptive predictive algorithm which is superior to traditional Perturbation and Observation (P&O) method. PV output power is predicted to improve the tracking speed and deduce the possibility of misjudgment of increasing or decreasing the PV output voltage. Because PV output power can be obtained directly, close loop can be established so as to achieve a precise prediction. Simulations and experiments prove that proposed MPPT control can track the maximum power point rapidly, and the system can operate steadily with this MPPT method.


2021 ◽  
Vol 16 ◽  
pp. 198-215
Author(s):  
A. Bharathi Sankar Ammaiyappan ◽  
R. Seyezhai

In recent days, photovoltaic (PV) system is the most promising renewable energy technologies and the PV cell has to operate at the optimum operating point to deliver maximum power. In order to obtain maximum power from PV, a maximum power point controller is required. This paper presents the simulation and hardware implementation of fuzzy logic (FL) maximum power point (MPPT) controller with FPGA technology for photovoltaic system. The MPPT algorithm is implemented for a Silicon carbide (SiC) MOSFET based boost DC-DC converter which provides fast switching, low losses and high voltage gain. The proposed MPPT algorithm is implemented on a SPARTAN/FPGA board platform based on the model developed and executed in MATLAB/SIMULINK. The entire system designed and implemented to hardware was successfully tested on a laboratory prototype PV array. The experimental results show the effectiveness and feasibility of the proposed controller and the results were satisfactory.


2019 ◽  
Vol 9 (2) ◽  
pp. 29-35
Author(s):  
Rachid Belaidi ◽  
Boualem Bendib ◽  
Djamila Ghribi ◽  
Belkacem Bouzidi ◽  
Mohamed Mghezzi Larafi

The main goal of maximum power point (MPP) tracking control is to extract the maximum photovoltaic (PV) power by finding the optimal operating point under varying atmospheric conditions to improve the efficiency of PV systems. In recent years, the field of tracking the MPP of PV systems has attracted the interest of many researchers from the industry and academia. This research paper presents a comparative study between the modern fuzzy logic based controller and the conventional perturb & observe (P&O) technique. The comparative study was carried out under different weather conditions in order to analyse and evaluate the performance of the PV system. The overall system simulation has been performed using Matlab/Simulink software environment. The simulation results show that the dynamic behaviour exhibited by the modern fuzzy controller outperforms that of the conventional controller (P&O) in terms of response time and damping characteristics.   Keywords: MPPT, photovoltaic system, fuzzy logic control, P&O algorithm.


2014 ◽  
Vol 1070-1072 ◽  
pp. 48-51
Author(s):  
Wen Ting Jia ◽  
Xue Ye Wei ◽  
Jun Hong Zhang ◽  
Yi Fei Meng

Closely related to the actual output power and the light intensity, the temperature of the photovoltaic cell panel and the load of the PV array or the like. In the case of the external environment is stable and load conditions change, the output power of the PV modules exist Maximum Power Point, in order to improve the self-tracking PV system energy conversion efficiency, maximum power point tracking method may ensure the system running at maximum power points. Photovoltaic power generation system, optimize allocation method of PV array are also discussed in this paper.


2013 ◽  
Vol 791-793 ◽  
pp. 1214-1219
Author(s):  
Jie Wang ◽  
Kai Zhang

At present, there are many commonly used maximum power point tracking (MPPT) control methods for solar photovoltaic system which have different degrees of output fluctuations. In order to solve the problem and improve the response speed further, a novel MPPT algorithm based on the extreme learning machine was put forward in this paper. Using the extreme learning machine which has small error, fast speed and simple structure train a mathematical model with the environmental temperature and light intensity as input and the maximum power point as output, the model can be used as the controller of the photovoltaic cells. The simulation results show that the error of the model meets the requirements, when the ambient temperature and light intensity change, it can respond quickly so as to photovoltaic cells work at the maximum power point and operate stably.


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