研究目的
To solve three problems associated with the Particle Swarm Optimization (PSO) when used as a Maximum Power Point Tracker (MPPT) for photovoltaic (PV) systems under partial shading conditions (PSCs) by introducing a novel fast adaptive PSO (APSO) strategy.
研究成果
The proposed APSO strategy effectively addresses the three main problems associated with conventional PSO when used as an MPPT for PV systems under PSCs. It reduces convergence time, avoids premature convergence, and dynamically tracks the GP under changing shading conditions. The simulation and experimental results demonstrate the superiority of the APSO strategy over conventional PSO in terms of tracking speed and dynamic GP tracking.
研究不足
The study focuses on the simulation and experimental validation of the APSO strategy under specific conditions (partial shading and dynamic irradiance changes). The performance under other environmental conditions or with different PV system configurations is not explored. Additionally, the experimental setup uses a limited number of PV modules, which may not fully represent large-scale PV systems.
1：Experimental Design and Method Selection:
The study employs a novel fast adaptive PSO (APSO) strategy to address the shortcomings of conventional PSO in tracking the global peak (GP) under dynamic partial shading conditions (PSCs). The methodology includes updating the starting values of the duty ratio of the DC-DC boost converter to anticipated peak locations, updating the memorized GP with the current maximum power when unchanged for two successive iterations, and using updated duty ratio values at anticipated peaks as initial values for particles in case of sudden PSCs changes.
2：Sample Selection and Data Sources:
The PV system simulation includes PV arrays interfaced to a boost converter and a three-phase PWM inverter connected to the electric utility via an LCL filter. The PV arrays consist of three groups connected in series, each with uniform irradiance, to model PSCs.
3：List of Experimental Equipment and Materials:
The simulation involves MATLAB code integrated with Simulink for the power circuit of the PV system, including PV arrays, boost converter, three-phase PWM inverter, and LCL filter. The PV module selected is Sunperfect Solar CRM185S156P-
4：Experimental Procedures and Operational Workflow:
The simulation tests the APSO strategy under varying irradiance conditions, including uniform irradiance and PSCs, to evaluate its performance in tracking the GP. The strategy's effectiveness is compared to conventional PSO with random initialization.
5：Data Analysis Methods:
The performance of the APSO strategy is analyzed based on convergence time, premature convergence rate, and the ability to track the GP under dynamic PSCs changes. The results are validated through experimental setup using a hardware implementation of the PV system.
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