基于克隆选择算法的光伏最大功率点跟踪控制

研究太阳能电池提高光电转换率问题,由于光伏发电系统中最大功率点难以实时跟踪,使光伏阵列输出功率达不到要求。为此提出采用克隆选择算法进行优化控制。根据光伏电池等效电路模型在SIMULINK中建立仿真模型进行特性分析,并编写克隆选择算法。通过在算法进化过程中合理地选取种群规模、克隆规模和变异率等参数,从而保证算法以最佳的搜索轨迹达到最优解。通过对算法有效性的验证,仿真结果表明:在温度、光强变化情况下,能实时跟踪到最大功率点,提高系统的鲁棒性和发电效率。

Maximum Power Point Tracking Control for Photovoltaic Based on Clonal Selection Algorithm

The clonal selection algorithm(CSA) was proposed for maximum power point tracking for photovoltaic system to optimize and solve the difficult problem of real-time tracking.The simulation model was established by using the equivalent circuit of photovoltaic cell in SIMULINK and running the CSA algorithm program in the m file under the MATLAB environment.By selecting the parameter reasonable population size,clonal size and mutation rate and so on in the process of evolutionary algorithm,the best search path was ensured to achieve the optimal solution.To verify the validity of the algorithm,an experiment was carried out and the result shows that,in case of variable temperature and light intensity,the algorithm can track the maximum power point in real-time,and improve the PV system’s robustness and power efficiency.