考虑电能质量的光伏优化配置研究

Research on Optimal Configuration of Photovoltaic System Considering Power Quality

粒子群算法和遗传算法是现在光伏规划中常用的方法,但前者容易陷入局部最优点,而后者的迭代收敛速度较慢且计算过程繁琐。提出了一种新的混合优化算法,即将遗传算法与粒子群算法结合起来,用二进制编码的方式将光伏的接入位置加入到粒子的信息中,利用仿真实验对考虑电能质量的光伏优化配置进行了验证分析,并利用改进的混合优化算法对数学模型进行求解,仿真结果证明了改进规划算法的合理有效性。

Particle swarm optimization(PSO)and genetic algorithm(GA)are commonly used in photovoltaic programming nowadays,but the former is easy to fall into local optimum,while the latter has a slow convergence rate and a cumbersome calculation process.This paper proposed a kind of new hybrid optimization algorithm,which combined GA with PSO and used the binary coding mode to make the interconnected location of photovoltaic join the message of particle.The simulation experiment was used to carry out the check analysis to the optimal configuration of photovoltaic system considering power quality and the improved hybrid optimization algorithm was used to solve the problem of mathematic model.The simulation experiments show that the improved planning algorithm is reasonable and effective.