基于TSA-P&O混合算法的光伏多峰值MPPT控制

Multi-peak MPPT Control of Photovoltaic Array Based on TSA-P&O Hybrid Algorithm

针对局部阴影遮挡等原因造成光伏阵列失配而引起的光伏功率输出多峰效应,以及最大功率点跟踪控制过程中易产生电压与功率波动的难题,提出了一种树种算法与扰动观察法相结合的改进多峰值最大功率点跟踪混合控制算法。首先,利用光伏P-U特性曲线单峰/多峰形态识别策略确保单峰条件下快速、低振荡地跟踪;其次,采用基于电压闭环的个体最优化输出控制策略降低电压与功率波动;最后,通过仿真和实验将提出的混合控制算法与粒子群优化、花授粉、遗传和差分进化4种算法进行综合性能对比。结果表明,所提的混合控制算法能够快速、准确、低振荡地跟踪到全局最大功率点,有效解决光伏阵列失配下光伏多峰值最大功率点跟踪控制难题。

Aimed at the multi-peak effect of photovoltaic(PV)power output caused by the mismatch of PV arrays due to factors such as partial shading,as well as the problem of voltage and power fluctuations which are easily generated in the control process of maximum power point tracking(MPPT),an improved multi-peak MPPT hybrid control algorithm based on the combination of tree seed algorithm(TSA)and perturb and observe(P&O)method is proposed.First,a single/multi-peak pattern identification strategy based on the P-U characteristic curve is used to ensure a fast and low oscillation tracking under the single-peak condition.Second,an individual optimal output control strategy based on voltage closed-loop is adopted to reduce the voltage and power fluctuations.Finally,the comprehensive performance is compared between the proposed hybrid control algorithm and other four algorithms such as particle swarm optimization algorithm,flower pollination algorithm,genetic algorithm and differential evolution algorithm.Results show that the proposed hybrid control strategy can track the global maximum power point accurately with a fast speed and low oscillations,which can effectively solve the multi-peak MPPT control problem under PV array mismatch.