In practical operating conditions, the Solar-Photo Voltaic (SPV) system experiences multifarious irradiation and temperature levels, which generate power with multiple peaks. This is considered as the nonuniform operating condition (NUOC). This requires accurate tracking of global power peaks to achieve maximum power from SPV, which is a challenging task. Hence, this paper presents an incremental Conductance based Particle Swarm Optimization (ICPSO) algorithm for accurate tracking of maximum global power from active power multiple peaks generated by the SPV. The proposed algorithm continuously adjusts the individual particle’s weight component, which depends on its distance from the global best position during the tracking process. The proposed algorithm has the merit of continuous adjustment of weight components which reduces active power oscillations at the optimal global position area. Proposed ICPSO algorithm has been successfully designed and implemented for Solar-photo voltaic (PV) under nonuniform operating condition. It is established that the proposed algorithm enhances the output power of the Solar-PV up to 7% with the maximum power tracking of 0.1 s compared to other maximum power point tracking algorithms.

中文翻译：

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非均匀工况下基于增量电导的粒子群优化算法用于太阳能光伏系统的全局最大功率跟踪

在实际操作条件下，太阳能光伏（SPV）系统会经历多种辐射和温度水平，从而产生具有多个峰值的功率。这被认为是非均匀操作条件（NUOC）。这就需要精确跟踪全局功率峰值以从SPV获得最大功率，这是一项艰巨的任务。因此，本文提出了一种基于电导的增量粒子群优化（ICPSO）算法，可从SPV产生的有功功率多个峰值中准确跟踪最大全局功率。所提出的算法不断地调整单个粒子的重量分量，这取决于其在跟踪过程中与全局最佳位置的距离。所提出的算法具有连续调整权重分量的优点，可以减少最佳全局位置区域的有功功率振荡。所建议的ICPSO算法已经成功地设计和实现了在非均匀工作条件下的太阳能光伏（PV）。可以确定的是，与其他最大功率点跟踪算法相比，该算法将Solar-PV的输出功率提高了7％，最大跟踪功率为0.1 s。