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Improved particle swarm optimization for maximum power point tracking in photovoltaic module arrays

机译:改进的粒子群优化技术可在光伏模块阵列中实现最大功率点跟踪

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摘要

In this paper, a maximum power point tracking (MPPT) method that incorporated shading and failure conditions in photovoltaic (PV) module arrays is developed. This MPPT method was built using improved particle swarm optimization (PSO). The PSO algorithm enables PV module arrays to perform MPPT for multi-peak power-voltage (P-V) output characteristic curves when shading or failures occur. This facilitates the tracking of actual maximum power points in PV module arrays. The HIP 2717 PV module produced by SANYO Electric Co., Ltd. was used in this study to assemble various array configurations. The characteristic curves of these array configurations when partial module shading or failure occurred were investigated. Numerous working conditions were selected for dual-peak, three-peak, and four-peak characteristics. PIC microcontrollers were then used to apply both the traditional and the proposed PSO algorithms to enable MPPT. A comparison of the measurement results showed that the proposed PSO algorithm exhibited superior tracking speed, response, and accuracy, compared with those of the traditional PSO algorithm. (C) 2015 Elsevier Ltd. All rights reserved.
机译:本文开发了一种最大功率点跟踪(MPPT)方法,该方法在光伏(PV)模块阵列中结合了阴影和故障条件。此MPPT方法是使用改进的粒子群优化(PSO)构建的。 PSO算法使PV模块阵列能够在发生阴影或故障时针对多峰电源电压(P-V)输出特性曲线执行MPPT。这有助于跟踪PV模块阵列中的实际最大功率点。本研究中使用了SANYO Electric Co.,Ltd.生产的HIP 2717 PV模块来组装各种阵列配置。研究了发生部分模块遮挡或故障时这些阵列配置的特性曲线。为双峰,三峰和四峰特性选择了多种工作条件。然后,使用PIC微控制器来应用传统PSO算法和提议的PSO算法来实现MPPT。测量结果的比较表明,与传统的PSO算法相比,该算法具有更好的跟踪速度,响应速度和精度。 (C)2015 Elsevier Ltd.保留所有权利。

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