Optimisation of solar PV plant locations for grid support using genetic algorithm and pattern search

V. Vermeulen, J. Strauss, H. Vermeulen
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引用次数: 8

Abstract

This paper presents the results of an exploratory study aimed at investigating the impacts of optimisation of PV plant locations in South Africa in the context of the seasonal and diurnal cycles associated with the system load profiles and solar generation profiles. The distribution of a normalised per-unit generation capacity is optimised across a set of locations chosen to represent the diurnal cycle along a west-east axis and the seasonal cycle along a north-south axis, using local solar irradiance profiles for the candidate sites. Optimisations are conducted for a range of objective functions representing different scenarios defined in terms of seasonal considerations and time-of-use (TOU) periods using both genetic algorithm (GA) and pattern search methods in the MATLAB simulation environment. Comparative analysis of the optimisation results indicate that the latitude of PV plant locations plays a significant role in seasonal performance, while optimisation along a longitude dimension offers higher power generation during daily peak demand periods.
利用遗传算法和模式搜索优化电网支持的太阳能光伏电站位置
本文介绍了一项探索性研究的结果,该研究旨在调查与系统负载概况和太阳能发电概况相关的季节性和昼夜周期背景下南非光伏电站位置优化的影响。标准化的单位发电量分布在一系列地点进行优化,这些地点沿着东西轴代表昼夜周期,沿着南北轴代表季节周期,使用候选地点的当地太阳辐照度剖面。在MATLAB仿真环境中,使用遗传算法(GA)和模式搜索方法,对一系列目标函数进行了优化,这些目标函数代表了根据季节考虑和使用时间(TOU)周期定义的不同场景。优化结果的对比分析表明,光伏电站位置的纬度在季节性性能中起着重要作用,而沿着经度维度的优化在每日需求高峰期间提供更高的发电量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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