基于进化规划的天气条件下光伏系统优化配置增强电力系统弹性

2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA) Pub Date : 2023-03-06 DOI:10.1109/ICPEA56918.2023.10093211

Nurul Thasyahirah Ellya Mohd Jailaini, Muhammad Murtadha Othman, Masoud Ahmadipour, Kamrul Hasan

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引用次数: 0

摘要

本项目通过系统可靠性评估，引入了考虑天气条件的光伏系统优化配置。利用光伏发电机组的嵌入式数据和天气条件对马尔可夫模型进行建模，得到强制停运率(FOR)，并将两者合并得到新的强制停运率。然后，利用一个24可靠性测试系统的负荷和由光伏系统规模组成的可变种群数来获得期望未服务能量(EUE)和期望负荷损失(LOLE)。将EP优化技术应用于确定光伏发电系统的最佳规模和发电机组(GU)， EUE接近于零，LOLE小于2.4小时/年。本文以天气条件对光伏发电系统的影响为例进行了分析。

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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Optimal Allocation of Photovoltaic (PV) System Considering Weather Conditions using Evolutionary Programming (EP) for Enhanced Power System Resiliency

This project introduces an optimal PV system allocation by considering weather conditions through a system reliability assessment. The Markov model is performed with embedded data of the PV generator and weather conditions to obtain a forced outage rate (FOR) and both (FOR) will be merged together to get a new FOR. Then, a load of a 24 Reliability Test System and a variant number of populations composed of PV system size is used to obtain the expected unserved energy (EUE) and loss of load expectation (LOLE). The EP technique for optimization is applied to determine the best sizing and generating unit (GU) of the PV system with the EUE close to zero and LOLE less than 2.4 hours per year. This paper used the effect of weather conditions on the PV system as a case analysis.

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2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA)

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