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一种用于解决多边配电系统中太阳能光伏系统最优分配以提高弹性的新型元启发式寻路算法。

A new meta-heuristic pathfinder algorithm for solving optimal allocation of solar photovoltaic system in multi-lateral distribution system for improving resilience.

作者信息

Janamala Varaprasad

机构信息

Department of Electrical and Electronics Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Bengaluru, Karnataka 560 074 India.

出版信息

SN Appl Sci. 2021;3(1):118. doi: 10.1007/s42452-020-04044-8. Epub 2021 Jan 12.

DOI:10.1007/s42452-020-04044-8
PMID:33458566
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7801878/
Abstract

A new meta-heuristic Pathfinder Algorithm (PFA) is adopted in this paper for optimal allocation and simultaneous integration of a solar photovoltaic system among multi-laterals, called interline-photovoltaic (I-PV) system. At first, the performance of PFA is evaluated by solving the optimal allocation of distribution generation problem in IEEE 33- and 69-bus systems for loss minimization. The obtained results show that the performance of proposed PFA is superior to PSO, TLBO, CSA, and GOA and other approaches cited in literature. The comparison of different performance measures of 50 independent trail runs predominantly shows the effectiveness of PFA and its efficiency for global optima. Subsequently, PFA is implemented for determining the optimal I-PV configuration considering the resilience without compromising the various operational and radiality constraints. Different case studies are simulated and the impact of the I-PV system is analyzed in terms of voltage profile and voltage stability. The proposed optimal I-PV configuration resulted in loss reduction of 77.87% and 98.33% in IEEE 33- and 69-bus systems, respectively. Further, the reduced average voltage deviation index and increased voltage stability index result in an improved voltage profile and enhanced voltage stability margin in radial distribution systems and its suitability for practical applications.

摘要

本文采用一种新的元启发式寻路算法(PFA),用于多侧线路间太阳能光伏系统的最优分配和同步集成,即线路间光伏(I-PV)系统。首先,通过求解IEEE 33节点和69节点系统中分布式发电问题的最优分配以实现损耗最小化,来评估PFA的性能。所得结果表明,所提出的PFA的性能优于粒子群优化算法(PSO)、教学学习优化算法(TLBO)、布谷鸟搜索算法(CSA)、引力搜索算法(GOA)以及文献中引用的其他方法。50次独立试验运行的不同性能指标比较主要表明了PFA的有效性及其对全局最优解的效率。随后,在不影响各种运行和辐射约束的情况下,实施PFA以确定考虑弹性的最优I-PV配置。进行了不同的案例研究,并从电压分布和电压稳定性方面分析了I-PV系统的影响。所提出的最优I-PV配置在IEEE 33节点和69节点系统中分别使损耗降低了77.87%和98.33%。此外,降低的平均电压偏差指数和增加的电压稳定指数导致径向配电系统中的电压分布得到改善,电压稳定裕度得到增强,并且其适用于实际应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1259/7801878/cc50ceb93ad0/42452_2020_4044_Fig11_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1259/7801878/6c0cbd98e9ea/42452_2020_4044_Fig2_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1259/7801878/37362b1afed9/42452_2020_4044_Fig4_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1259/7801878/3828e5d61ffc/42452_2020_4044_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1259/7801878/de218ae8419c/42452_2020_4044_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1259/7801878/04e2bbb0262b/42452_2020_4044_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1259/7801878/5a3e8df9aa6d/42452_2020_4044_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1259/7801878/122c68b806b9/42452_2020_4044_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1259/7801878/cc50ceb93ad0/42452_2020_4044_Fig11_HTML.jpg

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