在不平衡配电系统中分配分布式光伏发电机的简化多目标规划方法

IF 4.2 Q2 ENERGY & FUELS
Sukalyan Maji, Partha Kayal
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引用次数: 0

摘要

三相电网中负载分布不均会导致电压不平衡,降低系统效率。增加间歇性光伏发电只会使问题更加棘手。考虑到负荷需求和光伏发电的季节性变化,本研究提出了一种在不平衡电网中精确布置光伏系统的新方法,以提高系统性能。在多目标问题框架内,借助新颖的价值自适应权重聚合(VAWA)灰狼优化器(GWO),实现了最高效的光伏系统托管。使用 VAW 聚合策略可有效缓解与多目标函数线性化问题相关的限制。这种方法适用于将多个目标合并为一个单一的聚合目标。为了研究和验证推荐的方法,我们考虑了两个不同的不平衡径向配电系统(URDS)。电压不平衡因数(VUF)、电压安全因数(VSF)和有功功率损耗(APL)是三个不同的目标,被认为是影响配电系统年度性能参数的关键因素。加入光伏系统后,印度 19 总线 URDS 测试网络的年平均 VSF、VUF 和 APL 分别提高了 0.62%、12.97% 和 38.81%。与光伏分配前相比,修改后的 IEEE 123 总线测试网络的年平均 VSF 和 APL 分别提高了 0.081% 和 13.42%。GWO 的收敛数据显示,在测试运行中,它多次达到全局最优解,性能优于 PSO。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A simplified multi-objective planning approach for allocation of distributed PV generators in unbalanced power distribution systems

Uneven distribution of loads in three-phase power networks causes voltage unbalances and reduces system’s efficiency. Adding PV generation that is intermittent only makes issues more challenging. Taking into account seasonal changes in both load demand and PV generation, this study presents a new method for the precise placement of PV systems inside unbalanced networks in order to enhance system performance. The most efficient PV hosting is accomplished with the help of a novel value-adaptive weight-aggregated (VAWA) grey-wolf optimizer (GWO) within a multi-objective problem framework. The use of the VAW aggregation strategy may effectively mitigate the limitations associated with the linearization problem with multiple objective functions. This approach is suitable for combining several objectives into a single aggregated objective. Two diverse unbalanced radial distribution systems (URDSs) are considered for the investigation in order to examine and validate the recommended method. Voltage unbalance factor (VUF), voltage security factor (VSF), and active power loss (APL) are three distinctive objectives that are considered to be key contributors to the distribution system performance parameter on an annual basis. The yearly average VSF, VUF, and APL of the Indian 19-bus URDS test network improved by 0.62%, 12.97%, and 38.81% once the PV system was included. Compared to before PV allocation, the modified IEEE 123-bus test network's annual average VSF and APL are improved by 0.081% and 13.42%, respectively. GWO convergence data from the obtained results reveals that it outperforms PSO by reaching the global optimum solution on multiple occasions with regard to test runs.

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来源期刊
Renewable Energy Focus
Renewable Energy Focus Renewable Energy, Sustainability and the Environment
CiteScore
7.10
自引率
8.30%
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审稿时长
48 days
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