Multi-Objective Approach for Distribution System Planning Considering Stochastic Customer-Owned Distributed Energy Resources

被引:0
|
作者
Ferraz, Renato S. F. [1 ]
Ferraz, Rafael S. F. [2 ]
Junior, Vanio F. S. [3 ]
Rueda-Medina, Augusto C. [1 ]
机构
[1] Univ Fed Espirito Santo, Dept Elect Engn, BR-29075910 Vitoria, Brazil
[2] Univ Fed Piaui, Dept Renewable Energy Technol, BR-64049550 Teresina, Brazil
[3] Univ Estadual Santa Cruz, Dept Engn & Comp, BR-45662900 Ilheus, Brazil
来源
IEEE ACCESS | 2025年 / 13卷
关键词
Capacitors; Planning; Optimization; Transformers; Resource management; Uncertainty; Switches; Distributed power generation; Reactive power; Photovoltaic systems; Capacitor allocation; distributed energy resources; multi-objective optimization; network reconfiguration; on-load tap changer transformer; voltage consistency indicator; NETWORK RECONFIGURATION;
D O I
10.1109/ACCESS.2025.3547277
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The installation of distributed energy resources (DERs) by end-customers has increased significantly in recent years. While customer-owned DERs offer various benefits, their integration adds complexity to distribution system planning due to the unpredictability of their quantity, sizes, and locations. Consequently, they are referred to as stochastic customer-owned DERs in this study. In the specialized literature, optimization-based DER allocation is often explored; however, these allocation problems typically assume that the distribution system operator has control over the allocation of DERs within the grid, whereas real-world investments are predominantly driven by end-customers. Therefore, in this article, a multi-objective planning approach is proposed considering stochastic customer-owned DERs. This approach simultaneously addresses dynamic network reconfiguration, capacitors allocation, and dynamic adjustment of on-load tap changer transformer. The main objective is to minimize power loss costs and improve the system's voltage profile by minimizing a novel voltage consistency indicator (VCI) introduced in this article. The optimization problem is solved using the Multi-objective Cuckoo Search, with the final solution selected through the Fuzzy Decision-making Method. Additionally, the Monte Carlo Method is employed to address uncertainties related to load, DER generation, and the quantity, sizes, and locations of customer-owned DERs. Finally, the results highlighted the importance of conducting a multi-period analysis, as it led to improvements compared to the static analysis. The proposed approach effectively reduced the VCI by 72.41% and minimized the power loss costs by 68.56% compared to the original system.
引用
收藏
页码:40561 / 40576
页数:16
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