Si, Ruihua, Yan, Xintong, Liu, Wanxun, Zhang, Ping, Wang, Mengdi, Li, Fengyong, Yang, Jiajia, and Su, Xiangjing (2025) Hybrid Optimization-Based Sequential Placement of DES in Unbalanced Active Distribution Networks Considering Multi-Scenario Operation. Energies, 18 (3). 474.

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Abstract

The increasing penetration of distributed generation (DG) brings about great economic and environmental benefits, while also negatively affecting the operation of distribution networks due to its high intermittency. Although distributed energy storage (DES) can effectively deal with the problems caused by massive DG penetrations by decoupling the generation and consumption of electricity, the placement of DES significantly determines the effectiveness of its capabilities. Unfortunately, existing DES placement studies are commonly based on a balanced network model, whereas practical distribution networks are unbalanced. In addition, existing DES placement studies are mostly based on an extreme scenario and rarely consider the operational complexity resulting from the uncertainties of DGs and loads. To address the aforementioned challenges, this paper proposes a hierarchical and sequential DES placement strategy in distribution networks by considering multi-scenario operations. Specifically, the proposed hierarchical framework for DES placement includes three sequential layers: outer, inter, and inner. In the outer layer, a multi-scenario comprehensive loss sensitivity index (MSCLSI) is first introduced to search for the most effective DES placement location. Subsequently, the sizing and scheduling of DES for the selected location are conducted through coordinated optimization across the inter and inner layers, which can be solved using a hybrid method combining particle swarm optimization and second-order cone programming (PSO-SOCP). Finally, a series of detailed simulations are carried out over the IEEE-33 test system and the experimental results demonstrate that the proposed scheme can provide significant effectiveness and superiority compared to the state-of-the-art schemes.

Item ID:	86358
Item Type:	Article (Research - C1)
ISSN:	1996-1073
Keywords:	distributed energy storage; optimal placement; hybrid optimization
Copyright Information:	© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/).
Date Deposited:	24 Jul 2025 04:12
FoR Codes:	40 ENGINEERING > 4008 Electrical engineering > 400804 Electrical energy storage @ 100%
SEO Codes:	17 ENERGY > 1703 Energy storage, distribution and supply > 170399 Energy storage, distribution and supply not elsewhere classified @ 100%
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