Hybrid Optimization-Based Sequential Placement of DES in Unbalanced Active Distribution Networks Considering Multi-Scenario Operation

Ruihua Si, Xintong Yan, Wanxun Liu, Ping Zhang, Mengdi Wang, Fengyong Li, Jiajia Yang () and Xiangjing Su ()
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Ruihua Si: State Grid Henan Economic Research Institute, Zhengzhou 450052, China
Xintong Yan: State Grid Henan Economic Research Institute, Zhengzhou 450052, China
Wanxun Liu: State Grid Henan Economic Research Institute, Zhengzhou 450052, China
Ping Zhang: State Grid Henan Economic Research Institute, Zhengzhou 450052, China
Mengdi Wang: Offshore Wind Power Research Institute, Shanghai University of Electric Power, Shanghai 200090, China
Fengyong Li: Offshore Wind Power Research Institute, Shanghai University of Electric Power, Shanghai 200090, China
Jiajia Yang: College of Science and Engineering, James Cook University, Townsville 4811, Australia
Xiangjing Su: Offshore Wind Power Research Institute, Shanghai University of Electric Power, Shanghai 200090, China

Energies, 2025, vol. 18, issue 3, 1-16

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.

Keywords: distributed energy storage; optimal placement; hybrid optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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