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ORIGINAL RESEARCH article
Front. Energy Res.
Sec. Energy Storage
Volume 12 - 2024 |
doi: 10.3389/fenrg.2024.1472486
Optimal Configuration Strategy of Energy Storage for Enhancing the Comprehensive Resilience and Power Quality of Distribution Networks
Provisionally accepted- 1 Economic and Technical Research Institute of State Grid Tibet Electric Power Co., Ltd, Tiebt, China
- 2 State Grid Tibet Electric Power Co., Ltd, Tibet, China
- 3 Nanjing NARI New Energy Technology Co., Ltd., Nanjing, China
Resilience assessment and enhancement in distribution networks primarily focus on the ability to support and recover critical loads after extreme events. With the increasing integration of new energy sources and power electronics, distribution networks have gained a degree of resilience. However, the impact of power quality issues on these networks has become more severe. In some cases, even networks assessed as highly resilient by users suffer equipment damage and substantial economic losses due to power quality issues. To address this issue, this paper builds upon conventional distribution network resilience assessment methods by supplementing and modifying indices in the dimensions of resistance and recovery to account for power quality issues. Furthermore, an optimized energy storage system (ESS) configuration model is proposed as a technical means to minimize the total operational cost of the distribution network while enhancing comprehensive resilience indices. The proposed nonlinear optimization model is solved using second-order cone relaxation techniques. Finally, the proposed strategy is simulated on the IEEE 33-node distribution network. The simulation results demonstrate that the proposed strategy effectively improves the comprehensive resilience indices of the distribution network and reduces the total operational cost.
Keywords: energy storage system, power quality, optimal configuration, Resilience of distribution networks, Distributed photovoltaic
Received: 29 Jul 2024; Accepted: 11 Nov 2024.
Copyright: © 2024 Chen, Chen, Yuan, Jiayang, Zhang, Lu, Zhu and Lin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Yunyao Chen, Economic and Technical Research Institute of State Grid Tibet Electric Power Co., Ltd, Tiebt, China
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