Improving Distributed Network Resilience with Energy Storage: An Optimal Planning Strategy Based on Subjective and Objective Weight Method

Authors

  • Yu Li Economic and Technical Research Institute of State Grid Tibet Electric Power Co., Ltd, Lhasa, Tibet, 850015, China
  • Bingqiang Wang Economic and Technical Research Institute of State Grid Tibet Electric Power Co., Ltd, Lhasa, Tibet, 850015, China
  • Yuzhou Chen State Grid Tibet Electric Power Co., Ltd, Lhasa, Tibet, 850000, China
  • Yaoxia Du State Grid Tibet Electric Power Co., Ltd, Lhasa, Tibet, 850000, China
  • Juan Du State Grid Tibet Electric Power Co., Ltd, Lhasa, Tibet, 850000, China
  • Qingxi Liao State Grid Tibet Electric Power Co., Ltd, Lhasa, Tibet, 850000, China
  • Yihong Wu State Grid Tibet Electric Power Co., Ltd, Lhasa, Tibet, 850000, China
  • Zhendong Zhou State Grid Tibet Electric Power Co., Ltd, Lhasa, Tibet, 850000, China
  • Qing Lu Nanjing NARI New Energy Technology Co., Ltd, Nanjing, 210037, China
  • Liuyong Zhu Nanjing NARI New Energy Technology Co., Ltd, Nanjing, 210037, China
  • Yujie Lin Nanjing NARI New Energy Technology Co., Ltd, Nanjing, 210037, China

DOI:

https://doi.org/10.13052/dgaej2156-3306.3954

Keywords:

Energy storage, power quality, resilience improvement, subjective and objective weight method, distributed networks

Abstract

The integration of large-scale distributed photovoltaics (PVs) has improved the conventional resilience of distribution networks to a certain extent, but it has also made the power quality problems of distribution networks more prominent under steady-state operation. At the same time, the increase in the proportion of sensitive loads has also made the impact of voltage sag events increasingly serious, resulting in equipment damage and significant economic losses on the user side due to power quality problems when the conventional resilience assessment results of distribution networks are high. Based on this, this paper proposes an optimal planning strategy for improving the resilience of distributed networks based on subject and objective weight method. Firstly, for the proposed resilience assessment indicators, the improved Analytic Hierarchy Process (AHP) is used to calculate the subjective weights of the indicators, and the entropy weight method is used to calculate the objective weights of the indicators. The optimal weight combining subjectivity and objectivity is obtained comprehensively. Secondly, by combining the proposed resilience and power quality indicators, a comprehensive resilience indicator objective function is established. Based on the second-order cone linearization method, a multi-objective energy storage (ES) optimization configuration model with the lowest daily operation cost and the optimal comprehensive resilience of the distribution network is established. Finally, based on IEEE 33 node simulation, the comparison of calculation examples shows that the proposed energy storage optimization configuration model can effectively reduce system economic costs, while improving the resilience and power quality level of the distribution network.

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Author Biographies

Yu Li, Economic and Technical Research Institute of State Grid Tibet Electric Power Co., Ltd, Lhasa, Tibet, 850015, China

Yu Li received the B.S. degree from Tibet University, Lhasa, China, in July 2011. She has worked at the Electric Power Dispatch and Communication Bureau of Tibet Autonomous Region since August 2002, and has been with the State Grid Tibet Electric Power Co., Ltd. headquarters since 2009. His research interests include power system studies.

Bingqiang Wang, Economic and Technical Research Institute of State Grid Tibet Electric Power Co., Ltd, Lhasa, Tibet, 850015, China

Bingqiang Wang received the M.S. degree from Qingdao University, Qingdao, China, in June 2010. His main research areas include power system planning and design, as well as research on new power systems.

Yuzhou Chen, State Grid Tibet Electric Power Co., Ltd, Lhasa, Tibet, 850000, China

Yuzhou Chen received the B.S. degree in engineering from Harbin Institute of Technology, Harbin, China, in 2014. He has worked at the Economic and Technical Research Institute of State Grid Tibet Electric Power Co., Ltd. since 2014. His research interests focus on power grid planning, substation design, and power grid project evaluation.

Yaoxia Du, State Grid Tibet Electric Power Co., Ltd, Lhasa, Tibet, 850000, China

Yaoxia Du received the B.S. degree from Panzhihua University, Panzhihua, China, in 2017. He has worked at the Economic and Technical Research Institute of State Grid Tibet Electric Power Co., Ltd. since 2017, with a research focus on power systems.

Juan Du, State Grid Tibet Electric Power Co., Ltd, Lhasa, Tibet, 850000, China

Juan Du received the B.S. degree from Tibet Nationalities University, Xianyang, China, in 2014. Since 2014, she has worked at the Tibet Economic Research Institute, focusing on science and technology project and contract management.

Qingxi Liao, State Grid Tibet Electric Power Co., Ltd, Lhasa, Tibet, 850000, China

Qingxi Liao received the B.S. degree in engineering from Lanzhou University of Technology, Lanzhou, China, in 2023. He has worked at the Economic and Technical Research Institute of State Grid Tibet Electric Power Co., Ltd. since 2023, with research interests in distribution networks.

Yihong Wu, State Grid Tibet Electric Power Co., Ltd, Lhasa, Tibet, 850000, China

Yihong Wu received the B.S. degree from Chongqing Three Gorges University, Chongqing, China, in 2016. Since 2016, he has worked at the Economic and Technical Research Institute of State Grid Tibet Electric Power Co., Ltd., focusing on transmission line design.

Zhendong Zhou, State Grid Tibet Electric Power Co., Ltd, Lhasa, Tibet, 850000, China

Zhendong Zhou received the B.S. degree from Tibet University, Lhasa, China, in 2018. He has worked at the Economic and Technical Research Institute of State Grid Tibet Electric Power Co., Ltd. since 2014. His research interests include project management, technical economics, and cost management.

Qing Lu, Nanjing NARI New Energy Technology Co., Ltd, Nanjing, 210037, China

Qing Lu received the B.S. degree from Jiangsu University of Science and Technology Nanzhou College, Zhenjiang, China, in 2012, and is expected to receive the M.S. degree from Jiangsu University of Science and Technology in 2026. He has worked at Nanjing Nari New Energy Technology Co., Ltd. since 2016, with research interests in photovoltaic inverters and energy storage converters.

Liuyong Zhu, Nanjing NARI New Energy Technology Co., Ltd, Nanjing, 210037, China

Liuyong Zhu received the B.S. degree from Nanjing Institute of Technology, Nanjing, China, in 2017. Since 2017, he has worked at Nanjing Nari New Energy Technology Co., Ltd., focusing on research and development of photovoltaic inverters and energy storage converters.

Yujie Lin, Nanjing NARI New Energy Technology Co., Ltd, Nanjing, 210037, China

Yujie Lin received the B.S. degree from Huaiyin Institute of Technology, Huai’an, China, in 2020, and the M.S. degree from Shanghai University of Electric Power, Shanghai, China, in 2023. Since 2023, he has worked at Nanjing Nari New Energy Technology Co., Ltd., with research interests in photovoltaic inverters and energy storage converters.

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Published

2024-12-24

How to Cite

Li, Y. ., Wang, B. ., Chen, Y. ., Du, Y. ., Du, J. ., Liao, Q. ., Wu, Y. ., Zhou, Z. ., Lu, Q. ., Zhu, L. ., & Lin, Y. . (2024). Improving Distributed Network Resilience with Energy Storage: An Optimal Planning Strategy Based on Subjective and Objective Weight Method. Distributed Generation &Amp; Alternative Energy Journal, 39(05), 1015–1044. https://doi.org/10.13052/dgaej2156-3306.3954

Issue

Section

Renewable Power & Energy Systems