A Multi-objective Optimization Planning Framework for Active Distribution System Via Reinforcement Learning

Authors

  • Hongtao Li State Grid Beijing Electric Power Research Institute, Beijing, 100075, China
  • Cunping Wang State Grid Beijing Electric Power Research Institute, Beijing, 100075, China
  • Hao Tian 1) Wuxi Research Institute of Applied Technologies Tsinghua University, Wuxi, 214072, China 2) La Consolacion University Philippines, 3000 Bulacan, Catmon Rd, Malolos
  • Zhigang Ren State Grid Beijing Electric Power Research Institute, Beijing, 100075, China
  • Ergang Zhao Wuxi Research Institute of Applied Technologies Tsinghua University, Wuxi, 214072, China
  • Lina Xu Wuxi Research Institute of Applied Technologies Tsinghua University, Wuxi, 214072, China

DOI:

https://doi.org/10.13052/dgaej2156-3306.3862

Keywords:

Planning, active distribution network planning, reinforcement learning, renewable energy source

Abstract

The effective planning of active distribution networks is crucial for utility companies to make informed decisions regarding investments in distributed generation, reliability assessment, reactive power planning, substation revisions, and feeder repositioning. However, the dynamic nature of the solution space makes it challenging for model-based optimization methods to ensure computational performance in active distribution network planning. To address this issue, this study proposes a planning method that focuses on improving computational performance through the continuous updating of the planning model’s solution space during the reinforcement learning training process. Based on simulations conducted on the IEEE 33-bus test system, the proposed planning strategy successfully enhances computational performance while minimizing investment costs compared to other strategies. With the proposed method, the investment cost and the operation cost are reduced by 32.42% and 23.91%, respectively.

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Author Biographies

Hongtao Li, State Grid Beijing Electric Power Research Institute, Beijing, 100075, China

Hongtao Li received his bachelor’s degree from Tianjin University in 1996 and his master’s degree in power systems and automation from North China Electric Power University in 2005. He is currently working at State Grid Beijing Electric Power Company. His research area is distribution network operation and control technology.

Cunping Wang, State Grid Beijing Electric Power Research Institute, Beijing, 100075, China

Cunping Wang received his bachelor’s degree in electrical engineering from Tianjin University in 2008 and Doctor’s degree in electrical engineering from Huazhong University of Science and Technology in 2013. He is currently working at State Grid Beijing Electric Power Company. His research areas include active distribution network operation and control, and high reliable power supply for important users.

Hao Tian, 1) Wuxi Research Institute of Applied Technologies Tsinghua University, Wuxi, 214072, China 2) La Consolacion University Philippines, 3000 Bulacan, Catmon Rd, Malolos

Hao Tian received his master’s degree in electrical engineering from North China University of Technology. He is currently working as a teacher at Wuxi University. He is mainly engaged in energy Internet planning, power system reliability assessment, power system analysis, power grid planning and other research work.

Zhigang Ren, State Grid Beijing Electric Power Research Institute, Beijing, 100075, China

Zhigang Ren received the master’s degree in high voltage and insulation technology from Xi’an Jiaotong University in 2009. He is currently working at State Grid Beijing Electric Power Company. His research area is power cable operation and condition monitoring technology.

Ergang Zhao, Wuxi Research Institute of Applied Technologies Tsinghua University, Wuxi, 214072, China

Erang Zhao received the bachelor’s degree in electrical engineering from Hebei of University Technology in 2014 and the master’s degree in electrical engineering from Tsinghua University in 2021, respectively. He is currently working as a researcher at Wuxi Research Institute of Applied Technologies, Tsinghua University. His research areas include power system operation and planning, microgrid operation.

Lina Xu, Wuxi Research Institute of Applied Technologies Tsinghua University, Wuxi, 214072, China

Lina Xu received the bachelor’s degree in Electronic Information Science and Technology from Xuzhou University of Engineering in 2018. She is currently working at Wuxi Research Institute of Applied Technologies, Tsinghua University. She is mainly engaged in engineering software development work.

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Published

2023-08-29

How to Cite

Li, H. ., Wang, C. ., Tian, H. ., Ren, Z. ., Zhao, E. ., & Xu, L. . (2023). A Multi-objective Optimization Planning Framework for Active Distribution System Via Reinforcement Learning. Distributed Generation &Amp; Alternative Energy Journal, 38(06), 1741–1762. https://doi.org/10.13052/dgaej2156-3306.3862

Issue

2023: Vol 38 Iss 6

Section

Renewable Power & Energy Systems