Research on a Self-Coordinated Optimization Method for Distributed Energy Resources Targeting Risk Mitigation

Authors

  • Hongtao Li State Grid Beijing Electric Power Company Beijing, China
  • Tian Hao Department of Electrical Engineering, Tsinghua University, Haidian District 100084, Beijing, China
  • Zijin Li State Grid Beijing Electric Power Company Beijing, China
  • Ergang Zhao Department of Electrical Engineering, Tsinghua University, Haidian District 100084, Beijing, China
  • Chen Wang State Grid Beijing Electric Power Company Beijing, China
  • Lina Xu Department of Electrical Engineering, Tsinghua University, Haidian District 100084, Beijing, China

DOI:

https://doi.org/10.13052/dgaej2156-3306.39312

Keywords:

Rapid Restoration, Model Predictive Control, Distribution Network,, Distributed Energy Sources, Resilience Assessment

Abstract

This passage discusses a rapid restoration optimization strategy for short-term global coordination and the synergistic autonomous regulation of distributed energy sources based on a model predictive control framework. A short-term rapid recovery global coordination optimization model is established through the prediction of network states under abnormal conditions. This model includes the energy management of distributed energy sources and recovery plans for critical loads. In terms of the autonomous regulation of distributed energy sources, based on the results of global coordination optimization and aiming to minimize load shedding losses and grid losses, an ultra-short-term rolling control strategy is formulated using power output and load switching as control variables. Finally, simulation analysis on the IEEE 33-node distribution network system indicates that the proposed model and method significantly accelerate the recovery speed of the distribution network and effectively enhance its resilience level.

Downloads

Download data is not yet available.

Author Biographies

Hongtao Li, State Grid Beijing Electric Power Company Beijing, China

Hongtao Li received the bachelor’s degree in electrical engineering from Tianjin University in 1997 and the master’s degree in electrical engineering from North China Electric Power University in 2005, respectively. He is currently working as a professor of engineering at State Grid Beijing Electric Power Company. His research areas include smart grid distribution system and New Electric Power System.

Tian Hao, Department of Electrical Engineering, Tsinghua University, Haidian District 100084, Beijing, China

Tian Hao 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.

Zijin Li, State Grid Beijing Electric Power Company Beijing, China

Zijin Li received the bachelor’s degree in renewable energy North China Electric Power University in 2011 and 2014. She is currently working as a senior engineer at State Grid Beijing Electric Power Company. Her research areas include hybrid ac/dc distribution network and microgrid.

Ergang Zhao, Department of Electrical Engineering, Tsinghua University, Haidian District 100084, Beijing, 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 Department of Electrical Engineering, Tsinghua University. His research areas include power system operation and planning, microgrid operation.

Chen Wang, State Grid Beijing Electric Power Company Beijing, China

Chen Wang was born in Beijing, China, in 1994. He received the B.S. and M.S. degree in electrical engineering from China Agricultural University, Beijing, China, in 2017 and 2021. His main research interests include hybrid ac/dc distribution network, renewable energy generation, and active distribution networks.

Lina Xu, Department of Electrical Engineering, Tsinghua University, Haidian District 100084, Beijing, 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.

References

S. Mirsaeidi, X. Dong, S. Shi, and D. Tzelepis, “Challenges, advances and future directions in protection of hybrid AC/DC microgrids,” IET Renewable Power Generation, vol. 11, no. 12, pp. 1495–1502, Oct. 2017.

B. Shen et al., “Research on the Morphological Development of New Distribution Networks,” in 2022 Asia Power and Electrical Technology Conference (APET), Nov. 2022, pp. 143–149.

S. Mallapaty, “How China could be carbon neutral by mid-century,” Nature, vol. 586, no. 7830, pp. 482–483, Oct. 2020.

D. Wu, J. Su, Z. Chen, and H. Liu, “Effects of Distributed Generation on Carbon Emission Reduction of Distribution Network,” Distributed Generation & Alternative Energy Journal, pp. 57–82, 2024.

L. Xu, Q. Guo, Y. Sheng, S. M. Muyeen, and H. Sun, “On the resilience of modern power systems: A comprehensive review from the cyber-physical perspective,” Renewable and Sustainable Energy Reviews, vol. 152, p. 111642, Dec. 2021.

D. K. Mishra, M. J. Ghadi, A. Azizivahed, L. Li, and J. Zhang, “A review on resilience studies in active distribution systems,” Renewable and Sustainable Energy Reviews, vol. 135, p. 110201, Jan. 2021.

S. A. Modaberi, S. Tohidi, S. G. Zadeh, and T. G. Bolandi, “A review of power system resilience assessment and enhancement approaches by focusing on wind farms and wind turbines,” IET Renewable Power Generation, vol. 17, no. 9, pp. 2391–2410, 2023.

C.-C. Liu, “Distribution Systems: Reliable But Not Resilient? [In My View],” IEEE Power and Energy Magazine, vol. 13, no. 3, pp. 93–96, May 2015.

D. Chippada and M. D. Reddy, “Optimal Placement and Sizing of Renewable and Non-Renewable Resources in Smart Grid,” Distributed Generation & Alternative Energy Journal, pp. 1033–1054, Mar. 2023.

S. Ghasemi and J. Moshtagh, “Distribution system restoration after extreme events considering distributed generators and static energy storage systems with mobile energy storage systems dispatch in transportation systems,” Applied Energy, vol. 310, p. 118507, Mar. 2022.

F. Fayaz and G. L. Pahuja, “Optimal Control of Hybrid Power System Integrated with Distributed Generation and Electric Vehicle,” Distributed Generation & Alternative Energy Journal, pp. 189–214, 2023.

J. Zhao et al., “An islanding partition method of active distribution networks based on chance-constrained programming,” Applied Energy, vol. 242, pp. 78–91, May 2019.

T. Zhao, B. Chen, S. Zhao, J. Wang, and X. Lu, “A Flexible Operation of Distributed Generation in Distribution Networks With Dynamic Boundaries,” IEEE Transactions on Power Systems, vol. 35, no. 5, pp. 4127–4130, Sep. 2020.

Z. Yang, Y. Xia, W. Hu, J. Jing, and L. Chen, “Dynamic Island Partition Strategy for Active Distribution System with Controllable Load Participation,” in 2020 IEEE Sustainable Power and Energy Conference (iSPEC), Nov. 2020, pp. 1927–1932.

X. Gu and H. Zhong, “Optimisation of network reconfiguration based on a two-layer unit-restarting framework for power system restoration,” IET Gener. Transm. Distrib., vol. 6, no. 7, p. 693, 2012.

S. Li, L. Wang, X. Gu, H. Zhao, and Y. Sun, “Optimization of loop-network reconfiguration strategies to eliminate transmission line overloads in power system restoration process with wind power integration,” International Journal of Electrical Power & Energy Systems, vol. 134, p. 107351, Jan. 2022.

W. Liu, L. Sun, Z. Lin, F. Wen, and Y. Xue, “Multi-objective restoration optimisation of power systems with battery energy storage systems,” IET Generation, Transmission & Distribution, vol. 10, no. 7, pp. 1749–1757, 2016.

H. Sekhavatmanesh and R. Cherkaoui, “Analytical Approach for Active Distribution Network Restoration Including Optimal Voltage Regulation,” IEEE Transactions on Power Systems, vol. 34, no. 3, pp. 1716–1728, May 2019.

H. T. Nguyen, J. Muhs, and M. Parvania, “Preparatory Operation of Automated Distribution Systems for Resilience Enhancement of Critical Loads,” IEEE Transactions on Power Delivery, vol. 36, no. 4, pp. 2354–2362, Aug. 2021.

C. Contreras, A. Triviño, and J. A. Aguado, “Distributed Model Predictive Control for voltage coordination of large-scale wind power plants,” International Journal of Electrical Power & Energy Systems, vol. 143, p. 108436, Dec. 2022.

M. M. Adibi and D. P. Milanicz, “Estimating restoration duration,” IEEE Transactions on Power Systems, vol. 14, no. 4, pp. 1493–1498, Nov. 1999.

J. Zhou, “Optimization of the Fast Frequency Regulation Strategy for Energy Storage-Assisted Photovoltaic Power Stations,” Distributed Generation & Alternative Energy Journal, pp. 263–296, Feb. 2024.

N. Nazir and M. Almassalkhi, “Guaranteeing a Physically Realizable Battery Dispatch Without Charge-Discharge Complementarity Constraints,” IEEE Trans. Smart Grid, vol. 14, no. 3, pp. 2473–2476, May 2023.

Published

2024-07-16

How to Cite

Li, H., Hao, T., Li, Z., Zhao, E., Wang, C., & Xu, L. (2024). Research on a Self-Coordinated Optimization Method for Distributed Energy Resources Targeting Risk Mitigation. Distributed Generation &Amp; Alternative Energy Journal, 39(03), 659–690. https://doi.org/10.13052/dgaej2156-3306.39312

Issue

Section

Renewable Power & Energy Systems