Distributed Energy Storage Configuration Method for AC/DC Hybrid Distribution Network Based on Bi-Level Optimization
Source abstract
Abstract
Aiming at prominent voltage quality problems in AC/DC hybrid distribution networks with a high proportion of distributed energy and diversified loads, this paper proposes a bi-level energy storage system (ESS) optimization model. The upper level optimizes the ESS configuration with the goal of minimizing the cost, and the lower level optimizes the real-time running state of the ESS. Considering multiple constraints, the improved PSO algorithm and the Gurobi solver are used to solve the problem. The test on the modified IEEE-33 node system verified that the model effectively improved voltage quality and reduced power system costs, which provides theoretical and engineering support for the scientific configuration of the ESS.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Optimal Power Flow Distribution · Microgrid Control and Optimization · HVDC Systems and Fault Protection
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
State Grid Jibei Electic Power Company Limited Smart Distribution Network Center, Qinhuangdao 066100, China
Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology, Northeast Electric Power University, Jilin 132012, China
Funding
State Grid Jibei Electric Power Company Limited Smart Distribution Network Center
References (23)
Show source-provided references
1. An optimal scheduling method for active distribution network considering source network load storage coordination
2. Dynamic Energy Storage Capacity Optimization Based on Ultra-Short-Term Prediction in Grid-Connected PV System10.1016/j.renene.2025.123644 ↗
3. Can distributed photovoltaic-battery systems power buildings with favorable matching performance and techno-economic feasibility?10.1016/j.enconman.2024.118260 ↗
4. A review on battery energy storage systems: Applications, developments, and research trends of hybrid installations in the end-user sector10.1016/j.est.2024.111192 ↗
5. Multi-objective particle swarm optimization algorithm based on multi-strategy improvement for hybrid energy storage optimization configuration10.1016/j.renene.2024.120086 ↗
6. Optimizing distributed generation and energy storage in distribution networks: Harnessing metaheuristic algorithms with dynamic thermal rating technology10.1016/j.est.2024.111989 ↗
7. A two-layer planning method for distributed energy storage with multi-point layout in high photovoltaic penetration distribution network10.1007/s42835-024-01945-1 ↗
8. Zhang, J., Zhu, L., Zhao, S., Yan, J., and Lv, L. (2023). Optimal Configuration of Energy Storage Systems in High PV Penetrating Distribution Network. Energies, 16.10.3390/en16052168 ↗
9. Gao, B., Du, Q., Zhan, G., and Han, J. (2025). A Bi-Level Optimization Scheme for Energy Storage Configuration in High PV-Penetrated Distribution Networks Based on Improved Voltage Sensitivity Strategy. Energies, 18.10.3390/en18081908 ↗
10. Zhang, S., Yan, J., Xie, P., Zhai, P., and Tao, Y. (2025). Power System Loss Reduction Strategy Considering Security Constraints Based on Improved Particle Swarm Algorithm and Coordinated Dispatch of Source–Grid–Load–Storage. Processes, 13.10.3390/pr13030831 ↗
11. Unified load flow calculation for flexible interconnected AC-MTDC distribution system considering control strategy switching with high penetration of DGs10.1016/j.ijepes.2021.107130 ↗
12. Exploiting the operational flexibility of AC-MTDC distribution system considering various flexible resources10.1016/j.ijepes.2022.108842 ↗
13. Tang, X., Qin, L., Yang, Z., He, X., Min, H., Zhou, S., and Liu, K. (2023). Optimal scheduling of AC–DC hybrid distribution network considering the control mode of a converter station. Sustainability, 15.10.3390/su15118715 ↗
14. A bi-level planning model and its solution method of AC/DC hybrid distribution network based on second-order cone programming and NNC method
15. IEEE (1991). IEEE 33-Node Radial Distribution Test System, Institute of Electrical and Electronics Engineers (IEEE). Available online: https://www.torontomu.ca/content/dam/cue/research/reports/33bus%20test%20system.pdf.
16. Wang, L., Zhao, Q., Wang, S., and Jiang, X. (2024). Enhancing flexibility evaluation in AC/DC distribution systems for sustainable energy integration. Front. Energy Res., 12.10.3389/fenrg.2024.1423189 ↗
17. Unified power flow solver for hybrid AC/DC distribution networks10.1109/TPWRD.2023.3271311 ↗
18. Modified power flow algorithm of AC/DC power network10.1007/s42835-023-01575-z ↗
19. A comprehensive review of hybrid AC/DC networks: Insights into system planning, energy management, control, and protection10.1007/s00521-024-10264-5 ↗
20. Optimal economic configuration of distributed energy storage systems for improving voltage quality in distribution network
21. Optimal dispatch of microgrid based on multi-objective particle swarm optimization
22. Review of energy storage system for wind power integration support10.1016/j.apenergy.2014.04.103 ↗
23. Zulpo, R.S., Leborgne, R.C., and Bretas, A.S. (2014, January 25–28). Optimal siting and sizing of distributed generation through power losses and voltage deviation. Proceedings of the 2014 16th International Conference on Harmonics and Quality of Power (ICHQP), Bucharest, Romania.10.1109/ICHQP.2014.6842788 ↗