A Method for Location and Capacity Determination of Energy Storage in Distribution Networks Based on an Improved Niched Particle Swarm Optimization Algorithm
A high proportion of distributed photovoltaic access to the distribution network is the inevitable trend of national energy transformation and development. however, its disorderly access leads to potential deficiencies such as limited consumption, excessive power quality and so on. The energy storage system can solve the time-space mismatch between new energy power generation and load. This paper studies the optimal configuration method of energy storage system in distribution network, which is suitable for high-proportion distributed photovoltaic disordered access, and establishes the energy storage location and capacity model aiming at node voltage fluctuation, network loss and life cycle cost. In view of the deficiency that the traditional particle swarm optimization algorithm is easy to fall into local convergence, an improved niche particle swarm optimization algorithm is proposed, which adaptively adjusts parameters to increase convergence and searchability, and adds niche technology and cross-mutation to prevent falling into local solution. Finally, the modeling and simulation of IEEE-33 node example shows that the node voltage fluctuation is effectively reduced by 30%, and the search accuracy of the improved niche particle swarm optimization algorithm is 22% higher than that of the traditional particle swarm optimization algorithm, which proves the effectiveness of the proposed scheme.
Authors
- Fan Zhang (ORCID: https://orcid.org/0000-0001-5967-9917)
- Zhifeng Li (ORCID: https://orcid.org/0000-0002-8786-8501)
- Li‐Zhen Fan (ORCID: https://orcid.org/0000-0003-2270-4458)
- Denghai Wang
- Yan Zhang (ORCID: https://orcid.org/0000-0002-7329-0382)
- Shenhui Gu
Institutions
- Daqing Oilfield General Hospital (CN)
- Xi'an Jiaotong University (CN)
Publication Details
- Published
- 2025-03-28
- DOI
- https://doi.org/10.1109/aeees64634.2025.11019685
- Primary Topic
- Power Systems and Renewable Energy
- Type
- article
- Field-Weighted Citation Impact
- 0.00