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

Institutions

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
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Method for Location and Capacity Determination of Energy Storage in Distribution Networks Based on an Improved Niched Particle Swarm Optimization Algorithm

Fan Zhang, Zhifeng Li, Li‐Zhen Fan, Denghai Wang et al.
Power Systems and Renewable Energy
article

A Method for Location and Capacity Determination of Energy Storage in Distribution Networks Based on an Improved Niched Particle Swarm Optimization Algorithm

Fan Zhang, Zhifeng Li, Li‐Zhen Fan, Denghai Wang, Yan Zhang, Shenhui Gu
article en

Abstract

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.

Daqing Oilfield General Hospital (CN), Xi'an Jiaotong University (CN)
Affordable and clean energy
Openalex Percentile: Top 89%
Power Systems and Renewable Energy
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A Method for Location and Capacity Determination of Energy Storage in Distribution Networks Based on an Improved Niched Particle Swarm Optimization Algorithm — Fan Zhang, Zhifeng Li, et al. · (2025) | TGRS Research Map | TGRS