Planning of DC Electric Spring with Particle Swarm Optimization and Elitist Non-Dominated Sorting Genetic Algorithm

Qingsong Wang; Siwei Li; Hao Ding; Ming Cheng; Giuseppe Buja

doi:10.17775/CSEEJPES.2022.04510

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Planning of DC Electric Spring with Particle Swarm Optimization and Elitist Non-Dominated Sorting Genetic Algorithm

Regular Papers | 更新时间：2026-10-15

- Planning of DC Electric Spring with Particle Swarm Optimization and Elitist Non-Dominated Sorting Genetic Algorithm
- Planning of DC Electric Spring with Particle Swarm Optimization and Elitist Non-Dominated Sorting Genetic Algorithm
- 中国电机工程学会电力与能源系统学报(英文) 2024年10卷第2期页码：574-583
- 作者机构：
  
  1. Jiangsu Provincial Key Laboratory of Smart Grid Technology and Equipment, School of Electrical Engineering, Southeast University,Nanjing,China
  2. School of Software Engineering, Southeast university,Suzhou,China
  3. Department of Industrial Engineering, University of Padova, Padova,Italy
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2022.04510
  中图分类号：
- 纸质出版：2024-03-01
- 稿件说明：
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Qingsong Wang, Siwei Li, Hao Ding, 等. Planning of DC Electric Spring with Particle Swarm Optimization and Elitist Non-Dominated Sorting Genetic Algorithm[J]. 中国电机工程学会电力与能源系统学报(英文), 2024,10(2):574-583.

Qingsong Wang, Siwei Li, Hao Ding, et al. Planning of DC Electric Spring with Particle Swarm Optimization and Elitist Non-Dominated Sorting Genetic Algorithm[J]. CSEE Journal of Power and Energy Systems, 2024, 10(2): 574-583.
Qingsong Wang, Siwei Li, Hao Ding, 等. Planning of DC Electric Spring with Particle Swarm Optimization and Elitist Non-Dominated Sorting Genetic Algorithm[J]. 中国电机工程学会电力与能源系统学报(英文), 2024,10(2):574-583. DOI： 10.17775/CSEEJPES.2022.04510.

Qingsong Wang, Siwei Li, Hao Ding, et al. Planning of DC Electric Spring with Particle Swarm Optimization and Elitist Non-Dominated Sorting Genetic Algorithm[J]. CSEE Journal of Power and Energy Systems, 2024, 10(2): 574-583. DOI： 10.17775/CSEEJPES.2022.04510.

摘要

Abstract

This paper addresses the planning problem of parallel DC electric springs (DCESs). DCES

a demand-side management method

realizes automatic matching of power consumption and power generation by adjusting non-critical load (NCL) and internal storage. It can offer higher power quality to critical load (CL)

reduce power imbalance and relieve pressure on energy storage systems (RESs). In this paper

a planning method for parallel DCESs is proposed to maximize stability gain

economic benefits

and penetration of RESs. The planning model is a master optimization with sub-optimization to highlight the priority of objectives. Master optimization is used to improve stability of the network

and sub-optimization aims to improve economic benefit and allowable penetration of RESs. This issue is a multivariable nonlinear mixed integer problem

requiring huge calculations by using common solvers. Therefore

particle Swarm optimization (PSO) and Elitist non-dominated sorting genetic algorithm (NSGA-II) were used to solve this model. Considering uncertainty of RESs

this paper verifies effectiveness of the proposed planning method on IEEE 33-bus system based on deterministic scenarios obtained by scenario analysis.

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