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Multi-Objective Optimal Scheduling of Microgrids Based on Improved Particle Swarm Algorithm

作     者:Guan, Zhong Wang, Hui Li, Zhi Luo, Xiaohu Yang, Xi Fang, Jugang Zhao, Qiang 

作者机构:Wudian New Energy Co Ltd Wuhu City Wuhu 241012 Peoples R China Tsinghua Univ Sichuan Energy Internet Res Inst Chengdu 610000 Peoples R China China Power Gharmony Energy Technol Co Ltd Beijing 102488 Peoples R China 

出 版 物:《ENERGIES》 (能源)

年 卷 期:2024年第17卷第7期

页      面:1760页

核心收录:

学科分类:0820[工学-石油与天然气工程] 08[工学] 0807[工学-动力工程及工程热物理] 

基  金:UK Research and Innovation, UKRI, (105149) UK Research and Innovation, UKRI 

主  题:microgrid multi-objective improved particle swarm algorithm optimal scheduling 

摘      要:Microgrid optimization scheduling, as a crucial part of smart grid optimization, plays a significant role in reducing energy consumption and environmental pollution. The development goals of microgrids not only aim to meet the basic demands of electricity supply but also to enhance economic benefits and environmental protection. In this regard, a multi-objective optimization scheduling model for microgrids in grid-connected mode is proposed, which comprehensively considers the operational costs and environmental protection costs of microgrid systems. This model also incorporates improvements to the traditional particle swarm optimization (PSO) algorithm by considering inertia factors and particle adaptive mutation, and it utilizes the improved algorithm to solve the optimization model. Simulation results demonstrate that this model can effectively reduce electricity costs for users and environmental pollution, promoting the optimized operation of microgrids and verifying the superior performance of the improved PSO algorithm. After algorithmic improvements, the optimal total cost achieved was CNY 836.23, representing a decrease from the pre-improvement optimal value of CNY 850.

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