一种基于遗传算法改进粒子群算法的光储氢并网型微电网容量配置优化模型研究

徐展鹏; 陈福新; 杨雪凡; 卢琴芬

doi:10.19912/j.0254-0096.tynxb.2024-0319

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太阳能学报 ›› 2025, Vol. 46 ›› Issue (7) : 144-153. DOI: 10.19912/j.0254-0096.tynxb.2024-0319

第二十七届中国科协年会学术论文

一种基于遗传算法改进粒子群算法的光储氢并网型微电网容量配置优化模型研究

徐展鹏¹, 陈福新¹, 杨雪凡², 卢琴芬²

作者信息 +

RESEARCH ON OPTIMIZATION MODEL OF CAPACITY CONFIGURATION OF PV/STORAGE/HYDROGEN GRID-CONNECTED MICROGRID BASED ON IMPROVED PSO ALGORITHM WITH GENETIC ALGORITHM

Xu Zhanpeng¹, Chen Fuxin¹, Yang Xuefan², Lu Qinfen²

Author information +

文章历史 +

摘要

以并网型光储氢微电网为研究对象,为提升其可再生能源消纳能力、碳减排能力和经济性,提出一种基于遗传算法改进粒子群算法的容量配置优化模型。优化模型目标函数为最大年综合利润,不仅将投资运维、绿证交易和碳交易机制引入系统运行成本和收益,且提出一种基于电氢储能实时收益系数的协调控制策略,使得光氢利润基于分时电价进行实时变化、储能设备的出力顺序根据实时收益系数来优化;优化变量为光、氢与储能的容量;优化方法为遗传算法改进的粒子群优化算法,其在改进粒子群优化算法引入遗传算法的思想,对粒子种群的位置进行选择、交叉与变异操作,提高全局优化能力。通过优化设计实例与影响因素分析实例,验证了优化模型的有效性。

Abstract

Taking PV/storage/hydrogen grid-connected microgrid as research objective, this study proposes a capacity configuration optimization model by improved PSO algorithm with genetic algorithm（GA） in order to improve its renewable energy consumption capacity, carbon emission reduction capacity and economic output. The optimization objective is maximum annual comprehensive profit, which not only introduces investment, operation and maintenance cost, green certificate trading revenue and carbon trading cost into operating cost and profit of system, but also proposes a coordination control strategy based on the real-time revenue coefficient of electric-hydrogen-storage. Therefore, the profitability of PV and hydrogen varies in real-time based on time-of-use price, and the dispatch priority of energy storage equipment is optimized according to the real-time revenue coefficient. The optimization variables are the capacities of PV, hydrogen and storage. The optimization method is an improved PSO algorithm incorporating GA concepts. By the operation of selection, crossover and mutation of the particle population position, the capacity of global optimization is improved. The effectiveness of optimization model is verified by both optimization design case and influence analysis case.

导出引用

徐展鹏, 陈福新, 杨雪凡, 卢琴芬. 一种基于遗传算法改进粒子群算法的光储氢并网型微电网容量配置优化模型研究[J]. 太阳能学报. 2025, 46(7): 144-153 https://doi.org/10.19912/j.0254-0096.tynxb.2024-0319

Xu Zhanpeng, Chen Fuxin, Yang Xuefan, Lu Qinfen. RESEARCH ON OPTIMIZATION MODEL OF CAPACITY CONFIGURATION OF PV/STORAGE/HYDROGEN GRID-CONNECTED MICROGRID BASED ON IMPROVED PSO ALGORITHM WITH GENETIC ALGORITHM[J]. Acta Energiae Solaris Sinica. 2025, 46(7): 144-153 https://doi.org/10.19912/j.0254-0096.tynxb.2024-0319

中图分类号： TM721.1

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