|国家科技期刊平台
首页|期刊导航|电力建设|基于共享氢容量备用的多微网双层优化方法

基于共享氢容量备用的多微网双层优化方法OA北大核心CSTPCD

Multiple Microgrid Bilayer Optimization Method Based on Shared Hydrogen Capacity Backup

中文摘要英文摘要

氢储能具有跨季节、跨区域存储等优势,但氢能长时存储带来的短期闲置现象以及以新能源为主体的微网源荷波动较大等问题亟需解决.构建了共享氢储能作为容量备用的多微网双层运行优化方法,以氢储能短期闲置容量作为微网备用,保证系统可靠供电.首先,提出一种基于系统净负荷预测误差近似服从正态分布框架下的多微网备用容量设定方法.其次,引入氢储能聚合商,构建了基于共享氢储能容量备用的多微网双层优化模型,并采用改进多目标麻雀搜索算法求解.最后,通过我国西北某地区的 3 个微网进行验证,与独立方案相比,所提共享模式下合作联盟总运行成本降低了 6.3%,碳排放量降低了 29%,综合能效提升了 4.8%.

Hydrogen storage offers advantages such as cross-seasonal and cross-regional storage;however,the short-term idle capacity caused by long-term hydrogen storage and significant fluctuations in the source and load of microgrids dominated by new energy sources urgently need to be addressed.This study develops a dual-layer operation optimization method for multiple microgrids,using shared hydrogen storage as capacity backup to utilize the short-term idle capacity of hydrogen storage to provide a backup for the microgrid,ensuring reliable power supply.First,a multi-microgrid reserve capacity setting method is proposed,based on an approximate normal distribution of system net load prediction error.Then,a hydrogen storage aggregator is introduced to construct a dual-layer optimization model for multiple microgrids based on shared hydrogen storage capacity,solved using an improved multi-objective sparrow search algorithm.Finally,through the verification of three microgrids in a specific region in northwest China,it was found that compared to independent solutions,the total operating cost of the cooperative alliance under the sharing model was reduced by 6.3%,carbon emissions were cut by 29%,and comprehensive energy efficiency improved by 4.8%.

王永利;姜斯冲;郭璐;贾舒婷;马恺玮;杜振翔

华北电力大学经济与管理学院,北京市 102206

动力与电气工程

共享氢储能容量备用合作博弈改进多目标麻雀搜索算法利益分配

shared hydrogen energy storagecapacity backupcooperative gameimproved multi-objective sparrow search algorithmbenefit distribution

《电力建设》 2024 (011)

65-78 / 14

This work is supported by National Natural Science Foundation of China(No.72371101).国家自然科学基金项目(72371101)

10.12204/j.issn.1000-7229.2024.11.006

评论