现代电力2026，Vol.43Issue(4)：613-624,中插4,13.DOI:10.19725/j.cnki.1007-2322.2024.0090
计及土地因素的微电网低碳经济优化配置方法
A Low-carbon Economic Optimization Configuration Method for Microgrids Considering Land Factors
摘要
Abstract
In the context of the"Double Carbon"strategy,reducing system carbon emissions while considering the economy has become a research focus on the optimal allocation of microgrids.Therefore,a two-layer optimal allocation method for microgrids with hydrogen-containing energy storage is proposed,considering carbon trading and demand response.By introducing a tiered carbon trading mechanism into the planning model and considering the impact of construction processes on land carbon emissions at carbon emission sources.The price-based demand response is introduced,with minimizing the net load fluctuation in the dispatch cycle as the objective function.In addition,users are guided to change their electricity consumption strategies to promote renewable energy accommodation.A two-layer optimization configuration framework is constructed,where the upper layer is utilized for microgrid configuration optimization,with the minimizing the annual equivalent comprehensive cost as the objective function.The lower layer is employed for microgrid operation optimization,with the objective of minimizing the sum of microgrid operating costs and carbon emission costs.Finally,combined with the actual data of a residential area in Jiangsu Province,enhanced whale optimization algorithm(E-WOA)is utilized to solve the two-layer optimal configuration model.The results of the case study verify the superiority of the proposed scheme and algorithm.关键词
并网型微电网/氢储能/优化配置/阶梯式碳交易/需求侧响应/增强型鲸鱼算法Key words
grid-connected microgrid/hydrogen energy storage/configuration optimization/tiered carbon trading/demand-side response/enhanced whale optimization algorithm分类
信息技术与安全科学引用本文复制引用
王磊,颜华卿,江伟建,周俊平..计及土地因素的微电网低碳经济优化配置方法[J].现代电力,2026,43(4):613-624,中插4,13.基金项目
国家自然科学基金项目(61873159) （61873159）
上海绿色能源并网工程技术研究中心资助项目(13DZ2251900). Project Supported by National Natural Science Foundation of China(61873159) （13DZ2251900）
Funded by Shanghai Green Energy Grid-Connected Engineering Technology Research Center(13DZ2251900). （13DZ2251900）
