电力系统自动化2025，Vol.49Issue(19)：49-61,13.DOI:10.7500/AEPS20241023002
基于熵理论的低碳综合能源系统信息-能量耦合优化
Information-Energy Coupling Optimization of Low-carbon Integrated Energy System Based on Entropy Theory
摘要
Abstract
With the increasing popularity of renewable energy sources(RESs),traditional integrated energy systems are transforming into low-carbon integrated energy systems(LCIES).However,compared with traditional electricity,there is no clear model for the quality and cost of electricity that explicitly considers the uncertainty of RES generation,which makes the low-cost and high-efficiency operation of LCIES more complex.To address this challenge,an analysis method based on the entropy theory is proposed to quantify the uncertainty cost and efficiency of RES generation.Firstly,an equivalent fuel cost model is proposed,which establishes the connection between the energy layer and the information layer,and equivalently quantifies the information cost of eliminating the uncertainty of RES.On this basis,the information energy quality coefficient is established by using the entropy theory to analyze the energy quality of RES.Finally,a fully distributed optimization algorithm based on neural dynamics is proposed to perform multi-objective optimization of cost and energy efficiency within LCIES.The simulation results verify the superiority of the proposed method in improving the energy efficiency and economy of the system.关键词
信息熵/能量质量/效率分析/成本优化/低碳综合能源系统/可再生能源/不确性Key words
information entropy/energy quality/efficiency analysis/cost optimization/low-carbon integrated energy system/renewable energy system/uncertainty引用本文复制引用
刘子铭,黄博南,王靖傲,王睿,孙秋野..基于熵理论的低碳综合能源系统信息-能量耦合优化[J].电力系统自动化,2025,49(19):49-61,13.基金项目
国家自然科学基金重点项目(62433013) （62433013）
国家自然科学基金面上项目(52377079) （52377079）
中央高校基本科研业务费专项资金资助项目(N2404001). This work is supported by National Natural Science Foundation of China(No.62433013,No.52377079)and Fundamental Research Funds for the Central Universities(No.N2404001). （N2404001）
