Multi-objective optimal configuration of CCHP system containing hybrid electric-hydrogen energy storage system

Q2 Energy Energy Informatics Pub Date : 2024-11-06 DOI:10.1186/s42162-024-00413-4
Jian Ye, Qiang Dong, Gelin Yang, Yang Qiu, Peng Zhu, Yingjie Wang, Liang Sun
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Abstract

In order to cope with the increasing energy demand and achieve the “double carbon “goal of China’s 14th Five-Year Plan,” combined with hydrogen energy storage technology, it has the characteristics of zero pollution, high efficiency and rich source. In the context of reducing energy consumption and the vigorous development of hydrogen energy storage technology, a multi-objective optimization configuration model with economy, energy consumption index and carbon emission index is proposed, which takes into account the working characteristics of the hydrogen energy storage system, and the exothermic heat release from the electrolysis tanks and fuel cells when they are working to provide the loads with an additional heat source of the Combined Cooling, Heating and Power (CCHP) system, to reduce energy consumption and carbon emission. Finally, taking a region as an example, a multi-objective optimization algorithm based on decomposition is used to solve the model, so as to obtain a series of alternatives with better optimization effect. At the same time, the two-way projection method based on interval intuitionistic fuzzy information is used to make decisions, and the scheme that optimizes the economy, energy consumption index and carbon emission index is obtained, which verifies the feasibility of the system proposed in this paper.

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包含电动-氢能混合储能系统的冷热电三联供系统的多目标优化配置
为应对日益增长的能源需求,实现我国 "十四五 "规划的 "双碳 "目标,结合氢能储能技术具有零污染、高效率、来源丰富等特点。在降低能耗、大力发展氢储能技术的背景下,提出了经济性、能耗指标和碳排放指标的多目标优化配置模型,该模型考虑了氢储能系统的工作特性,通过电解槽和燃料电池工作时放热,为负荷提供冷热电联供系统的附加热源,达到降低能耗和碳排放的目的。最后,以某区域为例,采用基于分解的多目标优化算法对模型进行求解,从而得到一系列优化效果较好的备选方案。同时,利用基于区间直觉模糊信息的双向预测法进行决策,得到了经济性、能耗指标和碳排放指标最优化的方案,验证了本文所提系统的可行性。
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来源期刊
Energy Informatics
Energy Informatics Computer Science-Computer Networks and Communications
CiteScore
5.50
自引率
0.00%
发文量
34
审稿时长
5 weeks
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