多利益相关者利益协调下的电氢一体化能源系统配置选择随机多准则决策

IF 8 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Zhiying Zhang , Yingying Xu , Yaoyao Yu , Xiaoyuan Chen , Huchang Liao
{"title":"多利益相关者利益协调下的电氢一体化能源系统配置选择随机多准则决策","authors":"Zhiying Zhang ,&nbsp;Yingying Xu ,&nbsp;Yaoyao Yu ,&nbsp;Xiaoyuan Chen ,&nbsp;Huchang Liao","doi":"10.1016/j.engappai.2025.111323","DOIUrl":null,"url":null,"abstract":"<div><div>The development of electricity-hydrogen integrated energy systems (IESs) is an important solution for promoting the transition to clean energy. Determining the optimal system configuration is challenging due to the involvement of multiple criteria and stakeholders. This paper introduces a robust evaluation framework for the configuration selection of park-level electricity-hydrogen IESs considering multiple stakeholder interests. Firstly, eight schemes are designed for an industrial park, and configuration optimization models are constructed to obtain the optimal capacities of the components. Then, a group decision-making model based on stochastic multiple criteria acceptability analysis and multi-objective optimization on the basis of ratio analysis plus full multiplicative form (MULTIMOORA) method is developed to analyze and rank schemes, which connects the optimization with decision-making under multiple factors. The proposed framework accommodates the imprecise preferences of multiple stakeholders and coordinates their interests from technological, economic, environmental, and social aspects. Additionally, compensatory effects between multiple criteria are modeled, enhancing the robustness of decision results. Results indicate that the combination of natural gas, photovoltaic panel, hydrogen storage, and gas boiler is the winning scheme, with an energy utilization ratio of 54 % and a 76 % reduction in carbon emissions. Economically, the scheme results in a levelized cost of energy of 0.201$/kWh and creates 28 jobs annually. Scenario analysis indicates that, under current high configuration costs, a single policy aimed at reducing hydrogen storage costs is insufficient to facilitate the widespread deployment of near-zero carbon emission electricity-hydrogen IESs. It is recommended that power restriction measures be implemented simultaneously.</div></div>","PeriodicalId":50523,"journal":{"name":"Engineering Applications of Artificial Intelligence","volume":"157 ","pages":"Article 111323"},"PeriodicalIF":8.0000,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Stochastic multiple criteria decision-making for configuration selection of electricity-hydrogen integrated energy systems with multiple stakeholder interest coordination\",\"authors\":\"Zhiying Zhang ,&nbsp;Yingying Xu ,&nbsp;Yaoyao Yu ,&nbsp;Xiaoyuan Chen ,&nbsp;Huchang Liao\",\"doi\":\"10.1016/j.engappai.2025.111323\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The development of electricity-hydrogen integrated energy systems (IESs) is an important solution for promoting the transition to clean energy. Determining the optimal system configuration is challenging due to the involvement of multiple criteria and stakeholders. This paper introduces a robust evaluation framework for the configuration selection of park-level electricity-hydrogen IESs considering multiple stakeholder interests. Firstly, eight schemes are designed for an industrial park, and configuration optimization models are constructed to obtain the optimal capacities of the components. Then, a group decision-making model based on stochastic multiple criteria acceptability analysis and multi-objective optimization on the basis of ratio analysis plus full multiplicative form (MULTIMOORA) method is developed to analyze and rank schemes, which connects the optimization with decision-making under multiple factors. The proposed framework accommodates the imprecise preferences of multiple stakeholders and coordinates their interests from technological, economic, environmental, and social aspects. Additionally, compensatory effects between multiple criteria are modeled, enhancing the robustness of decision results. Results indicate that the combination of natural gas, photovoltaic panel, hydrogen storage, and gas boiler is the winning scheme, with an energy utilization ratio of 54 % and a 76 % reduction in carbon emissions. Economically, the scheme results in a levelized cost of energy of 0.201$/kWh and creates 28 jobs annually. Scenario analysis indicates that, under current high configuration costs, a single policy aimed at reducing hydrogen storage costs is insufficient to facilitate the widespread deployment of near-zero carbon emission electricity-hydrogen IESs. It is recommended that power restriction measures be implemented simultaneously.</div></div>\",\"PeriodicalId\":50523,\"journal\":{\"name\":\"Engineering Applications of Artificial Intelligence\",\"volume\":\"157 \",\"pages\":\"Article 111323\"},\"PeriodicalIF\":8.0000,\"publicationDate\":\"2025-06-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Engineering Applications of Artificial Intelligence\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0952197625013259\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering Applications of Artificial Intelligence","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0952197625013259","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

发展电氢一体化能源系统是推动向清洁能源转型的重要解决方案。由于涉及多个标准和涉众,确定最佳系统配置具有挑战性。本文介绍了考虑多个利益相关者利益的电站级电氢能源系统配置选择的鲁棒性评估框架。首先,针对某工业园区设计了8个方案,并构建了配置优化模型,得到了组件的最优容量。然后,基于比率分析和全乘法形式(MULTIMOORA)方法,建立了基于随机多准则可接受性分析和多目标优化的群体决策模型,对方案进行分析和排序,将优化与多因素下的决策联系起来。拟议的框架容纳了多个利益相关者的不精确偏好,并从技术、经济、环境和社会方面协调了他们的利益。此外,还建立了多准则间的补偿效应模型,增强了决策结果的鲁棒性。结果表明,天然气+光伏板+储氢+燃气锅炉组合是最佳方案,能源利用率达54%,碳排放量减少76%。从经济上看,该计划的平均能源成本为0.201美元/千瓦时,每年创造28个就业机会。情景分析表明,在当前的高配置成本下,旨在降低储氢成本的单一政策不足以促进近零碳排放电力-氢能源的广泛部署。建议同时采取限电措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stochastic multiple criteria decision-making for configuration selection of electricity-hydrogen integrated energy systems with multiple stakeholder interest coordination
The development of electricity-hydrogen integrated energy systems (IESs) is an important solution for promoting the transition to clean energy. Determining the optimal system configuration is challenging due to the involvement of multiple criteria and stakeholders. This paper introduces a robust evaluation framework for the configuration selection of park-level electricity-hydrogen IESs considering multiple stakeholder interests. Firstly, eight schemes are designed for an industrial park, and configuration optimization models are constructed to obtain the optimal capacities of the components. Then, a group decision-making model based on stochastic multiple criteria acceptability analysis and multi-objective optimization on the basis of ratio analysis plus full multiplicative form (MULTIMOORA) method is developed to analyze and rank schemes, which connects the optimization with decision-making under multiple factors. The proposed framework accommodates the imprecise preferences of multiple stakeholders and coordinates their interests from technological, economic, environmental, and social aspects. Additionally, compensatory effects between multiple criteria are modeled, enhancing the robustness of decision results. Results indicate that the combination of natural gas, photovoltaic panel, hydrogen storage, and gas boiler is the winning scheme, with an energy utilization ratio of 54 % and a 76 % reduction in carbon emissions. Economically, the scheme results in a levelized cost of energy of 0.201$/kWh and creates 28 jobs annually. Scenario analysis indicates that, under current high configuration costs, a single policy aimed at reducing hydrogen storage costs is insufficient to facilitate the widespread deployment of near-zero carbon emission electricity-hydrogen IESs. It is recommended that power restriction measures be implemented simultaneously.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Engineering Applications of Artificial Intelligence
Engineering Applications of Artificial Intelligence 工程技术-工程:电子与电气
CiteScore
9.60
自引率
10.00%
发文量
505
审稿时长
68 days
期刊介绍: Artificial Intelligence (AI) is pivotal in driving the fourth industrial revolution, witnessing remarkable advancements across various machine learning methodologies. AI techniques have become indispensable tools for practicing engineers, enabling them to tackle previously insurmountable challenges. Engineering Applications of Artificial Intelligence serves as a global platform for the swift dissemination of research elucidating the practical application of AI methods across all engineering disciplines. Submitted papers are expected to present novel aspects of AI utilized in real-world engineering applications, validated using publicly available datasets to ensure the replicability of research outcomes. Join us in exploring the transformative potential of AI in engineering.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信