农村地区生物质-太阳能-风能综合利用多能互补系统的多目标优化

IF 9.9 1区 工程技术 Q1 ENERGY & FUELS Energy Conversion and Management Pub Date : 2024-11-11 DOI:10.1016/j.enconman.2024.119241
Min Chen , Jiayuan Wei , Xianting Yang , Qiang Fu , Qingyu Wang , Sijia Qiao
{"title":"农村地区生物质-太阳能-风能综合利用多能互补系统的多目标优化","authors":"Min Chen ,&nbsp;Jiayuan Wei ,&nbsp;Xianting Yang ,&nbsp;Qiang Fu ,&nbsp;Qingyu Wang ,&nbsp;Sijia Qiao","doi":"10.1016/j.enconman.2024.119241","DOIUrl":null,"url":null,"abstract":"<div><div>Rural areas possess abundant renewable energy sources, such as solar and biomass energy; however, the current methods of energy utilization suffer from low efficiency and serious pollution issues. As rural residents’ living standards continue to improve, there is an urgent need to optimize and adjust the structure of rural energy systems. Multi-energy complementary systems (MECS) have the potential to enhance energy utilization efficiency, achieve high efficiency and energy savings, significantly reduce carbon emissions, and effectively address the challenges faced by rural energy development. This study explores a typical framework for rural MECS that integrates photovoltaic, wind turbine, and biomass biogas combined cooling, heating, and power technology while considering the partial load ratio of equipment components and coupling characteristics between different energy sources. Based on various scenarios of valley electricity utilization, multi-objective optimization models are established to determine the capacity of MECS with economy, environment, and primary energy saving rate as objective functions. The non-dominated sorting genetic algorithm (NSGA-II) along with Technique for Order Preference by Similarity to Ideal Solution decision-making method is adopted to obtain optimal solutions from the Pareto solution set. The case study conducted in a rural area of central China has demonstrated the effective enhancement of coupling capacity in MECS through battery storage. By actively storing energy during off-peak electricity periods, battery storage strengthens the complementary capabilities of photovoltaic systems, wind turbines, and itself. This approach allows for a reduction in planned capacity for photovoltaic and wind power systems within MECS while increasing the planned capacity for internal combustion engines, resulting in respective decreases in system investment costs by 16.19% and 13.18%. Furthermore, incorporating more biogas-fired cogeneration during off-peak electricity periods improves the system’s performance economically, environmentally, and with regards to primary energy saving rate.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"323 ","pages":"Article 119241"},"PeriodicalIF":9.9000,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-objective optimization of multi-energy complementary systems integrated biomass-solar-wind energy utilization in rural areas\",\"authors\":\"Min Chen ,&nbsp;Jiayuan Wei ,&nbsp;Xianting Yang ,&nbsp;Qiang Fu ,&nbsp;Qingyu Wang ,&nbsp;Sijia Qiao\",\"doi\":\"10.1016/j.enconman.2024.119241\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Rural areas possess abundant renewable energy sources, such as solar and biomass energy; however, the current methods of energy utilization suffer from low efficiency and serious pollution issues. As rural residents’ living standards continue to improve, there is an urgent need to optimize and adjust the structure of rural energy systems. Multi-energy complementary systems (MECS) have the potential to enhance energy utilization efficiency, achieve high efficiency and energy savings, significantly reduce carbon emissions, and effectively address the challenges faced by rural energy development. This study explores a typical framework for rural MECS that integrates photovoltaic, wind turbine, and biomass biogas combined cooling, heating, and power technology while considering the partial load ratio of equipment components and coupling characteristics between different energy sources. Based on various scenarios of valley electricity utilization, multi-objective optimization models are established to determine the capacity of MECS with economy, environment, and primary energy saving rate as objective functions. The non-dominated sorting genetic algorithm (NSGA-II) along with Technique for Order Preference by Similarity to Ideal Solution decision-making method is adopted to obtain optimal solutions from the Pareto solution set. The case study conducted in a rural area of central China has demonstrated the effective enhancement of coupling capacity in MECS through battery storage. By actively storing energy during off-peak electricity periods, battery storage strengthens the complementary capabilities of photovoltaic systems, wind turbines, and itself. This approach allows for a reduction in planned capacity for photovoltaic and wind power systems within MECS while increasing the planned capacity for internal combustion engines, resulting in respective decreases in system investment costs by 16.19% and 13.18%. Furthermore, incorporating more biogas-fired cogeneration during off-peak electricity periods improves the system’s performance economically, environmentally, and with regards to primary energy saving rate.</div></div>\",\"PeriodicalId\":11664,\"journal\":{\"name\":\"Energy Conversion and Management\",\"volume\":\"323 \",\"pages\":\"Article 119241\"},\"PeriodicalIF\":9.9000,\"publicationDate\":\"2024-11-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy Conversion and Management\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0196890424011828\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Conversion and Management","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0196890424011828","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0

摘要

农村地区拥有丰富的可再生能源,如太阳能、生物质能等,但目前的能源利用方式存在效率低、污染严重等问题。随着农村居民生活水平的不断提高,农村能源系统结构亟待优化调整。多能互补系统(MECS)有望提高能源利用效率,实现高效节能,大幅减少碳排放,有效应对农村能源发展面临的挑战。本研究探索了一种典型的农村 MECS 框架,该框架集成了光伏、风力涡轮机和生物质沼气冷热电三联供技术,同时考虑了设备组件的部分负载率和不同能源之间的耦合特性。根据不同的谷电利用场景,建立多目标优化模型,以经济、环境和一次能源节约率为目标函数,确定 MECS 的容量。采用非支配排序遗传算法(NSGA-II)以及与理想解相似的排序偏好技术决策方法,从帕累托解集中获得最优解。在中国中部农村地区进行的案例研究表明,通过电池储能可有效提高 MECS 的耦合能力。通过在非用电高峰期主动储存能量,电池储能增强了光伏系统、风力涡轮机和自身的互补能力。这种方法可以减少 MECS 中光伏发电系统和风力发电系统的计划发电量,同时增加内燃机的计划发电量,从而使系统投资成本分别降低 16.19% 和 13.18%。此外,在非用电高峰期增加沼气热电联产,可提高系统的经济、环保和一次能源节约率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Multi-objective optimization of multi-energy complementary systems integrated biomass-solar-wind energy utilization in rural areas
Rural areas possess abundant renewable energy sources, such as solar and biomass energy; however, the current methods of energy utilization suffer from low efficiency and serious pollution issues. As rural residents’ living standards continue to improve, there is an urgent need to optimize and adjust the structure of rural energy systems. Multi-energy complementary systems (MECS) have the potential to enhance energy utilization efficiency, achieve high efficiency and energy savings, significantly reduce carbon emissions, and effectively address the challenges faced by rural energy development. This study explores a typical framework for rural MECS that integrates photovoltaic, wind turbine, and biomass biogas combined cooling, heating, and power technology while considering the partial load ratio of equipment components and coupling characteristics between different energy sources. Based on various scenarios of valley electricity utilization, multi-objective optimization models are established to determine the capacity of MECS with economy, environment, and primary energy saving rate as objective functions. The non-dominated sorting genetic algorithm (NSGA-II) along with Technique for Order Preference by Similarity to Ideal Solution decision-making method is adopted to obtain optimal solutions from the Pareto solution set. The case study conducted in a rural area of central China has demonstrated the effective enhancement of coupling capacity in MECS through battery storage. By actively storing energy during off-peak electricity periods, battery storage strengthens the complementary capabilities of photovoltaic systems, wind turbines, and itself. This approach allows for a reduction in planned capacity for photovoltaic and wind power systems within MECS while increasing the planned capacity for internal combustion engines, resulting in respective decreases in system investment costs by 16.19% and 13.18%. Furthermore, incorporating more biogas-fired cogeneration during off-peak electricity periods improves the system’s performance economically, environmentally, and with regards to primary energy saving rate.
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
Energy Conversion and Management
Energy Conversion and Management 工程技术-力学
CiteScore
19.00
自引率
11.50%
发文量
1304
审稿时长
17 days
期刊介绍: The journal Energy Conversion and Management provides a forum for publishing original contributions and comprehensive technical review articles of interdisciplinary and original research on all important energy topics. The topics considered include energy generation, utilization, conversion, storage, transmission, conservation, management and sustainability. These topics typically involve various types of energy such as mechanical, thermal, nuclear, chemical, electromagnetic, magnetic and electric. These energy types cover all known energy resources, including renewable resources (e.g., solar, bio, hydro, wind, geothermal and ocean energy), fossil fuels and nuclear resources.
期刊最新文献
Performance and feasibility assessment of an adsorptive-dehumidification system utilizing a heat pipe-based desiccant-coated heat exchanger Cylindrical near-field solar thermophotovoltaic system with multilayer absorber/emitter structures: Integrated solar radiation absorption and cooling energy consumption Transportation and process modelling-assisted techno-economic assessment of resource recovery from non-recycled municipal plastic waste Municipal solid waste thermochemical conversion to substitute natural gas: Comparative techno-economic analysis between updraft gasification and chemical looping Improved numerical modeling of photovoltaic double skin façades with spectral considerations: Methods and investigations
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1