考虑需求管理的智能能源枢纽最优节能

IF 1.4 Q4 GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY

Environmental and Climate Technologies Pub Date : 2022-01-01 DOI:10.2478/rtuect-2022-0094

Ngakan Ketut Acwin Dwijendra, O. Candra, Ihsan Ali Mubarak, Hassan Taher Braiber, Muneam Hussein Ali, I. Muda, R. Sivaraman, A. Iswanto

{"title":"考虑需求管理的智能能源枢纽最优节能","authors":"Ngakan Ketut Acwin Dwijendra, O. Candra, Ihsan Ali Mubarak, Hassan Taher Braiber, Muneam Hussein Ali, I. Muda, R. Sivaraman, A. Iswanto","doi":"10.2478/rtuect-2022-0094","DOIUrl":null,"url":null,"abstract":"Abstract This study focused on energy saving in energy hub system using smart grid technologies and management of the energy demand. The two-layer energy management is proposed for implementing energy saving. In first layer, energy demand such as electrical, thermal and natural gas are optimized subject to optimal level of the demand at day-ahead. Then, optimized energy demand is applied in second layer to reduction energy generation costs. The optimization of the proposed approach is done by shuffled frog leaping algorithm (SFLA), and results at several case studies to confirmation of the proposed approach are investigated.","PeriodicalId":46053,"journal":{"name":"Environmental and Climate Technologies","volume":"19 1","pages":"1244 - 1256"},"PeriodicalIF":1.4000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimal Energy-Saving in Smart Energy Hub Considering Demand Management\",\"authors\":\"Ngakan Ketut Acwin Dwijendra, O. Candra, Ihsan Ali Mubarak, Hassan Taher Braiber, Muneam Hussein Ali, I. Muda, R. Sivaraman, A. Iswanto\",\"doi\":\"10.2478/rtuect-2022-0094\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract This study focused on energy saving in energy hub system using smart grid technologies and management of the energy demand. The two-layer energy management is proposed for implementing energy saving. In first layer, energy demand such as electrical, thermal and natural gas are optimized subject to optimal level of the demand at day-ahead. Then, optimized energy demand is applied in second layer to reduction energy generation costs. The optimization of the proposed approach is done by shuffled frog leaping algorithm (SFLA), and results at several case studies to confirmation of the proposed approach are investigated.\",\"PeriodicalId\":46053,\"journal\":{\"name\":\"Environmental and Climate Technologies\",\"volume\":\"19 1\",\"pages\":\"1244 - 1256\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental and Climate Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2478/rtuect-2022-0094\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental and Climate Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/rtuect-2022-0094","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY","Score":null,"Total":0}

引用次数: 0

摘要

摘要本研究主要研究了在能源枢纽系统中应用智能电网技术进行能源节约和能源需求管理。为了实现节能，提出了两层能源管理。在第一层，电力、热力和天然气等能源需求根据前一天的最优需求水平进行优化。然后，在第二层应用优化的能源需求来降低能源生产成本。利用洗牌青蛙跳跃算法(SFLA)对该方法进行了优化，并对几个实例的结果进行了验证。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Optimal Energy-Saving in Smart Energy Hub Considering Demand Management

Abstract This study focused on energy saving in energy hub system using smart grid technologies and management of the energy demand. The two-layer energy management is proposed for implementing energy saving. In first layer, energy demand such as electrical, thermal and natural gas are optimized subject to optimal level of the demand at day-ahead. Then, optimized energy demand is applied in second layer to reduction energy generation costs. The optimization of the proposed approach is done by shuffled frog leaping algorithm (SFLA), and results at several case studies to confirmation of the proposed approach are investigated.

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

Environmental and Climate Technologies GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY-

CiteScore

3.10

自引率

28.60%

发文量

审稿时长

16 weeks

期刊介绍： Environmental and Climate Technologies provides a forum for information on innovation, research and development in the areas of environmental science, energy resources and processes, innovative technologies and energy efficiency. Authors are encouraged to submit manuscripts which cover the range from bioeconomy, sustainable technology development, life cycle analysis, eco-design, climate change mitigation, innovative solutions for pollution reduction to resilience, the energy efficiency of buildings, secure and sustainable energy supplies. The Journal ensures international publicity for original research and innovative work. A variety of themes are covered through a multi-disciplinary approach, one which integrates all aspects of environmental science: -Sustainability of technology development- Bioeconomy- Cleaner production, end of pipe production- Zero emission technologies- Eco-design- Life cycle analysis- Eco-efficiency- Environmental impact assessment- Environmental management systems- Resilience- Energy and carbon markets- Greenhouse gas emission reduction and climate technologies- Methodologies for the evaluation of sustainability- Renewable energy resources- Solar, wind, geothermal, hydro energy, biomass sources: algae, wood, straw, biogas, energetic plants and organic waste- Waste management- Quality of outdoor and indoor environment- Environmental monitoring and evaluation- Heat and power generation, including district heating and/or cooling- Energy efficiency.