C. Tseng, Ngakan Ketut Acwin Dwijendra, Maria Jade Catalan Opulencia, S. Ganieva, I. Muda
{"title":"需求侧参与下智能微电网的最优能源管理","authors":"C. Tseng, Ngakan Ketut Acwin Dwijendra, Maria Jade Catalan Opulencia, S. Ganieva, I. Muda","doi":"10.2478/rtuect-2022-0018","DOIUrl":null,"url":null,"abstract":"Abstract The energy management in energy systems is the main solution for energy companies in order to provide minimization of the energy generation costs and emission polluting. In this work, a multi-criteria optimization model is implemented for minimizing the generation cost and emission in a smart micro grid (SMG) at day-ahead planning. In this modelling, the demand side participates in optimal energy management through two strategies such as demand shifting and onsite generation by the energy storage system (ESS). The optimal participation of demand side is modelled based on energy price in energy market. Implementation of the proposed approach in GAMS software is done, and weight sum method (WSM) is employed for solving multi-criteria optimization. The desired optimal solution of multi-criteria objectives is found via the max-min fuzzy procedure. Finally, confirmation of the proposed approach is analysed by numerical simulation in two case studies.","PeriodicalId":46053,"journal":{"name":"Environmental and Climate Technologies","volume":"136 1","pages":"228 - 239"},"PeriodicalIF":1.4000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Optimal Energy Management in a Smart Micro Grid with Demand Side Participation\",\"authors\":\"C. Tseng, Ngakan Ketut Acwin Dwijendra, Maria Jade Catalan Opulencia, S. Ganieva, I. Muda\",\"doi\":\"10.2478/rtuect-2022-0018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract The energy management in energy systems is the main solution for energy companies in order to provide minimization of the energy generation costs and emission polluting. In this work, a multi-criteria optimization model is implemented for minimizing the generation cost and emission in a smart micro grid (SMG) at day-ahead planning. In this modelling, the demand side participates in optimal energy management through two strategies such as demand shifting and onsite generation by the energy storage system (ESS). The optimal participation of demand side is modelled based on energy price in energy market. Implementation of the proposed approach in GAMS software is done, and weight sum method (WSM) is employed for solving multi-criteria optimization. The desired optimal solution of multi-criteria objectives is found via the max-min fuzzy procedure. Finally, confirmation of the proposed approach is analysed by numerical simulation in two case studies.\",\"PeriodicalId\":46053,\"journal\":{\"name\":\"Environmental and Climate Technologies\",\"volume\":\"136 1\",\"pages\":\"228 - 239\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental and Climate Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2478/rtuect-2022-0018\",\"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-2022-0018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY","Score":null,"Total":0}
Optimal Energy Management in a Smart Micro Grid with Demand Side Participation
Abstract The energy management in energy systems is the main solution for energy companies in order to provide minimization of the energy generation costs and emission polluting. In this work, a multi-criteria optimization model is implemented for minimizing the generation cost and emission in a smart micro grid (SMG) at day-ahead planning. In this modelling, the demand side participates in optimal energy management through two strategies such as demand shifting and onsite generation by the energy storage system (ESS). The optimal participation of demand side is modelled based on energy price in energy market. Implementation of the proposed approach in GAMS software is done, and weight sum method (WSM) is employed for solving multi-criteria optimization. The desired optimal solution of multi-criteria objectives is found via the max-min fuzzy procedure. Finally, confirmation of the proposed approach is analysed by numerical simulation in two case studies.
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.