{"title":"Multi-objective design optimization of cryo-polygeneration systems for urban microgrids: Balancing cost-effectiveness and sustainability","authors":"Alessio Tafone , Sundar Raj Thangavelu , Shigenori Morita , Alessandro Romagnoli","doi":"10.1016/j.energy.2025.136550","DOIUrl":null,"url":null,"abstract":"<div><div>Small- and medium-scale polygeneration systems provide multiple energy services to urban districts, including business parks, universities, and hospitals, offering significant energy, economic, and environmental benefits. These systems enhance energy efficiency, reduce cost, and lower emissions, especially in tropical urban areas with year-round cooling demand. This paper presents a multi-objective design methodology for polygeneration systems in tropical climates, integrating distributed energy technologies such as medium-scale gas turbines, solar photovoltaic, chillers, and energy storage. The proposed methodology adopts optimization approach to determine the optimal configuration and capacities of distributed energy systems to achieve various business goals, such as economic and sustainability objectives. The multi-objective design methodology employs a three-level optimization approach: simulation using the Transient System Simulation Tool, Pareto-based search conducted in Matrix Laboratory software, and an interface connecting the simulation tool with the optimization platform. This process generates a Pareto front of design solutions, balancing economic and environmental objectives. The proposed design methodology was applied to a case study of a polygeneration system at the Nanyang Technological University campus in Singapore, optimized across four superstructure configurations. Results show significant reductions in energy costs and CO2 emissions compared to the baseline, with a comparative analysis of various scenarios. The findings provide a comprehensive view of design options, allowing energy experts to balance economic and sustainability objectives for optimal system performance.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"328 ","pages":"Article 136550"},"PeriodicalIF":9.0000,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0360544225021929","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
Abstract
Small- and medium-scale polygeneration systems provide multiple energy services to urban districts, including business parks, universities, and hospitals, offering significant energy, economic, and environmental benefits. These systems enhance energy efficiency, reduce cost, and lower emissions, especially in tropical urban areas with year-round cooling demand. This paper presents a multi-objective design methodology for polygeneration systems in tropical climates, integrating distributed energy technologies such as medium-scale gas turbines, solar photovoltaic, chillers, and energy storage. The proposed methodology adopts optimization approach to determine the optimal configuration and capacities of distributed energy systems to achieve various business goals, such as economic and sustainability objectives. The multi-objective design methodology employs a three-level optimization approach: simulation using the Transient System Simulation Tool, Pareto-based search conducted in Matrix Laboratory software, and an interface connecting the simulation tool with the optimization platform. This process generates a Pareto front of design solutions, balancing economic and environmental objectives. The proposed design methodology was applied to a case study of a polygeneration system at the Nanyang Technological University campus in Singapore, optimized across four superstructure configurations. Results show significant reductions in energy costs and CO2 emissions compared to the baseline, with a comparative analysis of various scenarios. The findings provide a comprehensive view of design options, allowing energy experts to balance economic and sustainability objectives for optimal system performance.
期刊介绍:
Energy is a multidisciplinary, international journal that publishes research and analysis in the field of energy engineering. Our aim is to become a leading peer-reviewed platform and a trusted source of information for energy-related topics.
The journal covers a range of areas including mechanical engineering, thermal sciences, and energy analysis. We are particularly interested in research on energy modelling, prediction, integrated energy systems, planning, and management.
Additionally, we welcome papers on energy conservation, efficiency, biomass and bioenergy, renewable energy, electricity supply and demand, energy storage, buildings, and economic and policy issues. These topics should align with our broader multidisciplinary focus.