{"title":"基于随机 MPC 的能源管理系统,用于集成住宅区的太阳能光伏发电、电池储能和电动汽车充电功能","authors":"M.I. Saleem, S. Saha, U. Izhar, L. Ang","doi":"10.1016/j.enbuild.2024.114993","DOIUrl":null,"url":null,"abstract":"<div><div>This paper presents a Stochastic Model Predictive Control (SMPC)-based energy management system (EMS) for residential complexes with integrated solar photovoltaics (PV), battery energy storage systems (BESS), and electric vehicle (EV) charging infrastructure. The EMS coordinates BESS operations, integrating solar generation, residential load demand, and EV charging. It optimizes BESS charging/discharging based on solar power, load demands, electricity pricing, and feed-in tariffs over a finite horizon, while considering uncertainties through multiple scenarios of load and EV charging demand, as well as solar generation. By accounting for battery degradation, cost savings, and revenue from energy transactions, the proposed EMS enhances BESS longevity and profitability. The EMS also manages reactive power provision from the BESS inverter, ensuring voltage stability in the presence of uncertainties. Extensive case studies on Matlab Simscape Electrical and real-time validation on the OPAL-RT simulator demonstrate the effectiveness of the proposed SMPC-based EMS in optimizing energy use, operational efficiency, and economic returns, contributing significantly to the sustainable energy management of the residential complex.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"325 ","pages":"Article 114993"},"PeriodicalIF":6.6000,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A stochastic MPC-based energy management system for integrating solar PV, battery storage, and EV charging in residential complexes\",\"authors\":\"M.I. Saleem, S. Saha, U. Izhar, L. Ang\",\"doi\":\"10.1016/j.enbuild.2024.114993\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This paper presents a Stochastic Model Predictive Control (SMPC)-based energy management system (EMS) for residential complexes with integrated solar photovoltaics (PV), battery energy storage systems (BESS), and electric vehicle (EV) charging infrastructure. The EMS coordinates BESS operations, integrating solar generation, residential load demand, and EV charging. It optimizes BESS charging/discharging based on solar power, load demands, electricity pricing, and feed-in tariffs over a finite horizon, while considering uncertainties through multiple scenarios of load and EV charging demand, as well as solar generation. By accounting for battery degradation, cost savings, and revenue from energy transactions, the proposed EMS enhances BESS longevity and profitability. The EMS also manages reactive power provision from the BESS inverter, ensuring voltage stability in the presence of uncertainties. Extensive case studies on Matlab Simscape Electrical and real-time validation on the OPAL-RT simulator demonstrate the effectiveness of the proposed SMPC-based EMS in optimizing energy use, operational efficiency, and economic returns, contributing significantly to the sustainable energy management of the residential complex.</div></div>\",\"PeriodicalId\":11641,\"journal\":{\"name\":\"Energy and Buildings\",\"volume\":\"325 \",\"pages\":\"Article 114993\"},\"PeriodicalIF\":6.6000,\"publicationDate\":\"2024-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy and Buildings\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0378778824011095\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CONSTRUCTION & BUILDING TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy and Buildings","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0378778824011095","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
A stochastic MPC-based energy management system for integrating solar PV, battery storage, and EV charging in residential complexes
This paper presents a Stochastic Model Predictive Control (SMPC)-based energy management system (EMS) for residential complexes with integrated solar photovoltaics (PV), battery energy storage systems (BESS), and electric vehicle (EV) charging infrastructure. The EMS coordinates BESS operations, integrating solar generation, residential load demand, and EV charging. It optimizes BESS charging/discharging based on solar power, load demands, electricity pricing, and feed-in tariffs over a finite horizon, while considering uncertainties through multiple scenarios of load and EV charging demand, as well as solar generation. By accounting for battery degradation, cost savings, and revenue from energy transactions, the proposed EMS enhances BESS longevity and profitability. The EMS also manages reactive power provision from the BESS inverter, ensuring voltage stability in the presence of uncertainties. Extensive case studies on Matlab Simscape Electrical and real-time validation on the OPAL-RT simulator demonstrate the effectiveness of the proposed SMPC-based EMS in optimizing energy use, operational efficiency, and economic returns, contributing significantly to the sustainable energy management of the residential complex.
期刊介绍:
An international journal devoted to investigations of energy use and efficiency in buildings
Energy and Buildings is an international journal publishing articles with explicit links to energy use in buildings. The aim is to present new research results, and new proven practice aimed at reducing the energy needs of a building and improving indoor environment quality.