Yifu Ding, Avinash Vijay, D. Neal, Daniel J. Rogers, M. Mcculloch
{"title":"Model Predictive Control for Grid-ready Microgrids in developing countries","authors":"Yifu Ding, Avinash Vijay, D. Neal, Daniel J. Rogers, M. Mcculloch","doi":"10.1109/PowerAfrica49420.2020.9219857","DOIUrl":null,"url":null,"abstract":"In an under-resourced environment, the optimal energy management of the off-grid system under the stochastic generation and load is an open technology challenge. To design the least-cost system whilst meeting the reliability requirement, this work develops a predictive control framework based on a real-world microgrid pilot design11This work is supported in part by the Engineering and Physical Sciences Research Council under Grant EP/R030111/1 Robust Extra Low Cost Nano-grids (RELCON). Considering users' preferences and various weather conditions, it employs model predictive control (MPC) and demonstrates superior performance in reliability improvement compared with the day-ahead case. Given the reliability requirements ranging from 70% to 90%, the MPC can achieve the 5.23% improvement with the same system cost, and close to the performance under the perfect foresight.","PeriodicalId":325937,"journal":{"name":"2020 IEEE PES/IAS PowerAfrica","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE PES/IAS PowerAfrica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PowerAfrica49420.2020.9219857","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In an under-resourced environment, the optimal energy management of the off-grid system under the stochastic generation and load is an open technology challenge. To design the least-cost system whilst meeting the reliability requirement, this work develops a predictive control framework based on a real-world microgrid pilot design11This work is supported in part by the Engineering and Physical Sciences Research Council under Grant EP/R030111/1 Robust Extra Low Cost Nano-grids (RELCON). Considering users' preferences and various weather conditions, it employs model predictive control (MPC) and demonstrates superior performance in reliability improvement compared with the day-ahead case. Given the reliability requirements ranging from 70% to 90%, the MPC can achieve the 5.23% improvement with the same system cost, and close to the performance under the perfect foresight.