{"title":"Profit-based optimal generation scheduling of a microgrid","authors":"N. Razali, A. Hashim","doi":"10.1109/PEOCO.2010.5559244","DOIUrl":null,"url":null,"abstract":"The paper proposes a formulation for profit-based optimal generation scheduling by a microgrid (µgrid). Current methods normally assume either islanded operation, or utility-grid connected µgrid but lacking in market participation elements. The paper addresses this gap whereby the formulated objective function allows for autonomous decision-making to determine the hour by hour optimal dispatch of generators subject to system constraints including market parameters. The distributed generations in the modelled µgrid consist of wind turbines, microturbines and photovoltaic arrays while the system inputs are based on tropical conditions. A case study on the difference between grid-connected and islanded operation is presented. The results demonstrate the efficiency of using genetic algorithm to solve the optimization problem.","PeriodicalId":379868,"journal":{"name":"2010 4th International Power Engineering and Optimization Conference (PEOCO)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 4th International Power Engineering and Optimization Conference (PEOCO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PEOCO.2010.5559244","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
The paper proposes a formulation for profit-based optimal generation scheduling by a microgrid (µgrid). Current methods normally assume either islanded operation, or utility-grid connected µgrid but lacking in market participation elements. The paper addresses this gap whereby the formulated objective function allows for autonomous decision-making to determine the hour by hour optimal dispatch of generators subject to system constraints including market parameters. The distributed generations in the modelled µgrid consist of wind turbines, microturbines and photovoltaic arrays while the system inputs are based on tropical conditions. A case study on the difference between grid-connected and islanded operation is presented. The results demonstrate the efficiency of using genetic algorithm to solve the optimization problem.