{"title":"Optimal power scheduling of an off-grid renewable hybrid system used for heating and lighting in a typical residential house","authors":"N. Tutkun, E. San","doi":"10.1109/EEEIC-2.2013.6737935","DOIUrl":null,"url":null,"abstract":"In Turkey, there is a significant increase in demand for electricity due to population and economic growth taken place in recent years. This is a major economic factor affecting electricity price on market as well as other factors such as an increase in oil and natural gas prices. To be more specific around 50% of electricity is generated by natural gas generators and 95% of natural gas is imported from other countries. However, Turkey has considerable amount of wind and solar energy potentials to generate electricity through wind turbines and photo-voltaic arrays either on-grid or off-grid. An off-grid hybrid system is more attractive in rural areas where access to grid is limited or unavailable. This study focuses on a power scheduling in a simple renewable hybrid system in order to minimize the operational unit cost using the binary-coded genetic algorithm instead of using mixed integer linear programming. The preliminary results indicated that the binary-coded genetic algorithm produced encouraging and meaningful outcomes to minimize operational unit cost in a typical renewable microgrid photo-voltaic/wind hybrid system.","PeriodicalId":445295,"journal":{"name":"2013 13th International Conference on Environment and Electrical Engineering (EEEIC)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 13th International Conference on Environment and Electrical Engineering (EEEIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EEEIC-2.2013.6737935","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
In Turkey, there is a significant increase in demand for electricity due to population and economic growth taken place in recent years. This is a major economic factor affecting electricity price on market as well as other factors such as an increase in oil and natural gas prices. To be more specific around 50% of electricity is generated by natural gas generators and 95% of natural gas is imported from other countries. However, Turkey has considerable amount of wind and solar energy potentials to generate electricity through wind turbines and photo-voltaic arrays either on-grid or off-grid. An off-grid hybrid system is more attractive in rural areas where access to grid is limited or unavailable. This study focuses on a power scheduling in a simple renewable hybrid system in order to minimize the operational unit cost using the binary-coded genetic algorithm instead of using mixed integer linear programming. The preliminary results indicated that the binary-coded genetic algorithm produced encouraging and meaningful outcomes to minimize operational unit cost in a typical renewable microgrid photo-voltaic/wind hybrid system.