{"title":"Optimising the Design of a Hybrid Power Supply Using a Genetic Algorithm","authors":"F. Daniel, A. Rix","doi":"10.1109/ROBOMECH.2019.8704763","DOIUrl":null,"url":null,"abstract":"This paper proposes the optimisation of a hybrid power supply (HPS) design by implementing a Genetic Algorithm (GA). Single-source renewable energy systems (RES) are associated with low capacity factor, high capital costs and intermittency. Combining two or more power sources, whether renewable or non-renewable, increases the system’s reliability in terms of power consistency, reduces fuel emissions and is a more sustainable and financial viable solution overall. A grid-connection and a battery storage system can further increase the dispatchability of the system. The design of each HPS can become more complex due to the location and stochastic availability of renewable energy sources. A GA is developed to solve this sizing problem. The objectives of the algorithm are: minimizing the loss of power supply probability, maximizing usage of renewable energy and minimizing capital and life cycle costs. A GA is developed to incorporate operational and dispatch strategies and a techno-economic and trade-off analysis is done to study the advantages and disadvantages of different combinations. This can help develop a methodology to choose the most suited HPS for the location and resource availability. The in-house GA will be compared with HOMER design software to highlight the similarities and differences between the two design strategies.","PeriodicalId":344332,"journal":{"name":"2019 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa (SAUPEC/RobMech/PRASA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa (SAUPEC/RobMech/PRASA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROBOMECH.2019.8704763","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper proposes the optimisation of a hybrid power supply (HPS) design by implementing a Genetic Algorithm (GA). Single-source renewable energy systems (RES) are associated with low capacity factor, high capital costs and intermittency. Combining two or more power sources, whether renewable or non-renewable, increases the system’s reliability in terms of power consistency, reduces fuel emissions and is a more sustainable and financial viable solution overall. A grid-connection and a battery storage system can further increase the dispatchability of the system. The design of each HPS can become more complex due to the location and stochastic availability of renewable energy sources. A GA is developed to solve this sizing problem. The objectives of the algorithm are: minimizing the loss of power supply probability, maximizing usage of renewable energy and minimizing capital and life cycle costs. A GA is developed to incorporate operational and dispatch strategies and a techno-economic and trade-off analysis is done to study the advantages and disadvantages of different combinations. This can help develop a methodology to choose the most suited HPS for the location and resource availability. The in-house GA will be compared with HOMER design software to highlight the similarities and differences between the two design strategies.