{"title":"混合可再生能源优化设计的野马优化(WHO)方法实现","authors":"Marliani, A. Arief, I. Gunadin","doi":"10.1109/ICCoSITE57641.2023.10127755","DOIUrl":null,"url":null,"abstract":"The use of renewable energy has been widely applied worldwide to reduce fossil energy use. A hybrid electric power system based on renewable energy is one of the solutions to produce maximum energy. In this paper, the hybrid systems discussed include photovoltaic (PV), wind turbine (WT), and battery storage (BS). This hybrid design system is very dependent on the load profile, potential energy sources, and geographical location of the research location. This research shows the technical design and capital cost of a hybrid electric power system that will be implemented as an alternative energy source for practical work on the Soroako Technical Academy or Akademi Teknik Soroako (ATS) vocational campus. Irradiance, temperature, average wind speed, and component sizing are the main parameters for the design. The technical analysis and capital cost design use MATLAB software with the wild horse optimization (WHO) algorithm. The results of the WHO analysis will be compared with the HOMER application. The results showed that the WHO algorithm method is better than the HOMER application, with a capital cost of $ 198,363.05 with a total of 772 PV units, 1 unit of WT, and 54 battery units.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Implementation of wild horse optimization (WHO) method for optimal hybrid renewable energy designs\",\"authors\":\"Marliani, A. Arief, I. Gunadin\",\"doi\":\"10.1109/ICCoSITE57641.2023.10127755\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The use of renewable energy has been widely applied worldwide to reduce fossil energy use. A hybrid electric power system based on renewable energy is one of the solutions to produce maximum energy. In this paper, the hybrid systems discussed include photovoltaic (PV), wind turbine (WT), and battery storage (BS). This hybrid design system is very dependent on the load profile, potential energy sources, and geographical location of the research location. This research shows the technical design and capital cost of a hybrid electric power system that will be implemented as an alternative energy source for practical work on the Soroako Technical Academy or Akademi Teknik Soroako (ATS) vocational campus. Irradiance, temperature, average wind speed, and component sizing are the main parameters for the design. The technical analysis and capital cost design use MATLAB software with the wild horse optimization (WHO) algorithm. The results of the WHO analysis will be compared with the HOMER application. The results showed that the WHO algorithm method is better than the HOMER application, with a capital cost of $ 198,363.05 with a total of 772 PV units, 1 unit of WT, and 54 battery units.\",\"PeriodicalId\":256184,\"journal\":{\"name\":\"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)\",\"volume\":\"99 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCoSITE57641.2023.10127755\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCoSITE57641.2023.10127755","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
可再生能源的使用已在世界范围内广泛应用,以减少化石能源的使用。以可再生能源为基础的混合电力系统是产生最大能量的解决方案之一。本文讨论的混合系统包括光伏(PV)、风力发电(WT)和电池储能(BS)。这种混合设计系统非常依赖于负载分布、潜在能源和研究地点的地理位置。这项研究显示了混合电力系统的技术设计和资金成本,该系统将作为Soroako技术学院或Akademi Teknik Soroako (ATS)职业校园实际工作的替代能源。辐照度、温度、平均风速和组件尺寸是设计的主要参数。技术分析和资金成本设计采用MATLAB软件,采用野马优化(WHO)算法。世卫组织的分析结果将与HOMER的应用进行比较。结果表明,WHO算法方法优于HOMER应用,资金成本为198,363.05美元,共计772台光伏机组,1台WT, 54台电池。
Implementation of wild horse optimization (WHO) method for optimal hybrid renewable energy designs
The use of renewable energy has been widely applied worldwide to reduce fossil energy use. A hybrid electric power system based on renewable energy is one of the solutions to produce maximum energy. In this paper, the hybrid systems discussed include photovoltaic (PV), wind turbine (WT), and battery storage (BS). This hybrid design system is very dependent on the load profile, potential energy sources, and geographical location of the research location. This research shows the technical design and capital cost of a hybrid electric power system that will be implemented as an alternative energy source for practical work on the Soroako Technical Academy or Akademi Teknik Soroako (ATS) vocational campus. Irradiance, temperature, average wind speed, and component sizing are the main parameters for the design. The technical analysis and capital cost design use MATLAB software with the wild horse optimization (WHO) algorithm. The results of the WHO analysis will be compared with the HOMER application. The results showed that the WHO algorithm method is better than the HOMER application, with a capital cost of $ 198,363.05 with a total of 772 PV units, 1 unit of WT, and 54 battery units.