Muhammad Alifudin Fahmi, I. Sudiharto, I. Ferdiansyah
{"title":"Particle Swarm Optimization Implementation as MPPT on Hybrid Power System","authors":"Muhammad Alifudin Fahmi, I. Sudiharto, I. Ferdiansyah","doi":"10.1109/IES50839.2020.9231774","DOIUrl":null,"url":null,"abstract":"The increasing need for electrical energy at the rate of an era, to meet the increase in the use of many alternative energy such as solar energy. The availability solar energy will never run out and solar energy can also be used as an alternative energy that can convert to electrical energy. Solar energy has a fluctuating nature where there is always a change in the amount of energy over time. By maximizing the utilization of solar panel energy can be achieved by the existence of methods such as MPPT (Maximum Power Point Tracking). Particle Swarm Optimization (PSO) is an algorithm that can be used as an MPPT, where PSO will learn every irradiation change that occurs and get maximum power which will then be used as a source for the battery charger. In this paper, using a hybrid power system that uses a source from PV and the grid 220Vac PLN. The sources obtained from the PLN grid will be used as a backup source. Using the Particle Swarm Optimization method as MPPT is able to get power of 198.85 Watt with efficiencies above 95% in the hybrid power system for battery chargers, and the presence of the PLN Grid as a backup source, when the PV system does not meet the load power requirements.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"353 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Electronics Symposium (IES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IES50839.2020.9231774","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
The increasing need for electrical energy at the rate of an era, to meet the increase in the use of many alternative energy such as solar energy. The availability solar energy will never run out and solar energy can also be used as an alternative energy that can convert to electrical energy. Solar energy has a fluctuating nature where there is always a change in the amount of energy over time. By maximizing the utilization of solar panel energy can be achieved by the existence of methods such as MPPT (Maximum Power Point Tracking). Particle Swarm Optimization (PSO) is an algorithm that can be used as an MPPT, where PSO will learn every irradiation change that occurs and get maximum power which will then be used as a source for the battery charger. In this paper, using a hybrid power system that uses a source from PV and the grid 220Vac PLN. The sources obtained from the PLN grid will be used as a backup source. Using the Particle Swarm Optimization method as MPPT is able to get power of 198.85 Watt with efficiencies above 95% in the hybrid power system for battery chargers, and the presence of the PLN Grid as a backup source, when the PV system does not meet the load power requirements.