{"title":"基于粒子群优化的太阳能经济调度","authors":"W. A. Augusteen, S. Geetha, R. Rengaraj","doi":"10.1109/ICEES.2016.7510618","DOIUrl":null,"url":null,"abstract":"In this proposed paper presents an innovative method to solve the economic dispatch problem with the solar energy system using particle swarm optimization technique (PSO). The solar radiations are considered on an hourly basis while we are considering for a day in PSO technique. The solar radiation depends on the standard environmental conditions and the total power output from the PV generator is taken as constant. In this system the battery is not connected and hence the total charge and discharge from the battery is set as zero. The particle movement in the PSO technique is directed by three activities, they are inertial, cognitive, and societal. The proposed method consists of the nonlinear uniqueness of a generator for instance like ramp limit, power balance constraints with their maximum and minimum operating limits and prohibited operating zones for the perceptible power system operation. For this proposed objective the PSO algorithm is an effective method to solve the ED problem and it is the implemented to solve most of the difficult optimization problems in the power system. In this proposed method consists of ten generating units and the solar radiation from the PV solar panel have been considered. The numerical result shows that the proposed method has a higher quality solution with reasonable computational time (speed) when compared with other past algorithm.","PeriodicalId":308604,"journal":{"name":"2016 3rd International Conference on Electrical Energy Systems (ICEES)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Economic dispatch incorporation solar energy using particle swarm optimization\",\"authors\":\"W. A. Augusteen, S. Geetha, R. Rengaraj\",\"doi\":\"10.1109/ICEES.2016.7510618\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this proposed paper presents an innovative method to solve the economic dispatch problem with the solar energy system using particle swarm optimization technique (PSO). The solar radiations are considered on an hourly basis while we are considering for a day in PSO technique. The solar radiation depends on the standard environmental conditions and the total power output from the PV generator is taken as constant. In this system the battery is not connected and hence the total charge and discharge from the battery is set as zero. The particle movement in the PSO technique is directed by three activities, they are inertial, cognitive, and societal. The proposed method consists of the nonlinear uniqueness of a generator for instance like ramp limit, power balance constraints with their maximum and minimum operating limits and prohibited operating zones for the perceptible power system operation. For this proposed objective the PSO algorithm is an effective method to solve the ED problem and it is the implemented to solve most of the difficult optimization problems in the power system. In this proposed method consists of ten generating units and the solar radiation from the PV solar panel have been considered. The numerical result shows that the proposed method has a higher quality solution with reasonable computational time (speed) when compared with other past algorithm.\",\"PeriodicalId\":308604,\"journal\":{\"name\":\"2016 3rd International Conference on Electrical Energy Systems (ICEES)\",\"volume\":\"87 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-03-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 3rd International Conference on Electrical Energy Systems (ICEES)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEES.2016.7510618\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 3rd International Conference on Electrical Energy Systems (ICEES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEES.2016.7510618","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Economic dispatch incorporation solar energy using particle swarm optimization
In this proposed paper presents an innovative method to solve the economic dispatch problem with the solar energy system using particle swarm optimization technique (PSO). The solar radiations are considered on an hourly basis while we are considering for a day in PSO technique. The solar radiation depends on the standard environmental conditions and the total power output from the PV generator is taken as constant. In this system the battery is not connected and hence the total charge and discharge from the battery is set as zero. The particle movement in the PSO technique is directed by three activities, they are inertial, cognitive, and societal. The proposed method consists of the nonlinear uniqueness of a generator for instance like ramp limit, power balance constraints with their maximum and minimum operating limits and prohibited operating zones for the perceptible power system operation. For this proposed objective the PSO algorithm is an effective method to solve the ED problem and it is the implemented to solve most of the difficult optimization problems in the power system. In this proposed method consists of ten generating units and the solar radiation from the PV solar panel have been considered. The numerical result shows that the proposed method has a higher quality solution with reasonable computational time (speed) when compared with other past algorithm.