{"title":"基于需求传播方法的空间负荷预测","authors":"J. Melo, E. Carreno, A. Padilha-Feltrin","doi":"10.1109/TDC-LA.2010.5762882","DOIUrl":null,"url":null,"abstract":"A method for spatial electric load forecasting using multi-agent systems, especially suited to simulate the local effect of special loads in distribution systems is presented. The method based on multi-agent systems uses two kinds of agents: reactive and proactive. The reactive agents represent each sub-zone in the service zone, characterizing each one with their corresponding load level, represented in a real number, and their relationships with other sub-zones represented in development probabilities. The proactive agent carry the new load expected to be allocated because of the new special load, this agent distribute the new load in a propagation pattern. The results are presented with maps of future expected load levels in the service zone. The method is tested with data from a mid-size city real distribution system, simulating the effect of a load with attraction and repulsion attributes. The method presents good results and performance.","PeriodicalId":222318,"journal":{"name":"2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America (T&D-LA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Spatial load forecasting using a demand propagation approach\",\"authors\":\"J. Melo, E. Carreno, A. Padilha-Feltrin\",\"doi\":\"10.1109/TDC-LA.2010.5762882\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A method for spatial electric load forecasting using multi-agent systems, especially suited to simulate the local effect of special loads in distribution systems is presented. The method based on multi-agent systems uses two kinds of agents: reactive and proactive. The reactive agents represent each sub-zone in the service zone, characterizing each one with their corresponding load level, represented in a real number, and their relationships with other sub-zones represented in development probabilities. The proactive agent carry the new load expected to be allocated because of the new special load, this agent distribute the new load in a propagation pattern. The results are presented with maps of future expected load levels in the service zone. The method is tested with data from a mid-size city real distribution system, simulating the effect of a load with attraction and repulsion attributes. The method presents good results and performance.\",\"PeriodicalId\":222318,\"journal\":{\"name\":\"2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America (T&D-LA)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America (T&D-LA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TDC-LA.2010.5762882\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America (T&D-LA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TDC-LA.2010.5762882","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Spatial load forecasting using a demand propagation approach
A method for spatial electric load forecasting using multi-agent systems, especially suited to simulate the local effect of special loads in distribution systems is presented. The method based on multi-agent systems uses two kinds of agents: reactive and proactive. The reactive agents represent each sub-zone in the service zone, characterizing each one with their corresponding load level, represented in a real number, and their relationships with other sub-zones represented in development probabilities. The proactive agent carry the new load expected to be allocated because of the new special load, this agent distribute the new load in a propagation pattern. The results are presented with maps of future expected load levels in the service zone. The method is tested with data from a mid-size city real distribution system, simulating the effect of a load with attraction and repulsion attributes. The method presents good results and performance.