{"title":"A spatial modeling technique for small area load forecast","authors":"H.C. Wu, C. Lu","doi":"10.1109/PESS.2001.970236","DOIUrl":null,"url":null,"abstract":"In a deregulated environment, competition will lead to an increase of electrical energy usage. The increase in the demand could lead to substantial expansion planning implications for many transmission and distribution (T&D) systems. Locations of future load growth have to be described with sufficient geographic precision to permit valid siting of future T&D equipment. Spatial load forecast provides information of future electric demand that includes location, magnitude and temporal characteristics. In this paper, a \"knowledge discovery in database (KDD)\" technique is used to determine automatically the preferential \"scores\" of small areas with respect to the possibility of land use changes, and consequently the load growth. It is an exploratory data analysis, trying to discover useful patterns in spatial data that are not obvious to the data user and to support the load forecast.","PeriodicalId":273578,"journal":{"name":"2001 Power Engineering Society Summer Meeting. Conference Proceedings (Cat. No.01CH37262)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2001 Power Engineering Society Summer Meeting. Conference Proceedings (Cat. No.01CH37262)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PESS.2001.970236","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In a deregulated environment, competition will lead to an increase of electrical energy usage. The increase in the demand could lead to substantial expansion planning implications for many transmission and distribution (T&D) systems. Locations of future load growth have to be described with sufficient geographic precision to permit valid siting of future T&D equipment. Spatial load forecast provides information of future electric demand that includes location, magnitude and temporal characteristics. In this paper, a "knowledge discovery in database (KDD)" technique is used to determine automatically the preferential "scores" of small areas with respect to the possibility of land use changes, and consequently the load growth. It is an exploratory data analysis, trying to discover useful patterns in spatial data that are not obvious to the data user and to support the load forecast.
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