Two-dimensional colour pattern load analysis: A tool supporting demand-side management

Mitropoulos, S; Assimakopoulos, V; Charalabidis, Y

dc.contributor.author	Mitropoulos, S	en
dc.contributor.author	Assimakopoulos, V	en
dc.contributor.author	Charalabidis, Y	en
dc.date.accessioned	2014-03-01T01:11:34Z
dc.date.available	2014-03-01T01:11:34Z
dc.date.issued	1995	en
dc.identifier.issn	01679236	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/11707
dc.subject	Compute graphics	en
dc.subject	Decision support systems	en
dc.subject	Demand-side management	en
dc.subject	Load analysis	en
dc.subject	Pattern recognition	en
dc.subject.other	Computer graphics	en
dc.subject.other	Electric load management	en
dc.subject.other	Electric power utilization	en
dc.subject.other	Electric utilities	en
dc.subject.other	Energy policy	en
dc.subject.other	Pattern recognition	en
dc.subject.other	Two dimensional color pattern load analysis	en
dc.subject.other	Decision support systems	en
dc.title	Two-dimensional colour pattern load analysis: A tool supporting demand-side management	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/0167-9236(93)E0054-H	en
heal.identifier.secondary	http://dx.doi.org/10.1016/0167-9236(93)E0054-H	en
heal.publicationDate	1995	en
heal.abstract	Load analysis is one of the most important operations that support demand-side management in large electric utilities. Ordinary load analysis techniques stress on statistical processing of hourly load data along predefined time axes, producing numerical results of a standard granularity, such as daily or weekly mean loads. In order to overcome these limitations, a new approach or load analysis was developed, based on applying a two-dimensional formulation of the hourly load data. The tables holding energy consumption values, where columns represent the days of the selected period and lines represent the 24 hours of the day, are then illustrated through the use of colour patterns. In such a way, chronological typical units of variable structure and granularity can be identified and provide the basis for an extensive cross-examination, resulting in optimized decision making and energy policy definition. In order to demonstrate the advantages of the approach, a dedicated DSS implementation and application in the Greek public power corporation was also performed. © 1995.	en
heal.journalName	Decision Support Systems	en
dc.identifier.doi	10.1016/0167-9236(93)E0054-H	en
dc.identifier.volume	13	en
dc.identifier.issue	2	en
dc.identifier.spage	159	en
dc.identifier.epage	166	en