Rule Induction-Based Knowledge Discovery for Energy Efficiency

Qipeng Chen, Zhong Fan, Dritan Kaleshi, Simon M D Armour

Research output: Contribution to journalArticle (Academic Journal)peer-review

7 Citations (Scopus)
357 Downloads (Pure)

Abstract

Rule induction is a practical approach to knowledge discovery. Provided that a problem is developed, rule induction is able to return the knowledge that addresses the goal of this problem as if-then rules. The primary goals of knowledge discovery are for prediction and description. The rule format knowledge representation is easily understandable so as to enable users to make decisions. This paper presents the potential of rule induction for energy efficiency. In particular, three rule induction techniques are applied to derive knowledge from a dataset of thousands of Irish electricity customers' time-series power consumption records, socio-demographic details, and other information, in order to address the following four problems: 1) discovering mathematically interesting knowledge that could be found useful; 2) estimating power consumption features for customers, so that personalized tariffs can be assigned; 3) targeting a subgroup of customers with high potential for peak demand shifting; and 4) identifying customer attitudes that dominate energy conservation.
Original languageEnglish
Pages (from-to)1423-1436
Number of pages14
JournalIEEE Access
Volume3
Early online date24 Aug 2015
DOIs
Publication statusPublished - 1 Sep 2015

Keywords

  • Energy efficiency
  • knowledge discovery
  • smart grids
  • subgroup discovery

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