Area-load based pricing in DSM through ANN and heuristic scheduling

N. Kunwar, K. Yash, R. Kumar

Research output: Contribution to journalArticlepeer-review

46 Citations (Scopus)

Abstract

To meet the fast growing demand of energy, in addition with increased generation, improved efficiency, stability and flexibility, smart techniques need to be adopted that are in compliance with the environment and energy conservation. In this paper, we present an autonomous demand-side energy management to encourage users to willingly modify their electricity consumption without compromising with service quality and customer satisfaction using load forecasting. The projected distributed demand side energy management (DSM) strategy gives each consumer an option to simply apply its best response strategy to current electric load and tariff in the power distribution system. Using NSGA II optimization technique on load prediction, it is obtained that an area-load based pricing method is beneficial for both electric utility and consumer. Finally, simulation results substantiate that the proposed approach can maximize load factor and reduce total energy cost as well as user's daily electricity charges.

Original languageEnglish
Article number6562791
Pages (from-to)1275-1281
Number of pages7
JournalIEEE Transactions on Smart Grid
Volume4
Issue number3
DOIs
Publication statusPublished - 2013
Externally publishedYes

Keywords

  • ANN
  • cost minimization
  • DSM
  • load factor
  • load scheduling
  • normal distribution
  • NSGA II
  • penalty
  • rebate
  • variable pricing

ASJC Scopus subject areas

  • General Computer Science

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