Residential Demand Response for Renewable Energy Resources in Smart Grid Systems

  • Laihyuk Park
  • , Yongwoon Jang
  • , Sungrae Cho*
  • , Joongheon Kim
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

With the current state of development in demand response (DR) programs in smart grid systems, there have been great demands for automated energy scheduling for residential customers. Recently, energy scheduling in smart grids have focused on the minimization of electricity bills, the reduction of the peak demand, and the maximization of user convenience. Thus, a user convenience model is proposed under the consideration of user waiting times, which is a nonconvex problem. Therefore, the nonconvex is reformulated as convex to guarantee optimal solutions. Moreover, mathematical formulations for DR optimization are derived based on the reformulated convex problem. In addition, two types of pricing policies for electricity bills are designed in the mathematical formulations, i.e., real-time pricing policy and progressive policy. With real-time pricing policy, convexity is guaranteed whereas progressive policy cannot. Then, heuristic algorithms are finally designed for obtaining approximated optimal solutions in progressive policy.

Original languageEnglish
Article number7927719
Pages (from-to)3165-3173
Number of pages9
JournalIEEE Transactions on Industrial Informatics
Volume13
Issue number6
DOIs
Publication statusPublished - 2017 Dec
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2005-2012 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Convex optimization
  • demand response
  • residential energy resources
  • smart grid

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Computer Science Applications
  • Electrical and Electronic Engineering

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