Distributed load demand scheduling in smart grid to minimize electricity generation cost

Siyu Yue, Di Zhu, Yanzhi Wang, Massoud Pedram

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Load demand scheduling of electricity consumers is an effective way to alleviate the peak power demand on the electricity grid and to combat the mismatch between generation and consumption. In this paper, we consider a scenario where multiple users cooperate to perform load demand scheduling in order to minimize the electricity generation cost. With the help of a central controller in the grid, a globally optimal solution can be achieved. However, this centralized solution may not always be feasible since it requires a huge amount of communication and the grid may not be equipped with such a central controller at all. Therefore, we propose a distributed load demand scheduling algorithm where each end user schedules its own tasks based on the partial information provided by other users. Simulation results show that this distributed load demand scheduling is able to achieve near-optimal solutions that has very little performance degradation compared to the centralized method.

Original languageEnglish (US)
Title of host publication2014 IEEE PES General Meeting / Conference and Exposition
PublisherIEEE Computer Society
EditionOctober
ISBN (Electronic)9781479964154
DOIs
StatePublished - Oct 29 2014
Externally publishedYes
Event2014 IEEE Power and Energy Society General Meeting - National Harbor, United States
Duration: Jul 27 2014Jul 31 2014

Publication series

NameIEEE Power and Energy Society General Meeting
NumberOctober
Volume2014-October
ISSN (Print)1944-9925
ISSN (Electronic)1944-9933

Other

Other2014 IEEE Power and Energy Society General Meeting
Country/TerritoryUnited States
CityNational Harbor
Period7/27/147/31/14

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Nuclear Energy and Engineering
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering

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