An energy-aware scheduling model under demand charge and time-based rate

Sajad Karimi, Soongeol Kwon

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

Abstract

In recent years, there has been a rising interest in improving energy efficiency and saving energy cost in the production scheduling because of the environmental concerns and energy cost. In this paper, we propose a mathematical optimization model that is designed to achieve energy-aware production scheduling for the general type of manufacturing setting where multiple jobs need to be processed on multiple machines. Considering energy charge based on time-based electricity price and demand charge based on peak power demand that are common practice of utility company to charge electricity bills for commercial and industrial consumers, the proposed optimization model can be formulated to minimize electricity bill. The key idea of the proposed model is to adjust production schedule in terms of the assignment and the deployment of each job in response to time-based electricity price while reducing peak power demand. Specifically, the proposed optimization model can be formulated to determine production schedule to adjust overall electricity power consumption while being aware of the power consumption pattern of each job, which can be extracted and formalized in an stage-wise fashion based on the nature of process. In particular, the proposed model can be formulated as a mixed integer linear program that can be solved by general purpose optimization package. To validate the proposed model, numerical experiments are conducted, and the results show that production schedule can be properly adjusted to reduce energy cost.

Original languageEnglish
Title of host publicationProceedings of the 2020 IISE Annual Conference
EditorsL. Cromarty, R. Shirwaiker, P. Wang
PublisherInstitute of Industrial and Systems Engineers, IISE
Pages1395-1400
Number of pages6
ISBN (Electronic)9781713827818
Publication statusPublished - 2020
Event2020 Institute of Industrial and Systems Engineers Annual Conference and Expo, IISE 2020 - Virtual, Online, United States
Duration: 2020 Nov 12020 Nov 3

Publication series

NameProceedings of the 2020 IISE Annual Conference

Conference

Conference2020 Institute of Industrial and Systems Engineers Annual Conference and Expo, IISE 2020
Country/TerritoryUnited States
CityVirtual, Online
Period20/11/120/11/3

Bibliographical note

Publisher Copyright:
© Proceedings of the 2020 IISE Annual. All Rights Reserved.

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

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