Multi-objective preemptive optimization of residential load scheduling problem under price and CO2 signals

Zakaria Yahia, Anup Pradhan

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

Abstract

This paper addresses the residential load scheduling problem with the objective of investigating the influence of price and CO2 signals in (i) the electricity bill, (ii) the consumer inconvenience, (iii) the electric peak load, and (iv) the CO2 emissions. These objectives were considered widely in the literature; however, they were not considered simultaneously in one model before. Furthermore, CO2 emissions targets constraint was not considered in the previous literature. This paper contributes by twofold. First, the CO2 signal is drawn up based on the proposed generation-mix plan in South Africa and an hourly CO2 emissions limit is guaranteed. Second, a multi-objective mixed integer programming model is proposed, and a preemptive multi-objective optimization approach is applied. The model is tested with and without considering the hourly CO2 emissions limit. Furthermore, the model is solved at four scenarios to explore the effect of the price and CO2 signals and the order of optimization. Results showed that the price and CO2 signals and the order of optimization have remarkable effect on the appliance schedule and on the four objectives.

Original languageEnglish
Pages (from-to)1926-1937
Number of pages12
JournalProceedings of the International Conference on Industrial Engineering and Operations Management
Volume2019
Issue numberMAR
Publication statusPublished - 2019
Event9th International Conference on Industrial Engineering and Operations Management, IEOM 2019 - Bangkok, Thailand
Duration: 5 Mar 20197 Mar 2019

Keywords

  • CO emissions
  • Electrical peak load reduction
  • Inconvenience
  • Multi-objective mixed integer programming
  • Residential load scheduling

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

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