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Generator Maintenance Scheduling Models for Electrical Power Systems: A Review

Shatha Abdulhadi Muthana1 and Ku Ruhana Ku-Mahamud 2
1. General Company of South Electricity Distribution, Ministry of Electricity, Iraq
2. School of Computing, Universiti Utara Malaysia, Malaysia

Abstract—Interest in Generator Maintenance Scheduling (GMS) has increased due to the advent of demand-related expansion in size for modern power systems. Timely maintenance plays a significant role in minimizing failures and helps in averting cost incurred as a result of production shutdowns. The GMS problem is a complex and nonlinear optimization problem that specifies the schedule for carrying out planned preventive maintenance on power generation units. There is no clear concept to GMS model types and choosing the appropriate maintenance scheduling type. Thus, this paper presented a comprehensive review on GMS models in electrical power systems that covers the maintenance strategies, main elements of GMS models, and optimization methods used in solving GMS models. The list of references comprised related works from the years 2000 until 2020, which were classified into three based on the objectives. A new type of objective function for the GMS models was among the suggestions provided. A numerical example which focuses on a multi-objective GMS model and a proposed multi-objective Pareto ant colony system algorithm are also presented. The results of this review will not only enable researchers to gain a good overview of the existing GMS models for electrical power systems but also provide a source of references in choosing an appropriate maintenance scheduling strategy that is suitable with the type of generating unit and existing operating conditions.
 
Index Terms—Electrical power system, optimization, scheduling, generator, multi-objectives

Cite: Shatha Abdulhadi Muthana and Ku Ruhana Ku-Mahamud, "Generator Maintenance Scheduling Models for Electrical Power Systems: A Review," International Journal of Electrical and Electronic Engineering & Telecommunications, Vol. 10, No. 5, pp. 307-318, September 2021. Doi: 10.18178/ijeetc.10.5.307-318

Copyright © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.