Affiliation:
1. Department of Electrical and Computer Engineering, Faculty of Engineering, Thammasat University, Klong Luang, Pathum Thani 12120, Thailand
Abstract
Conventional generation maintenance scheduling (GMS) is a solution to increase the reliability of power systems and minimize the operation and maintenance costs paid by generation companies (GenCos). Nonetheless, environmental aspects, such as zero carbon emissions, have attracted global attention, leading to emission costs being paid by electricity generators. Therefore, to obtain GMS plans that consider these factors, this paper proposes multi-objective GMS models to minimize operation, maintenance, and emission costs by using lexicographic optimization as a mathematical tool. A demand response program (DRP) is also adapted to decrease emission generation and operational expenditures. The probability that no generation unit (GU) fails unexpectedly and the average net reserve value, comprising the system reliability with and without considering the GU failure rate, are demonstrated. Numerical examples are implemented for the IEEE 24-bus reliability test system. A GMS algorithm presented in a published work is run and compared to verify the robustness of the proposed GMS models. Our results indicate that this paper provides comprehensive approaches to the multi-objective GMS problem focusing on operation, maintenance, carbon, and DRP costs in consideration of technical and environmental aspects. The use of lexicographic optimization allows for the systematic and hierarchical consideration of these objectives, leading to significant benefits for GenCos.
Funder
Faculty of Engineering at Thammasat University
Subject
Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction
Reference44 articles.
1. The present status of maintenance strategies and the impact of maintenance on reliability;Endrenyi;IEEE Trans. Power Syst.,2001
2. Probabilistic evaluation of the effect of maintenance on reliability—An application;Endrenyi;IEEE Trans. Power Syst.,1998
3. Resources for the Future (2022, August 15). Carbon Pricing 201: Pricing Carbon in the Electricity Sector. Available online: https://www.rff.org/publications/explainers/carbon-pricing-201-pricing-carbon-electricity-sector/.
4. International Energy Agency (2022, August 15). The Potential Role of Carbon Pricing in Thailand’s Power Sector. Thailand, 2021. Available online: https://www.iea.org/reports/the-potential-role-of-carbon-pricing-in-thailands-power-sector.
5. Parry, I. (2022, August 15). Putting a Price on Pollution. Available online: https://www.imf.org/Publications/fandd/issues/2019/12/the-case-for-carbon-taxation-and-putting-a-price-on-pollution-parry.