Unit Commitment for Power Generation Systems Based on Prices in Smart Grid Environment Considering Uncertainty

Hassan Shokouhandeh, Mehrdad Ahmadi Kamarposhti, Ilhami Colak and Kei Eguchi
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Hassan Shokouhandeh: Department of Electrical Engineering, Semnan University, Semnan, Iran
Mehrdad Ahmadi Kamarposhti: Department of Electrical Engineering, Jouybar Branch, Islamic Azad University, Jouybar, Iran
Ilhami Colak: Department of Electrical and Electronics Engineering, Faculty of Engineering and Architectures, Nisantasi University, Istanbul, Turkey
Kei Eguchi: Department of Information Electronics, Fukuoka Institute of Technology, Fukuoka, Japan

Sustainability, 2021, vol. 13, issue 18, 1-13

Abstract: With the growing demand for electricity, the inability of governments to provide the necessary resources to invest in the electricity industry and the rising price of fossil fuels, the tendency is to study and pay attention to economic issues in power systems studies. In this paper a new modified version of gray wolf optimization (MGWO) is proposed to solve the unit commitment (UC) problem in a power system in case of uncertainty. Market price variation is the main source of uncertainty in the UC program. Therefore, a model based on normal probability density function (PDF) is present for reducing the market price uncertainty effect in the model. Simulations are done for a standard 10 thermal units power system, and the results of the optimization by the proposed MGWO are compared with the previous version of the GWO algorithm and particle swarm optimization (PSO) algorithm results. The simulation results confirm the superiority of the proposed MGWO algorithm over the two algorithms PSO and GWO.

Keywords: unit commitment planning; uncertainty; smart grid; power generation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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