Open Access

ARTICLE

Optimal Operation of Distributed Generations Considering Demand Response in a Microgrid Using GWO Algorithm

Hassan Shokouhandeh¹, Mehrdad Ahmadi Kamarposhti^2,*, William Holderbaum³, Ilhami Colak⁴, Phatiphat Thounthong⁵

1 Department of Electrical Engineering, Semnan University, Semnan, Iran
2 Department of Electrical Engineering, Jouybar Branch, Islamic Azad University, Jouybar, Iran
3 School of Science, Engineering and Environment, University of Salford, Salford, UK
4 Department of Electrical and Electronics Engineering, Faculty of Engineering and Architectures, Nisantasi University, Istanbul, Turkey
5 Renewable Energy Research Centre (RERC), Department of Teacher Training in Electrical Engineering, Faculty of Technical Education, King Mongkut’s University of Technology North Bangkok, 1518, Pracharat 1 Road, Bangsue, Bangkok, 10800, Thailand

* Corresponding Author: Mehrdad Ahmadi Kamarposhti. Email:

(This article belongs to the Special Issue: Metaheuristics Optimization for Real-World Applications)

Computer Systems Science and Engineering 2023, 47(1), 809-822. https://doi.org/10.32604/csse.2023.035827

Received 06 September 2022; Accepted 14 December 2022; Issue published 26 May 2023

Abstract

The widespread penetration of distributed energy sources and the use of load response programs, especially in a microgrid, have caused many power system issues, such as control and operation of these networks, to be affected. The control and operation of many small-distributed generation units with different performance characteristics create another challenge for the safe and efficient operation of the microgrid. In this paper, the optimum operation of distributed generation resources and heat and power storage in a microgrid, was performed based on real-time pricing through the proposed gray wolf optimization (GWO) algorithm to reduce the energy supply cost with the microgrid. Distributed generation resources such as solar panels, diesel generators with battery storage, and boiler thermal resources with thermal storage were used in the studied microgrid. Also, a combined heat and power (CHP) unit was used to produce thermal and electrical energy simultaneously. In the simulations, in addition to the gray wolf algorithm, some optimization algorithms have also been used. Then the results of 20 runs for each algorithm confirmed the high accuracy of the proposed GWO algorithm. The results of the simulations indicated that the CHP energy resources must be managed to have a minimum cost of energy supply in the microgrid, considering the demand response program.

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Keywords

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