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Optimal Management of Energy Storage Systems for Peak Shaving in a Smart Grid
1 Department of Mechanical Engineering, Al-Zaytoonah University of Jordan, Amman, 11733, Jordan
2 Department of Energy Engineering, Zarqa University, Zarqa, 13133, Jordan
3 Department of Electrical and Electronics Engineering, Faculty of Engineering and Architectures, Nisantasi University, Istanbul, 34398, Turkey
4 Department of Electrical Engineering, Jouybar Branch, Islamic Azad University, Jouybar, Iran
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:
Computers, Materials & Continua 2023, 75(2), 3317-3337. https://doi.org/10.32604/cmc.2023.035690
Received 31 August 2022; Accepted 14 January 2023; Issue published 31 March 2023
Abstract
In this paper, the installation of energy storage systems (EES) and their role in grid peak load shaving in two echelons, their distribution and generation are investigated. First, the optimal placement and capacity of the energy storage is taken into consideration, then, the charge-discharge strategy for this equipment is determined. Here, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to calculate the minimum and maximum load in the network with the presence of energy storage systems. The energy storage systems were utilized in a distribution system with the aid of a peak load shaving approach. Ultimately, the battery charge-discharge is managed at any time during the day, considering the load consumption at each hour. The results depict that the load curve reached a constant state by managing charge-discharge with no significant changes. This shows the significance of such matters in terms of economy and technicality.Keywords
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