A Comprehensive Optimization Framework for Techno-Economic Demand Side Management in Integrated Energy Systems

Moataz Ayman Shaker, Ibrahim Mohamed Diaaeldin (), Mahmoud A. Attia, Amr Khaled Khamees, Othman A. M. Omar, Mohammed Alruwaili, Ali Elrashidi () and Nabil M. Hamed
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Moataz Ayman Shaker: Engineering Physics and Mathematics Department, Ain Shams University, Cairo 11517, Egypt
Ibrahim Mohamed Diaaeldin: Engineering Physics and Mathematics Department, Ain Shams University, Cairo 11517, Egypt
Mahmoud A. Attia: Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt
Amr Khaled Khamees: Engineering Physics and Mathematics Department, Ain Shams University, Cairo 11517, Egypt
Othman A. M. Omar: Engineering Physics and Mathematics Department, Ain Shams University, Cairo 11517, Egypt
Mohammed Alruwaili: Department of Electrical Engineering, College of Engineering, Northern Border University, Arar 91431, Saudi Arabia
Ali Elrashidi: Electrical Engineering Department, University of Business and Technology, Jeddah 23435, Saudi Arabia
Nabil M. Hamed: Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt

Energies, 2025, vol. 18, issue 16, 1-31

Abstract: This paper proposes a comprehensive mathematical optimization framework for techno-economic demand side management (DSM) in hybrid energy systems (HESs), with a focus on standalone configurations. The framework incorporates load growth projections and the probabilistic uncertainties of renewable energy sources to enhance planning robustness. To identify high-quality near-optimal solutions, several advanced metaheuristic algorithms were employed, including the Exponential Distribution Optimizer (EDO), Teaching-Learning-Based Optimization (TLBO), Circle Search Algorithm (CSA), and Wild Horse Optimizer (WHO). The results highlight substantial economic and environmental improvements, with battery integration yielding a 69.7% reduction in total system cost and an 84.3% decrease in emissions. Additionally, this study evaluated the influence of future load growth on fuel expenditure, offering realistic insights into the techno-economic viability of HES deployment.

Keywords: demand side management; hybrid energy systems; cost of energy; renewable energy sources; loss of power supply probability (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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