A Comprehensive Optimization Framework for Techno-Economic Demand Side Management in Integrated Energy Systems
Year: 2025
Type: article
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.
Source: Energies
DOI: 10.3390/en18164280
Authors: Moataz Ayman Shaker, Ibrahim Mohamed Diaaeldin, Mahmoud A. Attia, Amr Khaled Khamees, Othman A. M. Omar, Mohammed Alruwaili, Ali Elrashidi, Nabil M. Hamed
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,137
Funder: Northern Border University
OpenAlex ID: W4413129530