Optimization algorithms for optimal sizing of smart grid considering demand-side management

Abstract

This chapter investigates the impact of demand-side management (DSM) on the optimization of hybrid renewable energy systems. DSM is presented as a strategic approach to optimize energy consumption by shifting demand in accordance with renewable energy generation patterns, thereby improving system efficiency and reducing reliance on fossil fuels. The methods of DSM are detailed, and the Salp swarm algorithm (SSA) is applied to determine the optimal configuration of the energy system, integrating renewable energy sources, energy storage, and conventional generators. A real case study in New Minia, Egypt, is used to demonstrate the practical application of DSM in a hybrid energy system. The results show that DSM leads to a reduction in the cost of energy and diesel generator (DG) operating costs while improving energy utilization efficiency by eliminating the dummy load ratio. Despite a slight increase in the loss of power supply probability (LPSP), DSM maintains system reliability and provides significant economic and environmental benefits. The increase in the LPSP is caused because the system has been optimally designed using the real load data before applying the DSM. The findings highlight DSM as a cost-effective and sustainable strategy for optimizing hybrid energy systems in regions with growing renewable energy penetration. The chapter also includes a number of useful MATLAB® codes that are essential for the implementation of the system, providing practical tools for simulating and optimizing the hybrid renewable energy system with DSM. These codes enable efficient modeling, analysis, and integration of various system components, facilitating the application of DSM strategies in real-world scenarios.