The energy sector in Egypt is undergoing a profound transformation, harnessing its abundant resources and employing advanced technologies to promote sustainability and achieve energy independence. This study introduces an energy management system that optimizes energy generation, storage, and utilization in residential settings. The proposed system integrates PV panels, wind turbines (WTs), and hybrid backup systems, including Battery Energy Storage Systems (BESS), Hydrogen Storage Systems (HSS), and Vehicle-to-Home (V2H) technology, to address the challenges posed by energy intermittency. Advanced optimization algorithms, such as the Transient Search (TS) Optimization algorithm, are employed to ensure efficient energy management, enhance reliability, and minimize operational costs. The system evaluates performance under various demand response (DR) scenarios, demonstrating significant economic benefits. Without DR, the total operational cost is $1268.42. Under a 20 % DR scenario, this reduces to $1260.95, representing a 0.59 % decrease. In a 30 % DR scenario, costs drop to $1253.63, a 1.17 % reduction, while a 40 % DR scenario results in $1231.63, a 2.91 % decrease. These findings underscore the progressive cost savings achieved through DR programs. The performance of the system is benchmarked against the Reptile Search Algorithm (RSA), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO) and Moth Flame Optimization (MFO) algorithm. The TS Optimization algorithm demonstrates superior accuracy, faster convergence, and better resource allocation, validating its effectiveness in managing energy systems for residential applications and contributing to Egypt's sustainable energy goals.