الفهرس 
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Abstract
The world’s greatest current challenge is saving energy and it is not an easy one-step task. It necessitates altering deeply ingrained behaviors. Recent years have witnessed a significant rise in the demand for electrical energy worldwide due to global-scale population growth and economic progress. Utility authorities seek to reduce end-user consumption in several ways, such as introducing higher tariff rates and Demand Response (DR) strategies. Hence, Home Energy Management System (HEMS) using renewables integrated into a Smart Grid (SG) scheme provides a solution for monitoring and scheduling appliances’ operational activities, which helps reduce consumption and increase energy efficiency. In this thesis, an Optimized Smart Home Energy Management System (OSHEMS) is tested in a laboratory setting to guarantee that it minimizes grid consumption and electricity bills while delivering the load in any circumstances. A hybrid experimental prototype for OSHEMS is designed and implemented which consists of a Photovoltaic-battery system that is connected to the grid. Home Energy Management Whale Optimization Algorithm (HEMWOA) is employed to solve the optimization problem and accomplish the objective of lowering power costs while raising customer comfort levels. Real-Time Price (RTP) or dynamic pricing tariffs that incentivize users to shift their load between peak hours, was a significant key in the investigation. By creating an OSHEMS algorithm and a real-time monitoring system, this system is capable of managing, scheduling, and monitoring energy sources and appliances as well as estimating its consumption from each source. The proposed HEMWOA methodology has achieved 46.3% reduction in the power provided by the power grid. As well as it achieves a reduction in the power cost by 57.7% compared with the non-scheduling scheme.