This paper introduces a dynamic Smart Home Energy Management System (SHEMS) integrating a hybrid photovoltaic (PV) and gravity energy storage (GES) system aimed at minimizing environmental impacts and household energy consumption. The novel SHEMS features a one-week dynamic forecasting model that adapts to variable electricity prices, smart appliance schedules, solar output, and energy storage states. These results demonstrate that the system not only reduces household energy usage but also cuts electricity bills significantly, supplying power autonomously for up to 8.5 hours daily. By leveraging real-time data from the Dark Sky API on cloud cover and temperature, this model accurately predicts solar radiation and PV generation, aligning it with both grid and residential demands. The forecasting accuracy was assessed using Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE), which improved to 12.55% and 4.91% respectively, from initial values of 22.46% for RMSE and 11.78% for MAPE. These advancements enhance grid stability and optimize energy storage during peak periods, reducing dependence on fossil fuels. The integration of innovative renewable energy technologies and sophisticated forecast modeling significantly boosts the system's efficiency, promoting the sustainable use of energy resources in line with environmental and economic goals.
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