SmartGridOptimizer-X: A Novel Energy-Efficient Design Framework for Sustainable Electrical Systems Integration

The SmartGRidOptimizer-X is an advanced hybrid forecasting model that can precisely forecast the energy demand by incorporating Temporal Convolutional Networks (TCNs), Long Short-Term Memory (LSTM) networks, and Adaptive Gradient Boosting Machines (Adaptive-GBMs). The model is also able to tackle the issues of complex energy systems by embracing multi-scale temporal dependencies and capitalizing on contextual aspects of weather, socio-economic, and historical trends. CNLSTM and Adaptive-GBM are used with 75 and 25 percent as optimized ensemble weights, respectively, making it stronger and more accurate. The system was tested aggressively on the Energy Prediction Smart-Meter Dataset with an incredible accuracy…