Abstract
This paper presents an innovative approach to microgrid energy management by integrating Model Predictive Control (MPC) with Artificial Intelligence (AI), focusing on the application of Long Short-Term Memory (LSTM) networks for load forecasting. We show that AI-enhanced MPC can significantly improve the efficiency and reliability of microgrid energy management. The fundamental results of the LSTM models highlight the effectiveness of our methodology in improving predictive accuracy and operational performance.
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