DC MicroGrids (MG) must have Energy Management Systems (EMS) to guarantee efficient, dependable, and environmentally friendly electricity. The application of Model Predictive Control (MPC), proved to be helpful due to its adaptability and capacity to use non-linear models. This paper, based on an extensive literature review, identifies and discusses the three key activities to improve the characteristics of DC microgrids, i.e.:...

This research seeks to enhance energy management systems (EMS) within a microgrid by focusing on the importance of accurate renewable energy prediction and its strong correlation with load curtailment. Analyzing the precision of disturbance predictions, reveals that predicting one hour in advance is more effective than immediate predictions or those made several hours beforehand. Furthermore, the study investigates scheduling load...

This research is primarily concentrated on predicting the output of photovoitaic power, an essential field in the study of renewable energy. The paper comprehensively reviews various forecasting methodologies, transitioning from conventional physical and statistical methods to advanced machine learning (ML) techniques. A significant shift has been observed from traditional point forecasting to machine learning-based forecasting...