Short-term Load Forecasting in Grid-connected Microgrid

Abstract

The integration of distributed energy resources (DER) into main grid need to consider the influence of many factors. One of them is the determination of electric load in Microgrid. Creating a feasible and efficient Microgrid based on the predicted power load is more relevant. The paper analyzes the forecasting of the electric energy consumption in Microgrids, analyzes the area of applicability, advantages and disadvantages of short-term forecasting methods of power consumption. Two methods - Group Method of Data Handling (GMDH) and Artificial Neural Networks (ANN) are used to determine short-term load forecasting.