Prediction interval based on type-2 fuzzy systems for wind power generation and loads in microgrid control design

Abstract

An important issue in the operation of isolated microgrids is how to properly address the uncertainties associated with renewable resources and loads. In this work, a new interval prediction model based on type-2 fuzzy systems is derived for capturing these uncertainties. This model provides the upper and lower boundaries of the predicted values with a certain coverage probability, as well as their expected values. This information could be used in the design of microgrid controllers, such as energy management systems. The proposed method is applied to forecast the wind power generation and the loads of the Huatacondo microgrid, which is located in northern Chile. A comparison with both linear and Takagi-Sugeno fuzzy interval models is also performed.