A short-term load forecasting model for demand response applications

Abstract

This paper discusses a new algorithm and defines the functionality required for developing a short-term load-forecasting module for demand response applications. Feedforward artificial neural network (ANN) algorithms are used to provide high forecasting performance when dealing with nonlinear and multivariate problems involving large datasets. The approach is thus suitable for short-term load prediction for disaggregated sites to optimize the demand response process when the data relating to the operating regime or load characteristics of the individual devices and loads connected are unavailable. A detailed description of the relevant external data needed for the forecast is explained. In p..