In this paper, we present Taguchi’s and rolling modeling methods of artificial neural network (ANN) for very-short-term electric demand forecasting (VSTEDF) from the consumers’ viewpoint. The rolling model is a metabolism technique that guarantees input data are always the most recent values. In ANN prediction, several factors that may influence the model should be well examined. Taguchi’s meth...

In this study, we demonstrate the contribution of IS-supported demand response (DR) programs to the development of a sustainable transport sector. Based on the energy informatics framework, we develop an IS artifact that can be used to apply DR programs for electric vehicle (EV) fleets. Furthermore, we quantify one DR program in economic terms by analyzing data gathered in an electric mobility ...

Since several years ago, power consumption forecast has attracted considerable attention from the scientific community. Although there exist several works that deal with this issue, it remains open. The good management of energy consumption in HVAC (Heating, Ventilation and Air Conditioning) systems for large households and public buildings may benefit from a sustainable development in terms of...

This paper presents a preliminary economic study on the feasibility of using electric vehicles (EVs) to provide demand response, carried out as part of the GREEN Grid project. A mathematical model is developed to track the charge cycle of an EV battery, and this in turn provides estimates of the cost associated with battery life degradation under different scenarios. Three case studies are pres...