This paper presents the use of an artificial neural network for classification on a residence house that uses local air temperature and solar insulation predictions to identify patterns at the desired location, in order to obtain a stochastic distribution of the daily solar profile. This is a first step on the further creation of a short-term operation model that allows determining the technical and economic impact of stationary/mobile batteries of electric vehicles in presence of microrenewables. This shortterm operation model will be in the day-ahead perfect market operation (unit commitment) where specific changes are made to consider stationary and mobile operation.
The foreseeable dynamic pricing of electricity combined with the emergence of the so-called electricity "prosumers" that not only consume, but also have the ability to produce and store electricity, necessitates the development of energy management systems even at residential level. In this context, the present work considers that in a modern residence, or a "smart house", electricity is generated from microrenewable energy sources, while the electricity storage options include a fixed battery as well as the battery from a plug-in electric vehicle. This paper presents the theoretical framework for the implementation of a domotic battery management system with the key characteristic that energy management decisions are made every 10 min, based on the forecasted conditions for the next 24 h. The results obtained from the simulation of the proposed system highlight the contribution not only of the fixed battery, but also of the electric vehicle's battery to the maximization of electricity cost savings.
This paper presents the use of an artificial neural network for classification on a residence house that uses wind and electricity consumption predictions to identify patterns at the desired location, in order to obtain a stochastic distribution of the daily wind and electricity profile. This is a step on the further creation of a short-term operation model that allows determining the technical and economic impact of stationary/mobile batteries of electric vehicles in presence of microrenewables along with the electricity consumption. This short-term operation model will be in the day-ahead perfect market operation (unit commitment) where specific changes are made to consider stationary and mobile operation.
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