The problem of accurately predicting the energy production from renewable sources has recently received an increasing attention from both the industrial and the research communities. It presents several challenges, such as facing with the high rate data are provided by sensors, the heterogeneity of the data collected, power plants efficiency, as well as uncontrollable factors, such as weather conditions and user consumption profiles. In this paper we describe Vi-POC (Virtual Power Operating Center), a project conceived to assist energy producers and, more in general decision makers in the energy market. In this paper we present the Vi-POC project and how we face with challenges posed by the specific application domain. The solutions we propose have roots both in big data management and in stream data mining.
Big Data Techniques For Renewable Energy Market (Discussion Paper)
CORIZZO R;MALERBA, Donato;
2014-01-01
Abstract
The problem of accurately predicting the energy production from renewable sources has recently received an increasing attention from both the industrial and the research communities. It presents several challenges, such as facing with the high rate data are provided by sensors, the heterogeneity of the data collected, power plants efficiency, as well as uncontrollable factors, such as weather conditions and user consumption profiles. In this paper we describe Vi-POC (Virtual Power Operating Center), a project conceived to assist energy producers and, more in general decision makers in the energy market. In this paper we present the Vi-POC project and how we face with challenges posed by the specific application domain. The solutions we propose have roots both in big data management and in stream data mining.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
