In recent years, the wide utilization of renewable energy sources has brought some problems for the dispatching of generated energy. In recent technical papers are proposed some solutions to improve the renewable energy dispatching: i. e. it is possible to set up an optimal strategy to recharge electric vehicles, or use batteries storage systems, supercapacitors or fuel cells. The aim of this papers is the application of multicriteria analysis to design batteries energy storage systems. By means of Bayesian inference is possible to take into account some uncertainties of batteries characteristics and estimate the best choice for the design of the storage system
The application of Bayes inference in multicriteria analysis to design energy storage systems in renewable power generation / Chiodo, Elio; DI NOIA, LUIGI PIO; Rizzo, Renato. - (2013), pp. 728-733. (Intervento presentato al convegno International Conference on Clean Electrical Power: Renewable Energy Resources Impact, ICCEP 2013 tenutosi a Alghero nel 11-13 Giugno 2013) [10.1109/ICCEP.2013.6586937].
The application of Bayes inference in multicriteria analysis to design energy storage systems in renewable power generation
CHIODO, ELIO;DI NOIA, LUIGI PIO;RIZZO, RENATO
2013
Abstract
In recent years, the wide utilization of renewable energy sources has brought some problems for the dispatching of generated energy. In recent technical papers are proposed some solutions to improve the renewable energy dispatching: i. e. it is possible to set up an optimal strategy to recharge electric vehicles, or use batteries storage systems, supercapacitors or fuel cells. The aim of this papers is the application of multicriteria analysis to design batteries energy storage systems. By means of Bayesian inference is possible to take into account some uncertainties of batteries characteristics and estimate the best choice for the design of the storage systemI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
