The application of Bayes inference in multicriteria analysis to design energy storage systems in renewable power generation

Author

Chiodo, Elio ; Di Noia, L.P. ; Rizzo, Rocco

Author_Institution

Dept. of Electr. Eng. & Inf. Technol., Univ. of Naples Federico II, Naples, Italy

fYear

2013

fDate

11-13 June 2013

Firstpage

728

Lastpage

733

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 system.

Keywords

Bayes methods; battery storage plants; power generation dispatch; Bayes inference; Bayesian inference; battery energy storage system design; electric vehicle recharge; fuel cells; generated energy dispatching; multicriteria analysis; optimal strategy; renewable energy dispatching; renewable energy sources; renewable power generation; supercapacitors; Batteries; Bayes methods; Discharges (electric); Power system stability; Renewable energy sources; Bayes inference; Energy Storage System; Multicriteria Analysis; Renewable power generation;

fLanguage

English

Publisher

ieee

Conference_Titel

Clean Electrical Power (ICCEP), 2013 International Conference on

Conference_Location

Alghero

Print_ISBN

978-1-4673-4429-6

Type

conf

DOI

10.1109/ICCEP.2013.6586937

Filename

6586937