DocumentCode :
134935
Title :
Estimating the rate of battery degradation under a stationary Markov operating policy
Author :
Donadee, Jonathan ; Ilic, Marija
Author_Institution :
Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA
fYear :
2014
fDate :
27-31 July 2014
Firstpage :
1
Lastpage :
5
Abstract :
Rechargeable Li-Ion battery energy storage is becoming a vital component of many power systems. The infinite horizon Markov decision problem (MDP) framework has been proposed for optimal scheduling of battery charging and discharging under uncertainty in many applications, such as hybrid electric vehicles and bulk electric power grids. In this paper we explain how to determine the expected rate of battery capacity degradation from the solution of an infinite horizon MDP and a degradation severity factor map. We apply the proposed methods to an example MDP from literature.
Keywords :
Markov processes; battery storage plants; lithium; secondary cells; battery capacity degradation; battery charging and discharging; battery degradation rate estimation; bulk electric power grids; degradation severity factor map; hybrid electric vehicles; infinite horizon MDP framework; infinite horizon Markov decision problem framework; optimal scheduling; rechargeable lithium ion battery energy storage; stationary Markov operating policy; Batteries; Degradation; Discharges (electric); Infinite horizon; Markov processes; System-on-chip; Markov chains; Markov decision problem (MDP); battery degradation; battery energy storage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
PES General Meeting | Conference & Exposition, 2014 IEEE
Conference_Location :
National Harbor, MD
Type :
conf
DOI :
10.1109/PESGM.2014.6939034
Filename :
6939034
Link To Document :
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