DocumentCode :
1799316
Title :
Using approximate dynamic programming for estimating the revenues of a hydrogen-based high-capacity storage device
Author :
Francois-Lavet, Vincent ; Fonteneau, Raphael ; Ernst, Damien
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Univ. of Liege, Liege, Belgium
fYear :
2014
fDate :
9-12 Dec. 2014
Firstpage :
1
Lastpage :
8
Abstract :
This paper proposes a methodology to estimate the maximum revenue that can be generated by a company that operates a high-capacity storage device to buy or sell electricity on the day-ahead electricity market. The methodology exploits the Dynamic Programming (DP) principle and is specified for hydrogen-based storage devices that use electrolysis to produce hydrogen and fuel cells to generate electricity from hydrogen. Experimental results are generated using historical data of energy prices on the Belgian market. They show how the storage capacity and other parameters of the storage device influence the optimal revenue. The main conclusion drawn from the experiments is that it may be advisable to invest in large storage tanks to exploit the inter-seasonal price fluctuations of electricity.
Keywords :
dynamic programming; electrolysis; fuel cells; hydrogen storage; power markets; Belgian market; day-ahead electricity market; dynamic programming principle; electrolysis; fuel cells; high-capacity storage device; hydrogen-based storage devices; interseasonal price fluctuations; maximum revenue estimation; optimal revenue; Dynamic programming; Electricity; Electrochemical processes; Fuel cells; Hydrogen; Hydrogen storage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Adaptive Dynamic Programming and Reinforcement Learning (ADPRL), 2014 IEEE Symposium on
Conference_Location :
Orlando, FL
Type :
conf
DOI :
10.1109/ADPRL.2014.7010624
Filename :
7010624
Link To Document :
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