TY - JOUR
T1 - Dynamic decision making in energy systems with storage and renewable energy sources
AU - Meisel, Stephan
AU - Powell, Warren Buckler
N1 - Funding Information:
Acknowledgements The work of the first author was supported by the German Academic Exchange Service (DAAD).
Publisher Copyright:
© 2017, Springer International Publishing AG.
PY - 2017
Y1 - 2017
N2 - We model an energy system with a storage device, a renewable energy source and with market access as a Markov decision process. We have identified four classes of pure policies (PFAs, CFAs, VFAs and lookaheads), each of which may work best depending on the characteristics of the system (volatility of prices, stationarity, accuracy of forecasts). We demonstrate that each of the four classes can work best on a particular instance of the problem. We describe the problem characteristics that bring out the best of each policy.
AB - We model an energy system with a storage device, a renewable energy source and with market access as a Markov decision process. We have identified four classes of pure policies (PFAs, CFAs, VFAs and lookaheads), each of which may work best depending on the characteristics of the system (volatility of prices, stationarity, accuracy of forecasts). We demonstrate that each of the four classes can work best on a particular instance of the problem. We describe the problem characteristics that bring out the best of each policy.
KW - Energy storage
KW - Sequential decision making
KW - Stochastic optimization
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U2 - 10.1007/978-3-319-51795-7_6
DO - 10.1007/978-3-319-51795-7_6
M3 - Conference article
AN - SCOPUS:85048159112
SN - 2297-0215
SP - 87
EP - 101
JO - Trends in Mathematics
JF - Trends in Mathematics
IS - 190029
T2 - 1st International Symposium on Energy System Optimization, ISESO 2015
Y2 - 9 November 2015 through 10 November 2015
ER -