DocumentCode :
177812
Title :
Distributed demand side management of heterogeneous rational consumers in smart grids with renewable sources
Author :
Eksin, Ceyhun ; Delic, Hakan ; Ribeiro, Alejandro
Author_Institution :
Dept. of Electr. & Syst. Eng., Univ. of Pennsylvania, Philadelphia, PA, USA
fYear :
2014
fDate :
4-9 May 2014
Firstpage :
1100
Lastpage :
1104
Abstract :
We consider a demand side management model in which the power provider adopts an adaptive pricing strategy that depends on fluctuations in renewable sources and consumption behavior of customers with heterogeneous marginal utilities in the smart grid. Given the adaptive pricing strategy, we formulate the power consumption behavior of customers as a repeated noncooperative game with incomplete information. We provide an explicit characterization of unique Bayesian Nash equilibrium strategy in terms of individual marginal utilities. The rational behavior is also characterized in a communication scheme where smart meters exchange consumption levels with neighboring meters. A local algorithm that computes equilibrium consumption and propagates beliefs is presented when the network is known. Simulation results show that communication is beneficial for welfare and that power provider can lower the peak-to-average ratio of total consumption by adjusting its target profit ratio.
Keywords :
demand side management; power consumption; renewable energy sources; smart meters; smart power grids; Bayesian Nash equilibrium strategy; adaptive pricing strategy; distributed demand side management; heterogeneous rational consumers; peak-to-average ratio; power consumption; power provider; renewable sources; smart grids; smart meters; Bayes methods; Equations; Games; Power demand; Pricing; Production; Smart grids; Noncooperative game theory; distributed demand side management; renewable energy; smart grid;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location :
Florence
Type :
conf
DOI :
10.1109/ICASSP.2014.6853767
Filename :
6853767
Link To Document :
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