Gearóid O'Brien
ABSTRACT
Demand Response, or adjusting the aggregate load profile as a means to help balance supply and demand in electricity grids, is currently a popular area of research. In this paper, we propose analyzing demand response schemes in a game theoretic setting, and utilizing the Shapley Value for fairly compensating participants of such schemes. As exact computation of the Shapley Value is intractable in general, we also propose a pseudo-randomized sampling method that can dramatically reduce the variance of the Shapley Value estimate when compared to other methods.
- M. Albadi and E. El-Saadany. Demand response in electricity markets: An overview. In Power Engineering Society General Meeting, 2007. IEEE.Google Scholar
Cross Ref
- E. Algaba, J. Bilbao, J. F. Garcia, and J. Lopez. Computing power indices in weighted multiple majority games. Mathematical Social Sciences, 46(1):63--80, 2003.Google ScholarCross Ref
- Y. Bachrach, E. Markakis, E. Resnick, A. D. Procaccia, J. S. Rosenschein, and A. Saberi. Approximating power indices: theoretical and empirical analysis. Autonomous Agents and Multi-Agent Systems, 20(2):105--122, Mar. 2010 Google ScholarDigital Library
- M. Junqueira, L. Da Costa, L. Barroso, G. Oliveira, L. Thomé, and M. Pereira. An aumann-shapley approach to allocate transmission service cost among network users in electricity markets. Power Systems, IEEE Transactions on, 22(4):1532--1546, 2007.Google Scholar
- G. O'Brien and R. Rajagopal. A Method for Automatically Scheduling Notified Deferrable Loads. In American Control Conference (ACC), 2013. To appear.Google ScholarCross Ref
Index Terms
- Efficient computation of shapley values for demand response programs
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