Decentralized surplus distribution estimation with weighted k-majority voting games

Abstract

Future energy grids and associated markets foster dynamic coalition formation in order to allow situational virtual power plant configurations. Collaboratively and distributed, such virtual power plants may take over responsibility on several emerging control tasks within the smart grid as a substitute for no longer available large plants. Temporary teamwork of individually owned and operated distributed energy resources demands for a proper and fair surplus distribution after product delivery. Distributing the surplus merely based on the absolute (load) contribution does not take into account that smaller units maybe provide the means for fine grained control as they are able to modify their load on a smaller scale. Bringing in flexibility, counts for several tasks. Shapley values provide a concept for the decision on how the generated total surplus of an agent coalition should be spread. In this paper, we propose a scheme for efficiently estimating computationally intractable Shapley values in a fully decentralized way. As a scheme to handle a set of different utility evaluation criteria we use weighted k-majority voting games. We demonstrate the applicability of the decentralized estimation by several simulation results in comparison with exact calculations.