A Fair Payment Scheme for Virtuous Community Energy Usage

In this work, we face a payment estimation problem that involves a community of users and an energy distributor (or producer). Our aim is to compute payments for every user in the community according to the single user’s consumption, the community’s consumption and the available energy. The proposed scheme influences the community in consuming in a virtuous way. In order to reach this goal, our payment function distributes incentives if the consumption is lower than the produced energy and penalties when the consumption exceeds the resources threshold. Our model satisfies efficiency and fairness properties both from the community (efficiency as an economic equilibrium among sellers and buyers) and the single user (fairness as an economic measure of energy good-behaving) points of view. By computing community-dependent energy bills, our model stimulates a virtuous users’ behaviour so that it approaches the production threshold as close as possible. We also provide a simulation based on real data referring to a dataset of buildings in California State, thus, showing several possible shapes of our payment scheme.

[1]  Tim Roughgarden,et al.  Algorithmic Game Theory , 2007 .

[2]  E. Rowland Theory of Games and Economic Behavior , 1946, Nature.

[3]  Stefano Bistarelli,et al.  A Mechanism Design Approach for Allocation of Commodities , 2016, ICTCS.

[4]  Vincent W. S. Wong,et al.  Optimal energy consumption scheduling using mechanism design for the future smart grid , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[5]  Yadati Narahari,et al.  Game Theory and Mechanism Design , 2014 .

[6]  Mohammed H. Albadi,et al.  Demand Response in Electricity Markets: An Overview , 2007, 2007 IEEE Power Engineering Society General Meeting.

[7]  Vincent W. S. Wong,et al.  Advanced Demand Side Management for the Future Smart Grid Using Mechanism Design , 2012, IEEE Transactions on Smart Grid.

[8]  Harold William Kuhn,et al.  Contributions to the Theory of Games (AM-39), Volume III , 1951 .

[9]  T. Rutherford,et al.  THE EU 20/20/2020 targets: An overview of the EMF22 assessment , 2009 .

[10]  Paolo Giuliodori,et al.  A Mechanism Design Approach for Energy Allocation , 2016, DC@AI*IA.

[11]  Hamed Mohsenian Rad,et al.  Optimal Residential Load Control With Price Prediction in Real-Time Electricity Pricing Environments , 2010, IEEE Transactions on Smart Grid.

[12]  Shing-Chow Chan,et al.  Demand Response Optimization for Smart Home Scheduling Under Real-Time Pricing , 2012, IEEE Transactions on Smart Grid.

[13]  G. Owen,et al.  A Simple Expression for the Shapley Value in a Special Case , 1973 .