Abstract
In this paper, an autonomous and distributive demand-side management based on Bayesian game theory is developed and applied among users in a grid connected micro-grid with storage. To derive that strategy, an energy consumption of shiftable loads belonging to a given user is modelled as a noncooperative three-player game of incomplete information, in which each user plays against the storage unit and an opponent gathering all the other users in the micro-grid. Each player is assumed to be endowed with statistical information about its behavior and that of its opponents so that he can take actions maximizing his expected utility. Results of the proposed strategy evaluated by simulating, under MATLAB environment, a connected micro-grid with storage device evidence its efficacy when employed to manage the charging of electric vehicles.
Highlights
Demand-Side Management (DSM), which is the management mechanism of demand side in the generation of the grid [1], seeks to address various problems such as efficient energy usage, improvement of the demand profile, reduction of the operation cost, shift energy consumption to reduce PAR, and balance power supply and demand [2]
An energy consumption of shiftable loads belonging to a given user is modelled as a noncooperative three-player game of incomplete information, in which each user plays against the storage unit and an opponent gathering all the other users in the micro-grid
The authors in [7] developed a scheduling strategy for DSM with a noncooperative game with incomplete information and each residential user does not know the energy consumption of other users instantly, but the future overall consumptions of all users were given with statistical information
Summary
The authors of [6] explore a Bayesian game theoretic framework for multiple energy producers competing in energy market in which each producer (player) optimizes its own objective function given the utility demand. The authors in [7] developed a scheduling strategy for DSM with a noncooperative game with incomplete information and each residential user does not know the energy consumption of other users instantly, but the future overall consumptions of all users were given with statistical information. Authors in [8] considered a game with incomplete information in which realtime information to the destination may not be guaranteed to be received adequately, due to the packet loss. The previous work developed for DSM using game theory did not take account the presence and the influence of storage in the smart micro-grid
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
