Optimal Wind Power Integration in Microgrid: A Dynamic Demand Response Game Approach

The large-scale integration of renewables is very challenging due to their intermittency and fluctuations. With the growing interest in smart grids and smart metering systems, one promising option to tackle these challenges is to design demand-side management (DSM) algorithms. Such algorithms can shape the load to follow renewable energy generation, which is the focus of this paper. Based on field data, we model such intertemporal variations of the available wind power as a Markov chain. We formulate a dynamic potential game for efficient cost sharing among users to encourage user cooperation and participation in DSM programs to coordinate load with wind power generation. Further, we analyze the designed dynamic game over a long period and investigate the efficiency of the constructed game model at equilibrium. Then, we develop astrategy proofmechanism, which will reach a Nash equilibrium of the designed game. Simulation results show that, on average, the Nash equilibrium of the proposed game can reduce the generation cost by 25% compared to the case without demand side management. For the case of a windy day, the generation cost further reduces up to 91%.