A game theoretical approach for energy trading in wireless networks powered by green energy

Green energy sources, such as solar and wind, provide an alternative solution for powering wireless networks. To maximize the utilization of green energy charged from different sources, it is desirable to allow energy trade among neighbor cells. In this paper, the local energy trade issues in a wireless mesh network powered by green energy are studied such that energy can be purchased either from neighbor cells or from electricity grid, based on the energy charging and discharging characteristics in each cell. Our objective is to determine the optimal price and quantity of energy purchase and sale for each cell such that the profits of all cells can be maximized and their energy demands can be fulfilled. To this end, the energy trading problem is formulated as a Stackelberg game. Based on the utility function, the closed-form expressions of the optimal energy quantity and price for trading are derived. Finally, an optimal scheme, namely, Optimal Profits Energy Trading (OPET), is proposed to maximize the profits of all cells. The proposed OPET can achieve the optimal solution with polynomial time complexity. Extensive simulations are conducted to verify the performance of the proposed scheme.