Abstract
With the development of smart grids, a renewable energy generation system has been introduced into a smart house. The generation system usually supplies a storage system with the capability to store the produced energy for satisfying a user’s future demand. In this paper, the main objective is to determine the best strategies of energy consumption and optimal storage capacities for residential users, which are both closely related to the energy cost of the users. Energy management with storage capacity optimization is studied by considering the cost of renewable energy generation, depreciation cost of storage and bidirectional energy trading. To minimize the cost to residential users, the non-cooperative game-theoretic method is employed to formulate the model that combines energy consumption and storage capacity optimization. The distributed algorithm is presented to understand the Nash equilibrium which can guarantee Pareto optimality in terms of minimizing the energy cost. Simulation results show that the proposed game approach can significantly benefit residential users. Furthermore, it also contributes to reducing the peak-to-average ratio (PAR) of overall energy demand.
Highlights
Smart grids have played an important role in the security of grid operations and the stability of energy supply [1]
Grids and consumers can both participate in the energy management in smart grids via the information network [6], which contributes to promoting the utilization of renewable energy resources and reducing the emission of greenhouse gases
From the above propositions 1–3, one can see that the non-cooperative game we proposed based on the payoff function (29) which can encourage residential users to make a best strategy of energy consumption and optimal battery capacity for reducing their cost
Summary
Smart grids have played an important role in the security of grid operations and the stability of energy supply [1]. The main contributions of this paper can be summarized as follows: 1) An energy consumption management program is proposed for multiple residential users using a game-theoretic method to obtain the scheduled energy consumption and optimal capacity for reducing users’ costs in three approaches, including shifting loads from on-peak hours to off-peak hours, selling energy back to the grid by PV generation and providing energy for users during peak demand hours with using batteries; 2) The existence of the Nash equilibrium and optimal battery capacity for the proposed on-cooperative game approach are both proved mathematically; 3) Simulations are conducted to confirm the effectiveness and efficiency of the approach and the results show that the cost of the residential user can be reduced but the PAR of the grid is reduced.
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