No abstract

a b s t r a c tThe rapid charging or discharging characteristics of battery energy storage system is an effective method to realize load shifting in distribution network and control the fluctuations of load power substantially. However, the type selection and capacity configuration of the batteries will be directly related to the economy of energy storage system for load shifting in the distribution network. An optimized model of hybrid battery energy storage system based on cooperative game model is proposed in this paper, in which lead-acid battery, lithium ion battery and vanadium redox flow battery are respectively regarded as the participants of the cooperative game model, the cost and benefit models are established in their corresponding game strategy spaces. The Nash equilibrium solutions of each game model obtained by genetic algorithm are applied to the planning and design of battery energy storage station with the most economical types of the batteries and the optimal capacity configuration of energy storage station. The simulation results verify the effectiveness of the proposed method and provide a theoretical basis for the planning and design of battery energy storage station.

Summary The installation of energy storage system to smooth the fluctuations of wind power output connected to the grid can effectively improve the electric quality and increase economic benefits of wind‐generated electricity. Aiming at the overall profit maximization of wind power generation and storage system (WPGSS), taking the smoothing effect of active power output, the cost of hybrid energy storage system, and the earnings of wind power connected to the grid into consideration, this paper brings forward a game theory‐based coordination and optimization control methodology for WPGSS adopting two low‐pass filters to smooth the fluctuation of wind power output. The smoothing control to the active power of wind power and the power distribution of the hybrid energy storage system is respectively achieved by regulating the time constants of the two filters. With the combinations of wind power–batteries and wind power–super‐capacitors as game's participants and the maximization of the WPGSS's overall profit as game's goal constraint conditions, game theory is introduced to realize the coordination and optimization between the time constants of the two filters. For comparative analysis, the model's optimal solution is respectively worked out by genetic algorithm and particle swarm optimization. The simulation results verify the effectiveness of the proposed method and provide a theoretical basis for the economic evaluation of the WPGSS. Copyright © 2016 John Wiley & Sons, Ltd.

No abstract

No abstract