Load Frequency Control For Multi-area Interconnected Systems With Electric Vehicles

With the continuous integration of renewable energy sources characterized by inherent randomness and high volatility,the stable operation of the power system faces formidable challenges,with frequency stability emerging as a particularly salient concern.Given the unique attributes of electric vehicles(EVs),such as their swift responsiveness,flexible dispatch capabilities,and dual functionality as both power sources and energy storage units,they can be regarded as a novel form of controllable load.Leveraging the Vehicle-to-Grid(V2G)technology,EVs can actively interact with the power grid,enabling the rational regulation of clustered EVs’ charging and discharging behaviors,thereby achieving peak shaving and off-peak filling to mitigate the strain on grid frequency regulation.The primary focus of this study revolves around the load frequency control issue in a multi-area interconnected power system incorporating electric vehicles.To achieve economically stable operation of the system,a coordinated distributed economic model predictive control approach is adopted.The main contributions of this research can be summarized as follows:The study involves the establishment of a comprehensive model for a multi-area interconnected power system that includes electric vehicles.This model encompasses the integration of electric vehicle aggregation and charging stations with the power system,enabling them to assume the role of auxiliary frequency regulation providers.Leveraging the unique travel characteristics of electric vehicles,the power allocation for each electric vehicle is determined based on its individual battery levels.This approach ensures that users’ travel demands are met while effectively utilizing the source-to-storage capabilities of electric vehicles to assist in power system frequency control.Furthermore,by incorporating the structure of thermal power generators,a tailored multi-area interconnected power system model is devised,specifically designed for load frequency control assisted by electric vehicles.Based on the interconnected power system model involving the participation of electric vehicles in frequency regulation,a novel coordinated distributed economic model predictive control strategy is proposed to ensure stable and economical operation.This strategy formulates an objective function that takes into account economic indicators,such as power generation costs and frequency control costs,specific to the interconnected power system.The system optimization problem is established based on terminal inequality constraints,and the optimal control inputs for each subsystem’s controller are obtained through iterative solutions.By constructing auxiliary stage objective functions and auxiliary optimization problems,the system’s auxiliary objective function is defined as a Lyapunov function,ensuring the closed-loop stability of the algorithm.The simulation results have successfully validated the effectiveness of the proposed strategy in achieving load frequency control with the assistance of electric vehicles in interconnected power systems.Through simulations conducted on a two-region interconnected power system,where electric vehicles provide support to thermal power generation for load frequency control,it indicate that electric vehicle participation in power system frequency regulation does not adversely impact normal user usage.On the contrary,the integration of electric vehicles effectively reduces frequency overshooting,resulting in enhanced dynamic and steady-state performance of the system.Moreover,through comparative analyses,we have confirmed that the coordinated distributed economic model predictive control algorithm outperforms other control strategies in terms of both control effectiveness and economic performance.This finding underscores the algorithm’s significant practical value and its potential for real-world applications.