Research On The Participation Of Electric Vehicles In Active Power Control Of The Power Grid Considering Aggregated Response

With the rapid development of China’s new energy industry and the continuous growth of user side loads,the contradiction between power supply and demand has further intensified.Due to the insufficient climbing capacity of traditional thermal power units,the lack of reserved reserve capacity in regional power grids,and the increasingly serious problem of mismatch between new energy output and load curve,new challenges have been brought to the active power coordination and control of the power grid.In recent years,with the development and application of vehicle to grid(V2G),demand response(DR),aggregate regulation and other technologies,interruptible and adjustable user side micro loads such as electric vehicles have grown rapidly and formed new schedulable resources.Electric vehicle loads have advantages such as fast response speed,high economy,and reflecting different users’ electricity consumption intentions,but they also have disadvantages such as small unit capacity and dispersed distribution.Therefore,this article aims to study the technology and application of electric vehicle load participation in active power control of the power grid by fully utilizing the massive adjustable electric vehicle resources on the demand side.On the basis of studying the quantitative evaluation method of the demand response potential of large-scale electric vehicles,the paper further proposes the active power control strategy for electric vehicles to participate in the power grid under the high permeability new energy access,improves the peak shaving and frequency modulation capability of the power grid,and ensures the safe and stable operation of the power system.The main content of this article is as follows:(1)Study the aggregation potential assessment of rapid demand response of large-scale electric vehicle load.Based on multi-source information such as the electrical characteristics of electric vehicle loads,user behavior,and external environment,and considering the dynamic response characteristics of large-scale electric vehicle loads under subjective and objective factors,a constraint model for the subjective and objective response capability of large-scale electric vehicles considering grid side and user side factors is proposed;Next,in order to evaluate the aggregation potential of similar groups and reduce computational workload,a k-means algorithm based electric vehicle group classification method is proposed;Finally,a comprehensive weight calculation method combining entropy weight method and Analytic Hierarchy Process was used to quantitatively evaluate the potential of large-scale electric vehicle loads participating in active power control of the power grid.The effectiveness of this evaluation method was verified through numerical simulations.(2)Research on mitigation strategies for grid peak shaving pressure considering the response of large-scale electric vehicles.Fully consider the load characteristics of different electric vehicles,and based on the differences in load and grid exchange methods,consider the scaled electric vehicle load as a flexible load,and establish a model for the elastic participation of scaled electric vehicle load in grid peak shaving considering clustering characteristics;Based on the information exchange and fusion of large-scale electric vehicle loads,analyze the dynamic change characteristics of various electric vehicle loads,comprehensively consider the weights of indicators such as power grid constraints,and combine the incentive policies of demand side response to participate in power grid scheduling.Utilizing dynamic time of use electricity prices and electric vehicle sequential charging and discharging technology,study the dynamic electricity price model of electric vehicles that takes into account system peak shaving costs;Furthermore,a two-stage optimization strategy for grid peak shaving considering the response of large-scale electric vehicles is proposed,and an example system is built on simulation software to verify the effectiveness of this control strategy.(3)Research on the participation of large-scale electric vehicles in primary frequency regulation strategies based on model predictive control.Analyze and establish a framework for the participation of electric vehicles in grid frequency control,study the primary frequency regulation model of the power system containing electric vehicles,aggregate large-scale electric vehicle loads as flexible regulation resources,and add them to the traditional Load Frequency Control(LFC)model to provide capacity support in frequency control.On this basis,a coordinated optimal control strategy for establishing a state space dynamic model is proposed and applied to an improved load frequency control model.Furthermore,a large-scale electric vehicle participation in primary frequency regulation strategy based on model predictive control is proposed.At the same time,in order to further optimize the frequency control effect,a delay compensation strategy is proposed,which uses a dynamic matrix control method based on model predictive control to offset input delay.The feasibility and effectiveness of the above strategy are verified in simulation software.