Research On Power Market Auxiliary Services Based On Virtual Power Plant

With the gradual opening up of the power market,the main members participating in the power market are diversified.It is of great significance to participate in peak and frequency modulation auxiliary services through reasonable dispatching of multiple power resources including electric vehicles,interruptible loads,and energy storage units.The proposal and development of Virtual Power Plant(VPP)technology provides new ideas and solutions for integrating diversified power resources and participating in auxiliary services in the power market.The VPP dispatch center integrates different power resources on a large scale,and through the data management and command control management of different power resources,it effectively solves the management and control problems of wide distributed energy distribution and large number of dispatches.Based on this,this paper conducts a study on the participation of virtual power plants in the power market peak and frequency modulation auxiliary services.Firstly,evaluate the performance and economics of different power sources participating in peak and frequency modulation auxiliary services in the virtual power plant.Establish controllable capacity models for electric private cars,electric buses,interruptible loads,and energy storage units.Through further simulation and analysis,determine the daily controllable capacity of different power resources in the virtual power plant to participate in peak and frequency regulation.A virtual power plant participating in the frequency modulation auxiliary service model was established with the highest frequency modulation benefit and the best comprehensive performance as the optimization goals;with the net load standard deviation and the peak shaving cost as the minimum,the virtual power plant participating in the peak adjustment auxiliary service model was established.The simulation results show that when the virtual power plant participates in the frequency modulation auxiliary service of the power market,it can obtain higher net income while improving the frequency modulation performance.By optimizing the scheduling of the virtual power plant to participate in the peak modulation auxiliary service,the standard deviation of the net load can be reduced.The peak and valley difference will increase the power system’s acceptance of new energy resources and alleviate the peak regulation difficulties of thermal power units.And by comparing and analyzing the peak and frequency modulation effects of power resources in different configurations in virtual power plants,the performance and economics of peak power and frequency modulation of virtual power plants under different configurations are significantly different.It provides a reference for the decision makers of virtual power plants to formulate virtual power plant configuration strategies.Secondly,considering the uncertainty of electric vehicle users’ travel and response,it poses a challenge for dispatching electric vehicles to participate in AGC tuning frequency bands.Based on this,this paper uses the empirical modal decomposition method to decompose the frequency modulation deviation of thermal power units into high frequency,intermediate frequency and low frequency parts as the reference output power of super capacitors,batteries and electric vehicles.An electric vehicle user response model based on Weber-Fishner’s law was established,and the concept of electric vehicle response deviation threshold was introduced to achieve a balance between risk and return of electric vehicle compensation,thereby formulating a more reasonable electric vehicle charge and discharge compensation price.Aiming at the best AGC frequency modulation effect and the highest net income expectation,a virtual power plant containing thermal power units,hybrid energy storage systems and electric vehicles was established to participate in the AGC frequency modulation scheduling model.The improved genetic algorithm was used to optimize the configuration and optimization of the hybrid energy storage system.Dispatching the output of various parts of the virtual power plant.The results of a numerical example show that the model can significantly improve the effect of AGC frequency modulation,and by reasonably setting the response deviation threshold of the electric vehicle.a higher expected net income can be obtained.Finally,this paper builds a two-stage bidding decision model for virtual power plants with electric vehicles to participate in peak shaving assistance services.The preliminary bidding strategy was formulated by predicting the dispatchable capacity of each component in the next day’s virtual power plant,including energy storage units,micro gas turbines,electric vehicles,and interruptible loads.Considering the quotation information of other bidders,a set of quotation scenarios is generated.The power market dispatch center performs market clearing with the goal of minimizing the peak shaving cost,and determines the marginal clearing price and volume of the peak shaving market in all scenarios.Based on this,the virtual power plant takes the maximum self-interest as the scheduling goal,and establishes a virtual power plant internal resource optimization scheduling model.Considering the randomness of the power plant’s participation in the peak-sharing auxiliary service of the virtual power plant,the uncertainty of quotations from other bidding entities is included externally,and the risk adjusted return on capital(RAROC)threshold constraint was introduced.A new model between benefits and risks.Among them,the external bidding is optimized using an improved genetic algorithm,and the optimal dispatch of the internal power resources of the virtual power plant is solved using Cplex to obtain the optimal bidding coefficient and the charge and discharge power of the internal resources.The simulation results verify the validity of the model.