| In recent years,with the widespread application of renewable energy power generation technologies such as wind power and photovoltaic,a large number of wind power and photovoltaic power units have been incorporated into the power grid.However,wind power and photovoltaic power generation have great uncertainties,which will have a great impact on the stability and security of power grid;with the development and popularity of electric vehicles(EVs),the charging and discharging behaviors of large-scale EVs are relatively random,which will also bring impact to the safe and stable operation of power grid.The virtual power plant can use electric vehicles as an energy storage device and aggregation it with distributed power supply in the same platform for unified management,which can alleviate the direct impact of distributed energy and large-scale electric vehicles on the grid to a certain extent.Based on the above background,this paper studies the optimal scheduling of multi-type energy virtual power plant with the participation of electric vehicles,constructs the economic scheduling strategy of virtual power plant including electric vehicles,wind power,photovoltaic and gas turbines,and optimizes the output of each energy source with the goal of the minimum fluctuation of power grid load and the lowest operating cost of the system,thus improving the stability of the power grid and reducing the operating cost of the system.The main work completed in this thesis is as follows:On the basis of summarizing the development status of virtual power plants including new energy power generation and electric vehicles and virtual power plants participating in market trading at home and abroad,by analyzing the internal structure and operation mode of virtual power plants,a mathematical model is established for the wind power units,photovoltaic power units,energy storage system,gas turbine units and travel behavior of electric vehicles in virtual power plants.It provides the theoretical basis for formulating the optimal scheduling scheme of virtual power plant.In view of the phenomenon of “peak on peak” of power grid load caused by large area of electric vehicles entering the power grid,electric vehicles were divided into charging only queue and charging/discharging adjustable queue according to their travel demand and state of charge when connected to the grid.In the output optimization stage of virtual power plant,the minimum fluctuation of power output of virtual power plant was taken as the optimization objective,orderly charging and discharging can be carried out in the regulated queue EVs by guiding the dynamic real-time electricity price which based on the load rate,so as to smooth the fluctuations caused by the wind-power output.In the other energy optimization stages,the operating cost of the system is taken as the optimization objective,and the charging behavior of the charge-only queue EVs are reasonably arranged through the real-time electricity price based on the load rate,so as to reduce the load peak-valley difference.Optimize energy output with the goal of minimizing load fluctuation and system operating cost.Through simulation verification,compared with the disorderly charging of electric vehicles,under the guidance of dual electricity price,orderly charging and discharging of electric vehicles can effectively reduce the fluctuation of new energy output,reduce the peak-valley difference of load,and calculate the operation cost of each output unit in the electric system.The comparison shows that the economy of the system operation has been effectively improved after optimization.On the basis of considering the optimal scheduling model of virtual power plant including electric vehicles under the guidance of electricity price,the three-stage bidding process of virtual power plant participating in multiple electricity markets is analyzed.In the day-ahead market,after signing a contract with the operator in the bilateral contract market,the virtual power plant predicts the EV charging load and the output of each unit through the historical data of the dispatching center,so as to formulate the day-ahead bidding strategy,and submits the strategy to the real-time market after unifying the market price before the clearing day.The intra-day scheduling center updates and re-predicts the wind power and photovoltaic output in real time,guides EV to carry out load transfer according to the electric vehicle demand quantity,charging time and intra-day electricity price collected by the load aggregator,reduces the load fluctuation,redevelops and reports the real-time market bidding strategy one by one,and completes the electricity transaction after unified clearing of the real-time market electricity price.In real-time phase,unbalanced electricity is absorbed by the balanced market.At the same time,the demand response is divided into price based demand response and incentive based demand response,and the charge-discharge management of a single electric vehicle is studied,so as to explore the influence of virtual power plant behavior on its own operating costs and the optimization results of bidding power of virtual power plant,electric vehicles and demand response.The results are verified by simulation examples,compared with only participating in a single power market,virtual power plants participating in multiple power markets at the same time can effectively reduce the operating costs of virtual power plants.Moreover,by taking Nissan LFAF,BYD E6,Mitsubishi i Mi and BMW MINI as examples,it is verified that different electric vehicle individuals are different due to their own parameters and their own states during access.At the same time,the change of total load in the power grid before and after the response of transferable load and interruptible load is compared.Experimental data show that the effect of peak clipping and valley filling after the virtual power plant participates in the demand response is remarkable,which effectively relieves the burden of the power grid in the peak period. |
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