Research On Energy Storage Scheduling Optimization Method Of Wind And Photovoltaic Power Curtailment

China’s current new energy generator set projects continue to expand,new energy power generation technology continues to mature.Especially the low price of wind power and photovoltaic,the domestic installed capacity of wind power and photovoltaic increased year by year.But another factor restricting the development of new energy units has not been improved,that is,the output of new energy units is unstable.In terms of wind power and photovoltaic units,due to the various power markets,there is still a large number of wind and light abandonment phenomenon,speed up the new energy power dispatch should be put on the agenda.To solve the power dispatching problem of technical means,the work should continue to be researched,developed and improved,make it can be large capacity,high yield and low cost.In this paper,the establishment of a set area as the research object,the establishment of mathematical model and intelligent algorithm model for related calculation,the advanced compressed air energy storage system(AA-CAES)is built to achieve the purpose of studying the optimization method of wind and optical abandoned energy storage scheduling.Firstly,according to the requirement of scheduling dual objective optimization,the particle swarm optimization algorithm(PSO)is introduced and improved by using niche technology and Pareto file,so as to realize the calculation of dual objective optimization problem.The test function is used to test the constructed algorithm,and the test results show good results.The test points are basically distributed on the Pareto true optimal front,and the convergence index and diversity index parameters are good,so the optimization algorithm is reliable.Secondly,based on the HOMOR software platform,the parameters of the set region are jointly constructed by importing the load data of the set region and downloading the meteorological data of the reference region.Set that wind power and photovoltaic jointly bear10% of the load capacity,fan selection is G1500,photovoltaic cell array is used in 1KW,aiming at the lowest total net present cost and the cost per kilowatt hour of standardization,the installed capacity is calculated to be 60 MW for fan and 33.56 MW for photovoltaic.The average value is used to collect the wind photovoltaic map of typical 24-hour load day in winter January and summer July.Then,according to the daily load law of heating,cooling and electricity of different buildings in the set area,the typical 24-hour daily cooling,heating and electricity load curve in January winter and July summer of the set area is constructed.Wind,photovoltaic,gas turbine and energy storage units are used to form a load output network in the set area.Combined with the output cost and electricity purchase and sale cost,the energy storage power dispatching of the units with scenery in the set area is optimized with the environmental pollution cost and operation cost as the dual objective function.The optimal solution under the dual objective of environmental pollution cost and operation cost of typical load days in July in summer and January in winter was calculated,and the scheduling curve under the operation strategy of optimal solution was given.Finally,the AA-CAES simulation model is established based on MATLAB/Simulink platform.According to the architecture of 1.5MW advanced demonstration power station of Chinese Academy of Sciences,the thermodynamic model of the main components of the system was built by modular modeling method.The operation value of the demonstration power station was taken as the design value,and the simulation analysis was carried out in cold state startup.The error between the simulation parameters and the design value was within 5%,and the model was reliable.Adjust the parameters to build a 10 MW class for simulation analysis,the simulation results show that the reliability.The research results obtained a reasonable dispatching curve of large capacity combined cooling,heat and power(CHP)in the set area,which can be used to guide future CHP dispatching with scenery,to optimize peak regulation and improve energy utilization efficiency.The AA-CAES energy storage system was studied,which provides a parameter basis for the establishment of large capacity energy storage power stations in the future.The research content of this paper provides ideas for the further development of large capacity generator sets with new energy in the future.