Economic Evaluation Of Energy Storage In New Energy And User-side Peak Shaving And Valley Filling

In recent years,with the continuous development of energy storage technology and national policy support,energy storage systems have gradually been widely used in power systems.The investment benefits brought by energy storage on the new energy and user side are the driving force for its promotion.At present,the problems to be solved in this field are: on the one hand,how to give full play to the overall performance advantages of the power characteristics and energy characteristics of the hybrid energy storage system according to different application scenarios;on the other hand,how to carry out the planning and operation of the energy storage system Synergistic consideration to obtain greater economic benefits.Based on this,this paper studies the economics of energy storage systems in new energy and user-side peak shaving and valley filling,and obtains energy storage system configuration capacity and optimal operation strategies in different scenarios.Firstly,according to the different power characteristics and energy characteristics of different energy storage elements,the high frequency and low amplitude characteristics of power type energy storage elements and the high frequency and low frequency characteristics of energy type energy storage elements are analyzed.By combining these two types of energy storage elements into a hybrid energy storage system,the characteristic advantages can be exerted in different scenarios and the overall life of the entire energy storage system can be improved.Then,the optimal configuration model of energy storage capacity in which the energy storage system participates in the new energy side peak shaving and valley filling is established.The model takes the maximum benefit of energy storage as the objective function,and takes energy storage system output constraints,SOC constraints,and minimum power abandonment as constraints,and obtains the optimal capacity of energy storage configuration through particle swarm optimization.In the optimization,the minimum value of the energy storage rated power,the energy storage state of charge,the difference between the wind power output and the dispatchable grid connection value of the new energy is taken as the reference charging and discharging power of the energy storage system.Finally,the actual wind and solar output data of new energy power plants are used as examples to verify the effectiveness of the model and algorithm.Finally,the economics of the energy storage system on the user side for peak shaving and valley filling is studied.According to the peak-valley electricity price difference on the user side,a double-layer programming model of battery-supercapacitor hybrid energy storage system is proposed.The annual return on investment of energy storage is used as the outer objective function,and the particle swarm algorithm is used to solve it;It is the inner objective function,which is optimized and solved by the CPLEX solver,and the optimal charge and discharge power of the energy storage device in each period is solved while the capacity of the energy storage system is optimally configured.And when establishing the hybrid energy storage system model,considering the difference in energy and power characteristics of batteries and supercapacitors,the charge and discharge frequency constraints are added to the constraints to limit the number of charge and discharge times of different energy storage elements in daily operation.Taking the actual monthly load of a industrial user as an example,the validity of the energy storage model and algorithm on the user side is verified.