Research On Dynamic Optimization Strategy Of Peaking Cost Of Power Grid Based On Multi-source Energy Storage Coordination

The integration of large-scale renewable energy into the grid increases the uncertainty of the demand for peak-shaving capacity of the power grid,which requires the power grid to have more flexible peak-shaving resources.The multi-source energy storage system based on electric and heat coordinated energy storage has a fast response.The characteristics of large instantaneous response capacity,etc.,provide new solutions to the problem of insufficient power grid peak-shaving resources and uncertain peak-shaving capacity demand.However,it is difficult for multi-source energy storage companies to make profits under the current peak shaving auxiliary service compensation mechanism in my country,and thus cannot fully mobilize the enthusiasm of energy storage resources to participate in peak shaving,which seriously affects the application and development of electric and thermal coordinated energy storage.From the perspective of the electric and thermal coordinated energy storage system,this paper explores a dynamic optimization method for the peak shaving cost of the power grid with the participation of multi-source energy storage systems.The cost of multi-source energy storage participates in the peak shaving of the power grid and the power of the multi-source energy storage system is optimized.Research on three aspects: allocation and dynamic optimization of bidding strategies of market entities under the market environment.This article first analyzes the characteristics of energy storage equipment and energy conversion equipment,and builds an overall architecture for multi-source energy storage systems to participate in power grid peak shaving.Taking into account the life loss caused by frequent charging and discharging of multi-source energy storage when participating in grid peak and valley regulation,the impact of depth of discharge and discharge rate on the cycle life of the battery is analyzed,and the life loss of the battery during one discharge is quantified.The life loss cost is included in the operating cost of multi-source energy storage participating in peak shaving to ensure accurate evaluation of the economics of multi-source energy storage participating in power grid peak shaving.At the same time,it considers the benefits of heating to heat users after the conversion of electrical energy into heat,and a refined cost model of multisource energy storage system participation in power grid peak shaving has been established.Secondly,in view of the uncertainty caused by the randomness and volatility of wind power output to the peak shaving capacity of the power grid,this paper analyzes the characteristics of wind power output and load characteristics in a typical day,and generates a demand scenario for the peak shaving capacity of the power grid.Source energy storage characteristics classify peak-shaving capacity demand scenarios;in order to improve the operating economy of multisource energy storage systems under different peak-shaving capacity requirements,multi-source energy storage systems have the lowest operating costs,and batteries and heat storage devices are the most expensive.Optimal power allocation is the optimization goal,and a power allocation model for electric and heat coordinated energy storage is established.The simulation results show that the electric and thermal coordinated energy storage can effectively reduce the amount of air curtailment,and the participation of heat storage devices in peak shaving can also increase the service time of energy storage equipment.Finally,in the context of the peak shaving auxiliary service market,establish a multi-agent game model for conventional power generation companies,new energy power generation companies,and multi-source energy storage companies with the maximum return of market entities as the objective function,and use the KH optimization algorithm to dynamically adjust each market entity the decision-making variables of the equilibrium clearing result of the peak shaving auxiliary service market.The built game model and solution algorithm are verified by simulation examples.The results show that with the continuous deepening of the game and the accumulation of market information,the bidding strategies among market entities will gradually reach an equilibrium state,effectively reducing the cost of power grid peak regulation.Improved market efficiency.