Research On Prediction Model Of Elastic Load Resource Aggregation And Regulation Potential

In recent years,power grid companies have carried out a large number of load regulation and source-grid-load interaction practices,verifying the significant role of demand response.However,the rapid growth of flexible load resources such as temperature control loads,electric vehicles,and customer-side energy storage brought about by the acceleration of China’s urbanization process has brought challenges to the balance of the grid.At present,the types of load resources participating in the interaction are relatively single,mainly air-conditioning loads and interruptible loads of industrial users.Grid-friendly resources such as energy storage and electric vehicles have not yet been applied on a large scale;and the existing adjustment methods are limited in application scenarios.Seasonal peak shaving and rapid load control after UHV faults cannot cope with large-scale clean energy fluctuations at any time and improve grid operation efficiency.Based on the above problems,the thesis carried out research on the elastic load resource aggregation and adjustment potential prediction model,providing method guidance for deep mining of power demand side resources and expanding the adjustment ability of the existing source network load system.First,starting from the definition of elastic load,the multi-dimensional classification method of elastic load is summarized,including classification methods based on spatial scale,time scale,and operating mode,and a load aggregation model for temperature-controlled loads,electric vehicles and energy storage is proposed.Secondly,in view of the load characteristics of elastic load resources,a layered establishment of elastic load resource aggregate response reliability index system,a response reliability evaluation model based on the response reliability index,and the response reliability evaluation from device-user-aggregated user level by level.Finally,a prediction model for the adjustable potential of elastic load resources is further proposed,which analyzes the credible adjustable potential of the two demand response scenarios of emergency load shedding and peak-shaving and valley filling,and verifies the credible adjustable potential of users in different interactive scenarios.The difference.