With the rapid development of IoT and smart grid

the role of demand-side resources in supply- demand balance is gradually increasing. However

a large number of disorderly applications of demand response techniques can affect the reliability of distribution networks. To address such problems

a virtual power plant economic optimal scheduling method combining baseline load forecasting with load reduction and load transfer is proposed.Firstly

based on the historical data

the output of wind/optical power station and the baseline load of electric vehicles are forecasted by using the triple exponential smoothing method

and the adjust-able capacity of power users is observed. Then

based on the timesharing tariff mechanism with the objective of virtual power plant economic optimum

system constraints such as power balance

wind/light new energy forecast output and energy storage system operation cost are added to establish the electric virtual. Finally

the accuracy and effectiveness of the proposed method are verified by the actual data of 5 centralized charging stations and wind power stations in Zhengzhou

Henan Province.