Adaptive control strategy of virtual power plant based on peak shaving demand response

A flexible load virtual power plant (VPP) with airconditioning load as the main load is affected by uncertainty in operation, which makes the peak shaving demand response deviate from the expected effect, because the existing DR strategy is based on the static target load curve, and therefore, an adaptive control method is proposed for the VPP with flexible load to participate in the peak shaving demand response (DR), In the proposed closedloop control model, the controlled process is decoupled into a small-scale and linear progress deviation model and a peak shaving correction model, where the progress deviation model apportions the planned peak shaving amount and the peak shaving correction model adjusts the target load curve, and an example verifies the validity of the method in terms of shaving mode, error and delay.