A Two-stage Robust Optimal Scheduling Method for Virtual Power Plants Taking into Account Multi-flexibility Resources
A two-stage robust optimization-based dual-layer optimal control strategy for virtual power plant aggregating multiple flexibility resources were proposed for wind power consumption and deep peaking in Inner Mongolia region.First,an upper-layer model was constructed based on wind power output and load forecast data with the goal of maximizing the revenue of the virtual power plant during the dispatching cy-cle,while taking into full consideration the cost and profit brought by the deep peaking of thermal power u-nits.Second,in the lower-layer model,with the goal of minimizing the operating cost of the virtual power plant,the risk brought by the uncertainty of wind power output and load was fully considered,and the rev-enue of the virtual power plant under different degrees of conservatism was obtained by introducing robust optimization control according to the adjustment of the correlation coefficient.The simulation results show that after the proposed power plant aggregates the deep peaking coal fired units(DPCFU),the virtual pow-er plant revenue increases by 174 200 yuan compared with that only participating in the conventional peak load unit.The virtual power plant can obtain greater benefits with less operation risk.In addition,the two-layer control strategy proposed in this paper can minimize the operation cost on the basis of obtaining the maximum benefits.At the same time,different scheduling schemes can be provided according to different robustness coefficients.
virtual power plantrobust controlaggregation characteristicsmulti-flexibility resourcesoptimal dispatching
万方数据
维普
