A Credible Regulating Capacity Evaluation Method of Virtual Control Units in Frequency Response

By employing virtual power plant technology, various types of distributed energy resources on the distribution side can be aggregated into a virtual control unit, allowing for direct participation in the frequency response of the power system. This aggregates effectively addresses the shortage of frequency regulation resources. The uncertainty associated with operational states and user behavior results in time-varying capabilities of individual distributed energy resources, leading to probabilistic characteristics in the adjustment capabilities of the virtual control unit. Consequently, it is essential to develop an evaluation method for the credible frequency response capacity of the virtual control unit, which will provide foundational information for power system operation and control tasks. To accurately simulate the operational states of distributed energy resources, individual models are constructed based on their operational characteristics and user behavior. Additionally, a frequency response capacity evaluation model for these individual resources is established, taking into account both resource characteristics and operational constraints. For the chosen resources, the feasible region is graphically represented to facilitate analysis, thereby forming an analytical calculation method for the frequency response capacity of individual resources. Key parameters involved in the aggregation process are identified, and an evaluation model for the credible frequency response capacity of the virtual control unit is developed using confidence levels and Monte Carlo simulations, based on the probabilistic distribution characteristics of these parameters. The feasibility and correctness of the proposed method are validated through Monte Carlo simulations across multiple scenarios. Furthermore, the simulation results allow for the assessment of the credible frequency response capacity of the virtual control unit at various confidence levels.