Power allocation optimization strategy for multiple virtual power plants with diversified distributed flexibility resources

The virtual power plant integrating the flexible resources in the distribution network can provide additional adjustment capacity for the auxiliary services of distribution network. However, the actual internal situation of distribution network including insufficient adjustable capacity of energy storage, unreasonable power allocation, and voltage overrun leads to the difficulties in optimization scheduling. Therefore, this paper proposes a power allocation optimization strategy of distributed electricity‐H2 virtual power plants (EHVPPs) with aggregated flexible resources. Specifically, a distributed EHVPP division method based on the granular K‐medoids clustering algorithm is proposed to realize the independent autonomy and coordinated interaction between EHVPPs, and in order to quantify the operation and regulation capacity of distributed EHVPPs, an aggregation approach of regulating feasible domains of flexibility resources based on the improved zonotope approximations is developed. Moreover, a power allocation strategy based on the flexibility weight factor is proposed to handle the calculated minimum deviation between the total active output of PV and the dispatching power command, realizing the self‐consistency of distributed EHVPPs. Comparative studies have demonstrated the superior performance of the proposed methodology in economic merits and self‐consistency efficiency. The virtual power plant integrating the flexible resources in the distribution network can provide additional adjustment capacity for the auxiliary services of distribution network. However, the actual internal situation of distribution network including insufficient adjustable capacity of energy storage, unreasonable power allocation, and voltage overrun leads to the difficulties in optimization scheduling. Therefore, this paper proposes a power allocation optimization strategy of distributed electricity‐H2 virtual power plants (EHVPPs) with aggregated flexible resources. Specifically, a distributed EHVPP division method based on the granular K‐medoids clustering algorithm is proposed to realize the independent autonomy and coordinated interaction between EHVPPs, and in order to quantify the operation and regulation capacity of distributed EHVPPs, an aggregation approach of regulating feasible domains of flexibility resources based on the improved zonotope approximations is developed. Moreover, a power allocation strategy based on the flexibility weight factor is proposed to hand