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In order to give full play to the frequency regulation ability of multiple types of resources such as wind power, energy storage, and controllable load in a microgrid, this paper proposes a hierarchical cooperative frequency regulation control strategy of wind-storage-load in a microgrid based on model prediction. Firstly, according to the operation characteristics of each resource in the microgrid, a hierarchical cooperative frequency regulation architecture of wind-storage-load is constructed. On this basis, the frequency regulation control models of wind power, energy storage, and controllable load are established, respectively, and the calculation method of the characteristic index of the system frequency response is proposed. Then, taking the maximum frequency deviation as the stratification index, a hierarchical cooperative frequency regulation control strategy of wind-storage-load based on model prediction is proposed, and a power compensation strategy for connecting the wind turbine frequency support is proposed for the wind turbine speed recovery stage. Finally, a microgrid model including wind power, energy storage, and controllable load is built on Matlab/Simulink for simulation analysis. The simulation results show that the proposed control strategy can control wind power, energy storage, and controllable load to participate in frequency modulation in advance, and improve the frequency stability of the system.

Nowadays, the influences of the communication structure on the frequency regulation performance in a multi-area power system are barely studied. In this paper, a decentralized frequency regulation method for a multi-area power system considering optimization of communication structure is presented, and the influence of the communication structure on the frequency regulation performance is studied. Firstly, the communication network model is described and the multi-area power system model considering communication structure is presented. Then, the optimization model of communication structure during a decentralized frequency regulation process is constructed. This model aims to speed up the convergence speed of the control together with ensuring the high algebraic connectivity of the communication structure. Quantum binary particle swarm optimization (QB-PSO) algorithm is introduced to solve this model and, based on this, the communication structure optimization process and frequency regulation method are proposed. The simulation results show that the proposed method could greatly improve the frequency control efficiency through the optimization of the communication structure.