For the purpose of considering the spatial-temporal characteristics (STC) of large-scale interconnected power system in the modeling, calculation, and analysis of dynamic frequency response (FR), this paper establishes a two-machine equivalent frequency response (TEFR) model and gets its closed-form solution (CFS), which can be used to analytically analysis and fast calculation. In the modeling, the network structure is idealized through simplified matrix of DC power flow and the system is reduced to a typical two-degree-of-freedom vibration system with viscous damping and excitation forces through breaking closed-loop and variable approximation. After that, modal analysis method is managed to obtain TEFR-CFS which represent the dynamic FR of TEFR model as the superposition of system FR and frequency oscillation. And the influence of parameters on frequency oscillation, such as electrical distance, inertial distribution, initial disturbance power distribution coefficient, etc., are analyzed. Furthermore, the analytical expressions of the key characteristics of dynamic FR, such as the initial decline slope, the nadir and the arrival time of nadir, etc., are derived. Numerical simulation proves that STC has significant influence on FR and can be described by TEFR model, TEFR-CFS and the expressions of its key characteristics with accuracy and efficiency.

Active frequency response (AFR) control is needed in current power systems. To solve the over-frequency problems of generators connected to non-disturbed buses during the AFR control period, the generators should be clustered into coherent groups. Thus, the control efficiency can be improved on the premise of ensuring control accuracy. Since the influencing factors (such as the model parameters, operation modes, and disturbance locations, etc.) of power system operation can be comprehensively reflected by the generator frequency, which is easily collected and calculated, the generator frequency can be used as the coherency identification input. In this paper, we propose a coherency identification method of AFR control based on support vector clustering for a bulk power system. By mapping data samples from the initial space to the high-dimensional feature space, the radius of the minimal enclosing sphere that can envelop all the data samples is obtained. Moreover, the coherency identification of generators is determined for AFR control according to the evaluating method of AFR clustering control effects and the evaluating index of cluster compactness and separation. The simulation results for the modified New England IEEE 10-generator 39-bus system and Henan power grid show that the proposed method is feasible and effective.