A Coherency Identification Method of Active Frequency Response Control Based on Support Vector Clustering for Bulk Power System

Abstract

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.

Keywords

• active frequency response
• bulk power system
• support vector clustering
• wide area measurement system
• frequency dynamic curve
• primary frequency control