Abstract
A reasonable islanding strategy of a power system is the final resort for preventing a cascading failure and/or a large-area blackout from occurrence. In recent years, the applications of wide area measurement systems (WAMS) in emergency control of power systems are increasing. Therefore, a new WAMS-based controlled islanding scheme for interconnected power systems is proposed. First, four similarity indexes associated with the trajectories of generators are defined, and the weights of these four indexes are determined by using the well-developed entropy theory. Then, a coherency identification algorithm based on hierarchical clustering is presented to determine the coherent groups of generators. Secondly, an optimization model for determining controlled islanding schemes based on the coherent groups of generators is developed to seek the optimal cutset. Finally, a 16-generator 68-bus power system and a reduced WECC 29-unit 179-bus power system are employed to demonstrate the proposed WAMS-based controlled islanding schemes, and comparisons with existing slow coherency based controlled islanding strategies are also carried out.
Highlights
Due to the ever-increasing energy demand, power systems are operating closer to their operation limits, and the growing complexity of power systems and the inevitable uncertainties in power system operation introduced by fast penetration of renewable stochastic generation increase the possibility of power system failures [1, 2]
In [16], an algorithm based on principal component analysis is presented for identifying coherent generators of an interconnected power system by using the measured data sets of generator speeds and bus angles
A coherency identification algorithm is first presented to determine the coherent generation groups based on the hierarchical clustering and wide area measurement systems (WAMS)
Summary
Due to the ever-increasing energy demand, power systems are operating closer to their operation limits, and the growing complexity of power systems and the inevitable uncertainties in power system operation introduced by fast penetration of renewable stochastic generation (such as wind and solar) increase the possibility of power system failures [1, 2]. Several methods have been proposed to split a power system into several islands [7,8,9,10,11,12], and some controlled islanding schemes are based on the coherent groups of generators in a given power system. An identification algorithm of the controlling group of generators is presented and a new power system islanding scheme is proposed based on the unified stability control framework in [13]. In [16], an algorithm based on principal component analysis is presented for identifying coherent generators of an interconnected power system by using the measured data sets of generator speeds and bus angles. The Fourier analysis method is proposed in [18] to identify the coherent groups of generators by analyzing the generator speed sets measured by WAMS. N is the total number of the sampling points; Tn is the time of the nth sampling point; dm;n and xm;n are the generator angle and rotating speed of the mth generator measured by PMUs at the nth sampling point (i.e. Tn), respectively
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