Preprint Article Version 1 This version not peer reviewed

Load Shedding Control Strategy Based on Transient Instability Evaluation of Power System Using Artificial Neural Network and Analytic Hierarchy Process Algorithm

Version 1 : Received: 4 September 2017 / Approved: 5 September 2017 / Online: 5 September 2017 (05:02:18 CEST)

How to cite: Trong, N.L.; Ngoc, A.N.; Huy, A.Q.; Phan Thi Thanh, B. Load Shedding Control Strategy Based on Transient Instability Evaluation of Power System Using Artificial Neural Network and Analytic Hierarchy Process Algorithm. Preprints 2017, 2017090014 (doi: 10.20944/preprints201709.0014.v1). Trong, N.L.; Ngoc, A.N.; Huy, A.Q.; Phan Thi Thanh, B. Load Shedding Control Strategy Based on Transient Instability Evaluation of Power System Using Artificial Neural Network and Analytic Hierarchy Process Algorithm. Preprints 2017, 2017090014 (doi: 10.20944/preprints201709.0014.v1).

Abstract

Emergency control load-shedding is a key solution to prevent blackouts in the power system. This paper proposed a new model of emergency controls load shedding based on the fast identification of the unstable state of the power system. K-means clustering algorithm divided the instability mode into the clusters. The results of analysis of this cluster were used as the basis for classification control. Building load shedding strategies is consisted of the pre-designed rules based on AHP algorithm. When the recognition of the power system “instability” is detected, the signal of load shedding control is triggered immediately, therefore the decision time is greatly shortened comparing to the traditional methods. The effectiveness of the proposed method was tested on the IEEE 39-bus to overcome the limitations of the last traditional methods.

Subject Areas

emergency control; load shedding; artificial neural network; dynamic power system stability

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