Open Access

ARTICLE

Parallel Integrated Model-Driven and Data-Driven Online Transient Stability Assessment Method for Power System

Ying Zhang¹, Xiaoqing Han², Chao Zhang¹, Ying Qu¹, Yang Liu¹, Gengwu Zhang^2,*

1 Electric Power Research Institute, State Grid Shanxi Electric Power Co., Ltd., Taiyuan, 030000, China
2 College of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan, 030024, China

* Corresponding Author: Gengwu Zhang. Email:

(This article belongs to the Special Issue: Hybrid Artificial Intelligence and Machine Learning Techniques in Renewable Energy Systems )

Energy Engineering 2023, 120(11), 2585-2609. https://doi.org/10.32604/ee.2023.026816

Received 27 September 2022; Accepted 20 June 2023; Issue published 31 October 2023

Abstract

More and more uncertain factors in power systems and more and more complex operation modes of power systems put forward higher requirements for online transient stability assessment methods. The traditional model-driven methods have clear physical mechanisms and reliable evaluation results but the calculation process is time-consuming, while the data-driven methods have the strong fitting ability and fast calculation speed but the evaluation results lack interpretation. Therefore, it is a future development trend of transient stability assessment methods to combine these two kinds of methods. In this paper, the rate of change of the kinetic energy method is used to calculate the transient stability in the model-driven stage, and the support vector machine and extreme learning machine with different internal principles are respectively used to predict the transient stability in the data-driven stage. In order to quantify the credibility level of the data-driven methods, the credibility index of the output results is proposed. Then the switching function controlling whether the rate of change of the kinetic energy method is activated or not is established based on this index. Thus, a new parallel integrated model-driven and data-driven online transient stability assessment method is proposed. The accuracy, efficiency, and adaptability of the proposed method are verified by numerical examples.

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Keywords

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