Power system transient stability preventive control optimization method driven by Stacking Ensemble Learning
The dynamic characteristics of the power system are becoming more and more complex, and the difficulty of operation control is increasing. Preventive control is the main means of power system transient stability control. This paper proposes a stacking ensemble learning-driven power system transient...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-10-01
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| Series: | Energy Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484723008417 |
| _version_ | 1827582180834934784 |
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| author | Zhijun Xie Dongxia Zhang Xiaoqing Han Wei Hu |
| author_facet | Zhijun Xie Dongxia Zhang Xiaoqing Han Wei Hu |
| author_sort | Zhijun Xie |
| collection | DOAJ |
| description | The dynamic characteristics of the power system are becoming more and more complex, and the difficulty of operation control is increasing. Preventive control is the main means of power system transient stability control. This paper proposes a stacking ensemble learning-driven power system transient stability preventive control optimization method. Firstly, a transient stability assessment model based on Stacking Ensemble Deep Belief Nets (SEDBN) network is established in this research. The performance of weak classifiers is improved by SEDBN’s multi-layer ensemble structure, and the created transient stability estimator can extract diverse features and has better robustness and generalization abilities. Secondly, the trained transient stability estimator is integrated into the Aptenodytes Forsteri Optimization (AFO) algorithm as a “transient stability constraint discriminator”. Finally, with the goal of minimizing the cost of preventive control, an optimization algorithm for the preventive control of power system transient stability driven by SEDBN is established. Simulation results on IEEE 39-bus systems show that the proposed method can achieve highly efficient control solutions. |
| first_indexed | 2024-03-08T22:46:49Z |
| format | Article |
| id | doaj.art-f8f2ced8966445e9b69dbeabf739323f |
| institution | Directory Open Access Journal |
| issn | 2352-4847 |
| language | English |
| last_indexed | 2024-03-08T22:46:49Z |
| publishDate | 2023-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Reports |
| spelling | doaj.art-f8f2ced8966445e9b69dbeabf739323f2023-12-17T06:38:47ZengElsevierEnergy Reports2352-48472023-10-019757765Power system transient stability preventive control optimization method driven by Stacking Ensemble LearningZhijun Xie0Dongxia Zhang1Xiaoqing Han2Wei Hu3Shanxi Key Laboratory of Power System Operation and Control, Taiyuan University of Technology, Taiyuan 030024, Shanxi Province, China; State Key Lab of Control and Simulation of Power Systems and Generation Equipments, Department of Electrical Engineering, Tsinghua University, Haidian District, Beijing 100084, China; Corresponding author at: Shanxi Key Laboratory of Power System Operation and Control, Taiyuan University of Technology, Taiyuan 030024, Shanxi Province, China.Shanxi Key Laboratory of Power System Operation and Control, Taiyuan University of Technology, Taiyuan 030024, Shanxi Province, China; China Electric Power Research Institute, Haidian District, Beijing 100192, ChinaShanxi Key Laboratory of Power System Operation and Control, Taiyuan University of Technology, Taiyuan 030024, Shanxi Province, ChinaState Key Lab of Control and Simulation of Power Systems and Generation Equipments, Department of Electrical Engineering, Tsinghua University, Haidian District, Beijing 100084, ChinaThe dynamic characteristics of the power system are becoming more and more complex, and the difficulty of operation control is increasing. Preventive control is the main means of power system transient stability control. This paper proposes a stacking ensemble learning-driven power system transient stability preventive control optimization method. Firstly, a transient stability assessment model based on Stacking Ensemble Deep Belief Nets (SEDBN) network is established in this research. The performance of weak classifiers is improved by SEDBN’s multi-layer ensemble structure, and the created transient stability estimator can extract diverse features and has better robustness and generalization abilities. Secondly, the trained transient stability estimator is integrated into the Aptenodytes Forsteri Optimization (AFO) algorithm as a “transient stability constraint discriminator”. Finally, with the goal of minimizing the cost of preventive control, an optimization algorithm for the preventive control of power system transient stability driven by SEDBN is established. Simulation results on IEEE 39-bus systems show that the proposed method can achieve highly efficient control solutions.http://www.sciencedirect.com/science/article/pii/S2352484723008417Stacking Ensemble LearningAptenodytes Forsteri Optimization algorithmTransient stabilityTransient stability preventive control |
| spellingShingle | Zhijun Xie Dongxia Zhang Xiaoqing Han Wei Hu Power system transient stability preventive control optimization method driven by Stacking Ensemble Learning Energy Reports Stacking Ensemble Learning Aptenodytes Forsteri Optimization algorithm Transient stability Transient stability preventive control |
| title | Power system transient stability preventive control optimization method driven by Stacking Ensemble Learning |
| title_full | Power system transient stability preventive control optimization method driven by Stacking Ensemble Learning |
| title_fullStr | Power system transient stability preventive control optimization method driven by Stacking Ensemble Learning |
| title_full_unstemmed | Power system transient stability preventive control optimization method driven by Stacking Ensemble Learning |
| title_short | Power system transient stability preventive control optimization method driven by Stacking Ensemble Learning |
| title_sort | power system transient stability preventive control optimization method driven by stacking ensemble learning |
| topic | Stacking Ensemble Learning Aptenodytes Forsteri Optimization algorithm Transient stability Transient stability preventive control |
| url | http://www.sciencedirect.com/science/article/pii/S2352484723008417 |
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