Data-driven power system stability assessment
With the increasing energy demand and environmental problems, the stability assessment of power systems has become a topic of great concern. In this paper, I utilized data-driven algorithms to conduct an in-depth study of power system stability problems. In addition, I constructed a stability assess...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/177233 |
| _version_ | 1824456969194307584 |
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| author | Kang, Hongyu |
| author2 | Xu Yan |
| author_facet | Xu Yan Kang, Hongyu |
| author_sort | Kang, Hongyu |
| collection | NTU |
| description | With the increasing energy demand and environmental problems, the stability assessment of power systems has become a topic of great concern. In this paper, I utilized data-driven algorithms to conduct an in-depth study of power system stability problems. In addition, I constructed a stability assessment model based on DT, SVM and ANN using Python. Then I trained and validated the model with a real power system dataset. Through experiments and data results visualization, the accuracy of DT is obtained as 0.9953, SVM as 0.9967 and ANN as 0.9968. Meanwhile, the ROC and AUC curves of ANN and SVM are close to the upper-left intersection, which proves that the model achievement is good. By evaluating and comparing the performance of the models, I found that the proposed models all have good generalization ability and accuracy in forecasting the stability of the power system, with ANN having the best model fit. |
| first_indexed | 2025-02-19T04:02:32Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/177233 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T04:02:32Z |
| publishDate | 2024 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1772332024-05-31T15:44:05Z Data-driven power system stability assessment Kang, Hongyu Xu Yan School of Electrical and Electronic Engineering xuyan@ntu.edu.sg Engineering Power system stability assessment With the increasing energy demand and environmental problems, the stability assessment of power systems has become a topic of great concern. In this paper, I utilized data-driven algorithms to conduct an in-depth study of power system stability problems. In addition, I constructed a stability assessment model based on DT, SVM and ANN using Python. Then I trained and validated the model with a real power system dataset. Through experiments and data results visualization, the accuracy of DT is obtained as 0.9953, SVM as 0.9967 and ANN as 0.9968. Meanwhile, the ROC and AUC curves of ANN and SVM are close to the upper-left intersection, which proves that the model achievement is good. By evaluating and comparing the performance of the models, I found that the proposed models all have good generalization ability and accuracy in forecasting the stability of the power system, with ANN having the best model fit. Bachelor's degree 2024-05-27T00:48:50Z 2024-05-27T00:48:50Z 2024 Final Year Project (FYP) Kang, H. (2024). Data-driven power system stability assessment. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/177233 https://hdl.handle.net/10356/177233 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering Power system stability assessment Kang, Hongyu Data-driven power system stability assessment |
| title | Data-driven power system stability assessment |
| title_full | Data-driven power system stability assessment |
| title_fullStr | Data-driven power system stability assessment |
| title_full_unstemmed | Data-driven power system stability assessment |
| title_short | Data-driven power system stability assessment |
| title_sort | data driven power system stability assessment |
| topic | Engineering Power system stability assessment |
| url | https://hdl.handle.net/10356/177233 |
| work_keys_str_mv | AT kanghongyu datadrivenpowersystemstabilityassessment |