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Year 2024, Volume: 11 Issue: 1, 48 - 57, 13.03.2024
https://doi.org/10.31202/ecjse.1316748

Abstract

References

  • [1] L. Ma, L. Wang, and Z. Liu, ‘‘Soft open points-assisted resilience enhancement of power distribution networks against cyber risks,’’ IEEE Transactions on Power Systems, vol. 38, no. 1, pp. 31–41, 2023.
  • [2] Z. Chu, S. Lakshminarayana, B. Chaudhuri, and F. Teng, ‘‘Mitigating load-altering attacks against power grids using cyber-resilient economic dispatch,’’ IEEE Transactions on Smart Grid, vol. 14, no. 4, pp. 3164–3175, 2023.
  • [3] P. Venkatesh and N. Visali, ‘‘Machine learning for hybrid line stability ranking index in polynomial load modeling under contingency conditions,’’ Intelligent Automation Soft Computing, vol. 37, no. 1, pp. 1001–1012, 2023.
  • [4] M. M. Roomi, W. S. Ong, S. M. S. Hussain, and D. Mashima, ‘‘Iec 61850 compatible openplc for cyber attack case studies on smart substation systems,’’ IEEE Access, vol. 10, pp. 9164–9173, 2022.
  • [5] S. Wang, Y. Jin, and M. Cai, ‘‘Enhancing the robustness of networks against multiple damage models using a multifactorial evolutionary algorithm,’’ IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 53, no. 7, pp. 4176–4188, 2023.
  • [6] P. Venkatesh and N. Visali, ‘‘Application of machine learning to generate a contingency ranking for power system security,’’ in 2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS), I. Coimbatore, Ed., 2023, pp. 590–595.
  • [7] A. A. Eladl, M. I. Basha, and A. A. ElDesouky, ‘‘Multi-objective-based reactive power planning and voltage stability enhancement using facts and capacitor banks,’’ Electrical Engineering, vol. 104, no. 5, pp. 3173–3196, 2022.
  • [8] X. Chen, L. Huang, D. Zheng, J. Chen, and X. Li, ‘‘Research and application of communication security in security and stability control system of power grid,’’ in 2022 Seventh Asia Conference on Power and Electrical Engineering (ACPEE), C. Hangzhou, Ed., 2022, pp. 1215–1221.
  • [9] B. L. al., ‘‘The voltage security region calculation method of receiving-end power system based on the equivalence of transient process,’’ IEEE Access, vol. 10, pp. 95 083–95 092, 2022.
  • [10] H. Delkhosh and H. Seifi, ‘‘Power system frequency security index considering all aspects of frequency profile,’’ IEEE Transactions on Power Systems, vol. 36, no. 2, pp. 1656–1659, 2021.

Evaluation and Improvement of Power System Security with the Application of Machine Learning

Year 2024, Volume: 11 Issue: 1, 48 - 57, 13.03.2024
https://doi.org/10.31202/ecjse.1316748

Abstract

The electricity grid has added many renewable and non-renewable energy sources to meet expanding demand. Sudden load variations exacerbate generator, transmission line, and distribution network issues. Load modelling choices are crucial for system prediction. This study indicates that ZIP load models with contingency criteria can accurately forecast load behaviour over time. The NR method predicts the contingency ranking with the High Bride Line Stability Ranking Index (HLSRI) under single line outage conditions, and an artificial neural network (ANN) is trained to predict the severity of the line outage and the system's behaviour. A mathematical model was utilised to analyse stability and cost with and without the UPFC and IPFC. Machine learning (ML) is used to rapidly predict the most affected transmission line during a contingency by clustering data using the J48 algorithm for the location of compensating devices. The PSO algorithm is used to develop an objective function to minimise fuel costs by maximising generating capacity. A transmission line failure and load variation might damage the electrical system. This study prioritises transmission line breakdowns and load changes. Power system security analysis provides power system status.

References

  • [1] L. Ma, L. Wang, and Z. Liu, ‘‘Soft open points-assisted resilience enhancement of power distribution networks against cyber risks,’’ IEEE Transactions on Power Systems, vol. 38, no. 1, pp. 31–41, 2023.
  • [2] Z. Chu, S. Lakshminarayana, B. Chaudhuri, and F. Teng, ‘‘Mitigating load-altering attacks against power grids using cyber-resilient economic dispatch,’’ IEEE Transactions on Smart Grid, vol. 14, no. 4, pp. 3164–3175, 2023.
  • [3] P. Venkatesh and N. Visali, ‘‘Machine learning for hybrid line stability ranking index in polynomial load modeling under contingency conditions,’’ Intelligent Automation Soft Computing, vol. 37, no. 1, pp. 1001–1012, 2023.
  • [4] M. M. Roomi, W. S. Ong, S. M. S. Hussain, and D. Mashima, ‘‘Iec 61850 compatible openplc for cyber attack case studies on smart substation systems,’’ IEEE Access, vol. 10, pp. 9164–9173, 2022.
  • [5] S. Wang, Y. Jin, and M. Cai, ‘‘Enhancing the robustness of networks against multiple damage models using a multifactorial evolutionary algorithm,’’ IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 53, no. 7, pp. 4176–4188, 2023.
  • [6] P. Venkatesh and N. Visali, ‘‘Application of machine learning to generate a contingency ranking for power system security,’’ in 2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS), I. Coimbatore, Ed., 2023, pp. 590–595.
  • [7] A. A. Eladl, M. I. Basha, and A. A. ElDesouky, ‘‘Multi-objective-based reactive power planning and voltage stability enhancement using facts and capacitor banks,’’ Electrical Engineering, vol. 104, no. 5, pp. 3173–3196, 2022.
  • [8] X. Chen, L. Huang, D. Zheng, J. Chen, and X. Li, ‘‘Research and application of communication security in security and stability control system of power grid,’’ in 2022 Seventh Asia Conference on Power and Electrical Engineering (ACPEE), C. Hangzhou, Ed., 2022, pp. 1215–1221.
  • [9] B. L. al., ‘‘The voltage security region calculation method of receiving-end power system based on the equivalence of transient process,’’ IEEE Access, vol. 10, pp. 95 083–95 092, 2022.
  • [10] H. Delkhosh and H. Seifi, ‘‘Power system frequency security index considering all aspects of frequency profile,’’ IEEE Transactions on Power Systems, vol. 36, no. 2, pp. 1656–1659, 2021.
There are 10 citations in total.

Details

Primary Language English
Subjects Engineering Practice
Journal Section Makaleler
Authors

Venkatesh P 0000-0003-3124-5396

Dr Visali N 0000-0001-5194-5854

Publication Date March 13, 2024
Submission Date June 19, 2023
Acceptance Date January 15, 2024
Published in Issue Year 2024 Volume: 11 Issue: 1

Cite

IEEE V. P and D. V. N, “Evaluation and Improvement of Power System Security with the Application of Machine Learning”, El-Cezeri Journal of Science and Engineering, vol. 11, no. 1, pp. 48–57, 2024, doi: 10.31202/ecjse.1316748.
Creative Commons License El-Cezeri is licensed to the public under a Creative Commons Attribution 4.0 license.
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