Abstract
In view of the current situation that the existing power grid operation risk assessment cannot be directly applied to the distribution network operation risk early warning, a power system operation risk early warning method based on chaos algorithm is proposed, the power system operation risk categories and incentives are analyzed, and the power system operation risk evaluation index is constructed based on chaos algorithm, which simplifies the power system operation risk early warning steps. Finally, it is confirmed by experiments, The power system operation risk early warning method based on chaos algorithm has high practicability and accuracy, and fully meets the research requirements.
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References
Lian, J., Fang, S., Zhou, Y.: Model predictive control of the fuel cell cathode system based on state quantity estimation. Comput. Simul. 37(07), 119–122 (2020)
Balaska, N., Ahmida, Z., Belmeguenai, A., Boumerdassi, S.: Image encryption using a combination of Grain-128a algorithm and Zaslavsky chaotic map. IET Image Proc. 14(6), 1120–1131 (2020)
Meng, L., Yin, S., Zhao, C., Li, H., Sun, Y.: An improved image encryption algorithm based on chaotic map** and discrete wavelet transform domain. Int. J. Netw. Secur. 22(1), 155–160 (2020)
Yang, F.: A fractional-order CNN hyperchaotic system for image encryption algorithm. Phys. Scr. 96(3), 035209 (2021). (17pp)
Sharma, E., Deo, R.C., Prasad, R., Parisi, A.V.: A hybrid air quality early-warning framework: an hourly forecasting model with online sequential extreme learning machines and empirical mode decomposition algorithms. Sci. Total Environ. 709, 135934.1-135934.23 (2020)
Zhu, Y., Li, G., Tang, S., Jiang, W., Zheng, Z.: Parameter identification method of hydraulic automatic gauge control system based on chaotic wolf pack optimization algorithm. AIP Adv. 11(5), 055302 (2021)
Mohammed, R., Jawad, L.M.: Secure image encryption scheme using chaotic maps and RC4 algorithm. Solid State Technol. 63(3), 3449–3465 (2020)
Ouertani, M.W., Manita, G., Korbaa, O.: Chaotic lightning search algorithm. Soft Comput. 25(3), 2039–2055 (2020). https://doi.org/10.1007/s00500-020-05273-0
Zhao, R., et al.: Selfish herd optimization algorithm based on chaotic strategy for adaptive IIR system identification problem. Soft Comput. 24(10), 7637–7684 (2019). https://doi.org/10.1007/s00500-019-04390-9
Zhang, C., Ding, S.: A stochastic configuration network based on chaotic sparrow search algorithm. Knowl. Based Syst. 220(10), 106924 (2021)
Chen, Y., Ran, Y., Wang, Z., Li, X., Yang, X., Zhang, G.: An extended MULTIMOORA method based on OWGA operator and Choquet integral for risk prioritization identification of failure modes. Eng. Appl. Artif. Intell. 91, 103605.1-103605.12 (2020)
Khalilzadeh, M., Shakeri, H., Zohrehvandi, S.: Risk identification and assessment with the fuzzy DEMATEL-ANP method in oil and gas projects under uncertainty. Procedia Comput. Sci. 181(3), 277–284 (2021)
Singh, V.P., Ujjwal, R.L.: Threat identification and risk assessments for named data networking architecture using SecRam. Int. J. Knowl. Based Intell. Eng. Syst. 25(1), 33–47 (2021)
Lo, H.-W., Shiue, W., Liou, J.J.H., Tzeng, G.-H.: A hybrid MCDM-based FMEA model for identification of critical failure modes in manufacturing. Soft Comput. 24(20), 15733–15745 (2020). https://doi.org/10.1007/s00500-020-04903-x
Le, V.D., Ngoc, T.T., Le, C.Q.: Analyze the sub-synchronous resonance risk of thermal power plants and take an effective solution to suppress: a case study for Vietnamese power system. J. Electr. Syst. 16(4), 448–477 (2020)
Wu, J., Wu, Z., Mao, X., Wu, F., Tang, H., Chen, L.: Risk early warning method for distribution system with sources-networks - loads-vehicles based on fuzzy C-mean clustering. Electr. Power Syst. Res. 180, 1060591–10605913 (2020)
Suo, C., Sun, H., Zhang, W., Zhou, N., Chen, W.: Adaptive safety early warning device for non-contact measurement of HVDC electric field. Electronics 9(2), 329 (2020)
Li, X., Liu, J., Bai, M., Li, J., Yu, D.: An LSTM based method for stage performance degradation early warning with consideration of time-series information. Energy 226(10), 120398 (2021)
Findlay, M., Peaslee, D., Stetter, J.R., Waller, S., Smallridge, A.: Distributed sensors for wildfire early warnings. J. Electrochem. Soc. 169(2), 020553 (2022). (13pp)
Kandanaarachchi, S., Anantharama, N., Munoz, M.A.: Early detection of vegetation ignition due to powerline faults. IEEE Trans. Power Deliv. 36(3), 1324–1334 (2021)
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Dai, S., Zhu, T., Wang, B.L., Wang, Y.Y., Lu, X.X. (2023). Research on Early Warning Method of Power System Operation Risk Based on Chaos Algorithm. In: Xue, Y., Zheng, Y., Gómez-Expósito, A. (eds) Proceedings of the 7th PURPLE MOUNTAIN FORUM on Smart Grid Protection and Control (PMF2022). PMF 2022. Springer, Singapore. https://doi.org/10.1007/978-981-99-0063-3_23
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DOI: https://doi.org/10.1007/978-981-99-0063-3_23
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