کاربرد استخراج قواعد انجمنی در شناسایی علت خاموشی‌ سیستم‌های هوشمند توزیع انرژی الکتریکی

[1] "U.S. Energy Information Administration (EIA)", [Online]. Available: https://www.eia.gov/tools/faqs/faq.php?id=108&t=1. [Accessed 13 8 2020]. [2] Guo T. and Milanović J. V., "Online Identification of Power System Dynamic Signature Using PMU Measurements and Data Mining", IEEE Trans, Power Systems, Vol. 31, No. 3, pp. 1760-1768, May. 2016. [3] Wang B., Fang B., Wang Y., Liu H. and Liu Y., "Power System Transient Stability Assessment Based on Big Data and the Core Vector Machine", IEEE Trans, Smart Grid, Vol. 7, No. 5, pp. 2561 - 2570, Sept. 2016. [4] Farajollahi M., Shahsavari A., Stewart E. M. and Mohsenian-Rad H., "Locating the Source of Events in Power Distribution Systems Using Micro-PMU Data", IEEE Trans, Power Systems, Vol. 33, No. 6, pp. 6343 - 6354, Nov. 2018. [5] Chicco G., Napoli R., Piglione F., Postolache P., Scutariu M. and Toader C., "Load pattern-based classification of electricity customers", IEEE Trans, Power Systems, Vol. 19, No. 2, pp. 1232 - 1239, May. 2004. [6] Chicco G. and Ilie I.-S., "Support Vector Clustering of Electrical Load Pattern Data", IEEE Trans, on Power Systems, Vol. 24, No. 3, pp. 1619 - 1628, Aug. 2009. [7] Singh S. K., Bose R. and Joshi A., "Energy theft detection in advanced metering infrastructure", in 2018 IEEE 4th World Forum on Internet of Things (WF-IoT), Singapore, Feb. 2018. [8] Chien C.-F. Chen S.-L. and Lin Y.-S., "Using Bayesian network for fault location on distribution feeder", IEEE Trans, Power Delivery, Vol. 17, No. 3, pp. 785 - 793, Jul. 2002. [9] Peng J.-T., Chien C. and Tseng T., "Rough set theory for data mining for fault diagnosis on distribution feeder", IEE Proceedings - Generation, Transmission and Distribution, Vol. 151, No. 6, pp. 689 - 697, Nov. 2004. [10] Deng X., Yuan R., Xiao Z., Li T. and Wang K. L. L., "Fault location in loop distribution network using SVM technology", International Journal of Electrical Power & Energy Systems, Vol. 65, pp. 254-261, Feb. 2015. [11] Recioui A., Benseghier B. and Khalfallah H., "Power system fault detection, classification and location using the K-Nearest Neighbors", in 2015 4th International Conference on Electrical Engineering (ICEE), Boumerdes, Dec. 2015. [12] Wanik D. W., Anagnostou E. N., Hartman B. M., Frediani M. E. and Astitha M., "Storm outage modeling for an electric distribution network in Northeastern USA", Natural Hazards, Vol. 79, p. 1359–1384, Jul. 2015. [13] Kankanala P., Pahwa A. and Das S., "Regression models for outages due to wind and lightning on overhead distribution feeders", in 2011 IEEE Power and Energy Society General Meeting, Detroit, Jul. 2011. [14] Nateghi R., Guikema S. D. and Quiring S. M., "Forecasting hurricane-induced power outage durations", Natural Hazard, Vol. 74, p. 1795–1811, Jun. 2014. [15] Sahai S. and Pahwa A., "A Probabilistic Approach for Animal-Caused Outages in Overhead Distribution Systems", in 2006 International Conference on Probabilistic Methods Applied to Power Systems, Stockholm, Jun. 2006. [16] Radmer D., Kuntz P., Christie R., Venkata S. and Fletcher R., "Predicting vegetation-related failure rates for overhead distribution feeders", IEEE Trans, Power Delivery, Vol. 17, No. 4, pp. 1170 - 1175, Oct. 2002. [17] Doostan M., Sohrabi R. and Chowdhury B., "A data‐driven approach for predicting vegetation‐related outages in power distribution systems," International Transactions on Electrical Energy Systems, Vol. 30, No. 1, Aug. 2019. [18] Hosseini Z. S., Mahoor M. and Khodaei A., "AMI-Enabled Distribution Network Line Outage Identification via Multi-Label SVM", IEEE Trans, Smart Grid, Vol. 9, No. 5, pp. 5470 - 5472, Sept. 2018. [19] Xu L. and Chow M.-Y., "A classification approach for power distribution systems fault cause identification", IEEE Trans, Power Systems, Vol. 21, No. 1, pp. 53 - 60, Feb. 2006. [20] Doostan M. and Chowdhury B. H., "Power distribution system equipment failure identification using machine learning algorithms", in 2017 IEEE Power & Energy Society General Meeting, Chicago, Jul. 2017. [21] Doostan M. and Chowdhury B. H., "Power distribution system fault cause analysis by using association rule mining", Electric Power Systems Research, Vol. 152, pp. 140-147, Nov. 2017. [22] Bashkari S., Sami A. and Rastegar M., "Outage Cause Detection in Power Distribution Systems based on Data Mining", IEEE Transactions on Industrial Informatics, Vol. 17, No. 1, pp. 640 - 649, Jan. 2021. [23] "rp5.ru Reliable Prognosis", [Online]. Available: https://rp5.ru/. [Accessed 4 6 2020]. [24] Zaki M. J. and Meira Jr. W., "Chapter 8. Itemset mining", in Data Mining and Analysis: Fundamental Concepts and Algorithms, Cambridge: Cambridge University Press, 2014, pp. 241-268. [25] Han J., Kamber M. and Pei J., "Mining Frequent Patterns, Associations, and Correlations: Basic Concepts and Methods", in Data Mining: Concepts and Techniques, Waltham: Morgan Kaufmann, 2012, pp. 243-278. [26] Pearson K., "X. On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling", The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science, Vol. 50, No. 302, pp. 157-175, 1900. [27] Zaki M. J. and Meira Jr. W., "Chapter 3. Categorical Attributes", in Data Mining and Analysis: Fundamental Concepts and Algorithms, Cambridge: Cambridge University Press, 2014, pp. 71-104.