Kurbatsky V., Tomin N. Identification of pre-emergency states in the electric power system on the basis of machine learning technologies // Proceedings of the World Congress on Intelligent Control and Automation (WCICA). 2016. P.378-383. ISBN (print): 9 781 467 . DOI: 10.1109/WCICA.2016.7578291 The paper proposes a concept of an intelligent system for early detection of pre-emergency state in electric power system as an option of preventive operation and emergency control. The main goal of such...
Теги: artificial intelligence , electric power systems , intelligent control , intelligent systems , learning algorithms , learning systems , construction principle , emergency control , emergency situation , emergeTomin N.V., Kurbatsky V.G., Sidorov D.N., Zhukov A.V. Machine Learning Techniques for Power System Security Assessment // IFAC-PapersOnLine. Vol.49. No.27. 2016. P.445-450. DOI: 10.1016/j.ifacol.2016.10.773 Modern electricity grids continue to be vulnerable to large-scale blackouts. As all states leading to large-scale blackouts are unique, there is no algorithm to identify pre-emergency states. Moreover, numerical conventional methods are computationally expensive, which makes it difficult to use...
Теги: artificial intelligence , electric power system security , electric power transmission networks , learning algorithms , learning systems , numerical methods , pattern recognition , smart power grids , blackouVoropai N., Kurbatsky V., Tomin N., Panasetsky D. Improving power system monitoring and control in Russian modern megalopolises // Proceedings of the 18th Mediterranean Electrotechnical Conference: Intelligent and Efficient Technologies and Services for the Citizen, MELECON 2016. 1 p. ISBN (print): 9 781 509 . DOI: 10.1109/MELCON.2016.7495341 In the paper a new intelligent system for monitoring and control of a complex multi-loop power system operation is developed to warn about dangerous states...
Теги: artificial intelligence , control , disaster prevention , disasters , electric power system control , intelligent systems , monitoring , standby power systems , transients , disaster management , feasibility stNegnevitsky M., Tomin N., Kurbatsky V., Panasetsky D., Zhukov A., Rehtanz C. A random forest-based approach for voltage security monitoring in a power system // 2015 IEEE Eindhoven PowerTech, PowerTech 2015. 1 p. ISBN (print): 9781479976. DOI: 10.1109/PTC.2015.7232460 Voltage collapse is a critical problem that impacts power system operational security. Timely and accurate assessment of voltage security is necessary to detect alarm states in order to prevent a large-scale blackout. This paper presents...
Теги: artificial intelligence , decision trees , electric power system security , learning systems , blackout , critical problems , large-scale blackout , operational security , random forests , security monitoringPanasetsky D., Tomin N., Voropai N., Kurbatsky V., Zhukov A., Sidorov D. Development of software for modelling decentralized intelligent systems for security monitoring and control in power systems // Proc. of Int. Conf. IEEE Power Tech, Eindhoven, Netherlands. 2015. 1 p. ISBN (print): 9781479976. DOI: 10.1109/PTC.2015.7232553 With rapidly increasing complexity of power grids in Europe, North America and Asia, liberalization of electricity markets and increasing penetration of renewable energy...
Теги: artificial intelligence , electric power system control , electric power system security , intelligent agents , intelligent systems , learning systems , matlab , monitoring , multi agent systems , power contro
