Dr. Anton Loskutov | Energy and Sustainability | Research Excellence Award

Published on by Research Hypothesis

Dr. Anton Loskutov | Energy and Sustainability | Research Excellence Award

Dr. Anton Loskutov | Energy and Sustainability | Research Excellence Award | Dr | Nizhegorodskiy Gosudarstvennyy Tekhnicheskiy University | Research Excellence Award

Dr. Anton Loskutov is an accomplished researcher, Associate Professor, and senior scientist whose work spans electric power systems, relay protection, digital substations, smart distribution networks, and machine-learning-driven automation technologies. Dr. Anton Loskutov completed his engineering education at Nizhny Novgorod State Technical University and earned his Ph.D. from Samara State Technical University, where his research centered on developing and studying novel topologies for medium-voltage smart urban distribution networks. His professional experience includes serving as an Associate Professor in the Department of Electric Power, Electricity Supply, and Power Electronics, as well as working as a senior researcher in the laboratory for autonomous hybrid electric power systems. Throughout his role, Dr. Anton Loskutov has actively contributed to relay protection algorithms, overhead line fault-location methods, intelligent network automation, distributed generation integration, and the application of sequential statistical methods to power system decision-making. His research interests encompass electrical network simulation, data-driven energy analytics, high-voltage system protection, artificial intelligence tools for fault recognition, and the development of advanced emergency mode detection frameworks. Dr. Anton Loskutov’s research skills include computational modeling, machine learning for energy diagnostics, development of protection schemes, system optimization, sequential probability testing, and applied algorithm design for electrical networks. His work is widely published in reputed international journals such as Energies, Algorithms, Information, and Technologies, and he has coauthored multiple papers presented in IEEE conferences and Scopus-indexed proceedings. In recognition of his contribution to the field, Dr. Anton Loskutov is an active member of CIGRE, participating in the B5 subcommittee working group on relay automation modeling technologies and representing young researchers in major international sessions. His honors include selection to the youth section of CIGRE and involvement in significant collaborative power engineering projects. Dr. Anton Loskutov continues to contribute to the academic and engineering community through mentoring, interdisciplinary teamwork, and innovative applied research that enhances the safety, efficiency, and resilience of modern electrical networks. With a strong background in intelligent grid development, a robust publication record, and ongoing participation in international technical communities, Dr. Anton Loskutov stands out as a dedicated scholar whose work significantly advances the modernization of power system protection, automation, and distributed energy technologies.

Profile: Scopus | ORCID

Featured Publications 

  1. Kulikov, A., Loskutov, A., Ilyushin, P., Kurkin, A., & Sluzova, A. (2025). High-voltage overhead power line fault location through sequential determination of faulted section. Technologies.

  2. Kulikov, A., Ilyushin, P., Loskutov, A., & Filippov, S. (2023). Fault location method for overhead power line based on a multi-hypothetical sequential analysis using the Armitage algorithm. Inventions.

  3. Kulikov, A., Loskutov, A., Bezdushniy, D., & Petrov, I. (2023). Decision tree models and machine learning algorithms in the fault recognition on power lines with branches. Energies.

  4. Kulikov, A., Ilyushin, P., & Loskutov, A. (2023). Enhanced readability of electrical network complex emergency modes provided by data compression methods. Information.

  5. Kulikov, A., Ilyushin, P., Loskutov, A., & Filippov, S. (2023). Application of search algorithms in determining fault location on overhead power lines according to the emergency mode parameters. Algorithms.

  6. Kulikov, A., Ilyushin, P., Loskutov, A., Suslov, K., & Filippov, S. (2022). WSPRT methods for improving power system automation devices in the conditions of distributed generation sources operation. Energies.

  7. Kulikov, A., & Loskutov, A. (2022). Relay protection and automation algorithms of electrical networks based on simulation and machine learning methods. Energies.

 

Aleksandr Kulikov | Energy and Sustainability | Research Excellence Award

Published on by Research Hypothesis

Prof. Dr. Aleksandr Kulikov | Energy and Sustainability | Research Excellence Award

Prof. Dr. Aleksandr Kulikov | Energy and Sustainability | Research Excellence Award | Lecturer | Nizhny Novgorod State Technical University | Russia

Prof. Dr. Aleksandr Kulikov is a distinguished scholar in electric power engineering, widely recognized for his advanced expertise in relay protection, emergency automation, distributed generation, digital signal processing, and the cybersecurity of modern electric networks. Prof. Dr. Aleksandr Kulikov holds multiple higher education degrees across engineering and economics, including a doctoral-level qualification in electric power systems, complemented by earlier academic work in radar, radio navigation, and economic system reliability. His professional experience spans leadership positions in major energy enterprises, where he served as Deputy Chief Engineer, Director of trunk electric grid operations, scientific supervisor for government-funded technology programs, and a long-serving professor at the Nizhny Novgorod State Technical University. Throughout his career, Prof. Dr. Aleksandr Kulikov has demonstrated outstanding commitment to academic excellence, supervising master’s students, postgraduate researchers, and doctoral candidates, many of whom have successfully defended their dissertations under his mentorship. His research interests cover a wide spectrum of modern power-system challenges, including high-voltage line fault detection, emergency-mode processing, machine-learning-based grid diagnostics, selective control of power-quality indicators, and the reliability of renewable-integrated microgrids. His research skills span analytical modeling, digital signal processing, industrial frequency analysis, reliability assessment, fault location techniques, and the development of novel algorithms and decision-support systems for complex power networks. Prof. Dr. Aleksandr Kulikov has contributed more than three hundred scientific works, including publications in Scopus-indexed and Web of Science–indexed journals, IEEE conference proceedings, and high-impact engineering journals. His inventions and patents further demonstrate his innovative contributions to advancing electric power technologies. Among his numerous awards and honors are prestigious regional, national, and international distinctions, including medals, honorary diplomas, and recognition for excellence in scientific innovation and contributions to the development of electrical grid infrastructure. His leadership roles include membership in dissertation councils, editorial board service for multiple scientific journals, and expert involvement in federal technology-development programs. Prof. Dr. Aleksandr Kulikov continues to advance the field through active research, academic mentorship, and scientific collaboration, maintaining a significant influence on the evolution of intelligent power systems and modern energy engineering. His longstanding dedication to the scientific community, strong record of innovation, and impact on the reliability of national power systems solidify his status as a leading figure deserving of international recognition.

Profile: ORCID 

Featured Publications 

  1. Kulikov, A., Loskutov, A., Ilyushin, P., Kurkin, A., & Sluzova, A. (2025). High-voltage overhead power line fault location through sequential determination of faulted section technologies.

  2. Ilyushin, P., Papkov, B., Kulikov, A., & Suslov, K. (2025). Algorithm and methods for analyzing power consumption behavior of industrial enterprises considering process characteristics.

  3. Kulikov, A. L., Sevostyanov, A. A., & Ilyushin, P. V. (2023). Analysis of electrical-power quality in modern power-supply systems with selective control of several indicators.

  4. Kulikov, A., Ilyushin, P., Loskutov, A., & Filippov, S. (2023). Application of search algorithms in determining fault location on overhead power lines according to the emergency mode parameters.

  5. Kulikov, A., Loskutov, A., Bezdushniy, D., & Petrov, I. (2023). Decision tree models and machine learning algorithms in the fault recognition on power lines with branches.

  6. Kulikov, A., Ilyushin, P., & Suslov, K. (2023). Enhanced readability of electrical network complex emergency modes provided by data compression methods.

  7. Kulikov, A., Ilyushin, P., Suslov, K., & Filippov, S. (2023). Estimating the error of fault location on overhead power lines by emergency state parameters using an analytical technique.