Electric Systems

Modeling & optimization of power systems and electromagnetic machines.

Our research in this area includes flexible and resilient power system design and operational optimization; modeling and analysis of electric machines for applications such as fault detection of motors, power efficiency improvement and design complexity reduction.

  • Researchers

  • Awards

    •  AWARD   Best conference paper of IEEE PES-GM 2020
      Date: June 18, 2020
      Awarded to: Tong Huang, Hongbo Sun, K.J. Kim, Daniel Nikovski, Le Xie
      MERL Contacts: Kyeong Jin (K.J.) Kim; Daniel Nikovski; Hongbo Sun
      Research Areas: Data Analytics, Electric Systems, Optimization
      Brief
      • A paper on A Holistic Framework for Parameter Coordination of Interconnected Microgrids Against Natural Disasters, written by Tong Huang, a former MERL intern from Texas A&M University, has been selected as one of the Best Conference Papers at the 2020 Power and Energy Society General Meeting (PES-GM). IEEE PES-GM is the flagship conference for the IEEE Power and Energy Society. The work was done in collaboration with Hongbo Sun, K. J. Kim, and Daniel Nikovski from MERL, and Tong's advisor, Prof. Le Xie from Texas A&M University.
    •  

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  • News & Events


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  • Internships

    • MD1381: Electric Motor Design

      MERL is seeking a motivated and qualified individual to conduct research in design, modeling, and simulation of electrical machines. The ideal candidate should have solid backgrounds in modeling (including model reduction)/co-simulation of electromagnetics and thermal dynamics of electrical machines, and demonstrated capability to publish results in leading conferences/journals. Experience with ANSYS, COMSOL, and real-time control experiments involving motor drives is a strong plus. Senior Ph.D. students in electrical or mechanical engineering are encouraged to apply. Start date for this internship is flexible and the duration is about 3-6 months.

    • MD1377: Adaptive Optimal Control of Electrical Machines

      MERL is seeking a motivated and qualified individual to conduct research in control of electrical machines. The ideal candidate should have solid backgrounds in adaptive dynamic programming and state/parameter estimation for electrical machines, demonstrated capability to publish results in leading conferences/journals, and experience with real-time control experiments involving high power devices. Senior Ph.D. students are encouraged to apply. Start date for this internship is flexible and the duration is about 3 months.

    • DA1536: Micro-grid fault analysis and detection

      MERL is seeking a highly motivated and qualified individual to join our summer internship program and conduct research in the area of micro-grid fault analysis and detection. The ideal candidate should have a solid background in micro-grid operation, transient analysis, fault detection, and power system protection. Experience with MATLAB or C/C++/Python is required. The duration of the internship is expected to be 3-6 months, and the start date is flexible. Candidates in their senior or junior years of a Ph.D. program are encouraged to apply. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.


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  • Recent Publications

    •  Zhang, S., Ye, F., Wang, B., Habetler, T.G., "Semi-Supervised Bearing Fault Diagnosis and Classification using Variational Autoencoder-Based Deep Generative Models", IEEE Sensors Journal, DOI: 10.1109/JSEN.2020.3040696, Vol. 21, No. 5, pp. 6476-6486, January 2021.
      BibTeX TR2021-002 PDF
      • @article{Zhang2021jan,
      • author = {Zhang, Shen and Ye, Fei and Wang, Bingnan and Habetler, Thomas G},
      • title = {Semi-Supervised Bearing Fault Diagnosis and Classification using Variational Autoencoder-Based Deep Generative Models},
      • journal = {IEEE Sensors Journal},
      • year = 2021,
      • volume = 21,
      • number = 5,
      • pages = {6476--6486},
      • month = jan,
      • doi = {10.1109/JSEN.2020.3040696},
      • url = {https://www.merl.com/publications/TR2021-002}
      • }
    •  Xiao, D., Sun, H., Nikovski, D.N., Shoichi, K., Mori, K., Hashimoto, H., "CVaR-constrained Stochastic Bidding Strategy for a Virtual Power Plant with Mobile Energy Storages", IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), DOI: 10.1109/ISGT-Europe47291.2020.9248799, November 2020, pp. 1171-1175.
      BibTeX TR2020-142 PDF
      • @inproceedings{Xiao2020nov,
      • author = {Xiao, Dongliang and Sun, Hongbo and Nikovski, Daniel N. and Shoichi, Kitamura and Mori, Kazuyuki and Hashimoto, Hiroyuki},
      • title = {CVaR-constrained Stochastic Bidding Strategy for a Virtual Power Plant with Mobile Energy Storages},
      • booktitle = {IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)},
      • year = 2020,
      • pages = {1171--1175},
      • month = nov,
      • doi = {10.1109/ISGT-Europe47291.2020.9248799},
      • url = {https://www.merl.com/publications/TR2020-142}
      • }
    •  Zhang, S., Ye, F., Wang, B., Habetler, T.G., "Few-Shot Bearing Anomaly Detection via Model-Agnostic Meta-Learning", International Conference on Electrical Machines and Systems (ICEMS), DOI: 10.23919/ICEMS50442.2020.9291099, November 2020, pp. 1341-1346.
      BibTeX TR2020-151 PDF
      • @inproceedings{Zhang2020nov2,
      • author = {Zhang, Shen and Ye, Fei and Wang, Bingnan and Habetler, Thomas G},
      • title = {Few-Shot Bearing Anomaly Detection via Model-Agnostic Meta-Learning},
      • booktitle = {2020 23rd International Conference on Electrical Machines and Systems (ICEMS)},
      • year = 2020,
      • pages = {1341--1346},
      • month = nov,
      • doi = {10.23919/ICEMS50442.2020.9291099},
      • url = {https://www.merl.com/publications/TR2020-151}
      • }
    •  Sun, H., Shoichi, K., Nikovski, D.N., Mori, K., Hashimoto, H., "Illegitimate Trade Detection for Electricity Energy Markets", International Conference on Smart Grids and Energy Systems (SGES), DOI: doi: 10.110910.1109/SGES51519.2020.00066, November 2020.
      BibTeX TR2020-147 PDF
      • @inproceedings{Sun2020nov,
      • author = {Sun, Hongbo and Shoichi, Kitamura and Nikovski, Daniel N. and Mori, Kazuyuki and Hashimoto, Hiroyuki},
      • title = {Illegitimate Trade Detection for Electricity Energy Markets},
      • booktitle = {International Conference on Smart Grids and Energy Systems (SGES)},
      • year = 2020,
      • month = nov,
      • doi = {doi: 10.110910.1109/SGES51519.2020.00066},
      • url = {https://www.merl.com/publications/TR2020-147}
      • }
    •  Huang, T., Sun, H., Kim, K.J., Nikovski, D.N., Xie, L., "A Holistic Framework for Parameter Coordination of Interconnected Microgrids against Disasters", IEEE Power & Energy Society General Meeting (PES), DOI: 10.1109/PESGM41954.2020.9281628, June 2020.
      BibTeX TR2020-082 PDF
      • @inproceedings{Huang2020jun,
      • author = {Huang, Tong and Sun, Hongbo and Kim, Kyeong Jin and Nikovski, Daniel N. and Xie, Le},
      • title = {A Holistic Framework for Parameter Coordination of Interconnected Microgrids against Disasters},
      • booktitle = {IEEE Power & Energy Society General Meeting (PES)},
      • year = 2020,
      • month = jun,
      • publisher = {IEEE},
      • doi = {10.1109/PESGM41954.2020.9281628},
      • url = {https://www.merl.com/publications/TR2020-082}
      • }
    •  Tian, N., Fang, H., Chen, J., Wang, Y., "Nonlinear Double-Capacitor Model for Rechargeable Batteries: Modeling, Identification and Validation", IEEE Transactions on Control Systems Technology, DOI: 10.1109/TCST.2020.2976036, pp. 1-15, April 2020.
      BibTeX TR2020-035 PDF
      • @article{Tian2020apr,
      • author = {Tian, Ning and Fang, Huazhen and Chen, Jian and Wang, Yebin},
      • title = {Nonlinear Double-Capacitor Model for Rechargeable Batteries: Modeling, Identification and Validation},
      • journal = {IEEE Transactions on Control Systems Technology},
      • year = 2020,
      • pages = {1--15},
      • month = apr,
      • doi = {10.1109/TCST.2020.2976036},
      • url = {https://www.merl.com/publications/TR2020-035}
      • }
    •  Poudel, S., Sun, H., Nikovski, D.N., Zhang, J., "Distributed Average Consensus Algorithm for Damage Assessment of Power Distribution system", IEEE PES Innovative Smart Grid Technologies Conference (ISGT), DOI: 10.1109/ISGT45199.2020.9087643, February 2020.
      BibTeX TR2020-013 PDF
      • @inproceedings{Poudel2020feb,
      • author = {Poudel, Shiva and Sun, Hongbo and Nikovski, Daniel N. and Zhang, Jinyun},
      • title = {Distributed Average Consensus Algorithm for Damage Assessment of Power Distribution system},
      • booktitle = {IEEE PES Innovative Smart Grid Technologies Conference (ISGT)},
      • year = 2020,
      • month = feb,
      • doi = {10.1109/ISGT45199.2020.9087643},
      • issn = {2472-8152},
      • isbn = {978-1-7281-3103-0},
      • url = {https://www.merl.com/publications/TR2020-013}
      • }
    •  Xu, H., Sun, H., Nikovski, D.N., Kitamura, S., Mori, K., Hashimoto, H., "Deep Reinforcement Learning for Joint Bidding and Pricing of Load Serving Entity", IEEE Transactions on smart grids, DOI: 10.1109/TSG.2019.2903756, Vol. 10, No. 6, pp. 6366-6375, January 2020.
      BibTeX TR2020-003 PDF
      • @article{Xu2020jan,
      • author = {Xu, Hanchen and Sun, Hongbo and Nikovski, Daniel N. and Kitamura, Shoichi and Mori, Kazuyuki and Hashimoto, Hiroyuki},
      • title = {Deep Reinforcement Learning for Joint Bidding and Pricing of Load Serving Entity},
      • journal = {IEEE Transactions on smart grids},
      • year = 2020,
      • volume = 10,
      • number = 6,
      • pages = {6366--6375},
      • month = jan,
      • doi = {10.1109/TSG.2019.2903756},
      • issn = {1949-3061},
      • url = {https://www.merl.com/publications/TR2020-003}
      • }
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