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

    •  EVENT   MERL 3rd Annual Open House
      Date & Time: Thursday, November 29, 2018; 4-6pm
      MERL Contacts: Marissa Deegan; Elizabeth Phillips; Jeroen van Baar; Anthony Vetro
      Location: 201 Broadway, 8th floor, Cambridge, MA
      Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio
      Brief
      • Snacks, demos, science: On Thursday 11/29, Mitsubishi Electric Research Labs (MERL) will host an open house for graduate+ students interested in internships, post-docs, and research scientist positions. The event will be held from 4-6pm and will feature demos & short presentations in our main areas of research including artificial intelligence, robotics, computer vision, speech processing, optimization, machine learning, data analytics, signal processing, communications, sensing, control and dynamical systems, as well as multi-physyical modeling and electronic devices. MERL is a high impact publication-oriented research lab with very extensive internship and university collaboration programs. Most internships lead to publication; many of our interns and staff have gone on to notable careers at MERL and in academia. Come mix with our researchers, see our state of the art technologies, and learn about our research opportunities. Dress code: casual, with resumes.

        Pre-registration for the event is strongly encouraged:
        merlopenhouse.eventbrite.com

        Current internship and employment openings:
        www.merl.com/internship/openings
        www.merl.com/employment/employment

        Information about working at MERL:
        www.merl.com/employment.
    •  
    •  TALK   Controlling the Grid Edge: Emerging Grid Operation Paradigms
      Date & Time: Thursday, July 7, 2016; 2:00 PM
      Speaker: Dr. Sonja Glavaski, Program Director, ARPA-E
      MERL Host: Arvind Raghunathan
      Research Area: Electric Systems
      Brief
      • The evolution of the grid faces significant challenges if it is to integrate and accept more energy from renewable generation and other Distributed Energy Resources (DERs). To maintain grid's reliability and turn intermittent power sources into major contributors to the U.S. energy mix, we have to think about the grid differently and design it to be smarter and more flexible.

        ARPA-E is interested in disruptive technologies that enable increased integration of DERs by real-time adaptation while maintaining grid reliability and reducing cost for customers with smart technologies. The potential impact is significant, with projected annual energy savings of more than 3 quadrillion BTU and annual CO2 emissions reductions of more than 250 million metric tons.

        This talk will identify opportunities in developing next generation control technologies and grid operation paradigms that address these challenges and enable secure, stable, and reliable transmission and distribution of electrical power. Summary of newly announced ARPA-E NODES (Network Optimized Distributed Energy Systems) Program funding development of these technologies will be presented.
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  • Internships

    • 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.

    • 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.


    See All Internships for Electric Systems
  • Recent Publications

    •  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), 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,
      • 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}
      • }
    •  Zhang, S., Ye, F., Wang, B., Habetler, T.G., "Semi-Supervised Learning of Bearing Anomaly Detection via Deep Variational Autoencoders", arXiv, November 2019.
      BibTeX arXiv
      • @article{Zhang2019nov,
      • author = {Zhang, Shen and Ye, Fei and Wang, Bingnan and Habetler, Thomas G},
      • title = {Semi-Supervised Learning of Bearing Anomaly Detection via Deep Variational Autoencoders},
      • journal = {arXiv},
      • year = 2019,
      • month = nov,
      • url = {https://arxiv.org/abs/1912.01096}
      • }
    •  Poudel, S., Sun, H., Nikovski, D.N., Zhang, J., "Resilient Restoration of Power Distribution System Based on Minimum Spanning Forest", IEEE Power & Energy Society General Meeting (PES), DOI: 10.1109/PESGM40551.2019.8973730, August 2019, pp. 1-5.
      BibTeX TR2019-081 PDF
      • @inproceedings{Poudel2019aug,
      • author = {Poudel, Shiva and Sun, Hongbo and Nikovski, Daniel N. and Zhang, Jinyun},
      • title = {Resilient Restoration of Power Distribution System Based on Minimum Spanning Forest},
      • booktitle = {IEEE Power & Energy Society General Meeting (PES)},
      • year = 2019,
      • pages = {1--5},
      • month = aug,
      • doi = {10.1109/PESGM40551.2019.8973730},
      • issn = {1944-9925},
      • url = {https://www.merl.com/publications/TR2019-081}
      • }
    •  Minot, A., Sun, H., Nikovski, D.N., Zhang, J., "Distributed Estimation and Detection of Cyber-Physical Attacks in Power Systems", IEEE International Conference on Communications Workshops (ICC), DOI: 10.1109/ICCW.2019.8756653, May 2019, pp. 1-6.
      BibTeX TR2019-035 PDF
      • @inproceedings{Minot2019may,
      • author = {Minot, Ariana and Sun, Hongbo and Nikovski, Daniel N. and Zhang, Jinyun},
      • title = {Distributed Estimation and Detection of Cyber-Physical Attacks in Power Systems},
      • booktitle = {IEEE International Conference on Communications Workshops (ICC)},
      • year = 2019,
      • pages = {1--6},
      • month = may,
      • doi = {10.1109/ICCW.2019.8756653},
      • issn = {2474-9133},
      • url = {https://www.merl.com/publications/TR2019-035}
      • }
    •  Xu, H., Sun, H., Nikovski, D.N., Shoichi, K., Mori, K., "Learning Dynamical Demand Response Model in Real-Time Pricing Program", IEEE PES Innovative Smart Grid Technologies Conference - North America (ISGT NA), February.
      BibTeX TR2018-198 PDF
      • @inproceedings{Xu2019feb,
      • author = {Xu, Hanchen and Sun, Hongbo and Nikovski, Daniel N. and Shoichi, Kitamura and Mori, Kazuyuki},
      • title = {Learning Dynamical Demand Response Model in Real-Time Pricing Program},
      • booktitle = {IEEE PES Innovative Smart Grid Technologies Conference - North America (ISGT NA)},
      • year = 2019,
      • month = feb,
      • url = {https://www.merl.com/publications/TR2018-198}
      • }
    See All Publications for Electric Systems