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

  • 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

    • CD1377: 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.

    • MP1263: Fault analysis for electric motors

      MERL is seeking a highly motivated intern to conduct research in electric machine fault analysis. The ideal candidate should be a senior Ph. D student in Electrical Engineering or related discipline with a solid background in the physics and engineering of electric motors, and early fault detection. Knowledge and experience in electric motor modeling and machine learning are desired. The candidate is expected to collaborate with MERL researchers to conduct theoretical analysis, numerical simulations, develop algorithms and prepare manuscripts for scientific publications. The duration of internship is expected to be 3 months and start date is flexible.

    • MP1381: 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

    •  Poudel, S., Sun, H., Nikovski, D.N., Zhang, J., "Distributed Average Consensus Algorithm for Damage Assessment of Power Distribution system", IEEE Innovative Smart Grid Technologies Conference (ISGT), February 2020.
      BibTeX Download PDFAbout TR2020-013
      • @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 Innovative Smart Grid Technologies Conference (ISGT)},
      • year = 2020,
      • month = feb,
      • 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, ISSN: 1949-3061, Vol. 10, No. 6, pp. 6366-6375, January 2020.
      BibTeX Download PDFAbout TR2020-003
      • @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 Download PDFAbout TR2019-153
      • @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://www.merl.com/publications/TR2019-153}
      • }
    •  Poudel, S., Sun, H., Nikovski, D.N., Zhang, J., "Resilient Restoration of Power Distribution System Based on Minimum Spanning Forest", IEEE PES General Meeting, DOI: 10.1109/PESGM40551.2019.8973730, ISSN: 1944-9925, August 2019, pp. 1-5.
      BibTeX Download PDFAbout TR2019-081
      • @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 PES General Meeting},
      • 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, ISSN: 2474-9133, May 2019, pp. 1-6.
      BibTeX Download PDFAbout TR2019-035
      • @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 Innovative Smart Grid Technologies North America (ISGT NA), February.
      BibTeX Download PDFAbout TR2018-198
      • @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 Innovative Smart Grid Technologies North America (ISGT NA)},
      • year = 2019,
      • month = feb,
      • url = {https://www.merl.com/publications/TR2018-198}
      • }
    •  Wang, B., Lin, C., Teo, K.H., "Coupled-Mode Analysis for Near-Field Thermal Radiation Devices", Biennial IEEE Conference on Electromagnetic Field Computation (CEFC), October 2018.
      BibTeX Download PDFAbout TR2018-154
      • @inproceedings{Wang2018oct,
      • author = {Wang, Bingnan and Lin, Chungwei and Teo, Koon Hoo},
      • title = {Coupled-Mode Analysis for Near-Field Thermal Radiation Devices},
      • booktitle = {Biennial IEEE Conference on Electromagnetic Field Computation (CEFC)},
      • year = 2018,
      • month = oct,
      • url = {https://www.merl.com/publications/TR2018-154}
      • }
    •  Tanovic, O., Ma, R., "Truly Aliasing-Free Digital RF-PWM Power Coding Scheme for Switched-Mode Power Amplifiers", IEEE Radio and Wireless Symposium (RWS), DOI: 10.1109/RWS.2018.8304948, March 2018.
      BibTeX Download PDFAbout TR2018-021
      • @inproceedings{Ma2018mar,
      • author = {Tanovic, Omer and Ma, Rui},
      • title = {Truly Aliasing-Free Digital RF-PWM Power Coding Scheme for Switched-Mode Power Amplifiers},
      • booktitle = {IEEE Radio and Wireless Symposium (RWS)},
      • year = 2018,
      • month = mar,
      • doi = {10.1109/RWS.2018.8304948},
      • url = {https://www.merl.com/publications/TR2018-021}
      • }
    See All Publications for Electric Systems