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Mountain
  Datong Paul Zhou





      Ph.D. Student, Hybrid Systems Laboratory

      University of California, Berkeley

      Department of Mechanical Engineering/
      Electrical Engineering and Computer Sciences

      307 Cory Hall, Desk 10

      Berkeley, CA 94720-1770

      datong.zhou [at] berkeley [dot] edu








About Me


I am a third year graduate student in Mechanical Engineering, working with Professor Claire Tomlin with a focus on Systems and Controls. My primary research interests lie in the field of energy markets, particularly in the interaction between end-users of electricity and load serving entities.

I graduated from Technische Universität München, Germany in 2011 with a major in Mechanical Engineering (with distinction). In the fall of 2016, I was a visiting student at the Laboratory for Information and Decision Systems (LIDS) of MIT, supervised by Prof. Munther A. Dahleh and Dr. Mardavij Roozbehani.

During the summer of 2015, I worked as a Consulting Intern for Siemens AG in Munich, Germany.

In my free time I enjoy doing triathlon, and I have achieved the title of Ironman 70.3 in July 2016.





Research


Demand-side management has emerged as a vital tool to align electricity demand and supply closer to an equilibrium. My goal is to understand and model the potential for eliciting a desired consumer behavior through Demand Side Response (DR), which intentionally seeks to modify electricity consumption from expected patterns with the help of monetary incentives. It is my ambition to utilize tools at the intersection of mathematics, statistics, operations research, and control theory with an eye towards data-driven analysis to answer the following questions:








Publications



Preprints / Working Papers


  1. D. Zhou, M. Balandat, M. Dahleh, and C. Tomlin. Eliciting Private User Information for Demand Response.
    [arXiv]

  2. D. Zhou, M. Roozbehani, M. Dahleh, and C. Tomlin. How Peer Effects Influence Energy Consumption.
    [arXiv]

  3. D. Zhou, M. Dahleh, and C. Tomlin. Hedging Strategies in Wholesale Electricity Markets.
    [arXiv]

  4. D. Zhou, M. Balandat, and C. Tomlin. Estimating Treatment Effects of a Residential Demand Response Program Using Non-Experimental Data.


Peer-Reviewed / Refereed Articles


  1. D. Zhou, M. Roozbehani, M. Dahleh, and C. Tomlin. Stability Analysis of Wholesale Electricity Markets under Dynamic Consumption Models and Real-Time Pricing. To appear in 2017 American Control Conference.
    [arXiv] [PDF]

  2. D. Zhou*, Q. Hu*, and C. Tomlin. Quantitative Comparison of Data-Driven and Physics-Based Models for Commercial Building HVAC Systems. To appear in 2017 American Control Conference.
    [PDF]

  3. D. Zhou, M. Balandat, and C. Tomlin. Residential Demand Response Targeting Using Observational Data. 55th Conference on Decision and Control, December 2016.
    [arXiv] [PDF] [DOI] [Talk Slides]

  4. D. Zhou, M. Balandat, and C. Tomlin. A Bayesian Perspective on Residential Demand Response Using Smart Meter Data. 54th Annual Allerton Conference on Communication, Control, and Computing, September 2016.
    [arXiv] [PDF] [DOI] [Talk Slides]

  5. Q. Hu, F. Oldewurtel, M. Balandat, E. Vrettos, D. Zhou, and C. Tomlin. Building Model Identification during Regular Operation - Empirical Results and Challenges. American Control Conference (ACC), July 2016.
    [arXiv] [PDF] [DOI]

  6. * Equal contribution among authors.






Teaching








Coursework

Mechanical Engineering


Electrical Engineering and Computer Sciences


Industrial Engineering and Operations Research


Other


       Current GPA: 3.97/4.0