Ryan E. Hanna

Ph.D. Candidate. Thesis topic: The value of reliability for microgrid adoption: Modeling interactions of technology choice, economics, and emissions. Expected graduation: Spring 2018.

Research and project advisors:
Prof. Jan Kleissl (co-PI)
Department of Mechanical and Aerospace Engineering
Associate Director, Center for Energy Research
University of California, San Diego

Prof. David Victor (co-PI)
School of Global Policy and Strategy
Director, Laboratory on International Law and Regulation
University of California, San Diego

Bill Torre
Center for Energy Research
Program Director of Energy Storage Systems
University of California, San Diego

Research

My research has spanned several topics and projects over 4+ years at UC San Diego. The consistent, core focus, though, is optimization and modeling of distributed energy resources. I include below brief summaries of research.

Modeling the value of reliability for microgrid business cases. Many observers believe the future electric grid will be low-carbon and perhaps decentralized. Microgrids may be a key enabler. In this work I am building a technology investment and dispatch model for microgrids that considers revenue streams from providing energy locally (both power and heat) as well as the value associated with improving service reliability for customers within the microgrid. I will apply the model in two ways. The first is customer-centric analysis to understand, systematically, how customers of different classes benefit economically from improved reliability. The second is policy analysis to understand how microgrids adopted to improve reliability can be leveraged to reduce greenhouse gas emissions from the wholesale power market.

Economic modeling of microgrids. Stand-alone distributed generation (e.g. solar PV, electric energy storage, CHP, thermal storage) and microgrids (which control combinations of these technologies) may shape a future decentralized electric grid. This work investigates the extent to which a decentralized paradigm can help decarbonize the grid, and in what ways that paradigm is optimal (or not). Regulations that will shape the future power system are far from certain, however—and that uncertainty affects the business cases for microgrids today. We are modeling policy, technology and market variables to understand how they affect the economics feasibility, or “business case”, for microgrids. These factors have real consequences, for policy or otherwise—e.g. they may push (or not) least-cost investment toward renewables.

Grid integration of solar energy. Solar PV power output is inherently intermittent. When adopted in high penetrations, such intermittency may degrade local power quality and cause voltage excursions or substation back-flow. In this research, we modeled five utility feeders using the distribution system simulator OpenDSS to explore the grid impacts of distributed and centralized  PV at increasing PV penetration levels.

Customer applications for solar+storage systems. Numerous uses for solar PV+battery energy storage (solar+storage) systems sited behind-the-meter have been proposed and studied—e.g., load shifting, peak load shaving, PV ramp rate control, and microgrid applications. At UC San Diego we have developed optimization algorithms for peak load shaving and PV ramp rate control using a solar+storage system. These algorithms have been simulated in the virtual environment and implemented operationally using real PV systems and second-life EV battery storage systems at the UC San Diego campus.

Peer-reviewed Publications

  • Hanna, R., Ghonima, M., Kleissl, J., Tynan, G., Victor, D.G., 2017. Evaluating business models for microgrids: Interactions of technology and policy. Energy Policy 103, 47-61. doi: 10.1016/j.enpol.2017.01.010.
  • R. Hanna, V. Disfani, J. Kleissl, “A game-theoretical approach to variable renewable generator bidding in wholesale electricity markets,” North American Power Symposium (NAPS) 2016, Sep. 2016. doi: 10.1109/NAPS.2016.7747919.
  • I.S. Bayram, V. Zamani, R. Hanna, J. Kleissl, On the Evaluation of Plug-in Electric Vehicle Data of a Campus Charging Network, 2016 IEEE International Energy Conference, EnergyCon 2016, Leuven, Belgium. doi: 10.1109/ENERGYCON.2016.7514026.
  • Hanna, R., Kleissl, J., Nottrott, A., Ferry, M., 2014. Energy dispatch schedule optimization for demand charge reduction using a photovoltaic-battery storage system with solar forecasting. Solar Energy 103, 269-287. doi: 10.1016/j.solener.2014.02.020.

Other Reports

  • R. Hanna, D. Gonatas, K. Murray, J. Kleissl. Development and simulation of battery energy storage and inverter control for PV ramp rate smoothing, Apr 2016. (Report submitted for CSI RD&D5 Subtask 3).
  • D.A. Nguyen, P. Ubiratan, M. Velay, R. Hanna, J. Kleissl, J. Schoene, V. Zheglov, B. Kurtz, B. Torre, V. Disfani, Impact Research of High Photovoltaics Penetration Using High Resolution Resource Assessment with Sky Imager and Power System Simulation, 2015. Available online.
  • W. Torre, R. Hanna, J. Kleissl, Cumulative Impacts of High Penetration of Electric Vehicle Charging and Photovoltaic Generation on Distribution Circuits, 2015. Available online.

Selected Conference Presentations and Invited Talks

  • Poster: R. Hanna, D. Victor, V. Disfani, J. Kleissl. The value of reliability for microgrids. DistribuTECH 2017, San Diego, CA, 2017 (invited; to be presented).
  • Paper: R. Hanna (presented), V. Disfani, J. Kleissl. A game-theoretical approach to variable renewable generator bidding in wholesale electricity markets. NAPS 2016, Denver, CO, 2016.
  • Keynote Talk: R. Hanna (presented), D. Victor. Squaring Microgrid Business Models with Grid Decarbonization. CaFFEET 2015, San Francisco, CA, 2015.
  • Poster: R. Hanna (presented), J. Kleissl, A. Nottrott, M. Ferry. Energy dispatch schedule optimization for demand charge reduction using a photovoltaic-battery storage system with solar forecasting. EESAT 2013, San Diego, CA, 2013.

Teaching

  • Teaching Assistant: MAE 126a – Environmental Engineering Lab.  Winter 2016.  Course taught by Prof. Jan Kleissl.
  • Teaching Assistant: MAE 110a – Thermodynamics.  Winter 2014.  Course taught by Prof. Jan Kleissl.
  • Teaching Assistant: MAE 121 – Air Pollution Transport and Dispersion Modeling.  Spring 2013.  Course taught by Mark Bennett.

Education

Ph.D. Mechanical Engineering. University of California, San Diego. Dissertation: The value of reliability for microgrid adoption: Modeling interactions of technology choice, economics, and emissions (ongoing).
M.S. Mechanical Engineering. University of California, San Diego, 2013. GPA: 3.69.
B.S. Mechanical Engineering. Washington University in St. Louis, St. Louis, Missouri. 2011. GPA: 3.97.
B.A. Physics, Mathematics minor. Pacific Lutheran University, Tacoma, Washington, 2009. GPA: 3.73.

Contact:

Ryan Hanna
Ph.D Candidate, Mechanical Engineering
rehanna@ucsd.edu
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