Grid Integration Research

Resources (To be updated):

  1. High resolution irradiance (GHI) data from 5 irradiance sensors at UCSD collected in March and April, 2015: download here (in Matlab format, i.e. .mat file).
  2. 1-sec PV power output data: 15 minute averaged data for 100 California Solar Initiative PV Sites were downscaled to 1 second data for the whole year of 2010.
  3. Pi to Matlab data retrieval tool in Matlab: Download here.
  4. Public distribution models used:
    1. IEEE models
    2. EPRI models: (1) Set 1: ckt5, ckt7, and ckt24 (Readme); and (2) Set 2: j1, k1, and m1 models (here).

Research projects (To be updated)

  1. Impact of high PV penetration on distribution networks.
  2. Control of smart devices on distribution networks.
  3. Integration of electric vehicles in micro/ smart grids.
  4. Integration of energy storage systems in micro/ smart grids.
  5. Economic microgrid modeling and assessment of microgrid modeling software.

Recent publications (To be updated):

  1. D.A. Nguyen, M. Valey, R. Hanna, J. Kleissl, J. Schoenes, V, Zheglov, B. Kurtz, and B. Torre. “Impact Research of High PV Penetration Using Solar Resource Assessment with Sky Imager and Distribution System Simulations.” Submitted to IEEE Transactions on Smartgrid (2015).
  2. D.A. Nguyen, and J. Kleissl. “Research on Impacts of Distributed versus Centralized Solar Resource on Distribution Network Using Power System Simulation and Solar Now-casting with Sky Imager.” Photovoltaic Specialist Conference (PVSC), 2015 IEEE 42th. 8-13 June 2015. Accepted manuscript.
  3. D.A. Nguyen, and J. Kleissl. “Stereographic methods for cloud base height determination using two sky imagers.” Solar Energy 107 (2014): 495-509. Link
  4. R. Hanna, J. Kleissl, A. Nottrott, M. Ferry, Energy dispatch schedule optimization for demand charge reduction using a photovoltaic-battery storage system with solar forecasting, Solar Energy 103, 2014 pp. 269-287. doi: 10.1016/j.solener.2014.02.020.

Summary of research (To be updated):

Economic microgrid modeling. Microgrid research over the past decade focused on proving the technical viability of the microgrid concept, and demonstrations have been successful. The technical literature on microgrids is consequently quite mature. However, as we now approach a time when governments and private investors seek to implement commercial microgrids, the business and regulatory cases for microgrids are rarely clear or established. To that end, we are using the economic model DER-CAM, developed by LBNL, to define and simulate microgrids with current and changing market conditions. In what market conditions are microgrids economically viable? What makes the business cases robust? What role do renewables and CHP play within the microgrid? How should regulators think about microgrids in the changing electricity market? Our research seeks to answer these questions and others.

Assessment of microgrid modeling software. In light of the increasing adoption of renewable and distributed energy resources onto the electric grid, numerous software tools to design and simulate grid networks, energy systems, renewables integration, and microgrids have been developed. These tools share many similarities but are also highly idiosyncratic in terms of their technical features and capabilities. This work has two phases: we are first benchmarking a selection of prominent software tools that can be used to design and simulate microgrids and microgrid integration; and second, based on the evaluation in the first phase, developing and simulating detailed microgrid case studies using a subset of the benchmarked tools. The goal of this research is to provide benchmark criteria and information about each software tool to facilitate comparison as required by future microgrid modeling work.

Notable results/figures (To be updated):