An energy storage algorithm for ramp rate control of utility scale PV (photovoltaics) plants

Balancing authorities are currently exploring options for preventing potential increases in ramping costs of conventional generators in the grid by setting ramping limits on variable energy resources. In this paper, we present the methodology and results of simulations on the smoothing performance of battery, flywheel and ultra-capacitor energy storage technologies connected to single large-scale PV (photovoltaics) plants subject to a 10%/minute ramping limit. The simulations were run using second-to-second output data of four large-scale PV plants of which two are in the Southeast of Canada (5 MW and 80 MW) and two in the Southwest of the US (21 and 30.24 MW). Energy storage units are sized for each plant on a baseline of 99% violation reductions and their performances are compared. We also present two dispatch strategies tailored to low and high cycle-life storage technologies which are modeled without forecasting measures and assuming perfect short-term forecast for the remainder of the averaging period.

[1]  Thomas N. Hansen,et al.  Utility Solar Generation Valuation Methods , 2009 .

[2]  S. Mallika,et al.  Review on Ultracapacitor- Battery Interface for Energy Management System , 2011 .

[3]  J. Kleissl,et al.  A Wavelet-Based Variability Model (WVM) for Solar PV Power Plants , 2013, IEEE Transactions on Sustainable Energy.

[4]  Vasilis Fthenakis,et al.  Empirical assessment of short‐term variability from utility‐scale solar PV plants , 2014 .

[5]  Paula A. Jarzemsky,et al.  Look Before You Leap: Lessons Learned When Introducing Clinical Simulation , 2008, Nurse educator.

[6]  Dale T. Bradshaw,et al.  DOE/EPRI Electricity Storage Handbook in Collaboration with NRECA , 2016 .

[7]  Adisa Azapagic,et al.  Environmental impacts of micro-wind turbines and their potential to contribute to UK climate change targets , 2013 .

[8]  T. Hoff,et al.  QUANTIFYING PV POWER OUTPUT VARIABILITY , 2010 .

[9]  J. Kleissl,et al.  Testing a wavelet-based variability model (WVM) for solar PV power plants , 2012, 2012 IEEE Power and Energy Society General Meeting.

[10]  Richard Perez,et al.  Mitigating Short-Term PV Output Intermittency , 2013 .

[11]  Yih-huei Wan,et al.  Dark Shadows , 2011, IEEE Power and Energy Magazine.

[12]  Hiroshi Yamaguchi,et al.  A method of estimating the output fluctuation of many photovoltaic power generation systems dispersed in a wide area , 2009 .

[13]  Dennis Moon,et al.  Observed Impacts of Transient Clouds on Utility Scale PV Fields , 2010 .

[14]  V. M. Fthenakis,et al.  1.11 – Storage Options for Photovoltaics , 2012 .

[15]  Joshua S. Stein,et al.  Quantifying and Simulating Solar-Plant Variability Using Irradiance Data , 2013 .

[16]  R. Piwko,et al.  Look Before You Leap: The Role of Energy Storage in the Grid , 2012, IEEE Power and Energy Magazine.

[17]  James F. Manwell,et al.  Lifetime Modelling of Lead Acid Batteries , 2005 .

[18]  K. Kiefer,et al.  Power characteristics of PV ensembles: experiences from the combined power production of 100 grid connected PV systems distributed over the area of Germany , 2001 .

[19]  A. Colmenar,et al.  Review of flywheel based energy storage systems , 2011, 2011 International Conference on Power Engineering, Energy and Electrical Drives.

[20]  Abraham Ellis,et al.  Simulated PV power plant variability: Impact of utility-imposed ramp limitations in Puerto Rico , 2013, 2013 IEEE 39th Photovoltaic Specialists Conference (PVSC).