Modeling Variability and Uncertainty of Photovoltaic Generation: A Hidden State Spatial Statistical Approach

IEEE Transactions on Power Systems

Volumn 30, Issue 6, 2015, Pages 2965-2973

  Tabone, Michaelangelo D ^a   Callaway, Duncan S ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Power system planning; solar energy; statistics

Indexed keywords

HIDDEN MARKOV MODELS; MARKOV PROCESSES; SOLAR ENERGY; SOLAR POWER GENERATION; STATISTICS; STOCHASTIC SYSTEMS; TRELLIS CODES; UNCERTAINTY ANALYSIS;

MODELING VARIABILITY; OPERATIONAL RESERVE; PHOTOVOLTAIC GENERATION; POWER SYSTEM PLANNING; RESERVE CAPACITY; SOLAR VARIABILITY; STATISTICAL APPROACH; STOCHASTIC VOLATILITY;

STOCHASTIC MODELS;

EID: 85002456135     PISSN: 08858950     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPWRS.2014.2372751     Document Type: Article

References (24)

1. Solar Energy Industry Association, Solar Market Insight Report 2013 Year in Review, Mar. 2014, Solar Energy Industry Association, Tech. Rep.
2. The California Solar Initiative, Apr. 2014 [Online]. Available: http://www.gosolarcalifornia.org/about/csi.php
3. G. E. Energy, Western Wind and Solar Integration Study, National Renewable Energy Laboratory, Golden, CO, USA, Tech. Rep. NREL/SR-550-47434, May 2010.
4. M. Rothleder, Track I Direct Testimony of Mark Rothleder on Behalf of the California Independent System Operator Corporation, California Public Utilities Commission, 2011.
5. M. Hummon, P. Denholm, J. Jorgenson, D. Palchak, B. Kirby, and O. Ma, Fundamental Drivers of the Cost and Price of Operating Reserves, National Renewable Energy Laboratory (NREL), Golden, CO, USA, Tech. Rep., 2013 [Online]. Available: http://www.nrel.gov/docs/fy13osti/58491.pdf
6. E. Ela, V. Diakov, E. Ibanez, and M. Heaney, "Impacts of variability and uncertainty in solar photovoltaic generation at multiple timescales," Contract vol. 303, p. 2753000, 2013 [Online]. Available: http://www.nrel.gov/docs/fy13osti/58274.pdf
7. A. Murata, H. Yamaguchi, and K. Otani, "A method of estimating the output fluctuation of many photovoltaic power generation systems dispersed in a wide area," Elect. Eng. Jpn. vol. 166, no. 4, pp. 9-19, Mar. 2009 [Online]. Available: http://onlinelibrary.wiley.com/doi/10.1002/eej.20723/abstract
8. A. Mills and R. Wiser, Implications of Wide-Area Geographic Diversity for Short-Term Variability of Solar Power, Lawrence Berkeley National Laboratory, 2010, Tech. Rep.
9. M. Milligan, P. Donohoo, D. Lew, E. Ela, B. Kirby, H. Holttinen, E. Lannoye, D. Flynn, M. O'Malley, and N. Miller, "Operating reserves and wind power integration: An international comparison," in Proc. 9th Int. Workshop Large-Scale Integration of Wind Power Into Power Systems, 2010, pp. 18-29.
10. H. Holttinen, M. Milligan, E. Ela, N. Menemenlis, J. Dobschinski, B. Rawn, R. Bessa, D. Flynn, E. Gomez Lazaro, and N. Detlefsen, "Methodologies to determine operating reserves due to increased wind power," in Proc. 2013 IEEE Power and Energy Society (PES) General Meeting, Jul. 2013, pp. 1-10.
11. M. R. Hummon, E. Ibanez, G. Brinkman, and D. Lew, Sub-Hour Solar Data for Power System Modeling From Static Spatial Variability Analysis, National Renewable Energy Laboratory (NREL), Golden, CO, USA, 2012, Tech. Rep. Pending.
12. M. Lave, J. Kleissl, and J. Stein, "A wavelet-based variability model (WVM) for solar PV power plants," IEEE Trans. Sustain. Energy, vol. 4, no. 2, pp. 501-509, 2013.
13. M. Lave and J. Kleissl, "Cloud speed impact on solar variability scaling - Application to the wavelet variability model," Solar Energy vol. 91, pp. 11-21, May 2013 [Online]. Available: http://www.sciencedirect. com/science/article/pii/S0038092X13000406
14. R. Perez, S. Kivalov, J. Schlemmer, K. Hemker, Jr., and T. E. Hoff, "Short-term irradiance variability: Preliminary estimation of station pair correlation as a function of distance," Solar Energy vol. 86, no. 8, pp. 2170-2176, Aug. 2012 [Online]. Available: http://www.sciencedirect. com/science/article/pii/S0038092X12000928
15. M. J. Reno and J. Stein, Using Cloud Classification to Model Solar Variability, Sandia National Laboratories, Tech. Rep., 2013 [Online]. Available: http://energy.sandia.gov/wp/wp-content/gallery/uploads/SAND-2013-1692C%-ASES-CloudCategoryVariability.pdf
16. J. Wegener, M. Lave, J. Luoma, and J. Kleissl, Temporal Downscaling of Irradiance Data via Hidden Markov Models on Wavelet Coefficients: Application to California Solar Initiative Data, 2012 [Online]. Available: http://solar.ucsd.edu/datasharing/doc/UCSDReport-1secCSI.pdf
17. R. Langrock, I. L. MacDonald, and W. Zucchini, "Some nonstandard stochastic volatility models and their estimation using structured hidden Markov models," J. Empiric. Finance vol. 19, no. 1, pp. 147-161, Jan. 2012 [Online]. Available: http://www.sciencedirect. com/science/article/pii/S0927539811000661
18. Y. Li, L. He, and R.-Q. Nie, "Short-term forecast of power generation for grid-connected photovoltaic system based on advanced Grey-Markov chain," in Proc. Int. Conf. Energy and Environment Technology, 2009 (ICEET '09), Oct. 2009, vol. 2, pp. 275-278.
19. P. Poggi, G. Notton, M. Muselli, and A. Louche, "Stochastic study of hourly total solar radiation in Corsica using a Markov model," Int. J. Climatol. vol. 20, no. 14, pp. 1843-1860, Nov. 2000 [Online]. Available: http://onlinelibrary.wiley.com/doi/10.1002/1097-0088(20001130)20:14<1843::AID-JOC561>3.0.CO;2-O/abstract
20. A. Mellit, M. Benghanem, A. H. Arab, and A. Guessoum, "A simplified model for generating sequences of global solar radiation data for isolated sites: Using artificial neural network and a library of Markov transition matrices approach," Solar Energy vol. 79, no. 5, pp. 469-482, Nov. 2005 [Online]. Available: http://www.sciencedirect.com/science/article/pii/S0038092X05000204
21. G. M. Masters, Renewable and Efficient Electric Power Systems, 1st ed. New York, NY, USA: Wiley-IEEE Press, Aug. 2004.
22. Y. Makarov, C. Loutan, J. Ma, and P. de Mello, "Operational impacts of wind generation on California power systems," IEEE Trans. Power Syst. vol. 24, no. 2, pp. 1039-1050, May 2009 [Online]. Available: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber= 4808228
23. E. Ibanez, G. Brinkman, M. Hummon, and D. Lew, "A solar reserve methodology for renewable energy integration studies based on subhourly variability analysis," in Proc. 2nd Int. Workshop Integration of Solar Power in Power Systems, Lisbon, Portugal, 2012 [Online]. Available: http://www.nrel.gov/docs/fy12osti/56169.pdf
24. C. Goebel and D. Callaway, "Using ICT-Controlled plug-in electric vehicles to supply grid regulation in California at different renewable integration levels," IEEE Trans. Smart Grid, vol. 4, no. 2, pp. 729-740, Jun. 2013.