Forecast value considering energy pricing in California

Applied Energy

Volumn 125, Issue , 2014, Pages 230-237

  Luoma, Jennifer ^a   Mathiesen, Patrick ^a   Kleissl, Jan ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Energy market; Energy prices; Forecast value; Solar energy

Indexed keywords

COMMERCE; COSTS; SOLAR ENERGY; SOLAR POWER GENERATION;

BIAS CORRECTION; DAY AHEAD MARKET; ENERGY MARKETS; ENERGY PRICES; LOCATIONAL MARGINAL PRICES; PRODUCTION FORECASTS; REAL-TIME MARKET; SOLAR PHOTOVOLTAIC PLANTS;

FORECASTING;

ACCURACY ASSESSMENT; ECONOMIC ANALYSIS; ENERGY POLICY; FORECASTING METHOD; NUMERICAL MODEL; PHOTOVOLTAIC SYSTEM; PRICING POLICY; REAL TIME; SOLAR POWER;

CALIFORNIA; UNITED STATES;

EID: 84898793179     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2014.03.061     Document Type: Article

References (23)

1. Botterud A., Zhou A., Wang J., Bessa R., Keko H., Mendes J., et al. Use of wind power forecasting in operational decision 2011, Argonne National Laboratory.
2. Murphy A.H. What is a good forecast? An essay on the nature of goodness in weather forecast. Weather Forecast 1993, 8:281-293.
3. Blatchford J, Zack J. Integration of solar energy into the participating intermittent resource program (PIRP). CAISO Issue Paper, April 2008.
4. Botterud A., Wang J., Miranda V., Bessa R. Wind power trading under uncertainty in LMP markets. IEEE Trans Power Sys 2012, 27(2):894-903.
5. Fabbri A., Gomez San Roman T., Rivier Abbad J., Quezada V.H.M. Assessment of the cost associated with wind generation prediction errors in a liberalized electricity market. IEEE Trans Power Syst August 2005, 20(3):1440-1446.
6. Bathurst G.N., Weatherill J., Strbac G. Trading wind generation in short term energy markets. IEEE Trans Power Syst 2002, 17(3):782-789.
7. Pinson P., Chevallier C., Kariniotakis G.N. Trading wind generation from short-term probabilistic forecasts of wind power. IEEE Trans Power Syst 2007, 22(3):1148-1156.
8. Mills A, Wiser R. Changes in the economic value of variable generation at high penetration levels: a pilot case study of California. In: Ernest Orlando Lawrence Berkeley technical note. LBLN-5445E; 2012. http://emp.lbl.gov/sites/all/files/lbnl.
9. Porter K, Fink S, Buckley M, Rogers J, Hodge B-M. A review of variable generation integration charges. In: National renewable energy laboratory technical report. NREL/TP-5500-57583; 2013. http://www.nrel.gov/docs/fy13osti/57583.pdf.
10. Milligan M, Miller A, Chapman F. Estimating the economic value of wind forecasting to utilities. NREL, Windpower; 1995.
11. Ruiz P., Philbrick C.R., Zak E., Cheung K.W., Sauer P. Uncertainty management in the unit commitment problem. IEEE Trans Power Syst 2009, 24(2):642-651.
12. Porter K, Fink S, Rogers J, Mudd C, Buckley M, Clark C. PJM Renewable integration study: review of industry practice and experience in the integration of wind and solar generation. In: GE energy technical report. 2012. http://pjm.com/.
13. Lew D, Piwko D, Miller N, Jordan G, Clark K, Freeman L. How do high levels of wind and solar impact the grid? The western wind and solar integration study. NREL, December 2010.
14. Giebel G, et al. The state-of-the-art in short-term prediction of wind power: a literature overview. 2nd ed. ANEMOS; 2011.
15. Ardani K, Margolis R. 2010 solar technologies market report. NREL Report; November 2011.
16. Jonsson T., Pinson P., Madsen H. On the market impact of wind energy forecasts. Energy Econ 2010, 32:313-320.
17. CIMIS. CIMIS overview, 2009. http://www.cimis.water.ca.gov/cimis/infoGenCimisOverview.jsp.
18. Campbell Scientific. LI200S Pyranometer instruction manual. Campbell Scientific Technical Specifications. Revision 2/96; 1996.
19. CIMIS. QC overview, 2009. http://www.cimis.water.ca.gov/cimis/dataQc.jsp.
20. CIMIS. Current hourly flags, 2009. http://www.cimis.water.ca.gov/cimis/dataQcCurrentHourly.jsp.
21. Janjic Z, Gall R, Pyle ME. Scientific documentation for the NMM solver. NCAR Technical Note NCAR/TN 477+STR; 2010.
22. Janjic Z, Black T, Pyle M, Ferrier B, Chuang HY, Jovic D, et al. User's guide for the NMM core of the weather research and forecast (WRF) modeling system version 3, 2011. p. 195.
23. Mathiesen P., Kleissl J. Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States. Sol Energy 2011, 85(5):967-977.