Hierarchical load hindcasting using reanalysis weather

IEEE Transactions on Smart Grid

Volumn 5, Issue 1, 2014, Pages 447-455

  Black, Jonathan D ^a   Henson, William L W ^a  

^a ISO New England   (United States)

Author keywords

Capacity value; effective load carrying capability; embedded generation; hindcasting; interannual variability; intermittent resource characterization; load forecasting; resource adequacy; solar power generation; variable generation; wind power generation

Indexed keywords

CAPACITY VALUE; EFFECTIVE LOAD CARRYING CAPABILITIES; EMBEDDED GENERATION; HINDCASTING; INTERANNUAL VARIABILITY; LOAD FORECASTING; RESOURCE ADEQUACY; RESOURCE CHARACTERIZATIONS; VARIABLE GENERATIONS;

CLIMATE CHANGE; DATA PROCESSING; DISTRIBUTED POWER GENERATION; ELECTRIC LOAD FORECASTING; SOLAR POWER GENERATION; WIND POWER;

NASA;

EID: 84892603293     PISSN: 19493053     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSG.2013.2278475     Document Type: Article

References (48)

1. B. Kirov and K. Georgieva, "Long-term variations and interrelations of ENSO, NAO and solar activity," Phys. Chem. Earth, Parts A/B/C, vol. 27, no. 6-8, pp. 441-448, 2002. (Pubitemid 34793903)
2. A. Keane, M.Milligan, C. J. Dent, B. Hasche, C. D. Annunzio, K. Dragoon, H. Holttinen, N. Samaan, L. Soder, and M. O'Malley, "Capacity value of wind power," IEEE Trans. Power Syst., vol. 26, no. 2, pp. 564-572, May 2011.
3. B. Hasche, A. Keane, and M. O'Malley, "Capacity value of wind power, calculation, and data requirements: The Irish power system case," IEEE Trans. Power Syst., vol. 26, no. 1, pp. 420-430, Feb. 2011.
4. D. Kavanaugh, A. Keane, and D. Flynn, "Capacity value of wave power," IEEE Trans. Power Syst., vol. 28, no. 1, pp. 412-420, Feb. 2013.
5. North American Electric Reliability Corporation (NERC), "Methods to model and calculate capacity contributions of variable generation for resource adequacy planning," NERC's Integration of Variable Generation Task Force, Mar. 2011 [Online]. Available: http://www.nerc.com/docs/pc/ivgtf/IVGTF1-2.pdf
6. GE Applications and Systems Engineering, EnerNex Corp., AWS Truepower, Dec. 2010, "New England wind integration study". Schenectady, NY, USA [Online]. Available: http://www.iso-ne.com/committees/comm-wkgrps/prtcpnts-comm/ pac/reports/2010/newis-report. pdf
7. GE Energy, May 2010, "Western wind and solar integration study," NREL Subcontract NREL/SR-550-47781, May 2010 [Online]. Available: http://www.nrel.gov/wind/systemsintegration/pdfs/2010/wwsis-final-report.pdf
8. EnerNex Corporation, "Eastern wind integration and transmission study," NREL Subcontract NREL/SR-5500-47086. Golden, CO, USA, Feb. 2011 [Online]. Available: http://www.nrel.gov/wind/systemsintegration/pdfs/2010/ ewits-final-report.pdf
9. W. L. W. Henson, J. G. McGowan, and J. F. Manwell, "Utilizing reanalysis and synthesis datasets in wind resource characterization for large-scale wind integration," Wind Eng., vol. 36, no. 1, pp. 97-110, Feb. 2012.
10. J. D. Black, Load Hindcasting: A Retrospective Regional Load Prediction Method Using Reanalysis Weather Data. Amherst, MA, USA: Dept. Mech. and Ind. Eng., Univ. Mass., 2011.
11. U. Henfridsson, V. Neimane, K. Strand, R. Kapper, H. Bernhoff, O. Danielsson, M. Leijon, J. Sundberg, K. Thorburn, E. Ericsson, and K. Bergman, "Wave energy potential in the Baltic Sea and the Danish part of the North Sea, with reflections on the Skagerrak," Ren. Energy, vol. 32, no. 12, pp. 2069-2084, Oct. 2007. (Pubitemid 46366710)
12. M. J. Khan andM. T. Iqbal, "Wind energy resource map of Newfoundland," Ren. Energy, vol. 29, no. 8, pp. 1211-1221, Jul. 2004. (Pubitemid 38423288)
13. R. A. Arinaga and K. F. Cheung, "Atlas of global wave energy from 10 years of reanalysis and hindcast data," Ren. Energy, vol. 39, no. 1, pp. 49-64, Mar. 2012.
14. V. R. Swain, V. J. Cardone, M. Ferguson, D. J. Gummer, E. L. Harris, E. A. Orelup, and A. T. Cox, "The MSC50 wind and wave reanalysis," presented at the 9th Int.WorkshopWave Hindcasting and Forecasting, Victoria, BC, Canada, 2006, unpublished.
15. A. Espejo, R. Minguez, A. Tomas, M. Menendex, F. J. Mendez, and I. J. Losada, "Directional calibrated wind and wave reanalysis databases using instrumental data for optimal design of off-shore wind farms," presented at the 2011 IEEE OCEANS Conf., Santander, Spain, Jun. 6-9, 2011, unpublished.
16. R. J. Davy and A. Troccoli, "Interannual variability of solar energy generation in Australia," Solar Energy, vol. 86, no. 12, pp. 3554-3560, Dec. 2012.
17. R. J. Hyndman and S. Fan, "Density forecasting for long-term peak electricity demand," IEEE Trans. Power Syst., vol. 25, no. 2, pp. 1142-1153, May 2010.
18. M. M. Rienecker, D. Dee, J. Woollen, G. P. Compo, K. Onogi, R. Gelaro, M. G. Bosilovich, A. da Silva, S. Pawson, S. Schuber, M. Suarez, D. Barker, H. Kamalhori, R. Kistler, and S. Saha, "Atmospheric reanalyses-Recent progress and prospects for the future," National Aeronautics and Space Administration, NASA TM-2012-104606, 29, Apr. 2010, NASA Technical Report Series on Global Modeling and Data Assimilation [Online]. Available: http://gmao.gsfc.nasa.gov/pubs/docs/NASATM2012-104606v29.pdf, Technical Workshop
19. L. Bengtsson, P. Arkin, P. Berrisford, P. Bougeault, C. K. Folland, C. Gordon, K. Haines,K. I.Hodges, P. Jones, P. Kallberg,N.Rayner,A. J. Simmons, D. Stammer, P. W. Thorne, S. Uppala, and R. S. Vose, "The need for dynamical climate reanalysis," Amer. Meteorol. Soc., vol. 88, no. 4, pp. 495-501, Apr. 2007.
20. R. S. Vose, S. Applequist, M. J. Menne, C. N. Williams, Jr., and P. Thorne, "An intercomparison of temperature trends in the U.S. Historical Climatology Network and recent atmospheric reanalyses," Geophys. Res. Lett., vol. 39, no. 10, pp. 1-6, May 2012.
21. World Climate Research Programme, "Report of the 4thWorld Climate Research Programme International Conference on Reanalyses," Silver Spring, MD, USA, May 2012 [Online]. Available: http://www.wcrpclimate. org/documents/ICR4-Report.pdf
22. "File Specification for MERRA Products Version 2.1" NASA Global Modeling and Assimilation Office, Greenbelt, MD, USA, Sep. 2008 [Online]. Available: http://gmao.gsfc.nasa.gov/research/merra/MERRA-FileSpec-DRAFT-09-02- 2008.pdf
23. "File Specification for GEOS-5 DAS Gridded Output" NASA Global Modeling and Assimilation Office, Greenbelt, MD, USA, Jul. 2008 [Online]. Available: http://gmao.gsfc.nasa.gov/products/documents/GEOS-5.2.0-File- Specification.pdf
24. "File Specification for GEOS-5.7.2" NASA Global Modeling and Assimilation Office, Greenbelt, MD, USA, May 2012 [Online]. Available: http://gmao.gsfc.nasa.gov/products/documents/GEOS-5.7.2-File-Specification.pdf
25. "The Mathworks, MATLAB User's Guide," The Mathworks, Inc., Natick,MA, USA, 2009.
26. T. Hong, "Short term electric load forecasting," Ph.D. dissertation, Op. Res. Elec. Eng., N. Carolina State Univ., Raleigh, NC, USA, 2010.
27. D. W. Bunn and E.D. Farmer, ComparativeModels for Electrical Load Forecasting. Chichester, UK: Wiley, 1985.
28. H. S. Hippert,D. W. Bunn, and R. C. Souza, "Large neural networks for electricity load forecasting: Are they overfitted?," Int. J. Forecasting, vol. 21, no. 3, pp. 425-434, Sep. 2005. (Pubitemid 40935944)
29. D. C. Montgomery and E. A. Peck, Introduction to Linear Regression Analysis, 4th ed. New York: Wiley, 2007.
30. T. Hong, P. Wang, and L. Willis, "A naïve multiple linear regression benchmark for short term load forecasting," presented at the 2011 IEEE Power Energy Soc.Gen.Meet., San Diego, CA,USA, Jul. 24-29, 2011, unpublished.
31. J. D. McQuigg, S. R. Johnson, and T. R. Tudor, "Meteorological diversity-load diversity, a fresh look at an old problem," J. of Applied Meteor., vol. 11, no. 4, pp. 561-566, June 1972.
32. S. Fan,Y. K.Wu,W. J. Lee, and C.Y. Lee, "Comparative study on load forecasting technologies for different geographical distributed loads," presented at the IEEE Power and Energy Society Gen.Mtg., San Diego, CA, July 24-29, 2011, unpublished.
33. C.Wright, C.W. Chan, and P. Laforge, "Conforming load and weather diversity for the analysis of a multi-region forecasting system," presented at the 25th IEEE Conf. Elect. Comput. Eng., Montreal, QC, Canada, Apr. 29-May 2 2012, unpublished.
34. S. Fan, Y. Wu, W. Lee, and C. Lee, "Multiregion load forecasting for system with large geographical area," IEEE Trans. Ind. App., vol. 45, no. 4, pp. 1452-1459, Jul. 2009.
35. R. Ramanathan, R. Engle, C. W. J. Granger, F. Vahid-Araghi, and C. Brace, "Short-run forecasts of electricity loads and peaks," Int. J. Forecasting, vol. 13, no. 2, pp. 161-174, Jun. 1997. (Pubitemid 127171119)
36. D. W. Bunn, "Forecasting loads and prices in competitive power markets," Proc. IEEE, vol. 88, no. 2, pp. 163-169, Feb. 2000. (Pubitemid 30558107)
37. R. Ashley, "Statistical significant forecasting improvements: How much out-of-sample data is likely necessary?," Int. J. Forecasting, vol. 19, no. 2, pp. 229-239, Jun. 2003. (Pubitemid 36831799)
38. I. Chong and C. Jun, "Performance of some variable selection methods whenmulticollinearity is present," Chemometrics Intell. Lab. Syst., vol. 78, no. 1-2, pp. 103-112, Jul. 2005. (Pubitemid 40884382)
39. M. Mitchell, "Genetic algorithms: An overview," in An Introduction to Genetic Algorithms, 1st ed. Cambridge,MA, USA: MIT Press, 1996, ch. 1, pp. 1-33.
40. H. Hasheminia and S. T. A. Niaki, "A genetic algorithm approach to find the best regression/econometric model among the candidates," Appl. Math. Comput., vol. 183, no. 1, pp. 337-349, Dec. 2006. (Pubitemid 44908613)
41. G. Kapetanios, "Variable selection in regression models using nonstandard optimisation of information criteria," Comp. Stat. Data Anal., vol. 52, no. 1, pp. 4-15, Sep. 2007. (Pubitemid 47331735)
42. Z. Liu, X. Xie, D. Zhang, and H. Liu, "Local partial least squaresmultistep model for short-term load forecasting," IEICE Trans. Fundam. Electr., Commun., Comput. Sci., vol. E89-A, no. 10, pp. 2740-2744, Jan. 2006. (Pubitemid 44582362)
43. S. Yang, M. Lu, and H. Xue, "Hybrid partial least squares and neural network approach for short-term electrical load forecasting," J. Control Theory Appl., vol. 6, no. 1, pp. 93-96, Feb. 2008. (Pubitemid 351661298)
44. R. Zhang, W. Cai, L. Ni, and G. L. Lebby, "Power system load forecasting using partial least square method," in Proc. 40th Southeastern Symp. Syst. Theory, New Orleans, LA, USA, 2008, pp. 169-173.
45. L. Kong and Y. Ma, "Load forecasting based on Kernel-based orthogonal projections to latent structures," in Proc. 2011 Int. Conf. Electr. Mech. Eng. Inf. Tech., Harbin, China, Aug. 2011, pp. 4451-4454.
46. R. Rosipal and N. Kramer, "Overview and recent advances in partial least squares," in Subspace, Latent Structure and Feature Selection Techniques, ser. Lecture Notes in Computer Science. Heidelberg, Germany: Springer, 2006, vol. 3940, pp. 34-51. (Pubitemid 44029878)
47. S. Wold, M. Sjostrom, and L. Eriksson, "PLS-regression: A basic tool of chemometrics," Chemometrics Intell. Lab. Syst., vol. 58, no. 2, pp. 109-130, Oct. 2001. (Pubitemid 33033283)
48. H. R. Glahn and D. A. Lowry, "The use of model output statistics (MOS) in objective weather forecasting," J. Appl. Meteorol., vol. 11, no. 8, pp. 1203-1211, Dec. 1972.