Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

access icon openaccess Compensation of temporal averaging bias in solar irradiance data

This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Received 09/11/2016, Accepted 21/04/2017, Revised 30/03/2017, Published 02/05/2017

Solar irradiance data is used for the prediction of solar energy system performance but is presently a significant source of uncertainty in energy yield estimation. This also directly affects the expected revenue, so the irradiance uncertainty contributes to project risk and therefore the cost of finance. In this study, the combined impact of temporal averaging, component deconstruction and plane translation mechanisms on uncertainty is analysed. A new method to redistribute (industry standard) hourly averaged data is proposed. This clearness index redistribution method is based on the statistical redistribution of clearness index values and largely corrects the bias error introduced by temporal averaging. Parameters for the redistribution model were derived using irradiance data measured at high temporal resolution by CREST, Loughborough University, over a 5-year period. The root mean square error of example net annual (2014) diffuse, beam and global yield of hourly averaged data were reduced from ∼15 to 1, 14 to 3 and 4 to 1%, respectively.

Inspec keywords: statistical distributions; solar power; mean square error methods

Other keywords: beam yield; temporal averaging bias; global yield; hourly averaged data; industry standard; root mean square error; solar energy system performance prediction; energy yield estimation; Loughborough University; clearness index redistribution method; CREST; irradiance uncertainty; statistical redistribution; component deconstruction; solar irradiance data; plane translation mechanisms

Subjects: Energy resources; Other topics in statistics; Numerical approximation and analysis; Solar energy; Probability theory, stochastic processes, and statistics; Interpolation and function approximation (numerical analysis)

References

    1. 1)
      • 19. Krawczynski, M.: ‘Solar spectral irradiance: measurement and application in photovoltaics’ (Loughborough University, 2014).
    2. 2)
      • 18. Tina, G., Gagliano, S.: ‘Probabilistic analysis of weather data for a hybrid solar/wind energy system’, Int. J. Energy Res., 2011, 35, (3), pp. 221–232.
    3. 3)
      • 8. Ridley, B., Boland, J., Lauret, P.: ‘Modelling of diffuse solar fraction with multiple predictors’, Renew. Energy, 2010, 35, (2), pp. 478–483.
    4. 4)
      • 10. Torres, J.L., De Blas, M., García, A., et al: ‘Comparative study of various models in estimating hourly diffuse solar irradiance’, 2010.
    5. 5)
      • 4. Goss, B.: ‘Design process optimisation of solar photovoltaic systems’ (Loughborough University, 2015), ch. 6.
    6. 6)
      • 16. Sengupta, M., Habte, A., Kurtz, S.: ‘Best practices handbook for the collection and use of solar resource data for solar energy applications’ (National Renewable Energy Laboratory, 2015).
    7. 7)
      • 5. Liu, B.Y.H., Jordan, R.C.: ‘The interrelationship and characteristic distribution of direct, diffuse and total solar radiation’, Sol. Energy, 1960, 4, (3), pp. 1–19.
    8. 8)
      • 11. Jacovides, C.P., Tymvios, F.S., Assimakopoulos, V.D., et al: ‘Comparative study of various correlations in estimating hourly diffuse fraction of global solar radiation’, Renew. Energy, 2006, 31, (15), pp. 2492–2504.
    9. 9)
      • 20. Cole, I.R.: ‘Modelling CPV’ (Loughborough Unversity, 2015).
    10. 10)
      • 12. Smale, N.: ‘Assessment and development of diffuse irradiance models for application within the UK, an MSc project report’ (Loughborough University, 2011), pp. 1–10.
    11. 11)
      • 1. Goss, B., Gottschalg, R., Betts, T.R.: ‘Uncertainty analysis of photovoltaic energy yield prediction’. 8th Photovoltaic Science, Applications and Technology Conf. (PVSAT-8), 2012.
    12. 12)
      • 13. Smietana, P.J., Flocchini, R.G., Kennedy, R.L., et al: ‘A new look at the correlation of Kd and Kt ratios and at global solar radiation tilt models using one-minute measurements’, Sol. Energy, 1984, 32, (1), pp. 99–107.
    13. 13)
      • 7. Boland, J., Ridley, B., Brown, B.: ‘Models of diffuse solar radiation’, Renew. Energy, 2008, 33, (4), pp. 575–584.
    14. 14)
      • 3. Goss, B., Cole, I.R., Koumpli, E., et al: ‘The performance of photovoltaic (PV) systems: modelling, measurement and assessment’, in Pearsall, N. (Ed.): (Woodhead Publishing, 2017, 1st edn.), ch. 4, p. 104.
    15. 15)
      • 2. Strobel, M.B., Betts, T.R., Friesen, G., et al: ‘Uncertainty in photovoltaic performance parameters – dependence on location and material’, Sol. Energy Mater. Sol. Cells, 2009, 93, (6-7), pp. 1124–1128.
    16. 16)
      • 15. Gueymard, C.A., Myers, D.R.: ‘Evaluation of conventional and high-performance routine solar radiation measurements for improved solar resource, climatological trends, and radiative modeling’, Sol. Energy, 2009, 83, (2), pp. 171–185.
    17. 17)
      • 21. Betts, T.R.: ‘Investigation of photovoltaic device operation under varying spectral conditions’ (Loughborough University, 2005).
    18. 18)
      • 6. Orgill, J.F., Hollands, K.G.T.: ‘Correlation equation for hourly diffuse radiation on a horizontal surface’, Sol. Energy, 1977, 19, (4), pp. 357–359.
    19. 19)
      • 9. Boland, J., Scott, L., Luther, M.: ‘Modelling the diffuse fraction of global solar radiation on a horizontal surface’, Environmetrics, 2001, 12, (2), pp. 103–116.
    20. 20)
      • 14. Rösemann, R.: ‘A guide to solar radiation measurement’ (Gengenbach Messtechnik, 2011, 2nd edn.).
    21. 21)
      • 17. Ransome, S., Funtan, P.: ‘Why hourly averaged measurement data is insufficient to model PV system performance accurately’. 20th European Photovoltaic Solar Energy Conf., 2005, pp. 2752–2755.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-rpg.2016.0903
Loading

Related content

content/journals/10.1049/iet-rpg.2016.0903
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
Print this page
This is a required field
Please enter a valid email address