Solar Energy - Comparing Photovoltaic Convertors
Solar photovoltaic technology converts the energy of sunlight directly into electricity. They have the advantage of not emitting pollutants and operating silently as they have no moving parts. The power generated by eleven different photovoltaic technologies and meteorological variables, such as irradiance and temperature, were recorded every half-hour at sites in the UK and Spain. These photovoltaic technologies included monocrystalline, multicrystalline and amorphous silicon, copper indium diselenide and cadmium telluride. Local linear quantile regression was used to determine the conversion efficiency of each technology as a function of the irradiance. This non-parametric technique also provides confidence intervals for the estimates. Monocrystalline silicon had the highest conversion efficiency, ranging between 10% and 13%.
PV-Compare [1-3], a project operated by the Environmental Change Institute, tested eleven different photovoltaic technologies, situated both in the UK and Spain. The results quantify the proportion of energy actually converted to electricity, known as the conversion efficiency [4]. A statistical technique known as local linear quantile regression (LLQR) [5] was used to estimate the median efficiency and confidence intervals, conditioned on the level of irradiance.
Comparing the efficiencies of the photovoltaic technologies in the UK (Fig. 2) and Spain demonstrated that the BP Solar 585 (monocrystalline silicon) was a clear winner in both locations, although there was a larger decrease in performance at the higher levels of irradiance in Spain. Cloudy conditions typically dominate in the UK giving rise to low irradiance, low temperatures and blue light, which decreases efficiency. While the initial increase in irradiance improves efficiency, blue light and hot temperatures eventually reduce efficiency. Overall the results of the comparison were relatively robust to the disparate climatic conditions in the two countries, suggesting that the analysis could be generalised to other climates.
[1] P.E. McSharry (2006), Assessing photovoltaic performance using local linear quantile regression in Proceedings of Energy and Power Systems, IASTED: Chiang Mai, Thailand. pp. 165-169.
[2] C.N. Jardine, T.R. Betts, R. Gottschalg, D.G. Infield, K. Lane (2002), Influence of spectral effects on the performance of multi-junction amorphous silicon cells in PV in Europe Conference and Exhibition: Rome.
[3] C.N. Jardine, G.J. Conibeer, K. Lane (2002), PVcompare: relative performance of photovoltaic technologies in northern and southern Europe in PV in Europe Conference and Exhibition: Rome.
[4] C.N. Jardine, K. Lane, G.J. Conibeer (2001), PVcompare: direct comparison of eleven PV technologies at two locations in northern and southern Europe in 17th European Conference on Photovoltaic Solar Energy Conversion: Munich.
[5] K.M. Yu, M.C. Jones (1998), Local linear quantile regression. Journal of the American Statistical Association, 93(441): pp. 228-237.