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|Title: ||Uncertainty considerations in photovoltaic measurements|
|Authors: ||Mihaylov, Blagovest V.|
|Issue Date: ||2016|
|Publisher: ||© Blagovest Mihaylov|
|Abstract: ||Measurement uncertainty is an indication of the quality of a given measurement and ultimately translates into the confidence with which a decision can be made. In the context of PV, measurement uncertainties propagate into energy yield uncertainty, which in turn culminates into financial risk associated with an investment. This risk increases the cost of a PV installation.
The aim of this thesis is to contribute towards the reduction of PV related measurement uncertainties. This is done in two ways. One is via developing and utilising more comprehensive methodologies for uncertainty propagation of complex measurands. The other is via more detailed estimates of the uncertainty contributors. In particular, the areas addressed in this thesis are the uncertainty estimation of the temperature coefficient measurements of modules; the uncertainty estimation of energy rating and module performance ratio measurements; and the uncertainties due to spectral effects on measurements performed with a flash solar simulator.
The reported deviation in measurements of the temperature coefficients of P_MAX of modules is in the order of ±10% to ±15%. This is larger than the difference in the temperature coefficients of modules of the same type. The first step to improving the deviation between measurements is to estimate the uncertainty in a robust way. It was identified that there was no accepted approach of doing this. These measurements are strongly correlated, which complicates the uncertainty estimates. For the sake of simplicity, previously correlations have been avoided and conservative estimates used instead. In this work, uncertainties in both temperature and power and their correlations are estimated and propagated into the overall temperature coefficient uncertainty. Furthermore, temperature coefficients were calculated via weighing the measurements with their associated uncertainties. This was done for five different measurement setups that represent the majority of setups used worldwide. The approach was validated with measurement intercomparison of two modules measured on all systems. The approach reduced the overall uncertainty by half compared to the previous conservative estimates. It was demonstrated that uncertainties as low as 3% are achievable. The improved uncertainty estimates enabled the identification of a systematic effect due to a class B spectrum. This work culminated in the lowest reported measurement deviation of ±3.2% for module P_MAXtemperature coefficient measurements that was within the stated measurement uncertainties.
The clear benefit of accounting for correlations was extended to measurements at different irradiance conditions and into the calculation of module performance ratio and energy rating. This was done via defining all the correlations between measurements and then propagating them with Monte Carlo simulations. The simulations are done with samples of a multivariate normal distribution with a variance-covariance matrix that corresponds to the estimated measurement correlations. It is demonstrated that both the energy rating and module performance ratio uncertainties strongly depend on the correlation estimates and that they cannot be conservatively overestimated. The module performance ratio uncertainty can be significantly lower than the measurement uncertainty at STC. This is because of the additional knowledge encoded into the selection of the underlying model used for calculating the energy rating. Therefore, the significance of the choice of model in the upcoming standard has been highlighted. It was confirmed that both bilinear interpolation and the proposed climatic datasets could be used for energy rating, but there are some areas that may need further investigation.
An alternative way of improving uncertainty estimates and in turn reducing the associated uncertainty is via a more detailed characterisation of the uncertainty sources. A key uncertainty source is due to spectral effects in flash solar simulators. To better quantify this source, a complementary device was built to monitor the spectrum. The device is based on a matrix of photodiodes with commercially available interference filters situated on top and custom designed data acquisition electronics. This device is used in conjunction with the spectroradiometer to estimate the effects of flash-variation on the spectrum, the spectral temporal stability of the flash and spectral uniformity of the simulator and the attenuation masks used for altering the irradiance levels. It was demonstrated that the spectrum changes significantly during the flash and between flashes. While this effect is partially corrected for via the monitoring cell, it introduces additional uncertainty for non c-Si modules. This uncertainty is minimised by changes in the operational procedures. The spectral non-uniformity of the attenuation masks was shown to be significant, i.e. as large as 4%, in the NIR, prompting further investigation of the additional uncertainty for non c-Si modules.
In this work, the methodology of estimating and propagating correlations in PV related measurements and the benefits of doing so are demonstrated. It is also highlighted that the uncertainty due to spectral effects goes beyond the uncertainty of spectroradiometer measurements. Finally, it is shown how they can be estimated with a complementary spectral monitor.|
|Description: ||A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University.|
|Appears in Collections:||PhD Theses (Mechanical, Electrical and Manufacturing Engineering)|
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