Benjamin C. Duck

Efficiently-cooled plasmonic amorphous silicon solar cells integrated with a nano-coated heat-pipe plate

Solar photovoltaics (PV) are emerging as a major alternative energy source. The cost of PV electricity depends on the efficiency of conversion of light to electricity. Despite of steady growth in the efficiency for several decades, little has been achieved to reduce the impact of real-world operating temperatures on this efficiency. Here we demonstrate a highly efficient cooling solution to the recently emerging high performance plasmonic solar cell technology by integrating an advanced nano-coated heat-pipe plate. This thermal cooling technology, efficient for both summer and winter time, demonstrates the heat transportation capability up to ten times higher than those of the metal plate and the conventional wickless heat-pipe plates. The reduction in temperature rise of the plasmonic solar cells operating under one sun condition can be as high as 46%, leading to an approximate 56% recovery in efficiency, which dramatically increases the energy yield of the plasmonic solar cells. This newly-developed, thermally-managed plasmonic solar cell device significantly extends the application scope of PV for highly efficient solar energy conversion.

An applied light-beam induced current study of dye-sensitised solar cells: Photocurrent uniformity mapping and true photoactive area evaluation

The conditions for light-beam induced current (LBIC) measurement were experimentally optimised for dye-sensitised solar cells. The impacts of too fast a laser diode modulation frequency (f) and too short a dwell time (t0) were investigated for their distortions, artefacts, and noise on the overall photocurrent map image. Optimised mapping conditions for fastest measurement were obtained at a f = 15 Hz and t0 = 900 ms. Whole device maps (nominal area 4 × 4 mm2) were obtained on devices in which fabrication defects were intentionally induced. The defects were readily resolved with the LBIC setup and conditions. The inclusion of defects had the effect of broadening the photocurrent distribution and producing a sub-optimal tail to photocurrent histograms. Photoactive areas were derived from LBIC maps and were larger than those predicted by the projected screen printing pattern by up to 25%, which has obvious implications for efficiency measurements made on nominal projected active area.

Comparison of methods for estimating the impact of spectrum on PV output

Spectral correction factors are often used to characterize the impact of spectral variations on PV module output. We compare three different methods to predict a spectral correction factor and validate these against outdoor spectroradiometer measurements. It is found that commonly used models lead to a constant error due to assumptions made when determining coefficients describing geometric air mass dependence. We term this error the site spectral offset. This offset directly impacts estimations of the available solar resource and therefore affects the accuracy of energy yield predictions. We determine its value for the temperate coastal climate of Newcastle, Australia to be -2%, +1% and -3% for c-Si, CdTe and CIGS respectively. Errors in the daily resource estimation compared to pyranometer values of up to 15% are found for one module type while absolute variation of up to 60 Wm-2 in hourly AM1.5 equivalent insolation is seen for all examples studied. Applying a modified version of the CREST estimation method results in a significant reduction in estimation errors over all timescales

Comparing standard translation methods for predicting photovoltaic energy production

Translation equations underpin all predictive models for the energy output of photovoltaics in the outdoor environment. These equations translate the performance of a PV device to an arbitrary temperature and irradiance, based on measurements taken under reference conditions. Little work has been done to compare and contrast the three translation methods recommended under IEC 60891. This is partly due to a lack of comprehensive test data, and partly due to the flexibility in the way these methods can be applied. Based on comprehensive outdoor test data, we have used software scripts to evaluate the performance of these three standard translation methods, where the choice of reference conditions has been optimized to produce the best result in different ranges of irradiance and temperature. This allows a fair comparison of their performance that is independent of the test site location. We map the performance of the three methods over a wide range of irradiance and temperature.

Energy yield potential of perovskite-silicon tandem devices

Metal-halide perovskite photovoltaic devices have recently become of great interest to the research community with efficiencies of the thin film devices already reported to exceed a single junction cell efficiency of 20%. Of particular interest with this type of device is its potential to be integrated with the well established silicon photovoltaic technology into a monolithic tandem device with the potential to deliver efficiencies of greater than 30% In such devices the most attractive prospect is to monolithically integrate the perovskite and silicon materials into a planar single device for ease of deposition and device construction. Such a series connected device comes with inherent current matching restrictions on the operating performance of the individual junctions when working in tandem. These restrictions significantly complicate the calculation of potential energy yield for such a tandem device due to the impact of spectrum, angle of incidence and temperature. We model the performance of a tandem device using experimentally determined performance characteristics combined with representative resource and environment datasets to evaluate the energy yield potential of perovskite-silicon tandem under outdoor conditions. We observe that the largest impact is caused by the spectral irradiance distribution (7.6%) followed by angle of incidence (2.7%) and temperature response differential (0.7%). Our modelling indicates that these combine to alter the energy yield for a tandem device by 4.5%.

Determining uncertainty for I–V translation equations

Photovoltaic energy yield predictions rely on methods that estimate outdoor performance under arbitrary conditions based on a set of reference measurements. The uncertainty in these predictions has direct economic impacts on both the perceived feasibility of new systems and the energy market value. A common approach uses a set of translation equations such as those proposed in IEC 60891. Previous work examining the performance of the standard translation methods has not addressed the important issue of uncertainty. This is due to both a lack of comprehensive test data, and the scope of the problem resulting from flexibility in the way these methods can be applied. We used synthetic data to characterize the behavior of these standard translation methods in the presence of input uncertainty. The inputs and their uncertainty can then be mapped to the prediction uncertainty over a wide range of conditions.

Improving the spectral correction function

Plane of array irradiance derived from common measurement sources is not usually directly applicable in modelling the energy yield of photovoltaic systems. Corrections to an effective irradiance value are required due to the differences in the spectral and angular response of irradiance measurement instruments (typically pyronometers or reference cells) when compared to the installed system. Empirical methods to provide this correction based on easily measured parameters are attractive both because of the simplicity of their implementation and the ability to tailor the solution to fit the system under study. Unfortunately the most common methods to correct for spectrum and angle of incidence do not adequately capture performance under non-ideal conditions. Here we demonstrate that for silicon modules an improved surface function combining air mass and clearness index is capable of being used as a site independent measure of spectral mismatch. Following a correction for precipitable water the same result is obtained from the procedure applied to cadmium telluride modules.

Near-field scanning optical lithography of PPV for functional devices

We show here for the first time a device manufactured by the technique of near-field scanning optical lithography (NSOL) functioning as an optical device. The technique of NSOL is used to manufacture an optical transmission phase grating (or phase mask) of the semi-conducting polymer poly(p-phenylene vinylene) (PPV), this was done as a proof of concept for device manufacture by this method. Structures on this scale are of interest for integrated optical devices. The phase mask was characterised using AFM and SEM and examined in the context of how well a diffraction pattern matches with theoretical calculations. Some calculations were performed to determine the feasibility of using a similar grating as a component of an all-optical switch. The ablation threshold of PPV was determined to complement the calculations.

Mode structure in continuum generation

A systematic, wavelength-resolved study of micro-structured optical fibre input coupling dependence has revealed wavelength-dependent higher order mode structure and orientation in the generated continuum. The constituent continuum wavelengths are not well matched by current theory.

Quantifying and reducing curve-fitting uncertainty in Isc

Current-voltage (I-V) curve measurements of photovoltaic (PV) devices are used to determine performance parameters and to establish traceable calibration chains. Measurement standards specify localized curve fitting methods, e.g., straight-line interpolation/extrapolation of the I-V curve points near short-circuit current, Isc. By considering such fits as statistical linear regressions, uncertainties in the performance parameters are readily quantified. However, the legitimacy of such a computed uncertainty requires that the model be a valid (local) representation of the I-V curve and that the noise be sufficiently well characterized. Using more data points often has the advantage of lowering the uncertainty. However, more data points can make the uncertainty in the fit arbitrarily small, and this fit uncertainty misses the dominant residual uncertainty due to so-called model discrepancy. Using objective Bayesian linear regression for straight-line fits for Isc, we investigate an evidence-based method to automatically choose data windows of I-V points with reduced model discrepancy. We also investigate noise effects. Uncertainties, aligned with the Guide to the Expression of Uncertainty in Measurement (GUM), are quantified throughout.