The most established key performance indicator for (PV) system performance is the performance ratio (PR) metric, which is the ratio of the actual to the expected specific yield of a PV system. Accurate PR calculations are crucial for the PV systems industry, as errors can potentially lead to hidden underperformance, unfair financial penalties and uncertainty in system value. In systems with high DC:AC ratios, the regular occurrence of inverter clipping causes problems with PR assessment which include masking degradation and increased seasonal variation. A common practice is to exclude clipped data from PR calculations, but this can bias the remaining dataset and masks problems with inverters. In this work, a new improved clipping-corrected PR (CCPR) metric is introduced and evaluated. CCPR takes into account clipping and weather variability, and allows the use of all datapoints during a PV system’s operation. We introduce the new metric and evaluate it for different locations around the world using synthetic data. Different types of clipping ratios and faults of the system are tested, demonstrating that the new PR metric is more robust compared to the current standardized PR metrics, and is not affected by weather conditions. In addition, we show that the new metric is robust against the use of low temporal resolution Typical Meteorological Year data for calculating expected PR, in contrast with standard PR metrics. The widespread adoption and potential standardization of this new metric can lead to more accurate PR assessment for PV systems, reduced contractual risks for companies in the sector and increased in confidence of PV generation by consumers.

Indoor photovoltaics (IPVs) harvest ambient light to produce electricity and can cleanly power the rapidly growing number of Internet-of-Things (IoT) sensors. The surge in IPV development, with new proposed materials, devices and products, creates the need to critically evaluate how IPV devices have advanced and to assess their prospects. In this Review, we analyse the status, challenges and opportunities of established and emerging IPV technologies, including metal-halide perovskite, organic photovoltaics, dye-sensitized solar cell and perovskite-inspired materials. Many emerging low-toxicity semiconductor materials could reach IPV efficiencies of up to 50

We fabricate a type of back-contact perovskite solar cell based on 1.5 μm-width grooves that are embossed into a plastic film whose opposing "walls" are selectively coated with either n- or p-type contacts. A perovskite precursor solution is then deposited into the grooves, creating individual photovoltaic devices. Each groove device is series-connected to its neighbors, creating minimodules consisting of hundreds of connected grooves. Here, we report on the fabrication of groove-based devices using slot-die coating to deposit the perovskite precursor and explore the structure of the perovskite in the grooves using a range of microscopy and spectroscopy techniques. Significantly, our devices do not contain any expensive or scarce elements such as indium, indicating that this technology is both sustainable and low-cost. Furthermore, all coating processes explored here were performed using roll-to-roll processing techniques. Our technology is therefore completely scalable and is consistent with high-throughput, low-cost manufacturing.

This study presents results of an intercomparison of indoor photovoltaics (PVs) among seven metrological institutes. Three types of solar cells were measured; organic and amorphous silicon cells representing current indoor products in the market and a reference solar cell. Three different light sources—AM1.5G, International Commission of Illumination Standard Illuminant A, and light‐emitting diodes (LED) L41—were used at illuminance levels 100–2000 lx. Each laboratory reported short‐circuit current as mandatory. Open‐circuit voltage, maximum power, and differential spectral responsivity were reported where possible. Measurements revealed notable discrepancies. At the 1000 lx level, best agreement of 7% as standard deviation was achieved for the amorphous silicon cell using Standard Illuminant A. Similarly, the worst agreement of 37% was found for the reference cell using AM1.5G. Measurement methods varied across the laboratories. Some participants used lamps for Standard Illuminant A and LED L41. These measurements were generally in agreement but deviated from measurements with LED‐based solar simulators, due to differences in measurement geometry, spectral properties, and treatment of infrared. Different illuminance measurement approaches, using either calibrated reference cells or luxmeters, further impacted consistency. This study highlights need for harmonized procedures to support reliable performance assessment of indoor PVs and gives recommendations to account for in standards.

There is an increasing interest in using indoor photovoltaic (IPV) devices to power Internet of Things applications, low power communications, and indoor environmental sensing. For the commercialization of IPV technologies, device performance measurements need to conform to the relevant standardized specifications. We present a novel IPV device measurement system that incorporates digital light processing (DLP) to deliver a spectrally invariant light source at all required illuminance levels, as specified by the indoor standard testing conditions in IEC TS 62607-7-2:2023. We evaluated the DLP system according to requirements for spectral coincidence, temporal stability, and non-uniformity at the sample plane. We demonstrate the measurements to define the classification status of the system and the unique benefits of the DLP system that allow a stable spectral profile and high levels of uniformity across all illuminance levels. This is the first reported measurement system for IPV device testing based on DLP technology, and the classification methodology of this work can be used as an example for the classification of indoor light simulators in laboratory environments based on the latest IEC TS 62607-7-2:2023.

Photovoltaics (PVs) are a critical technology for curbing growing levels of anthropogenic greenhouse gas emissions, and meeting increases in future demand for low-carbon electricity. In order to fulfill ambitions for net-zero carbon dioxide equivalent (CO _2 eq) emissions worldwide, the global cumulative capacity of solar PVs must increase by an order of magnitude from 0.9 TW _p in 2021 to 8.5 TW _p by 2050 according to the International Renewable Energy Agency, which is considered to be a highly conservative estimate. In 2020, the Henry Royce Institute brought together the UK PV community to discuss the critical technological and infrastructure challenges that need to be overcome to address the vast challenges in accelerating PV deployment. Herein, we examine the key developments in the global community, especially the progress made in the field since this earlier roadmap, bringing together experts primarily from the UK across the breadth of the PVs community. The focus is both on the challenges in improving the efficiency, stability and levelized cost of electricity of current technologies for utility-scale PVs, as well as the fundamental questions in novel technologies that can have a significant impact on emerging markets, such as indoor PVs, space PVs, and agrivoltaics. We discuss challenges in advanced metrology and computational tools, as well as the growing synergies between PVs and solar fuels, and offer a perspective on the environmental sustainability of the PV industry. Through this roadmap, we emphasize promising pathways forward in both the short- and long-term, and for communities working on technologies across a range of maturity levels to learn from each other.

Local defects and non-uniformities in optoelectronic materials and devices can have an impact on their quality and performance characteristics. The development of non-destructive optical metrology methods that provide spatially resolved information on defects and inhomogeneities is crucial for multiple industries that rely on high quality semiconductor materials and devices, from power electronics and LEDs to solar cells and photodiodes. Traditional point-by-point scanning approaches for microscopy and spectroscopy offer mapping solutions that can produce invaluable datasets, nevertheless in most cases measurements are time-consuming, require complex measurement setups or give very weak signals. In this work we present how a compressed sensing approach can benefit optical metrology techniques and the principles of how to adopt and implement a compressed sensing optical system in practice for semiconductor metrology. As examples, we demonstrate through a simulation process a proposed compressed sensing spectral photoluminescence measurement methodology for characterization of semiconductor materials and devices. The focus in this work is specifically wide bandgap semiconductor materials. The features, advantages and challenges of this compressed sensing optical measurement approach are discussed, including the minimum noise levels required for experimental implementation. Different approaches for reconstruction of the spectral PL datacubes are presented.

Metastability is a characteristic feature of perovskite solar cell (PSC) devices that affects power rating measurements and general electrical behaviour. In this work the metastability of different types of PSC devices is investigated through current–voltage (I–V) testing and voltage dependent photoluminescence (PL-V) imaging. We show that advanced I–V parameter acquisition methods need to be applied for accurate PSC performance evaluation, and that misleading results can be obtained when using simple fast I–V curves, which can lead to incorrect estimation of cell efficiency. The method, as applied in this work, can also distinguish between metastability and degradation, which is a crucial step towards reporting stabilised efficiencies of PSC devices. PL-V is then used to investigate temporal and spatial PL response at different voltage steps. In addition to the impact on current response, metastability effects are clearly observed in the spatial PL response of different types of PSCs. The results imply that a high density of local defects and non-uniformities leads to increased lateral metastability visible in PL-V measurements, which is directly linked to electrical metastability. This work indicates that existing quantitative PL imaging methods and point-based PL measurements of PSC devices may need to be revisited, as assumptions such as the absence of lateral currents or uniform voltage bias across a cell area may not be valid.

Photovoltaics (PVs) are a critical technology for curbing growing levels of anthropogenic greenhouse gas emissions, and meeting increases in future demand for low-carbon electricity. In order to fulfil ambitions for net-zero carbon dioxide equivalent (CO2eq) emissions worldwide, the global cumulative capacity of solar PVs must increase by an order of magnitude from 0.9 TWp in 2021 to 8.5 TWp by 2050 according to the International Renewable Energy Agency, which is considered to be a highly conservative estimate. In 2020, the Henry Royce Institute brought together the UK PV community to discuss the critical technological and infrastructure challenges that need to be overcome to address the vast challenges in accelerating PV deployment. Herein, we examine the key developments in the global community, especially the progress made in the field since this earlier roadmap, bringing together experts primarily from the UK across the breadth of the photovoltaics community. The focus is both on the challenges in improving the efficiency, stability and levelized cost of electricity of current technologies for utility-scale PVs, as well as the fundamental questions in novel technologies that can have a significant impact on emerging markets, such as indoor PVs, space PVs, and agrivoltaics. We discuss challenges in advanced metrology and computational tools, as well as the growing synergies between PVs and solar fuels, and offer a perspective on the environmental sustainability of the PV industry. Through this roadmap, we emphasize promising pathways forward in both the short- and long-term, and for communities working on technologies across a range of maturity levels to learn from each other.

Bifacial photovoltaic (PV) systems harvest additional light reflected from the ground. The proportion of light reflected from the ground (albedo) is a critical parameter in estimating the expected performance of these systems. It is important that albedo data are available at the system design stage are accurate and relevant, and that the confidence in these data can be quantified. This work investigates the challenges of different albedo data sources and proposes solutions towards more reliable datasets. Satellite sources, such as the NASA Moderate Resolution Imaging Spectrometer (MODIS) products, provide data that can be used to model effective albedo anywhere in the world. Nevertheless, there are numerous sources of error that can add uncertainty in bifacial gain, reducing confidence and increasing financial risk. For smaller sites (<similar to 10 MW) located in varied land-scapes, the scaling error caused by the low spatial resolution can be large. By analysing case studies in complex agricultural landscapes, we investigate the accuracy of different albedo measurement approaches. Monitoring stations with reference cells and pyranometers were deployed to validate satellite data and to realise a site measurement campaign for albedo measurements. Since these sites are much smaller than a MODIS pixel, we have evaluated alternative approaches, including "typical landscapes" with adjustments for local latitude and weather, and a novel method of combining MODIS data with higher resolution satellite data. The latter offers a practical solution with good agreement with the ground-based station.

Photocurrent response mapping is a powerful imaging technique for assessing defects and losses in photovoltaic devices. However, it has not enjoyed widespread application because high‐resolution measurements of large samples can last several hours, while weak signals from micrometer‐sized laser spots require lock‐in amplification. An alternative approach presented recently is the use of digital micromirror devices combined with compressed sensing theory. There are significant benefits when using such methods, such as signal amplification, undersampling options, and simplified measurement systems. Nevertheless, high computational requirements have limited the experimental application of this method to low‐resolution outputs. Herein, the mathematical background and the experimental approach toward megapixel resolution, ultrafast compressed sensing current mapping are presented, overcoming previous computational and experimental barriers. A high‐power digital light processing projection system is developed for the experimental application. Solutions to computational issues, sampling optimization, and measurement strategies are presented and the flexibility of the system regarding the sizes of photovoltaic devices that can be measured is demonstrated.

Semiconductor materials have a significant role to play towards the national Net Zero targets, through their roles in renewable energy generation, electricity distribution, and efficient energy consumption. Both established and emerging semiconductors have relevant net zero applications such as: power electronics for electric vehicles, grid infrastructure, and inverters for renewable energy generation, photovoltaics, as well as efficient telecommunications and lighting/display devices. Quality control is critical to the manufacturing industry for these semiconductor materials where defect-related yield and performance losses are widely recognised challenges. This report describes research carried out by NPL within the NMS programme towards developing a new imaging approach for wafer-scale defect identification. We have explored the use of compressed sensing as a strategy for increasing the throughput and sensitivity of defect inspection for various semiconductor materials. In particular we consider the novel application of compressed sensing (CS) to time-resolved photoluminescence (TRPL) mapping, where the local photoluminescence lifetime of the semiconductor reveals the presence of defects and inhomogeneities. We evaluate the feasibility and the potential gains in performance compared with traditional point-by-point measurement strategies and evaluate the feasibility of applying the method to several semiconductor materials. The developed system of this work is currently operating as a typical TRPL system, with single point and raster scanning capability. This has added a capability that did not previously exist at NPL. Simulations of the CS TRPL sampling process have showed that the methodology is feasible and can be applied to achieve TRPL mapping with high resolution for small areas of semiconductor wafers with the developed instrument. In addition, the simulations have provided the necessary insights into how the reconstruction process can be applied for the CS TRPL method. Comparison of the instrument specifications with typical material parameters for ‘Net Zero’ materials indicates that the current system is well-suited for TRPL measurements of the vast majority of photovoltaic absorber materials. The current capabilities also apply to many organic semiconductors and transition metal dichalcogenides, which have various optoelectronic applications relevant to ‘Net Zero’ technologies. The potential upgrades of the system in regard to light sources, detectors, optical components or algorithms have been discussed.

The IEC 61853 standard series aims to provide a standardized measure for photovoltaic (PV) module energy rating, namely the Climate Specific Energy Rating (CSER). For this purpose, it defines procedures for the experimental determination of input data and algorithms for calculating the CSER. However, some steps leave room for interpretation regarding the specific implementation. To analyze the impact of these ambiguities, the comparability of results, and the clarity of the algorithm for calculating the CSER in Part 3 of the standard, an intercomparison is performed among research organizations with ten different implementations of the algorithm. We share the same input data, obtained by measurement of a commercial crystalline silicon PV module, among the participating organizations. Each participant then uses their individual implementations of the algorithm to calculate the resulting CSER values. The initial blind comparison reveals differences of 0.133 (14.7%) in CSER. After several comparison phases, a best practice approach is defined, which reduces the difference by a factor of 210 to below 0.001 (0.1%) in CSER for two independent PV modules. The best practice presented in this article establishes clear guidelines for the numerical treatment of the spectral correction and power matrix extrapolation, where the methods in the standard are not clearly defined. Additionally, we provide input data and results for the PV community to test their implementations of the standard's algorithm. To identify the source of the deviations, we introduce a climate data diagnostic set. Based on our experiences, we give recommendations for the future development of the standard.

This is the data from PV module energy rating standard IEC 61853-3 intercomparison. Details can be found in: M. R. Vogt, S. Riechelmann, A. M. Gracia-Amillo, A. Driesse, A. Kokka, K. Maham, P. Kärhä, R. Kenny, C. Schinke, K. Bothe, J. C. Blakesley, E. Music, F. Plag, G. Friesen, G. Corbellini, N. Riedel-Lyngskær, R. Valckenborg, M. Schweiger, W. Herrmann, „PV module energy rating standard IEC 61853-3 intercomparison and best practice guidelines for implementation and validation”, accepted IEEE JPV. DOI (identifier) 10.1109/JPHOTOV.2021.3135258

Although photovoltaic (PV) devices are rated at standard testing conditions (STCs), these STCs are rarely met, either outdoors, or when PV devices are used for indoor applications. Thus, it is beneficial to fully characterise the linearity of PV devices with respect to irradiance. Moreover, high accuracy linearity measurements are essential for reference cells (RCs), as they ensure the precision of the measured irradiance. This work presents a new technique for linearity measurements of PV devices based on digital light processing (DLP). The proposed system uses a digital micromirror device coupled with projection optics and a high-power LED array. By creating a series of patterns projected on the device under test with a specific number of bright and dark pixels, linearity measurements can be implemented through a spatial dithering process. Since the dithering process is mechanical, it is expected that any spectral variability effects for the different dithering levels or electrical non-linearities of the light source are avoided. The developed system can provide thousands of measurement points on the linearity curve of a device in seconds, which is impossible with any other currently established methods. Measurements of RCs with known linearity curves are acquired and are validated by conventional methods. Results demonstrate that the DLP method provides equal measurement accuracy compared to conventional systems, but at significantly higher resolution (points on the linearity curve) and order of magnitude higher measurement speed.

Controlling the radiative properties of monolayer transition metal dichalcogenides is key to the development of atomically thin optoelectronic devices applicable to a wide range of industries. A common problem for exfoliated materials is the inherent disorder causing spatially varying nonradiative losses and therefore inhomogeneity. Here we demonstrate a five-fold reduction in the spatial inhomogeneity in monolayer WS2, resulting in enhanced overall photoluminescence emission and quality of WS2 flakes, by using an ambient-compatible laser illumination process. We propose a method to quantify spatial uniformity using statistics of spectral photoluminescence mapping. Analysis of the dynamic spectral changes shows that the enhancement is due to a spatially sensitive reduction of the charged exciton spectral weighting. The methods presented here are based on widely adopted instrumentation. They can be easily automated, making them ideal candidates for quality assessment of transition metal dichalcogenide materials, both in the laboratory and industrial environments.

In this work, a non-destructive, automated procedure to extract the I-V characteristics of individual cells of fully encapsulated photovoltaic (PV) modules is proposed. The approach is able to correctly identify and extract the electrical parameters of underperforming cells, due for example to defects or degradation. The approach uses multiple I-V measurements on the PV module assuming specific levels of shading on the individual cells. The single circuit models for the cells are obtained through the solution of an inverse fitting problem. The approach was validated in a simulated environment through statistical analysis, with the cell parameters based on real silicon PV devices. The computational complexity of the approach is also investigated and validation examples with different configurations of PV modules, including bypass diodes are presented. The approach was validated on several tests to assess noise robustness, flexibility in terms of cells non-uniformities and scalability towards larger systems, resulting in a lean and accurate procedure for I-V curves extraction. The proposed methodology can be potentially utilised for automated quality assurance and fault assessment of PV modules, investigation of degradation mechanisms of cells in PV modules, or quantitative validation of other optical imaging techniques such as luminescence imaging and infrared thermography.

The IEC 61853 standard series “Photovoltaic (PV) module performance testing and energy rating” aims to provide a standardized measure for PV module performance, namely the Climate Specific Energy Rating (CSER). An algorithm to calculate CSER is specified in part 3 based on laboratory measurements defined in parts 1 and 2 as well as the climate data set given in part 4. To test the comparability and clarity of the algorithm in part 3, we share the same input data, obtained by measuring a standard photovoltaic module, among different research organizations. Each participant then uses their individual implementations of the algorithm to calculate the resulting CSER values. The initial blind comparison reveals differences of 0.133 (14.7%) in CSER between the ten different implementations of the algorithm. Despite the differences in CSER, an analysis of intermediate results revealed differences of less than 1% at each step of the calculation chain among at least three participants. Thereby, we identify the extrapolation of the power table, the handling of the differences in the wavelength bands between measurement and climate data set, and several coding errors as the three biggest sources for the differences. After discussing the results and comparing different approaches, all participants rework their implementations individually and compare the results two more times. In the third intercomparison, the differences are less than 0.029 (3.2%) in CSER. When excluding the remaining three outliers, the largest absolute difference between the other seven participants is 0.0037 (0.38%). Based on our findings we identified four recommendations for improvement of the standard series.