Photovoltaic (PV) system performance is linked to climatic conditions in which the system operates. This leads to the Köppen-Geiger-Photovoltaic (KGPV) climate classification. KGPV is created by overlaying four irradiation levels with the commonly used Köppen-Geiger climate zones. Potential drawbacks of this approach are that the climate features are not considered in a combined manner in the sorting process and that the KGPV zones inherent a dependence on precipitation. We propose a machine-learning approach to address this deficiencies and improve PV climate classification. First, supervised learning is used to evaluate the correlation between climate features and a PV system's specific energy yield. We find that the inclusion of the darkest and brightest irradiation months as well as UV irradiation improves accuracy, while wind speed, relative humidity, precipitation and annual mean daily temperature difference have little impact on accuracy. Subsequently, k-means clustering combined with comprehensive qualitative analysis, identifies a PV classification based on seven climate features and 21 clusters. A mountainous climate characterized by moderate to low temperature and high irradiation is uncovered compared to KGPV. Moreover, this new PV climate classification reduces the sum of squared errors by 58 % compared to KGPV clearly signifying a more accurate PV climate classification approach.

Perovskite/silicon (PS) technology includes three main configurations: two-terminal (2T), three-terminal (3T), and four-terminal (4T). Previous studies have made various comparisons between these configurations, significantly advancing our understanding of these devices. While these studies mostly focus on simulations on cell level, we perform bandgap energy ((Formula presented.)) optimization at the module level for different configurations under outdoor conditions. Using opto-electrical simulations, we predict the energy yield of each module at four geographical locations, with varying values of (Formula presented.). The optimal (Formula presented.) for the 2T, 3T, and 4T modules are 1.62, 1.80, and 1.82 eV, respectively. We also perform a loss analysis to explore the differences in power losses among the configurations. These loss differences can be attributed to the configurations having different optimal (Formula presented.) values (affecting the thermalization losses) or different module designs (affecting the interconnection losses). Among all losses, mismatch losses play the most critical role in optimizing the bandgap. Overall, all optimized configurations have similar energy yields (all differences within 1.5%) across all locations. Finally, we compare the robustness of the different configurations against different scenarios of perovskite degradation. Our results show that the 4T module is the least sensitive to degradation in the perovskite subcell.

As crystalline silicon (c-Si) solar cells approach their theoretical efficiency limit, the perovskite/silicon (PerSi) tandem technology offers a promising solution for further improving the efficiency of photovoltaic (PV) modules. However, as perovskite cells are facing stability issues, it is unclear whether PerSi modules will have a larger lifetime energy yield (LEY) than c-Si modules. In this work, we present a novel methodology to simulate the LEY of PerSi tandem devices, accounting for environmental stress factor-dependent degradation across four different climates. Our approach combines a physics-based analytical degradation model for components shared with c-Si modules and a scenario-based degradation model for the perovskite top cell. This method enables us to identify the tolerable degradation rate (k_tol) of the perovskite cell under different scenarios and climatic conditions. We find that k_tol is lowest when degradation occurs in the short-circuit current, reaching a minimum value of 1.2% per year in Delft (the Netherlands). Additionally, we demonstrate that k_tol inversely depends on the module lifetime, reaching values up 7.6% per year in Lagos (Nigeria). Moreover, we show that module efficiency (η_mod) significantly impacts k_tol. For instance, increasing η_mod from 28.0% to 32.9% raises k_tol by approximately 50%. Additionally, we propose a simplified model that can predict k_tol without the computationally intensive simulations, which has a root-mean-square error of 0.34% per year. Lastly, environmental impact assessments reveal that PerSi modules are more sustainable in all impact categories when the degradation rate is 80% of k_tol for LEY.

Advanced and emerging photovoltaic (PV) technologies play a crucial role in meeting the increasing global energy demand sustainably. Simulations are essential for predicting system behavior and improving our understanding of complex PV architectures. This work extends an existing modeling framework designed for novel PV systems, offering a modular and flexible workflow suitable for diverse research applications. The framework computes PV performance from first-principles physics, removing the need for module datasheets. It comprises two pre-processing steps and six simulation steps. The first steps determine the optical behavior of the modules, followed by irradiance modeling and temperature calculations. The final steps evaluate the electrical characteristics and the conversion to alternating current at the full-system level. The framework incorporates detailed energy loss analysis and includes advanced features such as partial shading, reverse-bias effects, and photon recycling. Two applications demonstrate its capabilities: comparing module configurations in urban settings and optimizing multi-junction PV system design. Results show that Smart modules enhance shade resilience, delivering approximately (Formula presented.) higher energy yields. Additionally, the optimal perovskite bandgap for perovskite/silicon tandem devices is found to be 1.60–1.62 eV. These outcomes highlight the framework's value for future PV system research and development. The developed software can be found at: https://github.com/YBlom1999/PVMD_Toolbox.

In the quest for advancing photovoltaic efficiency, the adoption of multijunction solar cell architectures has emerged as a promising approach. Perovskite/silicon double-junction solar cells have already achieved efficiencies surpassing 33%, exceeding the theoretical efficiency limit for single-junction devices. To enhance efficiency even further, exploring perovskite/perovskite/silicon (PPS) triple-junction solar cells seems a logical next step, as they offer the potential to further reduce thermalization losses and achieve even higher efficiencies. This study delves into the potential of various configurations of PPS modules, exploring different subcell interconnections. Initially, we present an optoelectrical model to simulate the performance of these devices, incorporating both luminescence coupling and cell-to-module losses. This enables us to optimize the bandgap energy of the top and middle perovskite subcells under both standard test conditions (STC) and outdoor conditions. Our analysis reveals that the addition of a perovskite subcell can improve the STC efficiency up to 9%–13%. This gain in STC performance also translates into a similar gain in energy yield, meaning that triple-junction devices produce 8%–14% more electricity than their double-junction reference devices.

Bifacial perovskite/silicon solar cells can combine the advantages of tandem technology (high efficiencies) and bifacial modules (additional received irradiance from the rear) to increase the energy yield of photovoltaic (PV) systems further. In literature, it has already been shown that for two-terminal tandems this would require a lower bandgap energy (E_g) for the perovskite cell, as the rear irradiance increases the current in the bottom cell creating a current mismatch, if this is not considered during optimization. This work expands on bifacial two-terminal tandem optimization by considering aspects not included before. Besides the E_g, the thickness (d) of the perovskite is also optimized, as this also affects the current matching. Additionally, this work studies the trends in different energy losses of the PV module to better understand what affects the optimal perovskite cell. Our simulations show that the optimal E_g is 1.61–1.65 eV and the optimal d is 650–750 nm, which agrees with the observations in literature. The optimal E_g and d are mostly a trade-off between mismatch and thermalization losses, meaning that the mismatch losses should not be fully minimized. Additionally, the irradiance from the rear side is converted less efficiently than the front side irradiance due to larger thermalization and reflection losses. Therefore, the energy yield of bifacial tandem modules, compared to monofacial tandem ones, only increases for large ground albedo. Finally, our results show that the bifacial tandems have over a 25% gain in energy yield compared to bifacial single junction modules and up to 5% gain compared to monofacial tandem modules.

Lead halide perovskites are a promising class of materials for solar cell applications. The perovskite bandgap depends on the material composition and is highly tunable. Opto-electrical device modelling is commonly used to find the optimum perovskite bandgap that maximizes device efficiency or energy yield, either in single junction or multi-junction configuration. The first step in this calculation is the optical modelling of the spectral absorptance. This requires as input the perovskite's complex refractive index N as a function of wavelength λ. The complex refractive index consists of real part n(λ) and imaginary part k(λ). For the most commonly used perovskites, n and k curves are available from spectroscopic ellipsometry measurements, but usually only for a few discrete bandgap energies. For solar cell optimization, these curves are required for a continuous range of bandgap energies. We introduce new methods for generating the n and k curves for an arbitrary bandgap, based on interpolating measured complex refractive index data. First, different dispersion models (Cody-Lorentz, Ullrich-Lorentz and Forouhi-Bloomer) are used to fit the measured data. Then, a linear regression is applied to the fit parameters with respect to the bandgap energy. From the interpolated parameters, the refractive index curve of perovskite with any desired bandgap energy is finally reconstructed. To validate our method, we compare our results with methods from literature and then use it to simulate the absorptance of a single junction perovskite and a perovskite/silicon tandem cell. This shows that our method based on the Forouhi-Bloomer model is more accurate than existing methods in predicting the complex refractive index of perovskite for arbitrary bandgaps.

The surge in global solar photovoltaic (PV) deployment as a measure to combat climate change is undeniable. However, this growth comes with its own set of challenges, particularly concerning the materials required for silicon-based PV modules. In this study, we quantify future material demand for silicon-based PV modules, considering technological advancements in PV module efficiency and material intensity. The annual material demand is projected to increase significantly for indium (38–286 times), silver (4–27 times), and other materials (2–20 times) over the period from 2022 to 2050, depending on PV deployment scenarios. Indium and silver demand are notably influenced by PV technology choice. Cumulative indium demand during 2022–2050 could range from 0 kt (for 100 % passivated emitter and rear contact or tunnel oxide passivated contact PV) to 209 kt (for 100 % perovskite-silicon four-terminal tandem PV). Cumulative silver demand during the same period could vary from 144 kt (for 100 % passivated emitter and rear contact PV) to 1121 kt (for 100 % silicon heterojunction PV). One promising approach to mitigate the increasing demand for primary materials is closed-loop recycling. By implementing efficient PV collection and recycling processes, cumulative primary material demand could be reduced by 10 % to 30 % between 2022 and 2050.

The photovoltaic (PV) module energy rating standard series IEC 61853 does not cover bifacial PV modules. However, the market share of bifacial PV modules has dramatically increased in recent years and is projected to grow. This work demonstrates how Parts 3 and 4 of the IEC 61853 standard could be extended to bifacial modules. First, we develop an irradiance model that uses the data already given in the standard IEC 61853-4 to calculate the irradiance on the rear side of the module. Second, we propose a way to extend the energy yield calculation algorithm IEC 61853-3 to include bifacial modules and make it available to the PV community. This rear irradiance and bifacial energy yield calculation procedure is tested using real outdoor measurements for a nine-month period with a root mean square difference between measured and simulated energy yield of 4.65%. To conclude, we investigate the impact of different climates and normalization on the bifacial module energy rating results.

Photovoltaic (PV) technology is raising attention as a low-cost green energy source. It mainly finds applications in solar fields, on building facades and on rooftop. One of the main issues that can occur is the shading of solar cells inside the photovoltaic module which could affect the maximum power output of the PV panel and the lifetime of the cell itself. In order to predict the behaviour of PV panels in partial shading conditions, simulations and then measurements on two different photovoltaic modules have been carried out and compared. Data have shown that the maximum power output of the panels under 1sun illumination can be predicted by simulation with a 3% discrepancy from measured values, independently from the type of technology and interconnections of the PV module.

The tandem PV technology can potentially increase the efficiency of PV modules over 30%. To design efficient modules, a quantification of the different losses is important. Herein, a model for quantifying the energy loss mechanisms in PV systems under real-world operating conditions with a level of detail back to the components and their fundamental properties is presented. Totally, 17 losses are defined and divided into four categories (fundamental, optical, electrical, and system losses). As example, a system based on a > 29% two-terminal perovskite/silicon tandem cell is considered. The loss distribution at standard test conditions is compared to four geographical locations. The results show that the thermalization, reflection, and inverter losses increase by 1.2%, 1.1%, and 1.4%, respectively, when operating outdoors. Additionally, it is quantified how fill factor gains partly compensate the current mismatch losses. For example, a mismatch of 7.0% in photocurrent leads to a power mismatch of 1.2%. Therefore, the power mismatch should be used as indicator for mismatch losses instead of a current mismatch. Finally, herein, it is shown that solar tracking increases not only the in-plane irradiance but also the efficiency of the tandem module.

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.

We investigate gentle front side textures for perovskite/silicon tandem solar cells. These textures enhance the absorption of sunlight, yet are sufficiently gentle to allow deposition of an efficient perovskite top cell. We present a tandem solar cell with such gentle texture, fabricated by Kaneka corporation, with an efficiency as high as 28.6%. We perform an extensive ray-optics study, exploring non-conformal textures at the front and rear side of the perovskite layer. Our results reveal that a gentle texture with steepness of only 23° can be more optically efficient than conventional textures with more than double that steepness. We also show that the observed anti-reflective effect of such gentle textures is not based a double bounce, but on light trapping by total internal reflection. As a result, the optical effects of the encapsulation layers play an important role, and have to be accounted for when evaluating the texture design for perovskite/silicon tandems.

We introduce a novel simulation tool capable of calculating the energy yield of a PV system based on its fundamental material properties and using self-consistent models. Thus, our simulation model can operate without measurements of a PV device. It combines wave and ray optics and a dedicated semiconductor simulation to model the optoelectronic PV device properties resulting in the IV-curve. The system surroundings are described via spectrally resolved ray tracing resulting in a cell resolved irradiance distribution, and via the fluid dynamics-based thermal model, in the individual cell temperatures. A lumped-element model is used to calculate the IV-curves of each solar cell for every hour of the year. These are combined factoring in the interconnection to obtain the PV module IV-curves, which connect to the inverter for calculating the AC energy yield. In our case study, we compare two types of 2 terminal perovskite/silicon tandem modules with STC PV module efficiencies of 27.7% and 28.6% with a reference c-Si module with STC PV module efficiency of 20.9%. In four different climates, we show that tandem PV modules operate at 1–1.9 °C lower yearly irradiance weighted average temperatures compared to c-Si. We find that the effect of current mismatch is significantly overestimated in pure optical studies, as they do not account for fill factor gains. The specific yields in kWh/kWp of the tandem PV systems are between −2.7% and +0.4% compared to the reference c-Si system in all four simulated climates. Thus, we find that the lab performance of the simulated tandem PV system translates from the laboratory to outdoors comparable to c-Si systems.