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.

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.

The monolithic integration of perovskite top cells on textured crystalline silicon affords efficient tandem devices with strong prospects for large-scale applications. Such integration has primarily relied on state-of-the-art recombination junctions, which typically comprise transparent conductive oxides and molecular self-assembled monolayer (SAM) contacts. However, the potential influence of bottom cell nanoroughness, which may vary based on specific processing routes and technologies, has received far less attention. Here, we systematically engineered the top surface nanoroughness of silicon heterojunction solar cells to examine its impact on monolithic perovskite–silicon tandem solar cells. We employed two approaches: (i) varying the thickness of (n)-type hydrogenated nanocrystalline silicon ((n)nc-Si:H) layers or (ii) applying a plasma treatment using a hydrogen and carbon dioxide gas mixture before the deposition of (n)nc-Si:H layers. Both methods enhanced the conductivity and crystallinity of (n)nc-Si:H layers and increased the surface nanoroughness, with plasma treatment enabling the efficient realization of distinct nanoroughness in thin (n)nc-Si:H (15-nm-thick) layers. Our results reveal that the surface nanoroughness imposed by (n)nc-Si:H layers influences the SAM anchoring, leading to increased work function shifts and improved SAM/perovskite interface quality, thereby impacting the overall tandem device performance. Notably, tandem devices incorporating higher-nanoroughness bottom cells achieved increased fill factors, dominating the observed tandem efficiency enhancements, with a peak efficiency of 32.6% enabled by a 30-second-long plasma treatment.

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.

The degradation of perovskite solar cells due to reverse bias (RB) is one of the remaining challenges hindering the commercialization of the technology. To overcome this challenge, a thorough understanding of and control over the breakdown (BD) voltage are crucial. A prerequisite for this is that the community “speaks the same language,” that is, that the reported BD voltages are comparable. A review of literature data shows that the impact of measurement parameters is often unknown and seems to depend strongly on sample properties. It follows that standardization is the only way to reach comparability. Here, a set of measurement parameters to fill this gap is proposed. Additionally, various definitions of a “BD voltage” are used in parallel without any way of relating them to each other; this metric and its determination need to be considered as well. After a thorough discussion of the available definitions, the use of the point of maximum curvature is introduced. Its main advantage is the possible connection to an analytical description of the BD mechanism. In this way, a starting point for scientists new to the field of RB stability is provided, and the ground for a broader discussion in the community is prepared.

The current industrial standard photovoltaic (PV) modules are dominated by crystalline-silicon (c-Si) PV technology, which cannot be easily recycled. This has generated worldwide concerns regarding the scarcity of critical raw materials and large waste streams of PV modules in the coming years. To overcome this problem, a lot of ongoing research focuses on upscaling the recycling process of present c-Si module designs by chemical, thermal and mechanical processes. Alternative research focuses on the development of new PV modules with enhanced circularity by design. In this work, we propose a new circular PV module design based on liquid-encapsulation technology in which silicon solar cells are encapsulated with a suitable liquid and an edge sealant instead of a polymer sheet. Our optical studies show that the selected liquids exhibit similar optical performance to ethylene vinyl acetate (EVA) due to their comparable refractive indices. We fabricate one-cell prototypes and observe comparable efficiency of liquid-encapsulated and EVA-encapsulated modules, signifying recyclable module design without an additional efficiency loss. To validate the module performance, we also simulate the optical performance of modules with different encapsulation materials. Furthermore, the new modules retained more than 95% of their efficiency after inducing accelerated ageing through damp heat, thermal cycling and humidity freeze tests, indicating the liquids as an excellent encapsulant material for PV. In the end, we disassemble the liquid-filled PV module and show the recovered components, which can directly be reused in new products. Therefore, this modular design bypasses the recycling process. Even more promising, the liquid encapsulation can improve the stability of perovskite/c-Si tandem solar cells due to the moisture barrier, which will be studied in the future. Adding further possibilities, in principle, with additional engineering, the liquid encapsulation could be used in a heat loop to turn the PV module into a photovoltaic-thermal (PV-T) module, thereby boosting the efficiency potential beyond that of traditional PV concept.

This article introduces a parallel differential power processing (PDPP) architecture for photovoltaic (PV)/battery applications. The PV to Virtual Bus (PV2VB) architecture enables the integration of a battery and manages its power while performing maximum power point tracking on the PV strings. In the proposed PV2VB PDPP architecture, the battery is positioned at the virtual bus, acting as the input for all string-level converters (SLCs). By selecting a lower voltage for the battery at the virtual bus compared to the PV string or the main bus voltages, component voltage ratings can be reduced. The architecture employs dual active bridge converters connected to bridgeless (BL) converters as SLCs to generate both positive and negative output voltages while providing isolation. These SLCs track the maximum power point of each PV string, while the central converter manages battery charging and discharging. Experimental results confirm the performance and effectiveness of the proposed PV2VB PDPP architecture, achieving efficiencies between 95.5% and 99%.

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.

Silicon is a promising alternative to the conventional graphite anodes due to its high theoretical capacity and favorable lithiation potential for lithium-ion batteries (LIBs) with liquid as well as solid-state electrolytes. However, lithiation-induced extreme volume change causes severe mechanochemical deformation and continuous formation of solid-electrolyte interphase leads to cell failure. One of the strategies to mitigate this problem is alloying silicon with a suitable element that can alter the surface electrochemistry and/or lithiation pathways, and acts as mechanical buffer. Nonetheless, these benefits come with a compromise on the specific capacity, which strongly influences the mass loading of the electrodes, highlighting the need to deconvolute the intertwined influence of composition and mass loading when designing high performance electrodes. In this work, we systematically studied the influence of composition and mass loading in monolithic amorphous silicon and non-stoichiometric silicon nitride (SiN_x) electrodes on their electrochemical performance as LIB anodes. The incorporation of nitrogen in the electrode matrix clearly improves the electrochemical stability at the expense of reduced specific capacity, while higher mass loading accelerates capacity fading, most critically in amorphous silicon electrodes. Postmortem analysis reveals that such capacity fading in the electrodes with higher mass loading can be related to delamination due to evolved tensile stress during the charge–discharge cycle. Yet, nitrogen-rich SiN_x monolithic electrodes accommodate strain more effectively. These findings demonstrate that while pristine Si delivers high specific capacity and long-term stability in thin films, thicker (>1 µm) monolithic electrodes benefit from higher nitrogen content in SiN_x, which provides more stable cycling and sustained capacity.

Offshore floating photovoltaics (OFPVs) emerge as a promising solution to overcome land constraints associated with inland renewable energy deployment. However, as OFPVs are still a developing technology, several performance-related uncertainties persist. The reduction in energy yield caused by wave-induced losses (WIL) is one such critical uncertainty that needs to be understood, quantified and minimised. To address this need, this work introduces a physics-based modelling framework that couples validated hydrodynamic simulations with opto-electrical analysis to accurately estimate WIL. An extensive sensitivity analysis is then carried out, performing over 100 simulations by systematically varying both design and environmental parameters. The results show that WIL ranges between 1%–30% on an hourly basis and exhibits a nonlinear dependence on both parameter groups. The resulting dataset is then used to develop S [Figure presented] IFT 1.0 - a surrogate model capable of predicting WIL across a wide range of design and operating conditions, achieving an average absolute RMSE of 3% relative to the physics-based model. The insights from S [Figure presented] IFT 1.0 are finally used to provide practical measures that minimise WIL at a system design level. Overall, this work provides a complete pathway to model, quantify, predict, and minimise WIL, promoting confident and scalable OFPV deployment.

Crystalline silicon (c-Si) solar cells are rapidly establishing new efficiency frontiers, with front/back-contacted (FBC) designs now exceeding 26.8 % power conversion efficiency (PCE) and interdigitated back-contacted (IBC) cells surger limitepassing 27 %. This progress is driving a shift from traditional FBC PERC architectures to high-performance TOPCon, SHJ, and IBC configurations, with carrier-selective contacts (CSCs) at the core of these breakthroughs. In this work, we identify three critical factors underpinning CSC effectiveness: the work function of contact layers, energy barriers at heterointerfaces, and energy alignment across the stack of layers forming the CSC. By using advanced numerical simulations, we establish a framework for evaluating and optimizing CSC designs, including state-of-the-art poly-Si, SHJ, and dopant-free structures. We also introduce novel architectures based on TCO materials with potentially simpler manufacturing processes. Our simulations reveal that advanced FBC structures, can reach PCEs up to 28 % deploying localized CSCs architecture. In optimized IBC configurations, efficiencies as high as 28.64 % are achievable. For both, FBC and IBC configurations patterning limitations remain a barrier to theoretical efficiency peaks. Future advances in precision patterning could further close this gap, pushing c-Si solar cells closer to their intrinsic limits. This study provides a roadmap for high-efficiency CSC integration in next-generation c-Si solar cells, establishing pathways to achieve performance over 28 % and accelerating the evolution of photovoltaic technology.

Sequential thermal evaporation is an emerging technique for obtaining perovskite (PVK) photoactive materials for solar cell applications. Advantages include solvent-free processing, accurate stoichiometry control, and scalable processing. Nevertheless, the power conversion efficiency (PCE) of PVK solar cells (PSCs) fabricated by evaporation still lags behind that of solution-processed PSCs. Here, based on multi-cycle sequential thermal evaporation, we systematically investigate the effects of the post-deposition annealing temperature on the PVK properties in terms of surface morphology, opto-electronic properties, and device performance. We find that the average grain size increases to almost 1 μm and charge carrier mobilities exceed 50 cm2 V−1 s−1 when the annealing temperature is increased to 170 °C. We introduce a trace of PbCl2 to the multi-cycle sequential deposition to improve the absorber crystallinity at a lower annealing temperature of 150 °C, as evidenced by the XRD and PL analyses. The resulting PSC in a p–i–n structure yields a PCE of 18.5% with a cell area of 0.09 cm2. With the same deposition parameters, the cell area is scaled up to 0.36 cm2, achieving champion PCEs of 17.06%. This indicates the great potential of this technology for the commercialization of PSCs in the future.

In realistic partial shading scenarios, the impact of low-intensity illumination needs to be considered. However, there is barely any research available and the published results are contradictory. Here, it is shown that the reverse bias behavior of perovskite solar cells under low-intensity illumination strongly depends on the voltage scan rate. As explanation, a hypothesis is developed and experimentally verified that is based on two antagonistic mechanisms: on one hand, illumination affects the mobile ions conductivity, decreasing the breakdown voltage. On the other hand, an electrochemical reaction caused by the reverse bias current increases the breakdown voltage. Since the two mechanisms occur on slightly different time scales, it depends on the voltage scan rate which mechanism dominates. These findings emphasize that more detailed research into the mechanism occurring in reverse bias and the factors affecting the reverse bias breakdown is still necessary. Firstly, a deeper understanding would be helpful for investigating the effect of realistic, non-ideal partial shading scenarios on perovskite modules. Secondly, knowing how cell properties and external factors influence the breakdown voltage is necessary for defining standardized measurement procedures that allow the comparison of different perovskite solar cells in regards to their reverse bias stability.

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.

Increasing the operating lifetime of photovoltaic (PV) modules is a key factor in further reducing their levelized cost of electricity. Analytical degradation models typically use the external relative humidity (RH) as a stress factor, rather than the moisture concentration inside the module. This study presents a Finite Element Method (FEM) model, built in COMSOL Multiphysics, to simulate the moisture ingress inside a PV module. We explore the effects of different encapsulant and backsheet materials, as well as various climatic conditions, on moisture penetration. Overall, the impact of the climate has a larger impact on the moisture ingress than the choice of material, implying that the PV module design should be adjusted for different climates. As FEM simulations are computationally intensive, we also present an analytical model, based on empirically determined characteristics, to simulate the moisture ingress. This reconstruction can be done with a deviation lower than 0.05 for all conditions. Finally, our findings indicate that the relative moisture content (RMC) within the module serves as a more accurate stress factor than outdoor RH. Degradation rates over time found in literature are captured more accurately when deploying RMC.

At standard test conditions (STC), the performance of photovoltaic modules is compared using efficiency. As irradiance and module temperature fluctuate over the year and STC efficiency does not assess the performance of the module accurately in real world conditions, the annual energy yield is used instead as performance metric. Perovskite/silicon tandem solar cells are being massively researched and sought after in PV industry for their efficiency well above 34% with further growth perspective. In this work, to evaluate and compare performance of different perovskite/silicon tandem photovoltaic (PV) modules based on different bottom cell technologies, we use a hybrid modelling approach. Such approach, combining experimentally obtained and simulated current-voltage curves, flexibly predicts the annual energy yield of novel tandem PV modules via our PVMD toolbox and enables their optimization in any location. In particular, considering (i) mono- and bi-facial architectures, (ii) 2-terminal and 4-terminal module configurations, and (iii) silicon heterojunction or novel poly-SiOx passivated c-Si solar bottom cells, we compare the annual energy yield of different perovskite/silicon tandem modules and we optimize their performance in different locations with respect to different perovskite thickness and bandgaps

Photovoltaic (PV) to virtual bus parallel differential power processing (PDPP) architecture can mitigate mismatch losses among PV strings. This article presents a comprehensive dynamic analysis by deriving a small-signal model of the PDPP architecture based on its state space model. Subsequently, the corresponding transfer functions and frequency response are obtained, offering valuable insights into the dynamic behavior of the architecture. To validate the accuracy of the derived model, the frequency response has also been achieved by observed data from both PLECS simulation and experiment through system identification. Besides, this article discusses the design considerations of the discrete controllers' parameters for both virtual and intermediate bus voltages and studies the stability of the architecture. Experimental measurements confirm the ability of the central controller to stabilize the virtual bus voltage to the desired level within 0.6 seconds, while the intermediate bus voltages settle within 15 ms, enabling proper maximum power point tracking of each PV string.

This article introduces an innovative parallel differential power processing (PDPP) architecture designed to mitigate the effect of mismatch among photovoltaic (PV) strings. The proposed PV to virtual bus PDPP architecture leverages a virtual bus as the input for all string-level converters. Notably, this approach allows for a reduction in the voltage rating of components since the virtual bus voltage can be set lower than the main bus or PV strings voltage. In this architecture, crucial requirements for the string-level converters (SLCs) include the capability to generate positive and negative output voltages and to provide isolation. To fulfill these requirements, a dual active bridge converter connected to a bridgeless converter as the PDPP SLCs is considered. In this architecture, while SLCs ensure maximum power point tracking (MPPT) for each PV string using conventional MPPT algorithms, the central converter controls the virtual bus voltage. Experimental results validate the performance of the proposed PV to virtual bus PDPP architecture with a system efficiency ranging from 96.4% to 99%.

The authors have operated a few minor modifications in response to helpful feedback received post-publication from the readership. These updates are solely intended to clarify certain aspects of the article and enhance its overall readability. The first update concerns the caption of Fig. 7, which has been revised to improve clarity for readers through the addition of explanatory notes. The second update pertains to the Technology Readiness Level (TRL) of a technology developer in Table 3, which has been updated based on the latest provided information. As a derivative of this change, Fig. 8(a), that is a visual representation of Table 3, has also been updated to reflect the revised TRLs. Additionally, the note in the caption of Table 3 has been slightly modified for improved clarity. These modifications do not affect the outcomes, analysis, or conclusions of the article and are solely intended to improve clarity for readers and consistency with respect to most recent information.[Figure presented] Fig. 7: Proposed classification framework. FPV designs compiled and classified based on research publications and designs used by technology providers. Note: (i) each reported archetype can be technically made modular with companies deploying different (proprietary) solutions for upscaling the surface coverage of the farm; (ii) the adjective “large” in the acronym ”LRP” is related to the area of the floater as a surface that is at least bigger than one PV module. Table 3: TRLs of different FPV archetypes hosted by different organisations. Note: This table shows the TRLs based on publicly available information and represents a snapshot in time. The TRLs are subject to change over time and may not reflect the most up-to-date values.[Figure presented][Figure presented] Fig. 8: Current technology readiness landscape. (a) The trend of TRLs for inland and offshore solar deployments, (b) number of organisations working on inland and offshore solar deployment. Data derived from Table 3.

Solar farm installers generally struggle with the allocation of irradiance sensors throughout the plant area, which are essential for monitoring purposes. Despite the existence of the International Electrotechnical Commission guidelines for photovoltaic (PV) plant monitoring, no specific guidance is provided when it comes to allocating sensors. This can be especially problematic for solar farms in hilly terrain. In this work, a software tool is built to allocate horizontal and in-plane irradiance sensors. Additionally, advice on the optimum number of sensors and the prevented error is provided based on the layout of the farm. The methodology consists of calculating the irradiance at every point of the solar farm area and finding the one closest to the average. This average is computed differently depending on the sensor type and monitoring purpose. A modification of the BRL irradiance decomposition model is also proposed to reduce the bias of the original model. The software has been applied to two case studies of existing solar farms in hilly areas in Greece and Germany, showing its applicability for real case scenarios in different climates and geological landscapes. The runtime of the software tool is mainly a function of solar farm size and the land morphology of its location. This methodology has been only developed for monofacial fixed-tilted PV farms.