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• Nygård, Magnus Moe; Riise, Heine Nygard; Eriksen, Erling Ween & Martsein, Erik Stensrud (2026). Nowcasting based on spatio-temporal string-level power measurements in utility-scale photovoltaic power plants. Solar Energy. ISSN 0038-092X. 310. doi: 10.1016/j.solener.2026.114480. Full text in Research Archive Show summary

  A novel method is proposed to estimate cloud motion vectors (CMVs) from endogenous photovoltaic (PV) power plant energy yield time-series data. The method is tested using three months of 1-min mean aggregated power output data collected from 8000+ string-sets in a 150+ MW PV power plant. The CMVs are used as input to a cloud speed persistence PV power forecast which is benchmarked against a smart persistence PV power forecast. Forecasts issued for the entire power plant achieve an overall forecast skill of 0.16 at a forecast horizon of 1-min. If the forecast is issued for smaller sections of the power plant with foresight provided by the remaining sections, an increase in forecast skill up to 0.47 is demonstrated. The results emphasize the potential that can be unlocked if highly resolved spatio-temporal energy-yield time-series data are coupled with exogenous data, for instance, captured through satellite imagery and all-sky imagers.

• Eriksen, Erling Ween; Nygård, Magnus Moe; Erdmann, Niklas & Riise, Heine Nygard (2026). Deep Learning Multihorizon Irradiance Nowcasting: A Comparative Evaluation of Three Methods for Leveraging Sky Images. IEEE Journal of Photovoltaics. ISSN 2156-3381. doi: 10.1109/JPHOTOV.2026.3675751. Full text in Research Archive Show summary

  We investigate three distinct methods of incorporating all-sky imager (ASI) images into deep learning (DL) irradiance nowcasting. The first method relies on a convolutional neural network (CNN) to extract features directly from raw RGB images. The second method uses state-of-the-art algorithms to engineer 2D feature maps informed by domain knowledge, e.g., cloud segmentation, the cloud motion vector, solar position, and cloud base height. These feature maps are then passed to a CNN to extract compound features. The final method relies on aggregating the engineered 2D feature maps into time-series input. Each of the three methods were then used as part of a DL model trained on a high-frequency, 29-day dataset to generate multi-horizon forecasts of global horizontal irradiance up to 15 minutes ahead. The models were then evaluated using root mean squared error and skill score on 7 selected days of data. Aggregated engineered ASI features as model input yielded superior forecasting performance, demonstrating that integration of ASI images into DL nowcasting models is possible without complex spatially-ordered DL-architectures and inputs, underscoring opportunities for alternative image processing methods as well as the potential for improved spatial DL feature processing methods.

• Øgaard, Mari; Eriksen, Erling Ween; Dahlioui, Dounia; Rønneberg, Sigrid; Müller, Thore & Riise, Heine Nygard (2026). Analyzing and modeling snow loss and snow loss accumulation in ground-mounted photovoltaic systems. EPJ Photovoltaics. 17. doi: 10.1051/epjpv/2026004. Full text in Research Archive Show summary

  Snow can cause significant energy loss in photovoltaic systems, making it essential to account for in performance modeling for all snow-prone regions. Previous snow loss research has been conducted primarily for roof mounted systems, and there is a lack of reported snow losses and validation of snow loss models for ground mounted systems. The aim of this work is to quantify snow loss and validate the Marion snow loss model for ground mounted PV systems using data from two scientific test sites in Norway. The quantification of snow losses indicates that ground mounted systems have lower snow losses compared to what have previously been documented for roof mounted systems in Norway and similar climates. Additionally, monofacial and bifacial arrays experienced similar losses. At the same test site, the bifacial array’s monthly losses were, on average, 0.2 percentage points higher than those of the monofacial array. In the snow loss model validation, the impact of snow data quality was evaluated. The global weather snow data sources assessed (ERA5-Land and ERA5 global) had a large share of snowfall events not giving snow accumulation. These events were linked to both small snowfalls and higher temperatures. The default pvlib implementation of the Marion model typically underestimates losses, but the error in relative yearly losses is less than 0.5 percentage points. The error in the modeling is mainly related to periods where the temperature is close to zero, when both the snow input data and the prediction of snow shedding are more uncertain. Ground interference due to large snow depths also leads to slower shedding and underestimation of losses in the model.

• Erdmann, Niklas; Bentsen, Lars Ødegaard; Stenbro, Roy; Riise, Heine Nygard; Warakagoda, Narada Dilp & Engelstad, Paal E. (2026). Multi-Horizon Time Series Forecasting of Non-Parametric CDFs with Deep Lattice Networks. Proceedings of the AAAI Conference on Artificial Intelligence. ISSN 2159-5399. 40(1), p. 255–264. Full text in Research Archive Show summary

  Probabilistic forecasting is not only a way to add more information to a prediction of the future, but it also builds on weaknesses in point prediction. Sudden changes in a time series can still be captured by a cumulative distribution function (CDF), while a point prediction is likely to miss it entirely. The modeling of CDFs within forecasts has historically been limited to parametric approaches, but due to recent advances, this no longer has to be the case. We aim to advance the fields of probabilistic forecasting and monotonic networks by connecting them and propose an approach that permits the forecasting of implicit, complete, and nonparametric CDFs. For this purpose, we propose an adaptation to deep lattice networks (DLN) for monotonically constrained simultaneous/implicit quantile regression in time series forecasting. Quantile regression usually produces quantile crossovers, which need to be prevented to achieve a legitimate CDF. By leveraging long short term memory units (LSTM) as the embedding layer, and spreading quantile inputs to all sub-lattices of a DLN with an extended output size, we can produce a multi-horizon forecast of an implicit CDF due to the monotonic constraintability of DLNs that prevent quantile crossovers. We compare and evaluate our approach's performance to relevant state of the art within the context of a highly relevant application of time series forecasting: Day-ahead, hourly forecasts of solar irradiance observations. Our experiments show that the adaptation of a DLN performs just as well or even better than an unconstrained approach. Further comparison of the adapted DLN against a scalable monotonic neural network shows that our approach performs better. With this adaptation of DLNs, we intend to create more interest and crossover investigations in techniques of monotonic neural networks and probabilistic forecasting.

• Honningdalsnes, Erlend Hustad; Marstein, Erik Stensrud; Lindholm, Dag; Bonesmo, Helge & Riise, Heine Nygard (2025). Wind sheltering in vertical agrivoltaics can increase crop yields: A modeling study for Northern Europe. Energy Nexus. 19. doi: 10.1016/j.nexus.2025.100516. Full text in Research Archive Show summary

  Vertical agrivoltaics can help reduce land use competition by integrating food crop cultivation between rows of vertical solar panels. However, its agricultural viability is often questioned due to panel shading. This study demonstrates that wind sheltering from vertical solar panels not only can compensate for the shading losses but lead to net-positive yield changes in Northern Europe. Crops benefit from wind shelter through improved soil moisture retention, higher ambient temperatures, and protection from wind erosion and damage. This study quantified the combined shading and wind sheltering effects on timothy grass (Phleum pratense L.) yields within large-scale vertical agrivoltaics across Norway, Sweden, and Finland. Our modeling framework integrated ERA5 weather data (2010–2023), Computational Fluid Dynamics for wind simulation (OpenFOAM), ray tracing for shading analysis (Honeybee Radiance), and a crop growth simulation model (CATIMO). Additionally, ERA5 temperature data was adjusted to explore shelter-induced warming effects. In the simulation, vertical agrivoltaics decreased ground irradiation by 15–16 % and reduced seasonal mean crop zone wind speeds by up to 40 % (up to 88 % for perpendicular winds), lowering evapotranspiration. When combining shading, wind reduction, and a conservative +0.5 ◦C shelter-induced temperature increase, the model predicted an average regional yield increase of +2.4 % compared to traditional agriculture. Yield improvements were highest in drought-prone soils (+3.7 %) and dry, sunny years (e.g., +9.2 % in 2018). This suggests that vertical agrivoltaics improves agricultural resilience under challenging conditions. These findings demonstrate that agrivoltaic modeling, particularly for vertical systems, should incorporate wind shelter effects to avoid fundamentally underestimating crop yield potential.

• Nygård, Magnus Moe; Wiig, Marie Syre; Roosloot, Nathan Abel; Otnes, Gaute; Øgaard, Mari & Riise, Heine Nygard [Show all 7 contributors for this article] (2025). Elucidating uncertainty in bifacial photovoltaic gain estimation. Solar Energy. ISSN 0038-092X. 292, p. 1–12. doi: 10.1016/j.solener.2025.113469. Full text in Research Archive Show summary

  The bifacial gain of fielded bifacial photovoltaic (PV) systems is commonly estimated by comparing the energy yield of the system with that of a monofacial reference. However, this approach is dependent on the selected reference, and can thus be associated with significant uncertainty, since the two technologies might have very different properties. This study investigates the significance of such differences when the bifacial gain is estimated from energy yield time series data. A series of corrections are applied to account for differences in installed capacity and responses with respect to temperature and irradiance. The analysis is carried out using data collected over two years from a 22.6 kWp ground-mounted fixed-tilt PV system in Norway using four different monofacial technologies as reference systems that all rely on Si as the active material but have different cell architectures. With no corrections applied, the estimated bifacial gain with the monofacial technology that most closely resembles the bifacial is determined to 12.6 % for the two-year period considered. The estimate increases to 13.1 % when correcting for irradiance and 14.4 % when also correcting for temperature. The results demonstrate that the applied corrections reduces the range between the smallest and largest estimate of the bifacial gain from 6.3 to 3.5 percentage points. Although it is possible that the range can be reduced further if differences in spectral response and degradation are accounted for, it should also be expected that some of the remaining variation reflects the measurement uncertainty inherent to this method of estimating the bifacial gain.

• Honningdalsnes, Erlend Hustad; Marstein, Erik Stensrud; Nygård, Magnus Moe; Wiig, Marie Syre & Riise, Heine Nygard (2025). Benchmarking irradiation models for photovoltaic applications: A comparative analysis of radiance-based tools. Solar Energy. ISSN 0038-092X. 296. doi: 10.1016/j.solener.2025.113566. Full text in Research Archive Show summary

  This study compared the accuracy, efficiency, and capabilities of three ray tracing tools—bifacial_radiance, ClimateStudio, and Honeybee Radiance—in modeling irradiance for photovoltaic (PV) systems. Despite similar performance in modeling hourly irradiance and monthly and annual cumulative irradiation levels, the tools exhibited differences in functionalities and computational efficiency. All models estimated cumulative annual front irradiation within 1.3% of measured values, with bifacial_radiance showing the largest error. For rear side irradiance, bifacial_radiance, ClimateStudio, and Honeybee Radiance underestimated irradiance by 2.82%, 5.40% and 8.74%, respectively. bifacial_radiance showed the highest model stochasticity in cumulative simulations due to its reliance on a single cumulative sky model. In contrast, ClimateStudio and Honeybee Radiance employ matrix-based approaches with hourly resolution within the period, averaging out stochasticity and making them more dependable for precise cumulative irradiation values. These matrix-based methods also significantly enhanced time-series analysis efficiency by modeling yearly irradiance with hourly resolution faster than bifacial_radiance analyzes a single point-in-time, while maintaining similar hourly error and bias levels. However, bifacial_radiance exhibited lower model stochasticity in hourly simulations. Enabled by the efficient simulation capabilities of ClimateStudio and Honeybee Radiance, a method for improving rear side irradiance modeling was tested. By combining simulations with different ground albedo values, this approach significantly reduced error and bias in rear side irradiance modeling. Ultimately, the choice of tool depends on study requirements, with bifacial_radiance being advantageous for hourly and sub-hourly resolution in short-term analyzes, while ClimateStudio and Honeybee Radiance are better suited for cumulative and extended time-series analyzes.

• Riise, Heine Nygard; Nygård, Magnus Moe; Aarseth, Bjørn Lupton; Dobler, Andreas & Berge, Erik (2024). Benchmark of estimated solar irradiance data at high latitude locations. Solar Energy. ISSN 0038-092X. 282. doi: 10.1016/j.solener.2024.112975. Full text in Research Archive
• Øgaard, Mari; Nysted, Vilde Stueland; Rønneberg, Sigrid; Otnes, Gaute; Foss, Sean Erik & Mongstad, Trygve [Show all 7 contributors for this article] (2024). Vertical bifacial PV systems: irradiance modeling and performance analysis of a lightweight system for flat roofs. EPJ Photovoltaics. 15. doi: 10.1051/epjpv/2024012. Full text in Research Archive
• Erdmann, Niklas; Bentsen, Lars Ødegaard; Stenbro, Roy; Riise, Heine Nygard; Warakagoda, Narada Dilp & Engelstad, Paal (2024). Deep and Probabilistic Solar Irradiance Forecast at the Arctic Circle. Conference record of the Photovoltaic Specialists Conference. ISSN 0160-8371. p. 1599–1606. doi: 10.1109/PVSC57443.2024.10748862. Full text in Research Archive
• Solas, Alvaro Fernandez; Riedel-Lyngskær, Nicholas C.; Hanrieder, Natalie; Santos, Fernanda Norde; Wilbert, Stefan & Riise, Heine Nygard [Show all 11 contributors for this article] (2024). Photovoltaic soiling loss in Europe: Geographical distribution and cleaning recommendations. Renewable Energy. ISSN 0960-1481. 239. doi: 10.1016/j.renene.2024.122086. Full text in Research Archive
• Honningdalsnes, Erlend Hustad; Bonesmo, Helge; Marstein, Erik Stensrud; Völler, Steve & Riise, Heine Nygard (2023). Autonomous Optimization of Agrivoltaic Systems With Vertical Bifacial PV Panels and the Grass Crop Timothy. EU PVSEC 2023. doi: 10.4229/EUPVSEC2023/4BV.3.13. Full text in Research Archive
• Mussard, Maxime; Riise, Heine Nygard; Wiig, Marie Syre; Rønneberg, Sigrid & Foss, Sean Erik (2023). Influence of Temperature Coefficient and Sensor Choice on PV System Performance. IEEE Journal of Photovoltaics. ISSN 2156-3381. 13(6), p. 920–928. doi: 10.1109/JPHOTOV.2023.3311896. Full text in Research Archive
• Klyve, Øyvind Sommer; Nygård, Magnus Moe; Riise, Heine Nygard; Fagerström, Jonathan & Marstein, Erik Stensrud (2023). The value of forecasts for PV power plants operating in the past, present and future Scandinavian energy markets. Solar Energy. ISSN 0038-092X. 255, p. 208–221. doi: 10.1016/j.solener.2023.03.044. Full text in Research Archive Show summary

  When participating in the Scandinavian wholesale energy markets with intermittent PV power, imbalances between market-committed and actual energy generation need to be economically accounted for in the imbalance settlement. The market-committed energy is based on forecasts issued at specific timestamps defined by the market. The economic value of such forecasts can be quantified for the past, present and future energy market regulations by comparing the achieved income using perfect forecasts to the income with imperfect forecasts. Differences between these regulations include changing from 60 min to 15 min market intervals, and from a dual-price to a single-price imbalance settlement structure. PV power production data were modelled from meteorological measurements carried out at 11 locations in each of the Nord Pool bidding areas. Forecasts generated from a smart persistence model and a more sophisticated numerical weather prediction (NWP) model were compared for these locations, and the value of these forecasts was estimated from historical market data for each of the 11 bidding areas. The results show that the estimated income, and income losses, are dependent on the electricity mix of the bidding areas. In addition, the transition from the dual-price to the single-price imbalance settlement structure reduces the value of providing accurate forecasts. Moreover, the added incentive to provide accurate forecasts when settling the markets and imbalances on 15 min instead of 60 min intervals is negligible with the single-price imbalance settlement. Finally, the results show that intraday trading is generally beneficial for PV power plants in Scandinavia.

• Øgaard, Mari; Frimannslund, Iver; Riise, Heine Nygard & Selj, Josefine Helene Krogh (2022). Snow Loss Modeling for Roof Mounted Photovoltaic Systems: Improving the Marion Snow Loss Model. IEEE Journal of Photovoltaics. ISSN 2156-3381. 12(4), p. 1005–1013. doi: 10.1109/JPHOTOV.2022.3166909. Full text in Research Archive
• Martinsen, Dina C.; Øgaard, Mari; Nygård, Magnus Moe; Wiig, Marie Syre; Sabatino, Marisa Di & Marstein, Erik Stensrud [Show all 7 contributors for this article] (2022). Evaluation of Irradiance Decomposition and Transposition Models for a Nordic Climate. Proceedings of the European Photovoltaic Solar Energy Conference. ISSN 2196-100X. doi: 10.4229/WCPEC-82022-4BV.4.22. Full text in Research Archive
• Øgaard, Mari Benedikte; Aarseth, Bjørn Lupton; Skomedal, Åsmund; Riise, Heine Nygard; Sartori, Sabrina & Selj, Josefine Helene Krogh (2021). Identifying snow in photovoltaic monitoring data for improved snow loss modeling and snow detection. Solar Energy. ISSN 0038-092X. 223, p. 238–247. doi: 10.1016/j.solener.2021.05.023. Full text in Research Archive Show summary

  As cost reductions have made photovoltaics (PV) a favorable choice also in colder climates, the number of PV plants in regions with snowfalls is increasing rapidly. Snow coverage on the PV modules will lead to significant power losses, which must be estimated and accounted for in order to achieve accurate energy yield assessment and production forecasts. Additionally, detection and separation of snow loss from other system losses is necessary to establish robust operation and maintenance (O&M) routines and performance evaluations. Snow loss models have been suggested in the literature, but developing general models is challenging, and validation of the models are lacking. Characterization and detection of snow events in PV data has not been widely discussed. In this paper, we identify the signatures in PV data caused by different types of snow cover, evaluate and improve snow loss modeling, and develop snow detection. The analysis is based on five years of data from a commercial PV system in Norway. In an evaluation of four snow loss models, the Marion model yields the best results. We find that system design and snow depth influence the natural snow clearing, and by expanding the Marion model to take this into account, the error in the modeled absolute loss for the tested system is reduced from 23% to 3%. Based on the improved modeling and the identified data signatures we detect 97% of the snow losses in the dataset. Endogenous snow detection constitutes a cost-effective improvement to current monitoring systems.

• Riise, Heine Nygard; Øgaard, Mari & Nærland, Tine Uberg (2021). Soiling and Snow Impact on a PV Plant at a Farm in Norway. Proceedings of the European Photovoltaic Solar Energy Conference. ISSN 2196-100X. p. 1241–1244. doi: 10.4229/EUPVSEC20212021-5CV.2.26. Full text in Research Archive
• Øgaard, Mari; Riise, Heine Nygard & Selj, Josefine Helene Krogh (2021). Estimation of snow loss for photovoltaic plants in Norway. Proceedings of the European Photovoltaic Solar Energy Conference. ISSN 2196-100X. doi: 10.4229/EUPVSEC20212021-5DO.4.5. Full text in Research Archive Show summary

  Large PV plants are increasingly common in locations with colder climates where snow can lead to significant PV power loss. For these locations, estimates of snow loss is necessary for accurate PV yield modeling. Robust estimation of snow loss is, however, challenging. Snow-induced loss is expected to vary with climate, weather, and PV plant design. In this work, we estimate snow loss from historical data for a set of PV plants in Norway. To extend the snow loss dataset, 12 years of weather data and a modified adaption of the Marion snow loss model are used to simulate snow loss for the analyzed PV plants over time. For the historical data, we observe variations in annual losses for the same system of more than 10 percentage points. For some of the systems, we find losses in a range from 0 to 100 % for the same month. As expected, systems with colder climates have higher loss than systems in warmer climates, and systems with higher tilt has lower loss than systems with lower tilt. With snow loss modeling we get improved understanding of typical and extreme values, and the potential inter-annual variation in monthly and annual snow loss.

• Riise, Heine Nygard; Øgaard, Mari; Zhu, Junjie; You, Chang Chuan; Andersson, Fredrik & Bønsnæs, Tommy [Show all 8 contributors for this article] (2021). Performance analysis of a BAPV bifacial system in Norway. In Angus, Rockett (Eds.), 2021 IEEE 48th Photovoltaic Specialists Conference (PVSC). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781665419222. p. 1304–1308. doi: 10.1109/PVSC43889.2021.9518963. Full text in Research Archive
• Øgaard, Mari; Riise, Heine Nygard & Selj, Josefine Helene Krogh (2021). Modeling Snow Losses in Photovoltaic Systems. Conference record of the Photovoltaic Specialists Conference. ISSN 0160-8371. doi: 10.1109/PVSC43889.2021.9518886. Full text in Research Archive Show summary

  To achieve accurate PV energy yield assessments for cold climate locations where snowfalls can lead to significant power losses in the wintertime, improvement and validation of snow loss modeling is necessary. In this paper we introduce a snow depth dependent clearing rate coefficient in the Marion snow loss model to account for the effect of different snow conditions on the natural snow clearing process. To evaluate the model, seven roof mounted PV plants with two different system configurations are analyzed. For both system configurations the snow depth dependent clearing rate coefficient yields lower error in the total modeled snow loss and capture climatic variations between locations better compared to the standard constant coefficient.

• Øgaard, Mari B.; Riise, Heine Nygard; Haug, Halvard; Sartori, Sabrina & Selj, Josefine H. (2020). Photovoltaic system monitoring for high latitude locations. Solar Energy. ISSN 0038-092X. 207, p. 1045–1054. doi: 10.1016/j.solener.2020.07.043. Full text in Research Archive Show summary

  Reliable monitoring of PV systems is essential to establish efficient maintenance routines that minimize the levelized cost of electricity. The existing solutions for affordable monitoring of commercial PV systems are however inadequate for climates where snow and highly varying weather result in unstable performance metrics. The aim of this work is to decrease this instability to enable more reliable monitoring solutions for PV systems installed in these climates. Different performance metrics have been tested on Norwegian installations with a total installed capacity of 3.3 MW: (i) comparison of specific yield, (ii) temperature corrected performance ratio, and (iii) power performance index based on both physical modelling and machine learning. The most influential effects leading to instability are identified as snow, low light, curtailment, and systematic irradiance differences over the system. The standard deviation of all the performance metrics is reduced when filters targeting these four effects are applied. Compared to general low irradiance or clear sky filtering, a greater reduction in the variation of the metrics is achieved, and more data remains in the useful dataset. The most suitable performance metrics are comparison of specific yield and performance index based on machine learning modelling. The analysis highlights two paths to accomplish increased reliability of PV monitoring systems without increased hardware costs. First, better reliability can be achieved by selecting a suitable performance metric. Second, the variability of the performance metric can be reduced by utilizing filters that specifically target the origin of the variability instead of using standard literature thresholds.

• Kumar, Raj; Bergum, Kristin; Riise, Heine Nygard; Monakhov, Eduard; Galeckas, Augustinas & Svensson, Bengt Gunnar (2020). Impact of post annealing and hydrogen implantation on functional properties of Cu2O thin films for photovoltaic applications. Journal of Alloys and Compounds. ISSN 0925-8388. 825(5), p. 1–8. doi: 10.1016/j.jallcom.2020.153982. Full text in Research Archive Show summary

  Polycrystalline cuprous oxide (Cu2O) thin films were sputtered, annealed (900 °C rapid thermal annealing) and subsequently implanted with various hydrogen ion (H+) doses from 5E13 to 2E15 cm−2 with a low acceleration energy of 36 keV at room temperature to tailor the functional properties of the thin films for solar cell application. The annealed and H+ implanted Cu2O thin films were post annealed at low temperatures from 100 °C to 600 °C in an inert atmosphere to promote hydrogen passivation of prevalent intrinsic acceptors and tune the carrier concentration for optimum performance as an absorption layer in a heterojunction solar cell. The H+ incorporation and post annealing tuned the structural, optical and electrical properties of annealed polycrystalline Cu2O thin films. The results show an enhancement of the excitonic feature around ∼2.0 eV with H+ dose. The normalized photoluminescence (PL) area around ∼1.7 eV was drastically enhanced with increasing H+ doses compared to excitonic and copper vacancy related area. The normalized total PL quantum efficiency shows an enhancement in yield with elevated H+ doses by two orders of magnitude. The hole concentration decreases down to ∼1013 cm−3, while hole mobility and resistivity increase to ∼27 cm2/V and ∼2.4 kΩcm, respectively, as the H+ implantation goes from lower to higher doses. In addition, the post annealing and H+ incorporation lead to a change in the energy level of the major acceptor from 0.21 eV to 0.27 eV above the valence band maximum. By following the qualitative (PL analysis) and quantitative (Hall data) outcomes, we can conclude that H+ implantation and post annealing likely indicates the passivation of both acceptor defects and compensating donor defects.

• Sky, Thomas Neset; Johansen, Klaus Magnus H; Frodason, Ymir Kalmann; Aarholt, Thomas; Riise, Heine Nygard & Prytz, Øystein [Show all 8 contributors for this article] (2019). Diffusion of indium in single crystal zinc oxide: a comparison between group III donors. Semiconductor Science and Technology. ISSN 0268-1242. 34(2), p. 1–6. doi: 10.1088/1361-6641/aafa4c. Full text in Research Archive
• Sky, Thomas Neset; Johansen, Klaus Magnus H; Riise, Heine Nygard; Svensson, Bengt Gunnar & Vines, Lasse (2018). Gallium diffusion in zinc oxide via the paired dopant-vacancy mechanism. Journal of Applied Physics. ISSN 0021-8979. 123(5). doi: 10.1063/1.5000123. Full text in Research Archive Show summary

  Isochronal and isothermal diffusion experiments of gallium (Ga) in zinc oxide (ZnO) have been performed in the temperature range of 900–1050 °C. The samples used consisted of a sputter-deposited and highly Ga-doped ZnO film at the surface of a single-crystal bulk material. We use a novel reaction diffusion (RD) approach to demonstrate that the diffusion behavior of Ga in ZnO is consistent with zinc vacancy (VZn) mediation via the formation and dissociation of GaZnVZn complexes. In the RD modeling, experimental diffusion data are fitted utilizing recent density-functional-theory estimates of the VZn formation energy and the binding energy of GaZnVZn. From the RD modeling, a migration energy of 2.3 eV is deduced for GaZnVZn, and a total/effective activation energy of 3.0 eV is obtained for the Ga diffusion. Furthermore, and for comparison, employing the so-called Fair model, a total/effective activation energy of 2.7 eV is obtained for the Ga diffusion, reasonably close to the total value extracted from the RD-modeling. © 2018 AIP Publishing

• Bergum, Kristin; Riise, Heine Nygard; Gorantla, Sandeep Madhukar; Lindberg, Per; Jensen, Ingvild Julie Thue & Gunnæs, Anette Eleonora [Show all 10 contributors for this article] (2018). Improving carrier transport in Cu2O thin films by rapid thermal annealing. Journal of Physics: Condensed Matter. ISSN 0953-8984. 30(7). doi: 10.1088/1361-648X/aaa5f4. Full text in Research Archive
• Schifano, Ramon; Riise, Heine Nygard; Domagala, J.; Azarov, Alexander; Ratajczak, R. & Monakhov, Edouard [Show all 11 contributors for this article] (2017). Comparison of the structural properties of Zn-face and O-face single crystal homoepitaxial ZnO epilayers grown by RF-magnetron sputtering. Journal of Applied Physics. ISSN 0021-8979. 121(1). doi: 10.1063/1.4973342. Full text in Research Archive Show summary

  Homoepitaxial ZnO growth is demonstrated from conventional RF-sputtering at 400 °C on both Zn and O polar faces of hydrothermally grown ZnO substrates. A minimum yield for the Rutherford backscattering and channeling spectrum, χmin, equal to ∼3% and ∼12% and a full width at half maximum of the 00.2 diffraction peak rocking curve of (70 ± 10) arc sec and (1400 ± 100) arc sec have been found for samples grown on the Zn and O face, respectively. The structural characteristics of the film deposited on the Zn face are comparable with those of epilayers grown by more complex techniques like molecular beam epitaxy. In contrast, the film simultaneously deposited on the O-face exhibits an inferior crystalline structure ∼0.7% strained in the c-direction and a higher atomic number contrast compared with the substrate, as revealed by high angle annular dark field imaging measurements. These differences between the Zn- and O-face films are discussed in detail and associated with the different growth mechanisms prevailing on the two surfaces. © 2016 AIP Publishing

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• Riise, Heine Nygard; Honningdalsnes, Erlend Hustad; Kjeldstad, Torunn & Rizzi, Jonathan (2026). Hvordan kan vi produsere mer fornybar energi uten å bygge ned matjord eller natur?​. Full text in Research Archive
• Riise, Heine Nygard (2026). Nature-inclusive operation and maintenance of PV parks – An expert elicitation of PV performance and ecological impacts. Full text in Research Archive
• Riise, Heine Nygard (2026). How does ground-mounted PV impact nature and the local environment? Preliminary conclusions from the Envisol project. Full text in Research Archive
• Riise, Heine Nygard & Hollingsæter, Oliver Heim (2026). Konfliktfri solkraft: gråarealer, tak og landbruksarealer på bondens premisser. Full text in Research Archive
• Honningdalsnes, Erlend Hustad; Marstein, Erik Stensrud; Bonesmo, Helge; Lindholm, Dag; Rizzi, Jonathan & Riise, Heine Nygard (2026). Vertical Agrivoltaic Systems Support Crop Growth. Full text in Research Archive
• Eriksen, Erling Ween; Nygård, Magnus Moe & Riise, Heine Nygard (2026). 3-Month Nordic Benchmark of ASI-Based Solar Nowcasting: Commercial Solutions and DL Literature Models. Full text in Research Archive Show summary

  Short‑term irradiance forecasting using all‑sky imagers (ASI) is useful for efficient PV plant control, grid balancing, and high-frequency energy trading. Yet knowing which solution is optimal based on the application and location is challenging due to a scarcity of solid comparisons between forecasting models. Intercomparison of models in the literature based on standard metrics is difficult, as the location and atmospheric conditions of the site play a major role in the scale of the errors of a forecast. Even metrics using normalization (nRMSE or nMAE) and metrics using a reference model (Skill Score) still suffer from this sensitivity. The only way to truly compare different forecasting solutions is through common datasets or benchmarking campaigns, ensuring that the solutions are evaluated on the same task in the same time period. To this end, we present a 3‑month benchmark (21 May–21 August) at 60 degree N in Kjeller, Norway, designed to assess the state-of-the-art (SOTA) scientific and commercial forecasting models. Three generations of scientific forecasting models are included in this benchmark: (i) SUNSET (CNN-architecture), (ii) a Transformer end‑to‑end model, and (iii) at least one SOTA generative model, to be evaluated for the final contribution. A defining aspect of this study is the inclusion of two commercial ASI forecasting products in addition to the literature models, evaluating the range of available nowcasting solutions. The evaluation covers RMSE, MAE, Skill Score (SS), and a ramp-detection metric. Preliminary results show that the Transformer model consistently outperforms smart persistence and the commercial solutions and other research models on all metrics for all horizons, except for the ramp prediction metric, where it underperforms all other models. Performance analysis across clear-sky index (k) and variability index (V) indicates that the atmospheric conditions strongly influence performance.

• Eriksen, Erling Ween; Riise, Heine Nygard & Nygård, Magnus Moe (2026). Nordic Benchmark of ASI-based Nowcasting Solutions. Full text in Research Archive Show summary

  Presentation of preliminary results of a benchmark of solar nowcasting solutions

• Eriksen, Erling Ween; Nygård, Magnus Moe & Riise, Heine Nygard (2026). Solar Nowcasting using AI. Full text in Research Archive Show summary

  Solar forecasting on the very shortest horizons (under 30 minutes) presents a unique problem: predicting the changes in power production tied to rapid atmospheric fluctuations. Cloud changes can reduce a PV plant's power output by more than 80% within a minute; predicting and mitigating this variability helps maintain the stability and robustness of PV-based power systems. However, clouds are complex, multi-scale phenomena that are not only difficult to measure but typically not physically modelled on the time and spatial scale that is relevant to minute-scale PV production. As both physical models and satellite methods are too coarsely resolved, solar nowcasting is usually handled as a time-series prediction using local sensing data. Over the past decade, as integration of PV has increased, this problem has gained research attention, and the solutions have shifted from traditional autoregressive methods to solutions based on deep learning. This presentation will introduce the field of solar nowcasting, focusing on the problem statement, examining what makes this task challenging, and how AI approaches present a promising avenue of investigation. It will then use a recent benchmarking of commercial and literature solar nowcasting solutions done at IFE as a focal point to analyze and discuss different machine learning approaches to this problem.

• Riise, Heine Nygard; Kjeldstad, Torunn; Honningdalsnes, Erlend Hustad; Simensen, Trond & Mehlhoop, Anne Catriona (2025). Solkraft på grå arealer. Full text in Research Archive
• Riise, Heine Nygard & Steel, Christian (2025). Grå arealer og hvordan vi kan ta de i bruk til solkraftverk. Full text in Research Archive
• Nygård, Magnus Moe; Riise, Heine Nygard & Eriksen, Erling Ween (2025). Cloud motion detection and short-term PV power forecasting using spatially resolved production data. Full text in Research Archive
• Marstein, Erik Stensrud; Klyve, Øyvind Sommer; Nygård, Magnus Moe; Olkkonen, Ville & Riise, Heine Nygard (2025). Quantifying the Benefits of Hybrid PV-wind Power Plants. Full text in Research Archive
• Øgaard, Mari; Eriksen, Erling Ween; Dahlioui, Dounia; Rønneberg, Sigrid; Müller, Thore & Riise, Heine Nygard (2025). Analyzing and Modeling Snow Loss in Ground-Mounted PV Systems. Full text in Research Archive
• Riise, Heine Nygard; Mehlhoop, Anne Catriona; Roosloot, Nathan Abel; Nygård, Magnus Moe; Eriksen, Erling Ween & Walpita, Harsha Lakmal [Show all 9 contributors for this article] (2025). Nature-Inclusive Operation and Maintenance of PV Parks – An Expert Elicitation of PV Performance and Ecological Impacts. Full text in Research Archive
• Honningdalsnes, Erlend Hustad; Marstein, Erik Stensrud; Mehlhoop, Anne Catriona; Skrindo, Astrid Brekke; Solstad, Heidi & Riise, Heine Nygard (2025). Microclimate and Biodiversity Measurements in Norway’s First East-West Tilted Agrivoltaic System. Full text in Research Archive
• Honningdalsnes, Erlend Hustad; Walpita, Harsha Lakmal; Nysted, Vilde Stueland; Marstein, Erik Stensrud; Selj, Josefine Helene Krogh & Riise, Heine Nygard (2025). Satellite Analysis of Floating PV Construction and Extreme Weather Resilience. Full text in Research Archive
• Honningdalsnes, Erlend Hustad; Marstein, Erik Stensrud & Riise, Heine Nygard (2025). Modellering og validering av avling i vertikale solparker. Full text in Research Archive
• Honningdalsnes, Erlend Hustad; Marstein, Erik Stensrud & Riise, Heine Nygard (2025). Modeling and validation of crop yields in vertical solar parks. Full text in Research Archive
• Hollingsæter, Oliver Heim; Kraugerud, Olav Fjeld; Honningdalsnes, Erlend Hustad & Riise, Heine Nygard (2025). Solkraft på bondens premisser. Full text in Research Archive
• Hollingsæter, Oliver Heim; Kraugerud, Olav Fjeld; Honningdalsnes, Erlend Hustad & Riise, Heine Nygard (2025). Solkraft på bondens premisser. Full text in Research Archive
• Hollingsæter, Oliver Heim; Kraugerud, Olav Fjeld; Honningdalsnes, Erlend Hustad & Riise, Heine Nygard (2025). Slik kan solkraft øke bondens inntekter. Full text in Research Archive
• Riise, Heine Nygard; Kjeldstad, Torunn & Honningdalsnes, Erlend Hustad (2025). Solceller på bakken kan gi mye strøm, men hva gjør det med naturen? [Internet]. forskning.no. Full text in Research Archive
• Øgaard, Mari; Eriksen, Erling Ween; Dahlioui, Dounia; Rønneberg, Sigrid & Riise, Heine Nygard (2025). Analyzing and modeling snow loss in ground-mounted PV systems. Full text in Research Archive
• Honningdalsnes, Erlend Hustad; Riise, Heine Nygard; Kjeldstad, Torunn; Marstein, Erik Stensrud; Stokkan, Gaute & Randle-Boggis, Richard [Show all 10 contributors for this article] (2024). Fordeler med solkraftverk på jord- og skogbruksarealer. Bondebladet. ISSN 0332-8414. Full text in Research Archive
• Eriksen, Erling Ween; Nygård, Magnus Moe & Riise, Heine Nygard (2024). Minute-scale forecasting using skycameras: Feature Extraction at high latitudes. Full text in Research Archive
• Nygård, Magnus Moe; Eriksen, Erling Ween & Riise, Heine Nygard (2024). Photovoltaic Power Plants As Efficient Cloud Motion Detectors. Full text in Research Archive
• Kjeldstad, Torunn; Riise, Heine Nygard; Hagen, Dagmar & Rizzi, Jonathan (2024). Slik kan solkraft-utbyggerne lære av konfliktene med vindkraft på land. Full text in Research Archive
• Riise, Heine Nygard; Honningdalsnes, Erlend Hustad; Hagen, Dagmar; Sydenham, Markus A. K.; Mehlhoop, Anne Catriona & Simensen, Trond Aalvik [Show all 8 contributors for this article] (2024). Envisol – Presenting a Cross-Disciplinary Project on How PV Power Plants Influence Nature. Full text in Research Archive
• Rønneberg, Sigrid; Kjeldstad, Torunn; Riise, Heine Nygard; Breen, Anneline Malling & Tollisen, Stian (2024). Alle nye bygg bør få integrerte solceller i bygningskroppen. Full text in Research Archive
• Eriksen, Erling Ween; Riise, Heine Nygard & Nygård, Magnus Moe (2024). Evaluation of the Impact of Local Sensing Data and Feature Extraction Techniques on High-Frequency Intra-Hour Irradiance Forecasting. Full text in Research Archive
• Honningdalsnes, Erlend Hustad & Riise, Heine Nygard (2024). Hvor og hvordan bør vi bygge solkraft i Norge? Full text in Research Archive
• Riise, Heine Nygard; Myhre, Stine Fleischer; Øgaard, Mari & Berge, Erik (2024). Solenergi i norske forhold. Full text in Research Archive
• Riise, Heine Nygard (2024). Benchmark of six irradiation products in Norway. Full text in Research Archive
• Riise, Heine Nygard & Kjeldstad, Torunn (2024). Hvor mye sol har vi i Norge og hva gir det i kWh? Full text in Research Archive
• Honningdalsnes, Erlend Hustad; Marstein, Erik Stensrud & Riise, Heine Nygard (2024). Microclimatic Changes in Norwegian Solar Power Systems. Full text in Research Archive
• Milani, Simone; Marstein, Erik Stensrud; Honningdalsnes, Erlend Hustad & Riise, Heine Nygard (2024). Water Reduction Potential for Olive Orchards within AgriPV Systems in Southern Italy. Full text in Research Archive
• Riise, Heine Nygard (2024). Dårlige estimater kan velte et solcelleprosjekt. [Journal]. Montel. Full text in Research Archive
• Honningdalsnes, Erlend Hustad; Marstein, Erik Stensrud; Lindholm, Dag; Bonesmo, Helge & Riise, Heine Nygard (2024). Reducing Wind Speeds and Boosting Agricultural Productivity with Vertical Bifacial Solar Panels. Full text in Research Archive
• Riise, Heine Nygard & Kjeldstad, Torunn (2024). SOLKRAFT PÅ GRÅ AREALER. Full text in Research Archive
• Øgaard, Mari & Riise, Heine Nygard (2024). Simulering i Norge - Datagrunnlag og modeller. Full text in Research Archive
• Myhre, Stine Fleischer; Rosenberg, Eva & Riise, Heine Nygard (2024). The role and impact of rooftop PV in the Norwegian energy system under different energy transition pathways. Full text in Research Archive
• Honningdalsnes, Erlend Hustad; Marstein, Erik Stensrud & Riise, Heine Nygard (2023). The Effect of PV Panels on Microclimatic Growth Conditions and Crop Yield in Agrivoltaic Systems. Full text in Research Archive
• Honningdalsnes, Erlend Hustad; Bonesmo, Helge; Marstein, Erik Stensrud; Völler, Steve & Riise, Heine Nygard (2023). Autonomous Optimization of Agrivoltaic Systems - A Case Study on Grass and Vertical Bifacial PV. Full text in Research Archive
• Klyve, Øyvind Sommer; Nygård, Magnus Moe; Riise, Heine Nygard; Fagerström, Jonathan & Marstein, Erik Stensrud (2023). What is the economic value of solar power forecasts in energy markets? - Scandinavian case study. Full text in Research Archive
• Øgaard, Mari & Riise, Heine Nygard (2023). How large snow losses do we expect in ground mounted PV power plants in Norway? Full text in Research Archive
• Øgaard, Mari; Rønneberg, Sigrid; Eriksen, Erling Ween; Nysted, Vilde Stueland; Otnes, Gaute & Foss, Sean Erik [Show all 8 contributors for this article] (2023). Vertical bifacial PV systems: modeling and performance analysis of a light-weight system for flat roofs. Full text in Research Archive
• Myhre, Stine Fleischer; Kvalbein, Lisa; Øgaard, Mari & Riise, Heine Nygard (2023). Technical potential for PV power from Norwegian rooftops. Full text in Research Archive
• Dobler, Andreas; Berge, Erik & Riise, Heine Nygard (2022). Toward five years of quality assured global irradiance data for solar resource mapping in Norway. Full text in Research Archive
• Nygård, Magnus Moe; Klyve, Øyvind Sommer; Riise, Heine Nygard; Fagerström, Jonathan; Selj, Josefine Helene Krogh & Marstein, Erik Stensrud (2022). The value of PV forecasts in the current and future Scandinavian energy market. Full text in Research Archive
• Foss, Sean Erik; Zhu, Junjie; Riise, Heine Nygard; Young, Jørgen & Borrebak, Per-Olof Fredrik Andersson (2022). BIPV development at IsolaSolar. Full text in Research Archive
• Martinsen, Dina C.; Øgaard, Mari; Nygård, Magnus Moe; Wiig, Marie Syre; Sabatino, Marisa Di & Marstein, Erik Stensrud [Show all 7 contributors for this article] (2022). Evaluation of irradiance decomposition and transposition models for a Nordic climate. Full text in Research Archive
• Øgaard, Mari & Riise, Heine Nygard (2022). How should monthly snow loss be included in PV yield assessments? Full text in Research Archive
• Seiffert, Christoph; Riise, Heine Nygard; Roosloot, Nathan; Brattheim, Sigurd; Nærland, Tine Uberg & Otnes, Gaute (2021). Outdoor and Indoor PV Module Testing and Characterisation Facilities at IFE. Full text in Research Archive
• Nygård, Magnus Moe; Wiig, Marie Syre; Otnes, Gaute; Roosloot, Nathan Abel; Riise, Heine Nygard & Øgaard, Mari [Show all 7 contributors for this article] (2021). Bifacial Gain In Nordic Conditions. Full text in Research Archive
• Selj, Josefine Helene Krogh & Riise, Heine Nygard (2021). Hvordan er den norske solressursen? Full text in Research Archive
• Riise, Heine Nygard; Øgaard, Mari & Nærland, Tine Uberg (2021). Soiling impact on a farmhouse, rooftop PV system in Eastern Norway. Full text in Research Archive
• Øgaard, Mari Benedikte; Riise, Heine Nygard & Selj, Josefine Helene Krogh (2021). Modeling Snow Losses in Photovoltaic Systems. Full text in Research Archive
• Øgaard, Mari; Riise, Heine Nygard & Selj, Josefine Helene Krogh (2021). PV snow losses in Norway: how much power is lost, and can it be predicted? Full text in Research Archive
• Øgaard, Mari; Riise, Heine Nygard & Selj, Josefine Helene Krogh (2021). Estimation of Snow Loss for Photovoltaic Plants in Norway. Full text in Research Archive
• Øgaard, Mari Benedikte; Aarseth, Bjørn Lupton; Skomedal, Åsmund; Riise, Heine Nygard; Sartori, Sabrina & Selj, Josefine Helene Krogh (2020). Identifying snow events in PV system data. Full text in Research Archive
• Grini, Sigbjørn; Borgersen, Jon Arthur; Sky, Thomas Neset; Frodason, Ymir Kalmann; Riise, Heine Nygard & Zimmermann, Christian (2018). Omvisning MENA. Full text in Research Archive
• Johansen, Klaus Magnus H; Bergum, Kristin; Riise, Heine Nygard & Grini, Sigbjørn (2017). Advanced characterization of solar energy materials and novel solar cell concepts. Full text in Research Archive
• Riise, Heine Nygard; Kjeldstad, Torunn; Sky, Thomas Neset & Borgersen, Jon Arthur (2017). MiNaLab-besøk frå Kongsskogen VGS. Full text in Research Archive
• Riise, Heine Nygard; Bathen, Marianne Etzelmüller; Grini, Sigbjørn; Olsen, Vegard Skiftestad & Sky, Thomas Neset (2017). Omvisning MENA. Full text in Research Archive
• Sky, Thomas Neset; Johansen, Klaus Magnus H; Vines, Lasse; Svensson, Bengt Gunnar & Riise, Heine Nygard (2017). Diffusion of Al in ZnO: the interplay with Zn-vacancies. Full text in Research Archive
• Riise, Heine Nygard; Bathen, Marianne Etzelmüller; Borgersen, Jon Arthur; Grini, Sigbjørn & Johansen, Klaus Magnus H (2017). Besøk frå Nanoskolen 2017. Full text in Research Archive
• Riise, Heine Nygard; Aarseth, Bjørn Brevig; Kjeldstad, Torunn; Borgersen, Jon Arthur & Olsen, Vegard Skiftestad (2017). Besøk frå deltakarar i Fysikk-OL. Full text in Research Archive
• Sky, Thomas Neset; Johansen, Klaus Magnus H; Vines, Lasse; Svensson, Bengt Gunnar & Riise, Heine Nygard (2017). Diffusion of Group III Elements in ZnO. Full text in Research Archive
• Honningdalsnes, Erlend Hustad; Riise, Heine Nygard & Marstein, Erik Stensrud (2026). Vertical agrivoltaic systems: Modeling, optimization, and monitoring - With special emphasis on northern climates. Universitetet i Oslo. Full text in Research Archive Show summary

  Agricultural activities occupy nearly half of the world’s habitable land, an area larger than the Americas and the European Union combined. This has largely come at the expense of natural habitats, and today, new land uses such as utility-scale photovoltaic (PV) electricity production add further pressure. Agrivoltaic systems, in which PV modules and agricultural crops coexist on the same land, offer a pathway to greater land-use efficiency without claiming additional territory from nature. Although both PV modules and food crops rely on sunlight as their primary energy source, synergistic effects between the two have been demonstrated worldwide. PV modules can, for instance, harvest irradiance that exceeds a crop’s biological saturation point, or provide shade and shelter under harsh environmental conditions. The efficacy of these synergies, however, depends strongly on the specific crops and climates involved. In Northern Europe, short growing seasons and, in some places, strong regulatory protection of scarce agricultural land may require that crop yields are maintained or improved. In this context, vertical bifacial agrivoltaic systems have attracted particular interest due to their low physical footprint and limited crop shading. In these systems, vertically mounted PV modules arranged in rows leave the inter-row space accessible for agricultural machinery while simultaneously functioning as windbreaks that improve the local microclimate in ways that most other agrivoltaic designs do not. This thesis develops computational frameworks for the design and evaluation of agrivoltaic systems, with particular emphasis on vertical bifacial systems in northern climates. The research is structured around methodological gaps identified in the literature. Paper I reviews the state of the art of agrivoltaic modeling, identifying weaknesses that several subsequent papers help address. Among these is the need for accurate optical modeling without the high computational cost of ray tracing tools commonly used for PV production modeling. Paper II addresses this bottleneck by identifying and benchmarking efficient matrix-based ray-tracing tools against industry-standard approaches, demonstrating that they deliver both the accuracy and speed required for autonomous optimization of agrivoltaic system design. Paper III then utilizes one of the identified ray-tracing tools within an autonomous optimization framework. The framework identifies system designs that maximize the Land Equivalent Ratio through optimal light sharing between food crops and PV modules. Optical modeling alone, however, neglects thermodynamic and aerodynamic changes that are especially relevant where vertical systems act as windbreaks. Paper IV therefore integrates computational fluid dynamics to analyze this windbreak effect. The results demonstrate how vertical photovoltaic rows create sheltered zones with significantly reduced wind speeds, which leads to reduced evapotranspiration and increased temperatures. The subsequent crop yield analysis shows that these beneficial mechanisms can compensate for shading, resulting in net-positive crop yields in high-latitude climates, particularly during years of drought. Finally, Paper V uses satellite remote sensing to monitor operating vertical systems across the world, offering a scalable way to independently verify agricultural productivity in commercial systems. The analysis finds no reduction in vegetation indices after installation, indicating that commercial systems maintain agricultural performance.

• Dobler, Andreas; Berge, Erik; Hygen, Hans Olav; Grini, Sigbjørn & Riise, Heine Nygard (2024). Quality control of radiation data for solar resource mapping. Norwegian Meteorological Institute. Full text in Research Archive
• Robsahm, Amalie Elisabeth; Olsen, Espen & Riise, Heine Nygard (2023). Simulation of a vertical bifacial PV system compared to measured values. Norges miljø- og biovitenskapelige universitet (NMBU). Full text in Research Archive Show summary

  Photovoltaic (PV) systems have gained great interest the recent years with an increasing rate of installed capacity. In addition to the monofacial solar panels, the interest in bifacial solar panels, with an expected market share of 30.0 % by 2030, increases. The bifacial solar panels utilize irradiance on both the front and rear sides of the panel to generate energy. Hence, they are able to generate more energy than monofacial solar panels, making them interesting due to the demand for energy-efficient solar panels. Over Easy Solar AS offers vertically mounted bifacial solar panels with a height of approximately 22.0 cm. Compared to conventional solar panels, they do not need intrusive fasteners and heavy ballast. Thereby, the solar panels are suitable for many flat roofs and green roofs as light and water are provided to the plants underneath. At the Institute for Energy Technology (IFE) at Kjeller, a test site including solar panels from Over Easy Solar AS has been mounted. As the technology from Over Easy Solar AS was introduced in 2021, addressing the performance using software to simulate the irradiance and power output, with possible factors affecting the simulations has not been researched much. In this thesis, the software bifacial_radiance was assessed by creating a 3D model and simulating the irradiance using backward ray tracing for the test site at IFE. Even though bifacial_radiance is a time-consuming software, simulations were performed for clear-sky days, overcast days, and days with varying weather, for all seasons in Norway. Overall, the results from bifacial_radiance show an overestimation of the irradiance compared to measured irradiance with a percentage difference of 5.06 % – 16.54 %, but the model gives a rough estimate of the expected irradiance. Still, there are some days where there is good compliance between simulated and measured irradiance, and other days with a large deviation, especially during the winter. There are many possible explanations for the deviation between simulated and measured irradiance such as albedo, shading, and snow. Differences between the 3D model and the test site, such as orientation, materials, surrounding objects, and positioning of objects are other factors that may affect the irradiance. This thesis thoroughly and systematically addresses factors that may affect the simulated and measured irradiance for a PV system. The simulated power using pvlib shows an overestimation of the DC and AC power compared to the measured values. Possible explanations are system losses such as shading and cable losses. Snow covering the solar panels is also a significant factor that may affect the measured power and cause a larger deviation in the results. When simulating the DC energy for a longer period of time, the percentage difference between measured and simulated energy varies in the range of 28.29 % – 119.58 %. Hence, further work and implementation of the factors such as shading and snow should be done to develop a more accurate model for simulating power and energy.

• Riise, Heine Nygard (2021). Algoritmar for energimodellering av PV. IFE. Full text in Research Archive
• Riise, Heine Nygard (2018). Materials and junctions for a novel oxide solar cell. Universitetet i Oslo. Full text in Research Archive Show summary

  Renewable energy is crucial for tackling the world’s climate and energy challenges. Solar cells already hold a significant portion of the global energy market, and increasing this portion is important for propelling the renewable revolution forward. In this work, a novel solar cell concept with the potential of boosting the solar cell efficiency is explored. A Si bottom cell absorbs the low-energy part of the sunlight, while an oxide top cell consisting of Cu2O and ZnO absorbs the high-energy part. Material and junction properties of the architecture is investigated electrically, optically, chemically and structurally. The thesis details the defect structure of Cu2O, epitaxial growth of ZnO, and the sputter growth of poly-Si. The Cu2O/Si, and Cu2O/ZnO junctions are characterized, and novel ways of realizing the shallow emitter in Si and improving the crystallinity of Cu2O are demonstrated.

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