Prosjekter
- FME SOLAR
- SuSolTech – The Research Center for Sustainable Solar Cell Technology
Publikasjoner
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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.
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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.
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Dahlioui, Dounia; Øgaard, Mari & Imenes, Anne Gerd
(2025).
Snow impact on PV performance: Assessing the zero-output challenge in cold areas.
Renewable and Sustainable Energy Reviews.
ISSN 1364-0321.
213.
doi:
10.1016/j.rser.2025.115468.
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Solar photovoltaic (PV) technology has a great potential for renewable energy generation. However, in cold climates with heavy snowfall, PV systems performance might be significantly reduced. This review investigates the impact of snow on solar PV in regions with harsh winters. It describes the snow soiling process while determining the main factors leading to snow losses in PV plants. Factors influencing snow losses are classified into four major categories: controllable factors, such as surface properties and PV installation characteristics, and uncontrollable factors, including climatic conditions and snow properties. The literature review reveals significant variations in reported snow losses due to the number of influential factors. One key recommendation is to improve PV system design to better accommodate snowy conditions, rather than relying on configurations optimized for milder conditions. The review also identifies a gap in the literature regarding the implementation of safety devices such as snow guards in the context of PV systems. With the increasing adoption of bifacial technologies, further research is needed to assess the benefits of snow's high albedo. For accurate snow loss modeling and shedding prediction, it is crucial to include additional factors impacting snow accumulation and clearing, such as liquid water content which affects snow adhesion. Additionally, enhancing models through image analysis and integrating drones for precise camera angles can significantly improve snow detection across various PV configurations and locations.
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Das, Opy; Dahlioui, Dounia; Zafar, Muhammad Hamza; Akhtar, Naureen; Moosavi, Syed Kumayl Raza & Sanfilippo, Filippo
(2025).
Ultra-short term PV power forecasting under diverse environmental conditions: A case study of Norway.
Energy Conversion and Management: X.
27.
doi:
10.1016/j.ecmx.2025.101072.
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Accurate short-term solar forecasting is critical for power plant operations, grid balancing, real-time dispatching, automatic generation control, and energy trading. In Norway, where solar radiation is limited in winter and highly variable in summer, accurate predictions are essential. This study focuses on ultra-short-term forecasting of solar radiation and power output from a 37.8 kWp solar photovoltaic (PV) power plant at the University of Agder (UiA), Grimstad (58.335322°N, 8.577718°E), in southern Norway. We propose a novel forecasting model that integrates Spatial Attention, Temporal Attention, Self-Attention, CNN, and BiLSTM architectures to enhance prediction accuracy. Using a custom dataset collected from the UiA PV plant, the model’s effectiveness was validated through comprehensive ablation studies and comparative analysis with state-of-the-art methods. The proposed model achieved a low RMSE of 0.162 kW using seven days of data, demonstrating its superiority in predicting short-term PV power outputs and associated uncertainties, outperforming conventional forecasting techniques.
Se alle arbeider i NVA
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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.
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Dahlioui, Dounia & Imenes, Anne Gerd
(2025).
Optimizing the Performance of Bifacial PV Modules Through Ground Albedo Enhancement.
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Øgaard, Mari; Eriksen, Erling Ween; Dahlioui, Dounia; Rønneberg, Sigrid & Riise, Heine Nygard
(2025).
Analyzing and modeling snow loss in ground-mounted PV systems.
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Dahlioui, Dounia & Imenes, Anne Gerd
(2024).
Snow Impact on PV Performance: Review and Investigation Towards Optimum System Design.
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PV technology faces certain challenges in cold climates such as snow and ice acting as barriers, obstructing light from reaching the cells, but also opportunities for increased albedo during snowy winters. This work presents two sections highlighting :
▪ A review of the impact of snow on PV performance focusing on the challenges and opportunities posed by snow accumulation.
▪ Distribution of snow losses across various PV technologies and climate zones, as reported in literature.
▪ Analysis and classification of factors influencing snow losses.
▪ Description of snow soiling process.
▪ Parametric analysis of energy yield and snow losses to tilt angle and ground coverage ratio through production modelling using Solar Advisor Model (SAM) for a case study in Grimstad
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Publisert
3. juni 2025 14:37
- Sist endret
3. juni 2025 14:53