University Graduate Center

• Bifacial gain is estimated with four different monofacial references in Norway. • Bifacial gain estimates depend on the properties of the monofacial reference. • Correcting for irradiance and temperature narrows the range between the estimates. • The best estimate of the bifacial gain is determined to 14.4 %. • Remaining variations in estimates may reflect measurement uncertainty in the method. 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 kW p 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.

In the field of remote sensing and Earth observation, deep neural networks (DNNs) have established themselves as important tools for many different image analysis applications. Estimation of terrain features from optical satellite imagery is a rarely studied application for which DNNs are well suited because of their ability to extract and combine information at various scales. To predict terrain slopes in optical images, we propose an R2U-Net using global multispectral Sentinel-2 (S2) L2A images as input, and ALOS World 3D DSM elevation data as target data. The R2U-Net takes advantage of a residual unit that benefits deep architecture training, and the recurrent residual convolutional layers provide better feature accumulation. Two models were experimented with; one model trained on only the optical RGB bands and one model trained on all S2 L2A bands. Evaluation of the multispectral- and RGB-trained models showed that the multispectral-trained model performs better than the RGB model, both during training and when evaluated on the test data. The multispectral model performs better overall than the RGB model in all the cases studied. Slope errors typically increase from low- to high-gradient terrain, but not at the same rate as the slope steepness itself, while aspect errors decrease as the models struggle more to predict the slope aspect in low-gradient terrain. This highlights that, in this case, using more spectral bands when predicting terrain slopes helps improve the model predictions. The results have also been shown to depend on the incoming angle of the sunlight, which is mostly due to the topographic shadows that are being cast onto the terrain.

Recent developments in the design of body-centered cubic (BCC) multicomponent alloys via computational tools have demonstrated the possibility of obtaining alloys with excellent hydrogen storage behavior. In this work, we employ the CALPHAD (Calculation of Phase Diagrams) method to design Nb-rich alloys of the Nb-Cr-Mn system that present hydrogen storage reversibility at room temperature under moderate pressure conditions. We employ the valence electron concentration (VEC) factor as a compositional guide to select compositions with suitable thermodynamic properties. Using electric arc melting, we synthesize two alloys, namely Nb85Cr10Mn5 and Nb70Cr20Mn10, both forming predominant BCC solid solutions with VEC ∼ 5.2 and minor amounts of a eutectic microconstituent composed of BCC and Laves C14 phases. Both alloys are easily hydrogenated at room temperature without the need for an activation treatment. The Nb85Cr10Mn5 alloy reaches a storage capacity of 2.1 wt% of H (298 K; Peq∼ 20 bar) whereas the Nb70Cr20Mn10 alloy reaches a capacity of 1.4 wt% (298 K; Peq∼ 21 bar). Benefits in the storage kinetic performance are correlated with the BCC + C14 microstructure. Pressure-Composition-Temperature (PCT) diagrams show moderate values of equilibrium pressure for hydrogen storage reversibility at room temperature. Room temperature absorption/desorption cycling measurements demonstrated a reversible capacity of 1.2 wt% of H (Peq∼ 29 bar) for the Nb85Cr10Mn5 alloy and 0.8 wt% of H (Peq∼ 31 bar) for the Nb70Cr20Mn10 alloy after twenty cycles.

This research investigated the relationship between cardiovascular disease (CVD) and depressive symptoms, as well as whether income and sibling count moderated this relationship. The database employed included adults between the ages of 40 and 91 (N = 674, Mean= 59) that completed a general survey as new immigrants. Participant data consisted of demographic information pertaining to participant age and participant sibling count, health information regarding CVD history and depressive symptoms, and income information. The study results show that South Asian Indian immigrants who endorsed a history of CVD were associated with reporting more depressive symptoms. As well, South Asian Indian immigrants with higher reported incomes had a stronger association between CVD history and depression symptoms. The number of siblings did not influence the association between depressive symptoms and a history of CVD. It is possible that high stress occupations, often associated with higher incomes, contribute to the onset of CVD and depressive symptoms.

Abstract Across Europe, negative public opinion has and may continue to limit the deployment of renewable energy infrastructure required for the transition to net‐zero energy systems. Understanding public sentiment and its spatio‐temporal variations is as such important for decision‐making and for developing socially accepted energy systems. In this study, we apply a sentiment classification model based on a machine learning framework for natural language processing, NorBERT, on data collected from Twitter between 2006 and 2022 to analyse the case of wind power opposition in Norway. From the 68,828 tweets with geospatial information, we show how discussions about wind power intensified in 2018/2019 together with a trend of more negative tweets up until 2020, both on a regional level and for Norway as a whole. Furthermore, we find weak geographical clustering in our data, indicating that discussions are country wide and not dominated by specific regional events or developments. Twitter data allow for detailed insight into the temporal nature of public sentiments and extending this research to additional case studies of technologies, countries and sources of data (e.g. newspapers, other social media) may prove important to complement traditional survey research and the understanding of public sentiment.

As an effective learning and assessment tool, E-portfolio has enjoyed great popularity with its great benefits in improving academic performances. However, few empirical studies have focused on integrating e-portfolio assessment into ESP courses by adopting blended learning mode. This study aims to investigate the effect of e-portfolio on students’ speaking proficiency in an ESP course within the context of blended learning and the learners’ use of self-reflection strategies. Data on students’ performance on the final speaking test, teacher observation and semi-structured interview were collected from second-year Business English students in Ningbo Polytechnics in China. The data were both qualitatively and quantitatively analysed. The findings revealed that the use of e-portfolio had a significant effect on improving students’ speaking proficiency in discourse and interactive communication. Evidence from the study also indicate that guided reflection has enabled students’ active engagement in e-portfolio development and thus their new understanding on the basis of reflection could be integrated into personal practices to help achieve learning outcomes.

Floating photovoltaic (FPV) systems are an emerging and increasingly competitive application of solar PV, especially in land area-constrained countries. This study focuses on the optimal dimensioning and scheduling of a grid-connected hybrid hydro-FPV system. The case study is based on a cascade hydropower system located in Sub-Saharan Africa. The techno-economic feasibility of the hybrid system is analysed under different types of revenue streams and load commitments. Moreover, the resource complementarity between solar irradiation and reservoir water inflow in different weather years is analysed. A linear programming model for optimal dimensioning/scheduling of a hybrid hydro-FPV system is proposed. The results indicate that hybridisation with FPV can under the proposed PPA and spot market structure increase the annual producer profits by 18–21% and 0–4%, respectively compared to a hydro-only system. Furthermore, it is estimated that the CAPEX of FPV should be around 42–57% lower than that of ground-mounted PV (GPV) with single-axis tracking for the hydro-FPV system to reach the same annual producer profit as the hydro-GPV system. Considering improved efficiency by cooling the FPV modules, the revenues increase by 0–3% depending on the selected weather year and market scheme.

Abstract According to Weyl, “‘inexhaustibility’ is essential to the infinite”. However, he distinguishes two kinds of inexhaustible, or merely potential, domains: those that are “extensionally determinate” and those that are not. This article clarifies Weyl's distinction and explains its enduring logical and philosophical significance. The distinction sheds lights on the contemporary debate about potentialism, which in turn affords a deeper understanding of Weyl.

As the world evolves, so does the energy demand. The storage of hydrogen using metal hydrides shows great promise due to the ability to store and deliver energy on demand while achieving higher volumetric density and safer storage conditions compared with traditional storage options such as compressed gas or liquid hydrogen. Research is typically performed on lab-sized samples and tanks and shows great potential for large scale applications. However, the effects of scale-up on the metal hydride’s performance are relatively less investigated. Studies performed so far on both materials, and hydride-based storage tanks show that the scale-up can significantly impact the system’s capacity, kinetics, and sorption properties. The findings presented in this review suggest areas of further investigation in order to implement metal hydrides in real scale applications.