cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Evaluation of the risk of acute kidney injury with the use of piperacillin/tazobactam among adult critically ill patients
Creators: name: Saad, Mohamed O.
name: Mohamed, Adham M.
name: Mitwally, Hassan A.
name: Shible, Ahmed A.
name: Ait Hssain, Ali
name: Abdelaty, Mohamed A.
Publisher: name: Manara - Qatar Research Repository
Year: 2022
Subjects: Clinical sciences
Medical microbiology

description: Purpose Piperacillin/tazobactam (PT), when combined with vancomycin, is associated with an increased risk of acute kidney injury (AKI). It is not known whether PT alone is associated with a higher incidence of AKI compared to other β-lactams among critically ill patients. The objective of this study was to compare the incidence of AKI associated with the use of PT to other β-lactams among adult critically ill patients Methods This retrospective study was conducted in the surgical and the medical intensive care units at two hospitals within Hamad Medical Corporation (HMC) in Qatar and included adult critically ill patients who received at least one dose of anti-pseudomonal β-lactams. The primary outcome was acute kidney injury, defined using the Kidney Disease Improving Global Outcomes (KDIGO) criteria. Multiple logistic regression with adjustment for pre-specified potential confounders was used for the primary outcome analysis. Results A total of 669 patients were included in the analysis: 507 patients in the PT group and 162 patients in the control (meropenem/cefepime) group. AKI occurred in 136 (26.8%) members of the PT group and 38 (23.5%) members of the control group [odds ratio (OR) 1.2; 95% confidence interval (CI) 0.79–1.8]. The results were not significantly altered after adjusting for the pre-specified potential confounders (adjusted OR 1.38; 95% CI 0.88–2.15). Conclusion In this study, PT was not associated with a higher risk of AKI compared to cefepime or meropenem among adult critically ill patients.Other Information Published in: Infection
 License: https://creativecommons.org/licenses/by/4.0
See article on publisher's website: http://dx.doi.org/10.1007/s15010-020-01480-x
Insights into the generation of hydroxyl radicals from H2O2 decomposition by the combination of Fe2+ and chloranilic acid
Creators: name: Ahmad, M. I.
name: Bensalah, N.
Publisher: name: Manara - Qatar Research Repository
Year: 2022
Subjects: subject: Environmental biotechnology
subject: FOS: Environmental biotechnology
subject: Biochemistry and cell biology

description: In this work, the degradation of chloranilic acid (CAA) by chemical oxidation with H2O2 alone and in the presence of ferrous iron Fe2+ catalyst was investigated in order to improve our understanding on the novel metal-independent approach. The interesting and efficient metal-independent hydroxyl radicals (OH) production by using halogenated quinones and H2O2 has been currently demonstrated. The results clearly confirmed the formation of OH radicals from the reaction of CAA with H2O2. CAA was slowly decayed by chemical oxidation with H2O2 and followed a pseudo-first kinetics. H2O2 doses ≥ 1000 mM were required to achieve complete CAA decay from 1 mM CAA. However, low total organic carbon (TOC) removal was measured with the accumulation of carboxylic acids. The addition of Fe2+ enhanced the kinetics of CAA degradation and reduced the required dose of H2O2. High TOC removal was obtained, almost complete release of chloride ions, without accumulation of carboxylic acids. The decolorization of methylene blue (MB) aqueous solutions was performed using H2O2, H2O2/CAA, H2O2/Fe2+, and H2O2/CAA/Fe2+. H2O2/CAA/Fe2+ was the most effective method in decolorizing MB solutions due to the accelerated Fe2+ regeneration. Coupling Fenton reagent with CAA seems to be promising alternative to physical activation in water and soil treatment.Other Information Published in: International Journal of Environmental Science and Technology
 License: https://creativecommons.org/licenses/by/4.0
See article on publisher's website: http://dx.doi.org/10.1007/s13762-021-03822-0
Comparison of biocrude oil production from self-settling and non-settling microalgae biomass produced in the Qatari desert environment
Creators: name: Das, P.
name: Thaher, M. I.
name: Khan, S.
name: AbdulQuadir, M.
name: Chaudhary, A. K.
name: Alghasal, G.
name: Al-Jabri, H.
Publisher: name: Manara - Qatar Research Repository
Year: 2022
Subjects: subject: Environmental biotechnology
subject: FOS: Environmental biotechnology
subject: Biochemistry and cell biology

description: The present study investigated the growth, harvesting, biocrude conversion, and recycling of the HTL aqueous phase for one self-settling (i.e., Chlorocystis sp.) and another non-settling (i.e., Picochlorum sp.) marine microalgae. Both the strains were grown simultaneously in 2 identical 25,000-L raceway ponds in the Qatari desert. The cell size of Picochlorum sp. was small (2–3 µm), and its biomass was harvested using a centrifuge. Cells of Chlorocystis sp. (6–9 µm) formed flocs that settled spontaneously in a sedimentation chamber. Harvested biomass of these two strains was then converted to biocrude oil, using a 500-mL Parr reactor. The biocrude yield of Picochlorum sp. and Chlorocystis sp. was 39.6 ± 1.15% and 34.8 ± 1.65%, respectively. The energy content of the biocrude oil was 32.78 and 33.38 MJ/kg for Chlorocystis sp. and Picochlorum sp., respectively. Both the strains were capable of efficiently utilizing more than 95% nitrogen of the HTL aqueous phase. Although lower biocrude yield was obtained from Chlorocystis sp., compared to Picochlorum sp., harvesting of Chlorocystis sp. would require much lower energy compared to Picochlorum sp. Therefore, a self-settling microalgae (e.g., Chlorocystis sp.) could potentially be a better candidate, over non-settling microalgae, for producing biofuel feedstock.Other Information Published in: International Journal of Environmental Science and Technology
 License: https://creativecommons.org/licenses/by/4.0
See article on publisher's website: http://dx.doi.org/10.1007/s13762-019-02364-w
Photovoltaic Energy Integration with Households’ Demand: A Case Study of a Residential Smart Grids Pilot in The Netherlands
Creators: name: Gerçek, C.
name: Reinders, A.
Publisher: name: WIP
Year: 2018
Subjects: PV Systems - Performance, Applications and Integration
Grid and Energy System Integration

description: 35th European Photovoltaic Solar Energy Conference and Exhibition; 1714-1719
description: This paper presents a data analysis of a residential smart grid pilot in the Netherlands with PV installations. This study has been executed in the ERA-Net Smart Grids Plus project “Co-Evolution of Smart Energy Products and Services” with the aim to evaluate the flexibility and self-consumption of generated PV energy in residential smart grids. The pilot that has been analysed, namely PowerMatching City, has various configurations with PV systems, heat-pumps and micro-cogeneration units which were used as a tool for the efficient integration of renewable power into electricity network. Different energy variables as electricity production, purchase or consumption of the pilot households has been announced monthly and yearly basis and discussed. In conclusion, the combination of μ-CHP and PV systems increases the self-sufficiency (40%) compared to households that have heat-pumps (20%).
Techno-Economic Evaluation of Voltage Dependent Active and Reactive Power Control to Reduce Voltage Violations in Distribution Grids
Creators: name: Knecht, R.
name: Carigiet, F.
name: Schwab, A.
name: Korba, P.
name: Baumgartner, F.P.
Publisher: name: WIP
Year: 2018
Subjects: PV Systems - Performance, Applications and Integration
Grid and Energy System Integration

description: 35th European Photovoltaic Solar Energy Conference and Exhibition; 1720-1725
description: High penetration of PV plants or numerous electric vehicle (EV) charging station stations connected to the
low voltage distribution grids (LVDG) may cause a voltage rise or voltage decrease respectively. There are several
measures of maintaining the voltage stability such as grid reinforcement, battery energy storage, line voltage regulator,
etc., although they vary in effectiveness and economic viability. This paper focuses on using decentralised voltagedependent
active and reactive power (PQ(V)) control of PV inverters to stabilise the voltage in the grid. Using two grid
models in Southern Germany and Switzerland the best PQ(V) control strategy is evaluated using load flow calculations.
The weakest node in the first grid exhibits a maximum voltage of 1.072 pu on a sunny day. Due to the implementation of
the PQ(V) control the maximum voltage is reduced to 1.024 pu at the same node. Costs considered for PQ(V) control are
the PV yield loss and the additional reactive power compensation, which amount to roughly CHF 2’600.- per year. The
future installation of EV charging stations may positively interact with PV feed-in. The voltage decrease can further be
limited using PQ(V) control. Further grids and means for voltage stabilisation will be analysed in the future.
Spatial Representation of Low-Voltage Network Hosting Capacity for Photovoltaic Roof-Top Installations Using an Open-Source Tool
Creators: name: Joos, M.
name: Lebert, N.
name: Gaiddon, B.
name: Séguin, E.
name: Gautreau, P.E.
Publisher: name: WIP
Year: 2018
Subjects: PV Systems - Performance, Applications and Integration
Grid and Energy System Integration

description: 35th European Photovoltaic Solar Energy Conference and Exhibition; 1726-1734
description: Just as solar cadastres have become the norm to assess the roof-top PV potential in the last years,
assessing the hosting capacity of the low-voltage network for electrical production is on the path to becoming a
necessity for an efficient solar production action plan. The model developed here is a hybrid tool composed of a
physical model computing results based on a real infrastructure and a statistical model using empirical rules based on
frequently encountered cases. The tool, built entirely on PostgreSQL/PostGIS, can be easily launched by non-experts
on any set of data and on any computer, and has a low computation time. Results show that the major limit in
connecting high shares of PV in existing grids is above all the low summer power consumption at noon. Key
messages can be drawn from results: 1) hosting capacity of the existing infrastructure on the two territories studied is
important but must be utilized with care by avoiding buildings located far from a substation, 2) on the long run, a
deep reflexion on grid settings and planning is compulsory in order to achieve ambitious shares of renewable
electricity at low marginal cost.
Energy Cluster Model for the Hunsrück-Hochwald National Park Region
Creators: name: Jung, D.
name: Te Heesen, H.
Publisher: name: WIP
Year: 2018
Subjects: PV Systems - Performance, Applications and Integration
Grid and Energy System Integration

description: 35th European Photovoltaic Solar Energy Conference and Exhibition; 1735-1738
description: We analyze the energy production and energy demand of ten municipalities in the national park region
Hunsrück-Hochwald in Southwest Germany. The energy cluster is characterized by a rural structure with 155,000 inhabitants
and just a small number of commercial and industrial companies. The region cannot fulfil its energy demand and thus,
we investigate the contribution of renewable energy capacity additions to the energy balance. This will help the region to
reduce greenhouse gas emission and to get a zero-emission energy cluster in 2050. From today to 2050, three municipalities
are even today an energy export subcluster and five municipalities show a turn-over from an import to an export subcluster.
In total, the national park region is changing from a negative annual energy balance to a positive one by using more wind
power as well as roof-top and ground-mounted PV systems. The results of the energy model of the national park region
can be transferred to other energy cluster and will help these clusters to identify expansion pathways for the integration of
renewable energy systems.
Performance of In-House Li-Ion Battery Storage System Based on Various Strategies
Creators: name: Verma, B.
name: Munzke, N.
name: Hiller, M.
Publisher: name: WIP
Year: 2018
Subjects: PV Systems - Performance, Applications and Integration
Grid and Energy System Integration

description: 35th European Photovoltaic Solar Energy Conference and Exhibition; 1739-1743
description: Energy storage systems with Lithium-ion batteries coupled to solar photovoltaic arrays will become a vital pillar in the future energy landscape. An important question is to maximize the self-supply ratio as well as the battery lifetime at. Out of the various critically important aspects affecting the performance and as a consequence the commercial viability, one is the system control software and its ability to predict both the energy needs of the customer as well as the energy supplied by the PV-array, throughout the day. At KIT, an intelligent control software was developed that incorporates online and offline PV forecast to predict the battery charging regime. These different forecasts methods control a 32 kWh AC-coupled Li-ion (NMC) battery energy storage system, using standard household load curves as well as one of the arrays (17.5 kW) of the 1 MW solar-storage facility as PV generation input. The battery is charged in a way that it is fully charged just a short period of time before sunset. The quantification of the level of intelligence of the storage system control software developed at KIT is done based on the following criteria: (a) the software performance based on the predictive module used (online or offline PV-prognosis), (b) the success of delayed charging in reducing the time spent at high state of charge (SOC) levels and (c) whether prediction errors lead to the battery not being fully charged so that the user’s self-sufficiency is unnecessarily reduced.
Short-Term Photovoltaic Power Forecasting Based on Artificial Neural Networks: A Numerical Weather Prediction-Free Approach
Creators: name: Theocharides, S.
name: Makrides, G.
name: Theristis, M.
name: Almonacid, F.
name: Fernández, E.F.
name: Georghiou, G.E.
Publisher: name: WIP
Year: 2018
Subjects: PV Systems - Performance, Applications and Integration
Solar Resource and Forecasting

description: 35th European Photovoltaic Solar Energy Conference and Exhibition; 1700-1705
description: The increased penetration of photovoltaic (PV) systems introduce new challenges for the stability of electricity grids. In this scope, a machine learning technique utilising artificial neural networks (ANN) was implemented to forecast the hour-ahead (HA) PV power production without the utilisation of numerical weather prediction (NWP) models. Instead, historical PV operational and meteorological data-sets were used for the training and validation stages of the model to calculate HA PV power generation data-sets for time t + 1h while the model input parameters (weather measurements) were applied for time t. The best-performing model comprised of four input parameters (in-plane global irradiance (GI), ambient temperature (Tamb), elevation angle (AlS), azimuth angle (AzS)), a single hidden layer and 22 hidden neurons. Additionally, the results obtained over a test set period of 55 days demonstrated that accurate HA forecasts could be achieved without incorporating NWP since a daily-normalised root mean square error (nRMSE) of 3.63% was achieved. Finally, the model performed very well during clear sky days with a nRMSE close to 1% whereas 57% of all days demonstrated a nRMSE below 5%.
Residential Battery Storage Sizing Based on Daily PV Production and Consumption Load Profile Characterization
Creators: name: Afxentis, S.
name: Florides, M.
name: Theocharides, S.
name: Venizelou, V.
name: Georghiou, G.E.
Publisher: name: WIP
Year: 2018
Subjects: PV Systems - Performance, Applications and Integration
Grid and Energy System Integration

description: 35th European Photovoltaic Solar Energy Conference and Exhibition; 1744-1749
description: The integration of battery energy storage
systems (BESS) to existing grid-connected residential PV
systems can reduce issues stemming from the increased
PV penetration and at the same time improve the
performance of the existing system. In this paper, a
methodology for determining the optimal sizing of BESS
is presented based on a clustering method by considering
energy profiles of residential prosumers in Cyprus. As
such, the daily energy required for residential premises
with existing 3 kWp photovoltaic system in Cyprus is
determined in three primary clusters. The clustering
procedure is carried out based on the daily import
electricity profiles recorded for the prosumers over the
period of one year which revealed the daily energy needs
of each cluster targeting to maximize self-consumption.
Additionally, the battery capacity level of each cluster is
compared with the daily export electricity of each
prosumer within the same cluster to reveal the amount of
users with enough surplus electricity to meet the capacity
requirement of each cluster. Finally, a power rate
dimensioning of the BESS power converter is performed
by analyzing the import power measurements over the
one year test period.
Modelling and Forecasting PV Production in the Absence of Behind-the-Meter Measurements
Creators: name: Landelius, T.
name: Andersson, S.
name: Abrahamsson, R.
Publisher: name: WIP
Year: 2018
Subjects: PV Systems - Performance, Applications and Integration
Solar Resource and Forecasting

description: 35th European Photovoltaic Solar Energy Conference and Exhibition; 1684-1689
description: This paper deals with the prediction of the net load from photovoltaic installations. The forecasts were
only based on information from a numerical weather prediction model and measured net load. The study thus tackles
the problem of estimating the contribution of PV power to the grid without knowing the actual production and
consumption “behind-the-meter”. The main approach using a physical model was compared with persistence
(forecast with yesterday’s values) and black box models represented by linear regression and an artificial neural
network. The artificial neural network performed best with a normalized (with installed power) RMSE of about 10 %.
Linear regression was only slightly inferior while the physical model performed worse (about 15 %). The physical
model only predicts the gross production and needs information about the on site consumption in order to predict the
net load. Here the consumption was predicted using persistence. This assumption did not hold up for the physical
model to match the performance of the black box models. Thus, a better description of the gross consumption is
needed in order to make the physical model more competitive.
Modeling Reflected Irradiance in Urban Environments – A Case Study for Simulation-Based Measurement Quality Control for an Outdoor PV Test Site
Creators: name: Bognar, A.
name: Loonen, R.
name: Valckenborg, R.M.E.
name: Hensen, J.L.M.
Publisher: name: WIP
Year: 2018
Subjects: PV Systems - Performance, Applications and Integration
Solar Resource and Forecasting

description: 35th European Photovoltaic Solar Energy Conference and Exhibition; 1672-1675
description: The increased application of PV in urban environments goes together with a growing awareness of the need to consider the influence of partial shading and reflected irradiance on PV performance. Most of the conventional PV simulation tools do not have the capabilities to account for the possible additional PV yield due to reflected sunlight. On the other end of the spectrum are complex ray-tracing tools that can accurately model reflected irradiance, but require a large amount of input data, are computationally intensive and have limited or no PV modeling algorithms. In this work, as a step towards quantifying uncertainties due to reflected irradiance in urban settings, the potential of a modeling strategy using building energy simulation software, with intermediate complexity is investigated using a case study of an outdoor PV test site.
Ensemble Detrending for Solar Nowcasting
Creators: name: Sanfilippo, A.
name: Martín Pomares, L.
name: Perez-Astudillo, D.
name: Bachour, D.
Publisher: name: WIP
Year: 2018
Subjects: PV Systems - Performance, Applications and Integration
Solar Resource and Forecasting

description: 35th European Photovoltaic Solar Energy Conference and Exhibition; 1696-1699
description: We present a novel treatment of detrending in solar forecasting where several ways of partitioning
training data into more cohesive subsets are used in parallel to improve predictions. First, a solar irradiance training set
covering a whole year is detrended according to season-based and cluster-based detrending criteria. Then, a
classification model is developed which predicts for each choice of time series what is the most appropriate detrending
option, including no detrending. A comparative evaluation of the emerging multi-detrending approach with single
detrending or no-detrending techniques shows very strong gains in error reduction.
Load Flow Simulation of a Low-Voltage PV-Battery Based DC Microgrid to Supply Small Isolated Communities
Creators: name: Ferreira Torres, P.
name: De Arimatéia Alves Vieira Filho, J.
name: Lima Chaar Junior, V.
name: Ferreira De Araújo, L.
name: Williamson, S.
name: Barros Galhardo, M.A.
name: Tavares Pinho, J.
name: Negrao-Macedo, W.
Publisher: name: WIP
Year: 2018
Subjects: PV Systems - Performance, Applications and Integration
Design and Installation of PV Systems

description: 35th European Photovoltaic Solar Energy Conference and Exhibition; 1636-1640
description: This paper presents the modelling and load flow simulation of a low-voltage distribution DC microgrid
which is developed in the test area of the Group of Studies and Development of Energy Alternatives (GEDAEUFPA).
This microgrid is intended to serve as a basis for conducting tests of operation modes, power conditioning
devices, control strategies, among other possibilities, as well as applications related to low voltage direct current
distribution systems, and to validate mathematical models of related processes. The simulated microgrid structure is
composed of three photovoltaic generators of 500 Wp each, a battery bank of 4.8 kWh, three charge controllers
forming a 24 V DC bus, and load banks distributed along a grid with a total length of 200 m. The modelling of
microgrid components are presented in detail, and the load flow study used is derived from the traditional Newton-
Raphson power flow algorithm used in AC systems.
Improving the Accuracy of the National Solar Radiation Database (1998-2016)
Creators: name: Sengupta, M.
name: Habte, A.
name: Lopez, A.
name: Xie, Y.
Publisher: name: WIP
Year: 2018
Subjects: PV Systems - Performance, Applications and Integration
Solar Resource and Forecasting

description: 35th European Photovoltaic Solar Energy Conference and Exhibition; 1662-1665
description: The National Solar Radiation Database (NSRDB) provides gridded satellite-based data sets for the United States and other parts of North and South America using cloud properties retrieved from the Geostationary Operational Environmental (GOES) series of satellites. These cloud properties in combination with ancillary atmospheric parameters are used in the Physical Solar Model (PSM) to compute solar radiation. This paper seeks to 1) describe the changes made in the PSM for the recent update to the National Solar Radiation Database (NSRDB 1998–2016) and 2) examine the performance of this update by comparing the data to high-quality ground-based measurements. We summarize the changes to the input data for the radiative transfer models as well as updates for the processing algorithms. We also analyze the performance and accuracy of the NSRDB across the United States. Additional details of the data set and model are described in [1]–[4].
Predicting Yields of Bifacial PV Power Plants – What Accuracy Is Possible?
Creators: name: Chiodetti, M.
name: Kang, J.
name: Reise, C.
name: Lindsay, A.
Publisher: name: WIP
Year: 2018
Subjects: PV Systems - Performance, Applications and Integration
Design and Installation of PV Systems

description: 35th European Photovoltaic Solar Energy Conference and Exhibition; 1623-1629
description: Realistic bifacial gains expected for large scale PV systems are in the range of 5% to 15%. This gain is
a big game changer when compared with other improvements in PV in the last few years. However, the performance
of a bifacial system will be strongly affected by its design and the resulting impact on the irradiance received on the
rear side of the modules. To accurately estimate the extra yield generated, new tools able to assess the irradiance
reaching the rear side are needed. Different methods are available to estimate the bifacial yield. A very accurate one
is to use 3D modeling of all the system components that can interfere with light combined with ray tracing. EDF
R&D and Fraunhofer ISE have both developed their own bifacial yield assessment tool based on ray tracing. To validate
this approach, both tools have been used for cross comparison simulations. Several validations have been carried
out against real bifacial systems – including large scale fixed tilt and horizontal single axis tracking systems. Results
of the validation and the tool comparison are presented here.
Mitigating Snow on Rooftop PV Systems for Higher Energy Yield and Safer Roofs
Creators: name: Aarseth, B.B.
name: Øgaard, M.B.
name: Zhu, J.
name: Strömberg, T.
name: Tsanakas, J.A.
name: Selj, J.H.
name: Marstein, E.S.
Publisher: name: WIP
Year: 2018
Subjects: PV Systems - Performance, Applications and Integration
Design and Installation of PV Systems

description: 35th European Photovoltaic Solar Energy Conference and Exhibition; 1630-1635
description: This study investigates the potential and technical limitations of applying a controlled forward bias on photovoltaic (PV)
modules for snow mitigation on building-applied photovoltaic (BAPV) systems installed in regions with substantial
snowfalls. Mitigating snow on BAPV systems has a twofold purpose: to reduce the mechanical stress on the PV modules
and the building structure itself, as well as to limit shading and thus increase the overall PV energy yield in the winter
months. The technology is tested in both a climate chamber and under field conditions in an operating, commercial rooftop
PV system covered with snow in Oslo, Norway. Payback time calculations for the snow mitigation is done both in terms
of energy and economy, with the latter taking the national power tax into account.
Both in the climate chamber and initial full-scale rooftop PV system tests, the system was successfully demonstrated.
Energy calculations show that there is large potential for optimization of the snow mitigation process to boost the PV
system’s energy yield in the spring. Hence, active snow mitigation can be a beneficial solution not only for necessary snow
mitigation, but also for boosting the yield of PV systems.
Open Source Tool for a Better Design of BIPV+ Battery System: An Applied Example
Creators: name: Lovati, M.
name: Adami, J.
name: Moser, D.
Publisher: name: WIP
Year: 2018
Subjects: PV Systems - Performance, Applications and Integration
Design and Installation of PV Systems

description: 35th European Photovoltaic Solar Energy Conference and Exhibition; 1641-1646
description: In this paper a case study is examined with an innovative open source tool for designing cost effective
BIPV+ battery systems. The aim is to bring awareness of the economic profitability and visual impact of a BIPV system
to the designer in the early stage of the architectural design. The main factors influencing the output are the sunlight
availability, its variation along the HOY (Hour Of the Year), the electric demand, the cost of different parts of the
system and the cost of electricity. The method is applied on a group of three residential high-rise buildings in northern
Italy, the system is optimized for maximum NPV(Net Present Value) or for an established IRR (Internal Rate of Return)
supposing different prices for the electric storage. The system has been sized using two different demand profiles: one
from a well known building standard and a realistic one produced with a stochastic generator and calibrated on a
measured aggregated demand profile. Using the realistic curve the coverage of the electric demand of the optimized
configuration goes beyond 20%.
Economic Validation of Large Power PV Irrigation Systems
Creators: name: Almeida, R.H.
name: Barata Carrêlo, I.A.
name: Lorenzo, C.
name: Narvarte Fernández, L.
Publisher: name: WIP
Year: 2018
Subjects: PV Systems - Performance, Applications and Integration
Design and Installation of PV Systems

description: 35th European Photovoltaic Solar Energy Conference and Exhibition; 1652-1655
description: This paper presents an economic evaluation of large-power PV irrigation systems (from 40 to 360 kWp) installed in Mediterranean countries, evaluating the economic feasibility of substituting or reducing their current energy sources (diesel or electrical grid) with a Photovoltaic (PV) generator and also an economic assessment based on PVIS simulated for ECOWAS region is also presented.
In the first case, five PV irrigation systems, operating in Portugal, Spain, Italy and Morocco were considered and two energetic scenarios were created in order to do the economic analysis (Optimistic and Pessimistic Scenario). The normalized Net Present Value (NPV) values are in the 2.3-3.8 €/Wp range, Internal Rate of Return (IRR) values are in the 10-16% range and Payback Period (PBP) values are in the 7-11 years range. Finally, the Levelized Cost of Energy (LCOE) values for PV irrigation systems the values are in the 0.05-0.20 €/kWh range, which represents a percentage reduction of 34-67% % if compared to the actualized cost of the previous energy source.
Regarding the second case, seven countries from the ECOWAS region were considered and two irrigation operating modes were compared (pumping to a water tank or at constant pressure). NPV values are in the 0.28-35.2x105 € range, (IRR) values are in the 8-47% range and (PBP) values are in the 2.1-10 years range. LCOE for PV irrigation systems are in the 0.04-0.15 €/kWh range, which represent percentage savings of 30-84% if compared to diesel-powered and grid-powered systems.
Exploring the metabolic features of purple non-sulfur bacteria for waste carbon utilization and single-cell protein synthesis
Creators: name: Rashid, Naim
name: Onwusogh, Udeogu
name: Mackey, Hamish R.
Publisher: name: Manara - Qatar Research Repository
Year: 2022
Subjects: subject: Environmental engineering
subject: FOS: Environmental engineering

description: In recent years, single-cell protein (SCP) has been considered a promising aquaculture feed to cope with the growing issue of food security. SCP is derived from microbes including algae, yeasts, and bacteria. Algae and yeasts have been comprehensively studied as SCP sources in the last few years. However, their large-scale application is not yet economical. Recently, the use of purple non-sulfur bacteria (PNSB) has been realized as a sustainable source of SCP. PNSB display unique metabolic features that distinguish them from other SCP sources. They can grow under various light and electron donor/acceptor conditions, can use a variety of low-cost carbon sources, give high substrate yield under their preferred photoheterotrophic growth mode, and demonstrate anti-pathogenic properties. They also use the infrared region of light that enables their straightforward enrichment under non-axenic conditions. Despite the unique characteristics of PNSB, their use as SCP has not been widely reported. This review provides comprehensive knowledge about different factors that influence the quality and quantity of SCP produced from PNSB. The effects of key factors including light, redox conditions, trace metals, carbon substrate, and substrate availability are discussed. Special focus is given to the use of PNSB as SCP in aquaculture and PNSBs concomitant role in improving water quality. This information would expand knowledge and enhance understanding to utilize PNSB as an alternative SCP source for aquaculture feed.Other Information Published in: Biomass Conversion and Biorefinery
 License: https://creativecommons.org/licenses/by/4.0
See article on publisher's website: http://dx.doi.org/10.1007/s13399-022-03273-8
Fully Automated Photovoltaic System Modelling for Low Cost Energy Management Applications Based on Power Measurement Data
Creators: name: Hanke, B.
name: Bottega, M.
name: Peters, D.
name: Maitanova, N.
name: Telle, J.-S.
name: Grottke, M.
name: Von Maydell, K.
name: Agert, C.
Publisher: name: WIP
Year: 2018
Subjects: PV Systems - Performance, Applications and Integration
Operation, Performance and Maintenance of PV Systems

description: 35th European Photovoltaic Solar Energy Conference and Exhibition; 1588-1593
description: Within this work an automated algorithm for the modelling of photovoltaic systems solely based on
smart meter power readings of the system is proposed assuming low cost, stationary rooftop photovoltaic systems. As
an example system, data from a nearly horizontal (7° tilt) thin film system is used for method validation. The
photovoltaic power output modelling results are compared to an individually engineered INSEL® model and a Linear
Regression (LR) Model. The resulting auto model output is discussed in the context of day ahead and intraday
photovoltaic power forecast using no-cost / low-cost irradiation information. This work presumes that the
characteristics of a photovoltaic system can be extracted from its clear sky /best system power curve. The extracted
best system curve can be used directly as a model by scaling the clear sky power output with the ratio of the radiation
to the clear sky radiation. The clear sky/best system curves are constructed by identifying the power maximum for a
given time of the day for a data set of a sample number of previous days.
The auto model is comparable to the fitted INSEL® model and the linear regression (LR). The yearly error metrics for
estimation of accuracy of the simulation, concerning 5-minute power values, are between -0.3% for the LR model,
3.7% for the INSEL® model and 4.7% for the auto model. Also the annual RMSE and MAE of the auto model (74.8
W and 27.4 W) are comparable to the LR (66.8 W and 26.2 W) and the INSEL® fit (68.1 W and 25.5 W). The auto
model operates with less input data (generated energy only) and no knowledge about the engineering, design or
surroundings of the PV system while yielding similar simulation results as conventional methods.
Calculation of expectation values of operators in the Complex Scaling method
Creators: name: Papadimitriou, G.
Publisher: name: arXiv
Year: 2015
Subjects: subject: Nuclear Theory (nucl-th)
subject: Atomic Physics (physics.atom-ph)
subject: FOS: Physical sciences

description: The complex scaling method (CSM) provides with a way to obtain resonance parameters of particle unstable states by rotating the coordinates and momenta of the original Hamiltonian. It is convenient to use an L$^2$ integrable basis to resolve the complex rotated or complex scaled Hamiltonian H$_θ$, with $θ$ being the angle of rotation in the complex energy plane. Within the CSM, resonance and scattering solutions do not exhibit an outgoing or scattering wave asymptotic behavior, but rather have decaying asymptotics. One of the consequences is that, expectation values of operators in a resonance or scattering complex scaled solution are calculated by complex rotating the operators. In this work we are exploring applications of the CSM on calculations of expectation values of quantum mechanical operators by retrieving the Gamow asymptotic character of the decaying state and calculating hence the expectation value using the unrotated operator. The test cases involve a schematic two-body Gaussian model and also applications using realistic interactions.
description: 13 pages, 10 figures
Is the corporate elite disintegrating? Interlock boards and the Mizruchi hypothesis
Creators: name: Mentzer, Kevin
name: Dudouet, Francois-Xavier
name: Haughton, Dominique
name: Latouche, Pierre
name: Rossi, Fabrice
Publisher: name: arXiv
Year: 2016
Subjects: subject: Physics and Society (physics.soc-ph)
subject: FOS: Physical sciences

description: This paper proposes an approach for comparing interlocked board networks over time to test for statistically significant change. In addition to contributing to the conversation about whether the Mizruchi hypothesis (that a disintegration of power is occurring within the corporate elite) holds or not, we propose novel methods to handle a longitudinal investigation of a series of social networks where the nodes undergo a few modifications at each time point. Methodologically, our contribution is twofold: we extend a Bayesian model hereto applied to compare two time periods to a longer time period, and we define and employ the concept of a hull of a sequence of social networks, which makes it possible to circumvent the problem of changing nodes over time.
A More Accurate Machine Learning Photovoltaic System Performance Analyser by Using Fuzzy Logic
Creators: name: Rodrigues, S.
name: Carvalho, J.P.
name: Geirinhas Ramos, H.
name: Morgado-Dias, F.
Publisher: name: WIP
Year: 2018
Subjects: PV Systems - Performance, Applications and Integration
Operation, Performance and Maintenance of PV Systems

description: 35th European Photovoltaic Solar Energy Conference and Exhibition; 1594-1604
description: Machine Learning Techniques (MLTs) deal well with the non-linear behaviour of the Photovoltaic systems and therefore are ideal to be used in Photovoltaic System Performance and Fault Analysis. The annual historical data of a roof-top Photovoltaic system located in Portugal in years 2015 and 2016 were used to train and test five different MLT prediction models such as the Regression Trees, Artificial Neural Networks, Multi-Gene Genetic Programming, Gaussian Process and Support Vector Machines for Regression. The aim of this work is to determine which MLT provides the most accurate prediction output results of the daily AC solar energy based on the solar irradiation inputs. An experimental setup including three experiments and 12 different scenarios was designed to achieve the aim of this work. Each scenario is associated to a season of the year in order to break down the complexity of the prediction model training. The first and second experiments simply compare various MLTs, but the third experiment describes a novel methodology that provides very accurate MLT estimate results, by means of a Hybrid Machine Learning and Computational Intelligence System that combines a Takagi-Sugeno type Fuzzy Logic Inference System with the various MLTs.
A spectroscopic study of the Globular Cluster NGC 4147
Creators: name: Villanova, Sandro
name: MOnaco, Lorenzo
name: Bidin, Cristian Moni
name: Assmann, Paulina
Publisher: name: arXiv
Year: 2016
Subjects: subject: Solar and Stellar Astrophysics (astro-ph.SR)
subject: Astrophysics of Galaxies (astro-ph.GA)
subject: FOS: Physical sciences

description: We present the abundance analysis for a sample of 18 red giant branch stars in the metal-poor globular cluster NGC 4147 based on medium and high resolution spectra. This is the first extensive spectroscopic study of this cluster. We derive abundances of C, N, O, Na, Mg, Al, Si, Ca, Ti, Cr, Fe, Ni, Y, Ba, and Eu. We find a metallicity of [Fe/H]=-1.84+-0.02 and an alpha-enhancement of +0.38+-0.05 (errors on the mean), typical of halo globular clusters in this metallicity regime. A significant spread is observed in the abundances of light elements C, N, O, Na, and Al. In particular we found a Na-O anti-correlation and Na-Al correlation. The cluster contains only 15% of stars that belong to the first generation (Na-poor and O-rich). This implies that it suffered a severe mass loss during its lifetime. Its [Ca/Fe] and [Ti/Fe] mean values agree better with the Galactic Halo trend than with the trend of extragalactic environments at the cluster metallicity. This possibly suggests that NGC 4147 is a genuine Galactic object at odd with what claimed by some author that proposed the cluster to be member of the Sagittarius dwarf galaxy. A anti-relation between the light s-process element Y and Na may also be present.
description: 10 pages, 12 figures, accepted for publication on MNRAS
Dynamical mechanism of fusion hindrance in heavy ion collisions
Creators: name: Amano, S.
name: Aritomo, Y.
name: Ohta, M.
Publisher: name: arXiv
Year: 2023
Subjects: subject: Nuclear Theory (nucl-th)
subject: FOS: Physical sciences

description: In the fusion process, the investigation of the reaction dynamics in the time evolution of the nuclear configuration is necessary. The neck parameter $ε$ which is one of the parameters representing the nuclear configuration in the two center shell model is important in fusion owing to the nucleons transferring through the neck. The time evolution of the neck has not been discussed in detail, but is crucial for fusion cross section in the assessment of new elements synthesis. The dynamical analysis for the fusion hindrance under the neck formation on the nuclear deformation space has been done. The fusion probability $P_\text{CN}$ considering the different denecking motion and the fusion hindrance are discussed. The calculations were performed using the dynamical model of nucleus-nucleus collisions based on the multidimensional Langevin equations.The formation of the neck bridge at the approaching stage is found to be crucial to the fusion hindrance. It is clarified that the inner barrier appears owing to the change in the degree of mass asymmetry $α$ with the relaxation of $ε$.The fusion hindrance occurs because the inner barrier is formed by the early neck formation. The role of the neck parameter $ε$ is critically important for the fusion dynamics.
description: 9 pages, 9 figures
Dynamic simulation of lead(II) metal adsorption from water on activated carbons in a packed-bed column
Creators: name: Hameed, Areeba
name: Hameed, Bassim H.
name: Almomani, Fares A.
name: Usman, Muhammad
name: Ba-Abbad, Muneer M.
name: Khraisheh, Majeda
Publisher: name: Manara - Qatar Research Repository
Year: 2022
Subjects: subject: Environmental engineering
subject: FOS: Environmental engineering

description: In this work, lead(II) adsorption on activated carbons, tire-derived activated carbon (TAC), and commercial activated carbon (CAC), in a packed-bed column, was simulated using the Aspen Adsorption® V11 flowsheet simulator. The simulator was used to model the fixed-bed adsorption column and to establish the breakthrough curves by varying the initial concentration of lead(II) ions (500 mg/L, 1000 mg/L, 2000 mg/L, and 3000 mg/L), the bed height (0.2 m, 0.3 m, 0.4 m, 0.5 m, and 0.6 m), and the flow rate (9.88 × 10−4 m3/s, 1.98 × 10−3 m3/s, 2.96 × 10−3 m3/s, 3.95 × 10−3 m3/s, and 4.94 × 10−3 m3/s), at constant temperature and pressure of 25 °C and 3 bar, respectively. At the optimum conditions of 500 mg/L lead(II) concentration, 0.6 m bed height, and 9.88 × 10−4 m3/s flow rate, the breakthrough times were 488 s and 23 s for TAC and CAC, respectively. Under the same conditions, the adsorption capacity obtained at t0.5 was 114.26 mg/g for TAC and 7.72 mg/g for CAC. The simulation results indicate the potential of TAC for the adsorption of lead(II) in comparison to CAC.Other Information Published in: Biomass Conversion and Biorefinery
 License: https://creativecommons.org/licenses/by/4.0
See article on publisher's website: http://dx.doi.org/10.1007/s13399-022-03079-8
Introducing ‘PEARL PV’: Performance and Reliability of Photovoltaic Systems - Evaluations of Large-Scale Monitoring Data
Creators: name: Reinders, A.H.M.E.
name: Moser, D.
name: Van Sark, W.G.J.H.M.
name: Oreski, G.
name: Pearsall, N.M.
name: Scognamiglio, A.
name: Leloux, J.
Publisher: name: WIP
Year: 2018
Subjects: PV Systems - Performance, Applications and Integration
Operation, Performance and Maintenance of PV Systems

description: 35th European Photovoltaic Solar Energy Conference and Exhibition; 1581-1587
description: This paper will introduce a recently initiated COST Action titled PEARL PV and show its 4-year research and work plan with the aim to create exposure, receive feedback from various stakeholders and involve new participants to this research network. The aim is i) to improve the energy performance and reliability of photovoltaic (PV) solar energy systems in Europe leading to lower costs of electricity produced by PV systems by a higher energy yield, ii) a longer life time eventually beyond the guaranteed 20 years as specified by manufacturers, and iii) a reduction in the perceived risk in investments in PV projects. This objective will be achieved by analyzing big data of the actual monitored long-term performance, defects and failures in PV systems installed all over Europe to quantitatively determine the absolute influences of components rated performance, key design of systems, installation, operation, maintenance practice, geographic location and weather factors on the performance, performance degradation over time and failure modes of these PV systems. The PEARL PV project aims at the formation of an inclusive network of PV system researchers, data resources that will be analyzed by researchers and experts that can include more-nuanced evidence-based reliability in PV system evaluation methods and simulation and design tools. The COST Action PEARL PV assembles an inclusive partnership network of PV system researchers with experience with PV monitoring and simulation, with solar resources, and with PV operators who collectively bring together their ongoing work to contribute to the collation, analysis and interpretation of an agglomeration of PV system performance data in Europe.
A statistical learning strategy for closed-loop control of fluid flows
Creators: name: Guéniat, Florimond
name: Mathelin, Lionel
name: Hussaini, M. Yousuff
Publisher: name: arXiv
Year: 2016
Subjects: subject: Machine Learning (stat.ML)
subject: Optimization and Control (math.OC)
subject: Fluid Dynamics (physics.flu-dyn)
subject: FOS: Computer and information sciences
subject: FOS: Mathematics
subject: FOS: Physical sciences

description: This work discusses a closed-loop control strategy for complex systems utilizing scarce and streaming data. A discrete embedding space is first built using hash functions applied to the sensor measurements from which a Markov process model is derived, approximating the complex system's dynamics. A control strategy is then learned using reinforcement learning once rewards relevant with respect to the control objective are identified. This method is designed for experimental configurations, requiring no computations nor prior knowledge of the system, and enjoys intrinsic robustness. It is illustrated on two systems: the control of the transitions of a Lorenz 63 dynamical system, and the control of the drag of a cylinder flow. The method is shown to perform well.