scholarly journals Electrical Generation of a Ground-Level Solar Thermoelectric Generator: Experimental Tests and One-Year Cycle Simulation

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3407
Author(s):  
Eduard Massaguer ◽  
Albert Massaguer ◽  
Eudald Balló ◽  
Ivan Ruiz Cózar ◽  
Toni Pujol ◽  
...  
Keyword(s):  
Output Power ◽  
Thermoelectric Generator ◽  
Experimental Tests ◽  
Ground Level ◽  
Weather Conditions ◽  
Energy Generation ◽  
Atmospheric Conditions ◽  
Cycle Simulation ◽  
One Year ◽  
Electrical Generation

Solar thermoelectric generators (STEGs) are a promising technology to harvest energy for off-grid applications. A wide variety of STEG designs have been proposed with the aim of providing non-intermittent electrical generation. Here, we designed and tested a STEG 0.5 m long formed by nine commercial thermoelectric generator modules and located at ground level. Data were used to validate a numerical model that was employed to simulate a one-year cycle. Results confirmed the very high variability of energy generation during daylight time due to weather conditions. By contrast, energy generation during night was almost independent of atmospheric conditions. Annual variations of nighttime energy generation followed the trend of the daily averaged soil temperature at the bottom of the device. Nighttime electrical energy generation was 5.4 times smaller than the diurnal one in yearly averaged values. Mean energy generation values per day were 587 J d−1 (daylight time) and 110 J d−1 (nighttime). Total annual energy generation was 255 kJ. Mean electrical output power values during daylight and nighttime were 13.4 mW and 2.5 mW, respectively. Annual mean output power was 7.9 mW with a peak value of 79.8 mW.

scholarly journals An Improved Whale Algorithm for Support Vector Machine Prediction of Photovoltaic Power Generation

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 212
Author(s):  
Yu-Wei Liu ◽  
Huan Feng ◽  
Heng-Yi Li ◽  
Ling-Ling Li
Keyword(s):  
Support Vector Machine ◽  
Prediction Model ◽  
Output Power ◽  
Input Data ◽  
Support Vector Machine Model ◽  
Weather Conditions ◽  
Clean Energy ◽  
Support Vector ◽  
Machine Model ◽  
Photovoltaic Power

Accurate prediction of photovoltaic power is conducive to the application of clean energy and sustainable development. An improved whale algorithm is proposed to optimize the Support Vector Machine model. The characteristic of the model is that it needs less training data to symmetrically adapt to the prediction conditions of different weather, and has high prediction accuracy in different weather conditions. This study aims to (1) select light intensity, ambient temperature and relative humidity, which are strictly related to photovoltaic output power as the input data; (2) apply wavelet soft threshold denoising to preprocess input data to reduce the noise contained in input data to symmetrically enhance the adaptability of the prediction model in different weather conditions; (3) improve the whale algorithm by using tent chaotic mapping, nonlinear disturbance and differential evolution algorithm; (4) apply the improved whale algorithm to optimize the Support Vector Machine model in order to improve the prediction accuracy of the prediction model. The experiment proves that the short-term prediction model of photovoltaic power based on symmetry concept achieves ideal accuracy in different weather. The systematic method for output power prediction of renewable energy is conductive to reducing the workload of predicting the output power and to promoting the application of clean energy and sustainable development.

scholarly journals Influence of Meteorological Conditions and Aerosol Properties on the COVID-19 Contamination of the Population in Coastal and Continental Areas in France: Study of Offshore and Onshore Winds

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 523
Author(s):  
Jacques Piazzola ◽  
William Bruch ◽  
Christelle Desnues ◽  
Philippe Parent ◽  
Christophe Yohia ◽  
...  
Keyword(s):  
Atmospheric Transport ◽  
Weather Conditions ◽  
Meteorological Conditions ◽  
Sea Spray ◽  
Atmospheric Conditions ◽  
Virus Transport ◽  
Virus Propagation ◽  
Viral Particles ◽  
The Social ◽  
Aerosol Properties

Human behaviors probably represent the most important causes of the SARS-Cov-2 virus propagation. However, the role of virus transport by aerosols—and therefore the influence of atmospheric conditions (temperature, humidity, type and concentration of aerosols)—on the spread of the epidemic remains an open and still debated question. This work aims to study whether or not the meteorological conditions related to the different aerosol properties in continental and coastal urbanized areas might influence the atmospheric transport of the SARS-Cov-2 virus. Our analysis focuses on the lockdown period to reduce the differences in the social behavior and highlight those of the weather conditions. As an example, we investigated the contamination cases during March 2020 in two specific French areas located in both continental and coastal areas with regard to the meteorological conditions and the corresponding aerosol properties, the optical depth (AOD) and the Angstrom exponent provided by the AERONET network. The results show that the analysis of aerosol ground-based data can be of interest to assess a virus survey. We found that moderate to strong onshore winds occurring in coastal regions and inducing humid environment and large sea-spray production episodes coincides with smaller COVID-19 contamination rates. We assume that the coagulation of SARS-Cov-2 viral particles with hygroscopic salty sea-spray aerosols might tend to inhibit its viral infectivity via possible reaction with NaCl, especially in high relative humidity environments typical of maritime sites.

The influence of weather conditions on mid-field ponds situated in a reclaimed area in Sępopolska Plain

2010 ◽  
Vol 39 (1) ◽  
Author(s):  
Ireneusz Cymes ◽  
Iwona Cymes ◽  
Ewa Dragańska ◽  
Sławomir Szymczyk
Keyword(s):  
Weather Conditions ◽  
Negative Influence ◽  
Ammonium Nitrogen ◽  
Water Evaporation ◽  
Atmospheric Conditions ◽  
Natural Reservoir ◽  
Quality Of Water ◽  
Water Ph ◽  
Chlorine Ions ◽  
Agricultural Areas

The influence of weather conditions on mid-field ponds situated in a reclaimed area in Sępopolska PlainThe investigations were conducted in northeastern Poland near Lidzbark Warmiński (54° 08" N, 20° 36" E). Five mid-field ponds situated on grasslands were chosen: four of them were dredged and deepened, and one of them remained as a natural reservoir. The aim of this paper was to assess the influence of weather conditions on the quantity and quality of water in mid-field ponds situated in agricultural areas. It was found that the quantity of water in mid-field ponds was related much more to the air temperature, which was responsible for either water evaporation or snow melting, rather than to the amount of precipitation. The reduction in the volume of water stored in the ponds during very dry years had a negative influence on its quality. During the observation period, the dredged ponds were characterized by permanent water tables, whereas the natural reservoir dried out in very dry years. Atmospheric conditions influenced the concentrations of ammonium nitrogen and calcium and chlorine ions in the studied water bodies. The volume of water retained in mid-field ponds influenced the concentrations of phosphorus and sulphates. Increased precipitation sums caused lower water pH; however in warmer periods, at increased pH and COD

scholarly journals Exploring the relation between aerosol optical depth and PM<sub>2.5</sub> at Cabauw, the Netherlands

2008 ◽  
Vol 8 (5) ◽  
pp. 17939-17986 ◽  
Author(s):  
M. Schaap ◽  
A. Apituley ◽  
R. M. A. Timmermans ◽  
R. B. A. Koelemeijer ◽  
G. de Leeuw
Keyword(s):  
The Netherlands ◽  
Ground Level ◽  
Weather Conditions ◽  
Fair Weather ◽  
Modis Aod ◽  
Data Points ◽  
Set Up ◽  
The Relationship ◽  
Lidar Observations ◽  
Pm2.5 Concentration

Abstract. To acquire daily estimates of PM2.5 distributions based on satellite data one depends critically on an established relation between AOD and ground level PM2.5. In this study we aimed to experimentally establish the AOD-PM2.5 relationship for the Netherlands. For that purpose an experiment was set-up at the AERONET site Cabauw. The average PM2.5 concentration during this ten month study was 18 μg/m3, which confirms that the Netherlands are characterised by a high PM burden. A first inspection of the AERONET level 1.5 (L1.5) AOD and PM2.5 data at Cabauw showed a low correlation between the two properties. However, after screening for cloud contamination in the AERONET L1.5 data, the correlation improved substantially. When also constraining the dataset to data points acquired around noon, the correlation between AOD and PM2.5 amounted to R2=0.6 for situations with fair weather. This indicates that AOD data contain information about the temporal evolution of PM2.5. We had used LIDAR observations to detect residual cloud contamination in the AERONET L1.5 data. Comparison of our cloud-screed L1.5 with AERONET L2 data that became available near the end of the study showed favorable agreement. The final relation found for Cabauw is PM2.5=124.5*AOD–0.34 (with PM2.5 in μg/m3) and is valid for fair weather conditions. The relationship determined between MODIS AOD and ground level PM2.5 at Cabauw is very similar to that based on the much larger dataset from the sun photometer data, after correcting for a systematic overestimation of the MODIS data of 0.05. We applied the relationship to a MODIS composite map to assess the PM2.5 distribution over the Netherlands. Spatial dependent systematic errors in the MODIS AOD, probably related to variability in surface reflectance, hamper a meaningful analysis of the spatial distribution of PM2.5 using AOD data at the scale of the Netherlands.

scholarly journals PEMANFAATAN DATA SATELIT HIMAWARI-8 SERTA DATA CURAH HUJAN DAN HARI HUJAN BULANAN DALAM ANALISIS KEJADIAN BANJIR KOTA PADANG, 9 SEPTEMBER 2017 DAN 26 SEPTEMBER 2018

2019 ◽  
Vol 3 ◽  
pp. 264
Author(s):  
Vinca Amalia Rizkiafama ◽  
Tesla Kadar Dzikiro ◽  
Agus Safril
Keyword(s):  
Satellite Data ◽  
Atmospheric Stability ◽  
Convective Cloud ◽  
Atmospheric Conditions ◽  
Flood Events ◽  
Growth Activity ◽  
One Year ◽  
Almost All ◽  
The City ◽  
Rainy Days

<p class="AbstractEnglish"><strong>Abstract:</strong> Flood events on Wednesday, September 26, 2018, in several sub-districts in the city of Padang showed different conditions with the Indonesian region in general which were in normal to drier conditions. One year earlier, precisely on September 9, 2017, there were floods in almost all areas of the city of Padang. This study aims to determine the atmospheric conditions during flood events from the climatological and meteorological side. The data used are monthly rainfall and a monthly number of Rainy Days (HH) from 1981-2018 from the Minangkabau Meteorological Station, as well as Himawari-8 Weather Satellite data. Satellite data is processed using Satellite Animation and Interactive Diagnosis (SATAID) software to obtain cloud cover analysis, cloud growth activities, and atmospheric lability levels. September 2017 and September 2018 are in the nature of normal rain with a percentage of 101% and 88%. The increase in the amount of rainfall in August 2017 to September 2017 is not significant at 27 mm compared to August 2018 to September 2018 which is significant at 148 mm. The number of rainy days in September 2017 and 2018 were 24 and 23 respectively, which showed that almost every day there was rain in those months. The meteorological analysis shows that there is convective cloud growth activity in the Padang area which is characterized by an unstable level of atmospheric stability which has the potential for moderate to heavy rainfall.</p><p class="KeywordsEngish"><strong>Abstrak:</strong> Kejadian banjir pada Rabu, 26 September 2018 di beberapa kecamatan di Kota Padang menunjukkan kondisi yang berlainan dengan wilayah Indonesia pada umumnya yang berada dalam kondisi normal hingga lebih kering. Satu tahun sebelumnya, tepatnya pada 9 September 2017 juga terjadi banjir hampir di seluruh wilayah Kota Padang. Penelitian ini bertujuan untuk mengetahui kondisi atmosfer pada saat kejadian banjir dari sisi klimatologis dan meteorologisnya. Data yang digunakan adalah curah hujan bulanan dan jumlah Hari Hujan (HH) bulanan dari tahun 1981-2018 dari Stasiun Meteorologi Minangkabau, serta data Satelit Cuaca Himawari-8. Data satelit diolah menggunakan piranti lunak Satellite Animation and Interactive Diagnosis (SATAID) untuk mendapatkan analisis tutupan awan, aktivitas pertumbuhan awannya, dan tingkat labilitas atmosfer. September 2017 dan September 2018 berada pada sifat hujan normal dengan presentase 101% dan 88%. Peningkatan jumlah curah hujan bulan Agustus 2017 ke September 2017 tidak signifikan yaitu sebesar 27 mm dibandingkan Agustus 2018 ke September 2018 yang signifikan yaitu sebesar 148 mm. Jumlah hari hujan di bulan September 2017 dan 2018 berturut-turut sebesar 24 dan 23 yang menunjukkan bahwa hampir setiap hari terjadi hujan di bulan-bulan tersebut. Analisis secara meteorologis menunjukkan bahwa terdapat aktivitas pertumbuhan awan konvektif di daerah Padang yang ditandai dengan tingkat stabilitas atmosfer yang labil sehingga berpotensi terjadinya hujan sedang hingga lebat.</p>

scholarly journals Meteorology in field artillery ballistic calculations

2021 ◽  
Vol 2090 (1) ◽  
pp. 012149
Author(s):  
M Mendel
Keyword(s):  
Atmospheric Pressure ◽  
Open Space ◽  
Meteorological Parameters ◽  
Meteorological Data ◽  
Armed Forces ◽  
Weather Conditions ◽  
Atmospheric Conditions ◽  
Area Of Interest ◽  
Single Probe ◽  
Atmospheric Data

Abstract The most important meteorological data are:ambient temperature, precipitation quantity, air humidity, amount and type of clouds, atmospheric pressure, wind direction and speed, visibility, weather phenomena. These coefficients impact the effectiveness of various combat activities, especially those conducted in an open space. Knowledge of future weather conditions is essential for planning the location, calculating times, choice of means, and other aspects relevant to the upcoming operations. Taking weather conditions into account is vital, specifically when it comes to planning combat operations, where the accuracy in cooperation is of paramount importance. Rocket forces and artillery is a particular type of armed forces where weather conditions are critical. The effectiveness of artillery depends on ballistic calculation precision, and so knowledge of atmospheric conditions is fundamental. Atmospheric data are collected from sounding using a single probe attached to a balloon. It is generally known that particular meteorological parameters change in a smooth spatial manner depending on various coefficients. Information about the atmosphere collected by a single probe may be insufficient, due to the possibility of a balloon drifting away from the area of interest, and the calculations are based on data received from its probe. In this paper, I will suggest a method for preparing artillery use meteorologically, which takes into account the distribution of particular meteorological coefficients over a given area.

scholarly journals CREATING MULTI-TEMPORAL MAPS OF URBAN ENVIRONMENTS FOR IMPROVED LOCALIZATION OF AUTONOMOUS VEHICLES

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 317-323
Author(s):  
J. Schachtschneider ◽  
C. Brenner
Keyword(s):  
Urban Areas ◽  
Autonomous Vehicles ◽  
Weather Conditions ◽  
Point Clouds ◽  
Urban Environments ◽  
Seasonal Effects ◽  
Data Set ◽  
Multi Temporal ◽  
One Year

Abstract. The development of automated and autonomous vehicles requires highly accurate long-term maps of the environment. Urban areas contain a large number of dynamic objects which change over time. Since a permanent observation of the environment is impossible and there will always be a first time visit of an unknown or changed area, a map of an urban environment needs to model such dynamics.In this work, we use LiDAR point clouds from a large long term measurement campaign to investigate temporal changes. The data set was recorded along a 20 km route in Hannover, Germany with a Mobile Mapping System over a period of one year in bi-weekly measurements. The data set covers a variety of different urban objects and areas, weather conditions and seasons. Based on this data set, we show how scene and seasonal effects influence the measurement likelihood, and that multi-temporal maps lead to the best positioning results.

scholarly journals Mapping users' expectations regarding extended-range forecasts

2018 ◽  
Vol 15 ◽  
pp. 99-106 ◽  
Author(s):  
Tiina Ervasti ◽  
Hilppa Gregow ◽  
Andrea Vajda ◽  
Terhi K. Laurila ◽  
Antti Mäkelä
Keyword(s):  
Everyday Life ◽  
Design Process ◽  
General Public ◽  
Online Survey ◽  
Weather Conditions ◽  
The Everyday ◽  
Extended Range ◽  
One Year ◽  
Weather Risks ◽  
Range Forecasts

Abstract. An online survey was used to map the needs and preferences of the Finnish general public concerning extended-range forecasts and their presentation. First analyses of the survey were used to guide the co-design process of novel extended-range forecasts to be developed and tested during the project. In addition, the survey was used to engage the respondents from the general public to participate in a one year piloting phase that started in June 2017. The respondents considered that the tailored extended-range forecasts would be beneficial in planning activities, preparing for the weather risks and scheduling the everyday life. The respondents also perceived the information about the impacts of weather conditions more important than advice on how to prepare for the impacts.

scholarly journals Correlations between weather parameters, atmospheric hydrogen sulphide level and vitamin B12 administration to H2S exposed workers

2019 ◽  
Vol 70 (1) ◽  
pp. 6-11
Author(s):  
Livia-Cristina Borcan ◽  
Florin Borcan ◽  
Elena-Ana Păuncu ◽  
Mirela Cleopatra Tomescu
Keyword(s):  
Blood Pressure ◽  
Vitamin B12 ◽  
Hydrogen Sulphide ◽  
Prolonged Exposure ◽  
Numerical Data ◽  
Weather Conditions ◽  
Professional Exposure ◽  
Exposed Workers ◽  
Weather Parameters ◽  
One Year

Abstract Hydrogen sulphide, a highly toxic gas, can be used in crenotherapy to balance all metabolic processes (minerals, fats and proteins). The main aims of this study were to correlate the weather characteristics with the atmospheric H2S level and to evaluate the antidote activity of B12 Vitamin in the case of prolonged exposure to this compound. 46 volunteers, people from the medical staff of an important Romanian thermal water spring spa, with professional exposure at H2S, were enrolled in this study; numerical data about their blood pressure, atmospheric H2S concentration and about the weather conditions were collected every month for one year. The results indicate an improvement in the blood pressure of volunteers treated with Vitamin B12; no significant correlation between the concentration of total urinary sulphur and the concentration of atmospheric H2S level was found.

scholarly journals Forecasting and Modelling of Solar Radiation for Photovoltaic (PV) Systems

2021 ◽  
Author(s):  
Ines Sansa ◽  
Najiba Mrabet Bellaaj
Keyword(s):  
Time Series ◽  
Solar Radiation ◽  
Cloud Cover ◽  
Moving Average ◽  
Arma Model ◽  
Weather Conditions ◽  
Pv Systems ◽  
Auto Regressive ◽  
Micro Grid ◽  
One Year

Solar radiation is characterized by its fluctuation because it depends to different factors such as the day hour, the speed wind, the cloud cover and some other weather conditions. Certainly, this fluctuation can affect the PV power production and then its integration on the electrical micro grid. An accurate forecasting of solar radiation is so important to avoid these problems. In this chapter, the solar radiation is treated as time series and it is predicted using the Auto Regressive and Moving Average (ARMA) model. Based on the solar radiation forecasting results, the photovoltaic (PV) power is then forecasted. The choice of ARMA model has been carried out in order to exploit its own strength. This model is characterized by its flexibility and its ability to extract the useful statistical properties, for time series predictions, it is among the most used models. In this work, ARMA model is used to forecast the solar radiation one year in advance considering the weekly radiation averages. Simulation results have proven the effectiveness of ARMA model to forecast the small solar radiation fluctuations.

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