scholarly journals Performance Investigation of Tempered Glass-Based Monocrystalline and Polycrystalline Solar Photovoltaic Panels

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Mardy Huot ◽  
Laveet Kumar ◽  
Jeyraj Selvaraj ◽  
Md Hasanuzzaman ◽  
Nasrudin Abd Rahim
Keyword(s):  
Real Time ◽  
Solar Irradiance ◽  
Weather Conditions ◽  
Ethylene Vinyl Acetate ◽  
Operating Conditions ◽  
Electrical Performance ◽  
Solar Photovoltaic ◽  
Tempered Glass ◽  
Time Data ◽  
Pv Panel

Solar photovoltaic (PV) converts sunlight into electricity and is an appropriate alternative to overcome the depletion of conventional fuels and global warming issues. The performance of a PV panel may vary with respect to PV cell technology, fabrication methods, and operating conditions. This research aims at performing an experimental study to investigate the electrical performance of novel tempered glass-based PV panels using two different types of solar cells: monocrystalline and polycrystalline. Tempered glass-based panels are modified forms of commercial PV panels, in which ethylene-vinyl acetate (EVA) and Tedlar are not utilized. This new fabrication method was carried out in this research. Real-time data recordings regarding the PV electrical characteristics ( I - V curve) and solar irradiance were conducted under Malaysian weather conditions on clear sunny days. Results indicated that, at solar irradiance of 900 W/m2, the outputs from the fabricated polycrystalline and monocrystalline PV panels were 67.4 W and 75.67 W, respectively. However, at the highest average solar irradiance (634.61 W/m2), which was obtained at 12:30 PM, the outputs from both panels were 47.87 W and 54.89 W. An I - V curve was obtained for the real-time weather. The electrical efficiencies of the two PV panels were analyzed to be 10.54% and 12.23%.

Real-Time Thermodynamic Performance Monitoring and Optimum Thermoeconomic Operation of Power Plants

2011 ◽  
Author(s):  
G. Hariharan ◽  
B. Kosanovic
Keyword(s):  
Linear Programming ◽  
Power Plant ◽  
Real Time ◽  
Power Plants ◽  
Operating Conditions ◽  
Recursive Least Squares ◽  
Time Data ◽  
Real Time Data ◽  
One Step ◽  
Inputs And Outputs

The ability of modern power plant data acquisition systems to provide a continuous real-time data feed can be exploited to carry out interesting research studies. In the first part of this study, real-time data from a power plant is used to carry out a comprehensive heat balance calculation. The calculation involves application of the first law of thermodynamics to each powerhouse component. Stoichiometric combustion principles are applied to calculate emissions from fossil fuel consuming components. Exergy analysis is carried out for all components by the combined application of the first and second laws of thermodynamics. In the second part of this study, techniques from the field of System Identification and Linear Programming are brought together in finding thermoeconomically optimum plant operating conditions one step ahead in time. This is done by first using autoregressive models to make short-term predictions of plant inputs and outputs. Then, parameter estimation using recursive least squares is used to determine the relations between the predicted inputs and outputs. The estimated parameters are used in setting up a linear programming problem which is solved using the simplex method. The end result is knowledge of thermoeconomically optimum plant inputs and outputs one step ahead in time.

scholarly journals How Can Existing Ground-Based Profiling Instruments Improve European Weather Forecasts?

2019 ◽  
Vol 100 (4) ◽  
pp. 605-619 ◽  
Author(s):  
A. J. Illingworth ◽  
D. Cimini ◽  
A. Haefele ◽  
M. Haeffelin ◽  
M. Hervo ◽  
...  
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Positive Impact ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Time Data ◽  
Weather Forecasts ◽  
Forecast Models ◽  
Wind Lidar ◽  
Microwave Radiometers

Abstract To realize the promise of improved predictions of hazardous weather such as flash floods, wind storms, fog, and poor air quality from high-resolution mesoscale models, the forecast models must be initialized with an accurate representation of the current state of the atmosphere, but the lowest few kilometers are hardly accessible by satellite, especially in dynamically active conditions. We report on recent European developments in the exploitation of existing ground-based profiling instruments so that they are networked and able to send data in real time to forecast centers. The three classes of instruments are i) automatic lidars and ceilometers providing backscatter profiles of clouds, aerosols, dust, fog, and volcanic ash, the last two being especially important for air traffic control; ii) Doppler wind lidars deriving profiles of wind, turbulence, wind shear, wind gusts, and low-level jets; and iii) microwave radiometers estimating profiles of temperature and humidity in nearly all weather conditions. The project includes collaboration from 22 European countries and 15 European national weather services, which involves the implementation of common operating procedures, instrument calibrations, data formats, and retrieval algorithms. Currently, data from 265 ceilometers in 19 countries are being distributed in near–real time to national weather forecast centers; this should soon rise to many hundreds. One wind lidar is currently delivering real time data rising to 5 by the end of 2019, and the plan is to incorporate radiometers in 2020. Initial data assimilation tests indicate a positive impact of the new data.

scholarly journals Construction worker productivity in hot and humid weather conditions

2019 ◽  
Vol 27 (1) ◽  
pp. 83-108
Author(s):  
Ammar Saeed Mohammed Moohialdin ◽  
Fiona Lamari ◽  
Marc Miska ◽  
Bambang Trigunarsyah
Keyword(s):  
Real Time ◽  
Construction Industry ◽  
Productivity Loss ◽  
Weather Conditions ◽  
Research Field ◽  
Future Research ◽  
Time Data ◽  
Worker Productivity ◽  
Content Type ◽  
The Impact

Purpose The purpose of this paper shows the effect of hot and humid weather conditions (HHWCs) on workers that has resulted in considerable loss in the construction industry, especially during the hottest periods due to decline in worker productivity (WP). Until the last few decades, there is very limited research on construction WP in HHWCs. Nevertheless, these studies have sparked interests on seeking for the most appropriate methods to assess the impact of HHWCs on construction workers. Design/methodology/approach This paper begins by reviewing the current measuring methods on WP in HHWCs, follows by presenting the potential impact of HHWCs on WP. The paper highlights the methodological deficiencies, which consequently provides a platform for scholars and practitioners to direct future research to resolve the significant productivity loss due to global warming. This paper highlights the need to identify the limitations and advantages of the current methods to formulate a framework of new approaches to measure the WP in HHWCs. Findings Results show that the methods used in providing real-time response on the effects of HHWCs on WP in construction at project, task and crew levels are limited. An integration of nonintrusive real-time monitoring system and local weather measurement with real-time data synchronisation and analysis is required to produce suitable information to determine worker health- and safety-related decisions in HHWCs. Originality/value The comprehensive literature review makes an original contribution to WP measurements filed in HHWCs in the construction industry. Results of this review provide researchers and practitioners with an insight into challenges associated with the measurements methods and solving practical site measurements issues. The findings will also enable the researchers and practitioners to bridge the identified research gaps in this research field and enhance the ability to provide accurate measures in HHWCs. The proposed research framework may promote potential improvements in the productivity measurements methods, which support researchers and practitioners in developing new innovative methods in HHWCs with the integration of the most recent monitoring technologies.

Test and Analysis of Exhaust Pollutants from Automobiles Based on GPS Technology

2010 ◽  
Vol 40-41 ◽  
pp. 675-681
Author(s):  
Ming Li Xian ◽  
Qing Huang Yong
Keyword(s):  
Real Time ◽  
Data Gathering ◽  
Operating Conditions ◽  
Vehicle Emission ◽  
Testing System ◽  
Time Data ◽  
Gps Technology ◽  
Urban Road ◽  
Real Time Data ◽  
Object Of Study

Taking the actual running vehicles on the urban roads of Ningpo City as the object of study, by using the brand-new on-vehicle automobile exhaust real-time testing system, and through actual testing by tracking the running vehicles and real-time data gathering, The paper analyzed urban road operating conditions, the vehicle emission situation on the actual roads, obtained the relations between the operating conditions, the speed and emissions and the law by which the automobile operating conditions affect the automobile exhausts.

scholarly journals Artificial Intelligence and Bio-Inspired Soft Computing-Based Maximum Power Plant Tracking for a Solar Photovoltaic System under Non-Uniform Solar Irradiance Shading Conditions—A Review

2021 ◽  
Vol 13 (19) ◽  
pp. 10575
Author(s):  
Amjad Ali ◽  
Kashif Irshad ◽  
Mohammad Farhan Khan ◽  
Md Moinul Hossain ◽  
Ibrahim N. A. Al-Duais ◽  
...  
Keyword(s):  
Soft Computing ◽  
Solar Irradiance ◽  
Weather Conditions ◽  
Review Article ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Flow Diagram ◽  
Maximum Output ◽  
Solar Photovoltaic ◽  
Partial Shading

Substantial progress in solar photovoltaic (SPV) dissemination in grid-connected and standalone power generation systems has been witnessed during the last two decades. However, weather intermittency has a non-linear characteristic impact on solar photovoltaic output, which can cause considerable loss in the system’s overall output. To overcome these inevitable losses and optimize the SPV output, maximum power point tracking (MPPT) is mounted in the middle of the power electronics converters and SPV to achieve the maximum output with better precision from the SPV system under intermittent weather conditions. As MPPT is considered an essential part of the SPV system, up to now, many researchers have developed numerous MPPT techniques, each with unique features. A Google Scholar survey from 2015–2021 was performed to scrutinize the number of published review papers in this area. An online search established that on different MPPT techniques, overall, 100 review articles were published; out of these 100, seven reviews on conventional MPPT techniques under shading or partial shading and only four under non-uniform solar irradiance are published. Unfortunately, no dedicated review article has explicitly focused on soft computing MPPT (SC-MPPT) techniques. Therefore, a comprehensive review of articles on SC-MPPT techniques is desirable, in which almost all the familiar SC-MPPT techniques have to be summarized in one piece. This review article concentrates explicitly on soft computing-based MPPT techniques under non-uniform irradiance conditions along with their operating principles, block/flow diagram. It will not only be helpful for academics and researchers to provide a future direction in SC-MPPT optimization research, but also help the field engineers to select the appropriate SC-MPPT for SPV according to system design and environmental conditions.

Fully Automated and Wirelessly Enabled Drillstem Tests: Seven-Zones Campaign Case Study in Sakhalin

2021 ◽  
Author(s):  
Elias Temer ◽  
Deiveindran Subramaniam
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Time Window ◽  
Weather Conditions ◽  
Testing Time ◽  
Well Testing ◽  
Well Test ◽  
Time Data ◽  
Operations Control ◽  
Bad Weather

Abstract Well test is one of the crucial steps required to forecast production investments of their fields. However, the operators face many challenges such as reduced capex, exploration budgets, and bad weather conditions that limit the well testing time window. To overcome these challenges, an automated well testing platform enabled a real time monitoring and controlling more zones in a single run for appraisal wells in the Sea of Okhotsk, Russia. This article highlights the test objectives, the job planning, and automated execution of wirelessly enabled operations in very hostile conditions and limited time period. The use of a telemetry system to well test seven zones allowed real-time data acquisition, control of critical downhole equipment, data transmission to the operator's office in town. Various operational cases will be discussed to demonstrate how automated data acquisition and downhole operations control has optimized operations for both the service company and the operator.

scholarly journals Mobile technologies for disease surveillance in humans and animals

2014 ◽  
Vol 81 (2) ◽  
Author(s):  
Mpoki Mwabukusi ◽  
Esron D. Karimuribo ◽  
Mark M. Rweyemamu ◽  
Eric Beda
Keyword(s):  
Developing Countries ◽  
Human Health ◽  
Real Time ◽  
Disease Surveillance ◽  
Open Data ◽  
Weather Conditions ◽  
Mobile Technologies ◽  
Surveillance Systems ◽  
Time Data ◽  
Real Time Data

A paper-based disease reporting system has been associated with a number of challenges. These include difficulties to submit hard copies of the disease surveillance forms because of poor road infrastructure, weather conditions or challenging terrain, particularly in the developing countries. The system demands re-entry of the data at data processing and analysis points, thus making it prone to introduction of errors during this process. All these challenges contribute to delayed acquisition, processing and response to disease events occurring in remote hard to reach areas. Our study piloted the use of mobile phones in order to transmit near to real-time data from remote districts in Tanzania (Ngorongoro and Ngara), Burundi (Muyinga) and Zambia (Kazungula and Sesheke). Two technologies namely, digital and short messaging services were used to capture and transmit disease event data in the animal and human health sectors in the study areas based on a server–client model. Smart phones running the Android operating system (minimum required version: Android 1.6), and which supported open source application, Epicollect, as well as the Open Data Kit application, were used in the study. These phones allowed collection of geo-tagged data, with the opportunity of including static and moving images related to disease events. The project supported routine disease surveillance systems in the ministries responsible for animal and human health in Burundi, Tanzania and Zambia, as well as data collection for researchers at the Sokoine University of Agriculture, Tanzania. During the project implementation period between 2011 and 2013, a total number of 1651 diseases event-related forms were submitted, which allowed reporters to include GPS coordinates and photographs related to the events captured. It was concluded that the new technology-based surveillance system is useful in providing near to real-time data, with potential for enhancing timely response in rural remote areas of Africa. We recommended adoption of the proven technologies to improve disease surveillance, particularly in the developing countries.

scholarly journals REGULATING WATER SUPPLY AND WATER CUTBACKS IN AGRICULTURE USING IOT BASED SMART IRRIGATION SYSTEM

2021 ◽  
Vol 9 (1) ◽  
pp. 629-633
Author(s):  
Prabhas Kumar Gupta, Dr. Nagendra Tripathi
Keyword(s):  
Data Analysis ◽  
Real Time ◽  
Irrigation System ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Underground Water ◽  
Contributing Factors ◽  
Time Data ◽  
Cloud Data ◽  
Real Time Data

Involvement of Machine Learning, Real-time Data Analysis and IOT are critically contributing factors in contemporary technical scenarios. Utilization of these three technologies can play a major role in the success of farming thereby modernizing the irrigation system. This paper is focused on the Smart Irrigation System which draws a lot from real-time data analysis, IOT and Machine Leaning. It also presents a study of a system that processes real time data and takes decision about to what extent the field needs to be irrigated. In this way water is saved, its misuse regulated and can be restored for future use if required. Here we rely on cloud data and some other agri-factors which help in decision making.  The Smart Irrigation System discussed here shall also regulate the use of underground water my incorporating IOT and weather forecast. The system will also contribute to effective irrigation taking in view the contemporary weather conditions and the requirement of water in the crop.

scholarly journals Optimization Of Thermal Module Solar Photovoltaic Using CFD-Simulation

2022 ◽  
Vol 961 (1) ◽  
pp. 012092
Author(s):  
Hussein M. Hamad ◽  
Soran J. Mohammed ◽  
M. F. Jabbar
Keyword(s):  
Surface Temperature ◽  
Cfd Simulation ◽  
Water System ◽  
Weather Conditions ◽  
Global Solar Radiation ◽  
Electrical Performance ◽  
Solar Photovoltaic ◽  
Constant Input ◽  
Maximum Enhancement ◽  
Mass Flowrate

Abstract Photovoltaic panels can directly generate electricity by converting solar energy, but the panels temperature reduce the efficiency of photovoltaic cells. The photovoltaic thermal PVT system technology is used to improve the electrical performance. In this study, the daily and monthly global solar radiation on a horizontal surface for Iraq have been measured and presented then used with PVT water system. ANSYS software is used to simulate the water temperature differences behavior and measure the surface temperature of PVT model using the collected irradiation with the mass flow rate at 0.01 and 0.02 kg per second. The CFID results were validated with previous studies and observed a good agreement. The simulation tests apply a constant input temperature to the PVT system in all the yearly weather conditions in order to enhance the surface temperature. The results observe the PVT thermal efficiency behavior and show the maximum enhancement which is reached to 61% with the mass flowrate 0.03 kg per second and constant low input temperature.

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