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ردیف | عنوان | نوع |
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1 |
LoRaWAN-Based IoT System Implementation for Long-Range Outdoor Air Quality Monitoring
پیاده سازی سیستم اینترنت اشیاء مبتنی بر LoRaWAN برای نظارت بر کیفیت هوای خارج از منزل در محدوده بلند-2022 This study proposes a smart long-range (LoRa) sensing node to timely collect the air quality in-
formation and update it on the cloud. The developed long-range wide area network (LoRaWAN)-
based Internet of Things (IoT) air quality monitoring system (AQMS), hereafter called LoRaWAN-
IoT-AQMS, was deployed in an outdoor environment to validate its reliability and effectiveness.
The system is composed of multiple sensors (NO2, SO2, CO2, CO, PM2.5, temperature, and hu-
midity), Arduino microcontroller, LoRa shield, LoRaWAN gateway, and The Thing Network
(TTN) IoT platform. The LoRaWAN-IoT-AQMS is a standalone system powered continuously by a
rechargeable battery with a photovoltaic solar panel via a solar charger shield for sustainable
operation. Our system simultaneously gathers the considered air quality information by using the
smart sensing unit. Then, the system transmits the information through the gateway to the TTN
platform, which is integrated with the ThingSpeak IoT server. This action updates the collected
data and displays these data on a developed Web-based dashboard and a Graphical User Interface
(GUI) that uses the Virtuino mobile application. Thus, the displayed information can be easily
accessed by users via their smartphones. The results obtained by the developed LoRaWAN-IoT-
AQMS are validated by comparing them with experimental results based on the high-
technology Aeroqual air quality monitoring devices. Our system can reliably monitor various
air quality indicators and efficiently transmit the information in real time over the Internet. keywords: پایش کیفیت هوا | Air quality monitoring | Iot lora lorawan | TTN ThingSpeak Virtuino |
مقاله انگلیسی |
2 |
Improved optical and electrical properties for heterojunction solar cell using Al2O3/ITO double-layer anti-reflective coating
بهبود خواص نوری و الکتریکی برای سلول های خورشیدی ناهمگون با استفاده از پوشش ضد انعکاس دو لایه Al2O3/ITO-2021 Silicon heterojunction solar cells have been gaining remarkable attention in the photovoltaic industry in recent
years owing to their low temperature coefficient and high efficiency. This study aimed to maximize the short
circuit current density (Jsc), which is directly correlated with the absorbance of the solar cells. An advanced ray
tracking model and hall effect measurement was used to improve the optical properties of Al2O3/ITO as a double layered anti-reflection coating (DLARC) on the solar cell. RF/DC power sputtering system was used to deposit
ITO layer, while atomic layer deposition was used to deposit Al2O3 on ITO to create a DLARC. An average
decrease in reflection from 9.33% to 4.74% and enhancement in EQE from 76.89% to 84.34% were observed for
the DLARC in the wavelength spectrum at 300–1100 nm. It also exhibited a higher Jsc value of 41.13 mA/cm2
and maximum conversion efficiency of 21.6%. The findings of both simulation and experiments showed that the
Al2O3/ITO DLARC has better anti-reflection properties than a single-layer ITO coating.
Keywords: Silicon heterojunction solar cell | Double layered anti-reflection coating | Optical Properties | Electrical Properties |
مقاله انگلیسی |
3 |
Comparison of electrical energy and power of PV with different cells materials in clear sky day condition
مقایسه انرژی الکتریکی و توان PV با مواد سلول های مختلف در شرایط روز آسمان صاف-2021 In present study, a comparison has been made on the basis of gain of the electrical energy and power
from solar cells or photovoltaic module. To evaluate the electrical energy and power, five different materials or cases have been considered, which are named as: case (i): c-Si, case (ii): p-Si, case (iii): a-Si, case
(iv): CdTe and case (v): CIGS. Each PV module has been considered for the analysis which dimension is
0.6051 m2. For case (i): PV cells are made of silicon crystalline, which is having 0.5 Volts and 4 Amp
and 36 cells are connected in series, which are producing 72 W. Such analysis has been studied for a clear
sky day condition, New Delhi, India. The comparative study is attempted to choose best for generating
electrical energy and power when high electrical enrgy demands in our society. It is also observed that
the maximum electrical energy and power have been found for case (i), whereas minimum for case
(iii), due to high PV cell temperature. The electrical energy and power have been 1.8 times higher in case
(i), than case (iii).
Keywords: Silicon materials | PV | Composite climate | Energy and power |
مقاله انگلیسی |
4 |
Towards improved and multi-scale liquefied natural gas supply chains: Thermodynamic analysis
به سمت زنجیره تأمین گاز طبیعی مایع بهبود یافته و چند مقیاس: تحلیل ترمودینامیکی-2021 The liquefied natural gas (LNG) chain requires significant amounts of resources. Enhancing its efficiency
is essential due to environmental concerns, amongst others. Here, we presented various optimization,
integration, and multi-scale opportunities that can improve the chain’s outputs for a given feed. Our
recommendations were derived from rigorous thermodynamic analyses while considering multiple operational modes. Many opportunities were identified; some are suitable for immediate implementation,
while others are futuristic. The most appealing options relate to the deployment of cutting-edge energy
generators. For 7.81GW feed exergy, the chain’s prevailing holding mode loss is enough to power a mega
LNG plant processing 23GW feed exergy. Many heat integration opportunities are missed due to standard
practices. Losses in standalone mode can be misleading. When considering the utility steps, liquefaction
and sweetening losses are the highest. Fuel cells and solar energy are well suited for these and can potentially enhance the chain LNG delivery by over 30%. Keywords: Pinch | Solid oxide fuel cells | Exergy | LNG | Solar |
مقاله انگلیسی |
5 |
Defect detection and quantification in electroluminescence images of solar PV modules using U-net semantic segmentation
تشخیص و تعیین کمبود در تصاویر الکترولومینسانس ماژول های PV خورشیدی با استفاده از تقسیم بندی معنایی U-net-2021 Electroluminescence (EL) images enable defect detection in solar photovoltaic (PV) modules that are otherwise invisible to the naked eye, much the same way an x-ray enables a doctor to detect cracks and fractures in bones. The prevalence of multiple defects, e.g. micro cracks, inactive regions, gridline defects, and material defects, in PV module can be quantified with an EL image. Modern, deep learning tech- niques for computer vision can be applied to extract the useful information contained in the images on entire batches of PV modules. Defect detection and quantification in EL images can improve the efficiency and the reliability of PV modules both at the factory by identifying potential process issues and at the PV plant by identifying and reducing the number of faulty modules installed. In this work, we train and test a semantic segmentation model based on the u-net architecture for EL image analysis of PV modules made from mono-crystalline and multi-crystalline silicon wafer-based solar cells. This work is focused on developing and testing a deep learning method for computer vision that is independent of the equipment used to generate the EL images, independent of the wafer-based module design, and independent of the image quality.© 2021 Elsevier Ltd. All rights reserved. Keywords: Electroluminescence | EL | PV | U-net | Semantic segmentation | Machine learning |
مقاله انگلیسی |
6 |
Using machine learning and computer vision to estimate the angular velocity of wind turbines in smart grids remotely
استفاده از یادگیری ماشین و بینایی ماشین برای برآورد سرعت زاویه ای توربین های بادی در شبکه های هوشمند از راه دور-2021 Today, power generation from clean and renewable resources such as wind and solar is of great salience. Smart grid technology efficiently responds to the increasing demand for electric power. Intelligent monitoring, control, and maintenance of wind energy facilities are indispensable to increase the performance and efficiency of smart grids (SGs). Integration of state-of-the-art machine learning algorithms and vision sensor networks approaches pave the way toward enhancing the wind farms’ performance. The generating power in a wind turbine farm is the most critical parameter that should be measured accurately. Produced power is highly related to weather patterns, and a new farm in a near area is also likely to have similar energy generation. Therefore, accurate and perpetual prediction models of the existing wind farms can be led to develop new stations with lower costs. The paper aims to estimate the angular velocity of turbine blades using vision sensors and signal processing. The high wind in the wind farm can cause the camera to vibrate in successive frames, and the noise in the input images can also strengthen the problem. Thanks to couples of solid computer vision algorithms, including FAST (Features from Accelerated Segment Test), SIFT (Scale-Invariant Feature Transform), SURF (Speeded Up Robust Features), BF (Brute-Force), FLANN (Fast Library for Approximate Nearest Neighbors), AE (Autoencoder), and SVM (support vector machines), this paper accurately localizes the Hub and track the presence of the Blade in consecutive frames of a video stream. The simulation results show that determining the hub location and the blade presence in sequential frames results in an accurate estimation of wind turbine angular velocity with 95.36% accuracy.© 2021 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/). Keywords: Machine vision | Blade detection | Image classification | Signal processing | Wind turbine | Smart grids |
مقاله انگلیسی |
7 |
Research on the policy route of China’s distributed photovoltaic power generation
تحقیق در مورد مسیر سیاست تولید انرژی فتوولتائیک و توزیع شده در چین-2020 The distributed photovoltaic power generation is an important way to make use of solar energy in
cities. China issues a series of policies to support the development of distributed photovoltaics in
law, electricity price, grid connection standard, project management, financial support and so on.
However, there are still some defects in policies and market mechanism. China creates a competitive
market with a significant number of projects of distributed photovoltaic power through the reform of
the electricity market, yet substantial drawbacks of the corresponding investment subsidies prevent
distributed photovoltaic power from rapidly developing. This paper summarizes the status quo of
China’s distributed photovoltaic power development, given its long-term plan, presents excellences and
shortcomings of the existing policy system, and looks into the supporting policies and implementation
paths for China’s distributed photovoltaic power in different stages. Innovative business models and
financial support models are conducive to the development of distributed photovoltaic power. Financial
innovation methods such as crowd funding and asset securitization should be encouraged to develop
a sound risk assessment mechanism for projects, involve insurance institutions, and establish a risk
sharing mechanism. In the context of a series of supporting policies, the distributed photovoltaic
power in China will move towards market-oriented standardization for a healthier and more stable
development. Keywords: Distributed photovoltaic power | Electricity price | Policy route | Development strategy |
مقاله انگلیسی |
8 |
Sustainable groundwater management in arid regions considering climate change impacts in Moghra region, Egypt
مدیریت پایدار آبهای زیرزمینی در مناطق خشک با توجه به تأثیر تغییرات آب و هوایی در منطقه مقرا ، مصر-2020 Egypt is one of the most water-scarce countries of the Middle East and North Africa region and is highly
vulnerable to climatic changes. In the Egyptian deserts, new land reclamation projects depend mainly on
groundwater as the main source of water. Also, solar energy is the most promising renewable source of energy for
pumping and transport of water. Moghra region is one of the well-known “1.5 Million Acres Reclamation Projects”
areas in the Western Desert. In this paper, a groundwater model was constructed and used to investigate
the sustainable groundwater management scenarios in Moghra region taking into consideration impacts of the
expected climate changes. Using MODFLOW/GMS software, Moghra model was prepared and calibrated based
on the region’s topographic, climatic, geologic and hydrologeolgic conditions. The model was used to explore the
impacts of climate changes; Sea Level Rise (SLR) by 1.0 m and temperature increase by 2�0C and 40�C on the
management scenarios. In addition, the required power for water management after 5, 10, 50 and 100 years were
determined. It was concluded that the best management scenario is to use 1000 wells to extract 1.2 Mm3/d of
water for serving a total area of 85,714 acres (360 km2). This scenario satisfies the project criteria that permits a
maximum drawdown less than 1 m/year. It was also concluded that SLR has mild effects on groundwater levels
due to the vast aquifer dimensions. Additionally, the increase in evapotranspiration due to temperature increase
will lead to a significant increase in the consumptive use. The power needed to extract water will continuously
increase due to the expected increase in drawdown. The required area for Photovoltaic (PV) solar plant was
determined and its value increased by 6% and 12% due to temperature increase of 2�C and 4�C, respectively. Keywords: ArcGIS | Climate change | Groundwater management | MODFLOW/GMS | Moghra aquifer | Solar energy |
مقاله انگلیسی |
9 |
Special interest tourism is not so special after all: Big data evidence from the 2017 Great American Solar Eclipse
جهانگردی با علاقه ویژه از همه مهم تر نیست: شواهد داده های بزرگ از خورشید گرفتگی بزرگ آمریکایی 2017-2020 This study puts to empirical test a major typology in the tourism literature, mass versus special interest tourism
(SIT), as the once-distinctive boundary between the two has become blurry in modern tourism scholarship. We
utilize 41,747 geo-located Instagram photos pertaining to the 2017 Great American Solar Eclipse and Big Data
analytics to distinguish tourists based on their choice of observational destinations and spatial movement patterns.
Two types of tourists are identified: opportunists and hardcore. The motivational profile of those tourists is
validated with the external data through hypothesis testing and compared with and contrasted against existing
motivation-based tourist typologies. The main conclusion is that large share of tourists involved in what is
traditionally understood as SIT activities exhibit behavior and profile characteristic of mass tourists seeking
novelty but conscious about risks and comforts. Practical implications regarding the potential of rural and urban
destinations for developing SIT tourism are also discussed. Keywords: Big data | Instagram photos | Social media | Spatial analysis | Special interest tourism | Astro-tourism |
مقاله انگلیسی |
10 |
Optimal planning of distributed photovoltaic generation for the traction power supply system of high-speed railway
برنامه ریزی بهینه از تولید فتوولتائیک توزیع شده برای سیستم منبع تغذیه کششی راه آهن با سرعت بالا-2020 The ever-increasing electricity price and energy consumption in high-speed railway industry push
railway companies to seek a promising way to realize their sustainable developments. Making full use of
the solar resource along with high-speed railways can be a potential solution to cut the electricity bill,
bring more profit to railway companies and realize the decarbonization of high-speed railway industry.
This paper studies the optimal planning of distributed photovoltaic generation (DPVG) and energy
storage system (ESS) for the traction power supply system (TPSS) of high-speed railway. A quantitative
method is proposed to study the time and space characteristics of photovoltaic generation and electricity
demand of high-speed trains. An integrated cost-benefit analysis framework is developed to evaluate the
effect of DPVG and ESS on the economy of TPSS. To derive the optimal planning scheme and energy
management strategy of DPVG and ESS, a mathematical programming model with the objective of
minimizing the total cost is proposed to seek the most economical solution. A hybrid global optimal
solution approach is developed to solve the model. A real-world case of Beijing-Baoding high-speed
railway in China is used to illustrate the capability and characteristics of the proposed model. The
computational results show that DPVG is able to supply 32:5% electricity demand of high-speed trains.
The integration of DPVG and ESS can help railway company save 4.2 million CNY each year in Beijing-
Baoding high-speed railway. This paper demonstrates the potential and applicability of DPVG and ESS
in high-speed railway industry. Keywords: High-speed railway | Photovoltaic generation | Energy storage system | Traction power supply system |
مقاله انگلیسی |