scholarly journals Validation of All-Sky Imager Technology and Solar Irradiance Forecasting at Three Locations: NREL, San Antonio, Texas, and the Canary Islands, Spain

2019 ◽  
Vol 9 (4) ◽  
pp. 684 ◽  
Author(s):  
Walter Richardson ◽  
David Cañadillas ◽  
Ariana Moncada ◽  
Ricardo Guerrero-Lemus ◽  
Les Shephard ◽  
...  
Keyword(s):  
Canary Islands ◽  
Solar Irradiance ◽  
Learning Strategy ◽  
San Antonio ◽  
Low Cost ◽  
Climatic Conditions ◽  
Operational Experience ◽  
Reference Architecture ◽  
Original Design ◽  
Sky Imager

Increasing photovoltaic (PV) generation in the world’s power grid necessitates accurate solar irradiance forecasts to ensure grid stability and reliability. The University of Texas at San Antonio (UTSA) SkyImager was designed as a low cost, edge computing, all-sky imager that provides intra-hour irradiance forecasts. The SkyImager utilizes a single board computer and high-resolution camera with a fisheye lens housed in an all-weather enclosure. General Purpose IO pins allow external sensors to be connected, a unique aspect is the use of only open source software. Code for the SkyImager is written in Python and calls libraries such as OpenCV, Scikit-Learn, SQLite, and Mosquito. The SkyImager was first deployed in 2015 at the National Renewable Energy Laboratory (NREL) as part of the DOE INTEGRATE project. This effort aggregated renewable resources and loads into microgrids which were then controlled by an Energy Management System using the OpenFMB Reference Architecture. In 2016 a second SkyImager was installed at the CPS Energy microgrid at Joint Base San Antonio. As part of a collaborative effort between CPS Energy, UT San Antonio, ENDESA, and Universidad de La Laguna, two SkyImagers have also been deployed in the Canary Islands that utilize stereoscopic images to determine cloud heights. Deployments at three geographically diverse locations not only provided large amounts of image data, but also operational experience under very different climatic conditions. This resulted in improvements/additions to the original design: weatherproofing techniques, environmental sensors, maintenance schedules, optimal deployment locations, OpenFMB protocols, and offloading data to the cloud. Originally, optical flow followed by ray-tracing was used to predict cumulus cloud shadows. The latter problem is ill-posed and was replaced by a machine learning strategy with impressive results. R2 values for the multi-layer perceptron of 0.95 for 5 moderately cloudy days and 1.00 for 5 clear sky days validate using images to determine irradiance. The SkyImager in a distributed environment with cloud-computing will be an integral part of the command and control for today’s SmartGrid and Internet of Things.

scholarly journals Deep Learning to Forecast Solar Irradiance Using a Six-Month UTSA SkyImager Dataset

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 1988 ◽  
Author(s):  
Ariana Moncada ◽  
Walter Richardson ◽  
Rolando Vega-Avila
Keyword(s):  
Deep Learning ◽  
Solar Irradiance ◽  
Imaging System ◽  
San Antonio ◽  
Raspberry Pi ◽  
Solar Panels ◽  
Original Design ◽  
Error Metrics ◽  
Ill Posed ◽  
Pv Power Generation

Distributed PV power generation necessitates both intra-hour and day-ahead forecasting of solar irradiance. The UTSA SkyImager is an inexpensive all-sky imaging system built using a Raspberry Pi computer with camera. Reconfigurable for different operational environments, it has been deployed at the National Renewable Energy Laboratory (NREL), Joint Base San Antonio, and two locations in the Canary Islands. The original design used optical flow to extrapolate cloud positions, followed by ray-tracing to predict shadow locations on solar panels. The latter problem is mathematically ill-posed. This paper details an alternative strategy that uses artificial intelligence (AI) to forecast irradiance directly from an extracted subimage surrounding the sun. Several different AI models are compared including Deep Learning and Gradient Boosted Trees. Results and error metrics are presented for a total of 147 days of NREL data collected during the period from October 2015 to May 2016.

Solar irradiance components estimation based on a low-cost sky-imager

Solar Energy ◽  
2021 ◽  
Vol 220 ◽  
pp. 269-281
Author(s):  
César D. Sánchez-Segura ◽  
Luis Valentín-Coronado ◽  
Manuel I. Peña-Cruz ◽  
Arturo Díaz-Ponce ◽  
Daniela Moctezuma ◽  
...  
Keyword(s):  
Solar Irradiance ◽  
Low Cost ◽  
Sky Imager

scholarly journals Experiments on Energy-Efficient Evaporative Cooling Systems for Poultry Farm Application in Multan (Pakistan)

2021 ◽  
Vol 13 (5) ◽  
pp. 2836
Author(s):  
Khawar Shahzad ◽  
Muhammad Sultan ◽  
Muhammad Bilal ◽  
Hadeed Ashraf ◽  
Muhammad Farooq ◽  
...  
Keyword(s):  
Heat Stress ◽  
Low Cost ◽  
Evaporative Cooling ◽  
Thermal Exposure ◽  
Climatic Conditions ◽  
The Body ◽  
Dew Point ◽  
Sweat Glands ◽  
Cooling Systems ◽  
Humidity Index

Poultry are one of the most vulnerable species of its kind once the temperature-humidity nexus is explored. This is so because the broilers lack sweat glands as compared to humans and undergo panting process to mitigate their latent heat (moisture produced in the body) in the air. As a result, moisture production inside poultry house needs to be maintained to avoid any serious health and welfare complications. Several strategies such as compressor-based air-conditioning systems have been implemented worldwide to attenuate the heat stress in poultry, but these are not economical. Therefore, this study focuses on the development of low-cost and environmentally friendly improved evaporative cooling systems (DEC, IEC, MEC) from the viewpoint of heat stress in poultry houses. Thermodynamic analysis of these systems was carried out for the climatic conditions of Multan, Pakistan. The results appreciably controlled the environmental conditions which showed that for the months of April, May, and June, the decrease in temperature by direct evaporative cooling (DEC), indirect evaporative cooling (IEC), and Maisotsenko-Cycle evaporative cooling (MEC) systems is 7–10 °C, 5–6.5 °C, and 9.5–12 °C, respectively. In case of July, August, and September, the decrease in temperature by DEC, IEC, and MEC systems is 5.5–7 °C, 3.5–4.5 °C, and 7–7.5 °C, respectively. In addition, drop in temperature-humidity index (THI) values by DEC, IEC, and MEC is 3.5–9 °C, 3–7 °C, and 5.5–10 °C, respectively for all months. Optimum temperature and relative humidity conditions are determined for poultry birds and thereby, systems’ performance is thermodynamically evaluated for poultry farms from the viewpoint of THI, temperature-humidity-velocity index (THVI), and thermal exposure time (ET). From the analysis, it is concluded that MEC system performed relatively better than others due to its ability of dew-point cooling and achieved THI threshold limit with reasonable temperature and humidity indexes.

A new automated stem CO2 efflux chamber based on industrial ultra-low-cost sensors

2019 ◽  
Author(s):  
Johannes Brändle ◽  
Norbert Kunert
Keyword(s):  
Gas Exchange ◽  
Low Cost ◽  
Climatic Conditions ◽  
Co2 Efflux ◽  
Diurnal Changes ◽  
Lowland Forest ◽  
Stem Respiration ◽  
Stem Co2 Efflux ◽  
Gas Exchange System ◽  
Controlling Processes

Abstract Tree autotrophic respiratory processes, especially stem respiration or stem CO2 efflux (Estem), are important components of the forest carbon budget. Despite the efforts to investigate the controlling processes of Estem in the last years a considerable lack in our knowledge remains on the abiotic and biotic drivers affecting Estem dynamics. It has been strongly advocated that long-term measurements would shed light into those processes. The expensive scientific instruments needed to measure gas exchange has prevented from applying Estem measurements on a larger temporal and spatial scale. Here, we present an automated closed dynamic chamber system based on inexpensive and industrially broadly applied CO2 sensors reducing the costs for the sensing system to a minimum. The CO2 sensor was cross-calibrated with a commonly used gas exchange system in the laboratory and in the field, and we found very good accordance of these sensors. We tested the system under harsh tropical climatic conditions, characterized by heavy tropical rainfall events, extreme humidity, and temperatures, in a moist lowland forest in Malaysia. We recorded Estem of three Dyera costulata trees with our prototype over various days. The variation of Estem was large among the three tree individuals and varied by 7.5-fold. However, clear diurnal changes in Estem were present in all three tree individuals. One tree showed high diurnal variation in Estem and the relationship between Estem and temperature was characterized by a strong hysteresis. The large variations found within one single tree species highlights the importance of continuous measurement to quantify ecosystem carbon fluxes.

scholarly journals Optimization of Design Scheme for Toll Plaza Based on M/M/C Queuing Theory and Cellular Automata Simulation Algorithm

2017 ◽  
Vol 11 (7) ◽  
pp. 1 ◽  
Author(s):  
Yi-Jian Liu ◽  
Jian Cao ◽  
Xiao-Yan Cao ◽  
Yuan-Biao Zhang
Keyword(s):  
Cellular Automata ◽  
Traffic Control ◽  
Queuing Theory ◽  
Low Cost ◽  
Evaluation Model ◽  
Original Design ◽  
Safety Coefficient ◽  
Toll Plazas ◽  
Important Field ◽  
Toll Plaza

As an important field in traffic control science, the research in design of toll plazas has increasingly attracted attention of scholars and society. A good design of toll plaza needs to meet a lot of conditions, such as high safety coefficient, high throughput and low cost level. In this study, we established an evaluation model of toll plaza based on cellular automata and M/M/C queuing theory applying to three aspects: safety coefficient, throughput and cost. Then, we took the Asbury Park Toll Plaza in New Jersey as an example to analyze its performance and further optimized the design of the toll plaza. Compared with the original design, the optimized toll plaza we designed is proved to be safer and preferable. Last but not least, we further analyzed the robustness of the designed toll plaza, proving that the designed toll plaza had a preferable performance in reality.

Energy in the 1980s - Operational experience in nuclear power stations

1974 ◽  
Vol 276 (1261) ◽  
pp. 571-586
Keyword(s):  
Nuclear Power ◽  
Nuclear Energy ◽  
Large Scale ◽  
Electrical Power ◽  
Operating Experience ◽  
Operational Experience ◽  
Original Design ◽  
Safety Requirements ◽  
Design Concepts ◽  
Power Stations

From the first self-sustaining nuclear reaction to the present day represents a span of three decades: within that time large-scale generation of electrical power from nuclear energy has become acknowledged as economic, safe and environmentally acceptable. Within the U .K . 10% of electricity consumed is of nuclear origin. Some of the C.E.G.B. reactors have been in service for over 10 years. The operating experience that has been gained shows how the original design concepts have been ultimately developed. Some of the difficulties encountered and the engineering solutions are presented. Operating experience feeds back to the design philosophy and safety requirements for future nuclear plant. In this way a foundation is provided for the further exploitation of what must become a major source of energy in the next decade.

scholarly journals Prediction of Solar Irradiance Based on Artificial Neural Networks

Inventions ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. 45 ◽  
Author(s):  
Waleed I. Hameed ◽  
Baha A. Sawadi ◽  
Safa J. Al-Kamil ◽  
Mohammed S. Al-Radhi ◽  
Yasir I. A. Al-Yasir ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Solar Irradiance ◽  
Open Circuit Voltage ◽  
Low Cost ◽  
Short Circuit ◽  
Short Circuit Current ◽  
Open Circuit ◽  
Pv Module ◽  
Artificial Neural

Prediction of solar irradiance plays an essential role in many energy systems. The objective of this paper is to present a low-cost solar irradiance meter based on artificial neural networks (ANN). A photovoltaic (PV) mathematical model of 50 watts and 36 cells was used to extract the short-circuit current and the open-circuit voltage of the PV module. The obtained data was used to train the ANN to predict solar irradiance for horizontal surfaces. The strategy was to measure the open-circuit voltage and the short-circuit current of the PV module and then feed it to the ANN as inputs to get the irradiance. The experimental and simulation results showed that the proposed method could be utilized to achieve the value of solar irradiance with acceptable approximation. As a result, this method presents a low-cost instrument that can be used instead of an expensive pyranometer.

scholarly journals Optimasi UV-Photolithography Aligner dan Photomask Menggunakan Produk Komersial untuk Microfabrication

2016 ◽  
Vol 2 (1) ◽  
Author(s):  
Delffika Canra ◽  
Dedi Suwandi
Keyword(s):  
Light Intensity ◽  
Exposure Time ◽  
Low Cost ◽  
Commercial Product ◽  
High Price ◽  
Percentage Error ◽  
Original Design ◽  
Main Component ◽  
Uv Lamps ◽  
Photolithography Process

The high price of a UV-photolithography aligner on the market is the reason for designing and characterize low cost UV-photolithography aligner. Photolithography process is simple but it needs patience, enable to modify photolithography aligner by using commercial components and certainly low price. The objective of this study is analyzing the ability of a commercial product in UV-photolithography process, search optimum exposure time and resolution. The method of photolithography process to be used is the method of contact alignment. Commercial UV lamps and cheap photomask are main component in this study. With a light intensity of 0.2 mW/cm2 require the exposure time at least 50 seconds. The smallest achievable resolution depends on the resolution photomask. The Results of smallest resolution is 165 m with a percentage error 10% of the original design.

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