scholarly journals Comparison between Historical and Real-Time Techniques for Estimating Marginal Emissions Attributed to Electricity Generation

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5261
Author(s):  
Amir Shahin Kamjou ◽  
Carol J. Miller ◽  
Mahdi Rouholamini ◽  
Caisheng Wang
Keyword(s):  
Real Time ◽  
Electricity Generation ◽  
Emission Factors ◽  
Social Consequences ◽  
Electricity Grid ◽  
The Us ◽  
System Operator ◽  
Environmental Emissions ◽  
New Policies ◽  
Time Frames

Electricity generation is tied to various environmental and social consequences. In prior studies, the environmental emissions associated with electricity generation were calculated using average emission factors (AEFs) whose use is different from the method of marginal emission factors (MEFs) in regard to the geographical redefinition and new policies applied to the US electricity grid in 2013. Moreover, the amount of emissions being released at a generation site depends on the technology of the generating units; it is important to take into account this factor as well. Thus, this paper provides comparisons between different historical and real-time approaches of estimating MEFs (i.e., CO2, SO2, and NOx) for the Midcontinent Independent System Operator (MISO) electricity region. The region under study is the same for all the scenarios, although the comparative time frames are different. The study is focused on the similarities observed in the data trends and system behaviors. We carry out different temporal comparisons whose results show the value of real-time approaches for estimating the MEFs for each location and at any time. These approaches can be extended to other regions to assist with proper investment and policy making, thereby increasing the grid efficiency, mitigating the environmental emissions, and clarifying the byproducts of energy consumption.

scholarly journals A Novel Power Market Mechanism Based on Blockchain for Electric Vehicle Charging Stations

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 307
Author(s):  
Zhaoxiong Huang ◽  
Zhenhao Li ◽  
Chun Sing Lai ◽  
Zhuoli Zhao ◽  
Xiaomei Wu ◽  
...  
Keyword(s):  
Social Welfare ◽  
Real Time ◽  
Electric Vehicle ◽  
Peak Load ◽  
Market Mechanism ◽  
Double Auction ◽  
Energy Trading ◽  
Charging System ◽  
Electric Vehicle Charging ◽  
System Operator

This work presents a novel blockchain-based energy trading mechanism for electric vehicles consisting of day-ahead and real-time markets. In the day-ahead market, electric vehicle users submit their bidding price to participate in the double auction mechanism. Subsequently, the smart match mechanism will be conducted by the charging system operator, to meet both personal interests and social benefits. After clearing the trading result, the charging system operator uploads the trading contract made in the day-ahead market to the blockchain. In the real-time market, the charging system operator checks the trading status and submits the updated trading results to the blockchain. This mechanism encourages participants in the double auction to pursue higher interests, in addition to rationally utilize the energy unmatched in the auction and to achieve the improvement of social welfare. Case studies are used to demonstrate the effectiveness of the proposed model. For buyers and sellers who successfully participate in the day-ahead market, the total profit increase for buyer and seller are 22.79% and 53.54%, respectively, as compared to without energy trading. With consideration of social welfare in the smart match mechanism, the peak load reduces from 182 to 146.5 kW, which is a 19.5% improvement.

Renewable electricity generation proposed pathways for the US and China

2021 ◽  
Vol 170 ◽  
pp. 212-223
Author(s):  
Bismark Ameyaw ◽  
Yao Li ◽  
Yongkai Ma ◽  
Joy Korang Agyeman ◽  
Jamal Appiah-Kubi ◽  
...  
Keyword(s):  
Electricity Generation ◽  
Renewable Electricity ◽  
The Us ◽  
Renewable Electricity Generation

Improving Operational Efficiency Using Automated Time Analysis for Multi-Well Pad Fracturing

2021 ◽  
Author(s):  
Fahd Siddiqui ◽  
Mohammadreza Kamyab ◽  
Michael Lowder
Keyword(s):  
Real Time ◽  
Operational Efficiency ◽  
Permian Basin ◽  
Potential Cost ◽  
Time Period ◽  
Cloud Server ◽  
The Us ◽  
Single Well ◽  
Complete Automation

Abstract The economic success of unconventional reservoirs relies on driving down completion costs. Manually measuring the operational efficiency for a multi-well pad can be error-prone and time-prohibitive. Complete automation of this analysis can provide an effortless real-time insight to completion engineers. This study presents a real-time method for measuring the time spent on each completion activity, thereby enabling the identification and potential cost reduction avenues. Two data acquisition boxes are utilized at the completion site to transmit both the fracturing and wireline data in real-time to a cloud server. A data processing algorithm is described to determine the start and end of these two operations for each stage of every well on the pad. The described method then determines other activity intervals (fracturing swap-over, wireline swap-over, and waiting on offset wells) based on the relationship between the fracturing and wireline segments of all the wells. The processed data results can be viewed in real-time on mobile or computers connected to the cloud. Viewing the full operational time log in real-time helps engineers analyze the whole operation and determine key performance indicators (KPIs) such as the number of fractured stages per day, pumping percentage, average fracture, and wireline swap-over durations for a given time period. In addition, the performance of the day and night crews can be evaluated. By plotting a comparison of KPIs for wireline and fracturing times, trends can be readily identified for improving operational efficiency. Practices from best-performing stages can be adopted to reduce non-pumping times. This helps operators save time and money to optimize for more efficient operations. As the number of wells increases, the complexity of manual generation of time-log increases. The presented method can handle multi-well fracturing and wireline operations without such difficulty and in real-time. A case study is also presented, where an operator in the US Permian basin used this method in real-time to view and optimize zipper operations. Analysis indicated that the time spent on the swap over activities could be reduced. This operator set a realistic goal of reducing 10 minutes per swap-over interval. Within one pad, the goal was reached utilizing this method, resulting in reducing 15 hours from the total pad time. The presented method provides an automated overview of fracturing operations. Based on the analysis, timely decisions can be made to reduce operational costs. Moreover, because this method is automated, it is not limited to single well operations but can handle multi-well pad completion designs that are commonplace in unconventionals.

scholarly journals Croatia's rural areas - renewable energy based electricity generation for isolated grids

2014 ◽  
Vol 18 (3) ◽  
pp. 731-742 ◽  
Author(s):  
Sonja Protic ◽  
Robert Pasicko
Keyword(s):  
Renewable Energy ◽  
Rural Areas ◽  
Electricity Generation ◽  
Renewable Energy Sources ◽  
Interdisciplinary Approach ◽  
Energy Sources ◽  
Electricity Grid ◽  
The Public ◽  
Balkan States ◽  
Supply Systems

Several Western Balkan states face the consequences of the Yugoslavian war, which left hometowns with dilapidated electricity grid connections, a high average age of power plant capacities and low integration of renewable energy sources, grid bottlenecks and a lack of competition. In order to supply all households with electricity, UNDP Croatia did a research on decentralized supply systems based on renewable energy sources. Decentralized supply systems offer cheaper electricity connections and provide faster support to rural development. This paper proposes a developed methodology to financially compare isolated grid solutions that primarily use renewable energies to an extension of the public electricity network to small regions in Croatia. Isolated grid supply proves to be very often a preferable option. Furthermore, it points out the lack of a reliable evaluation of non-monetizable aspects and promotes a new interdisciplinary approach.

scholarly journals Internet of medical things – integrated, ultrasound-based respiration monitoring system for incubators

2020 ◽  
Author(s):  
◽  
Tareq Abdulqader
Keyword(s):  
Real Time ◽  
Respiration Rate ◽  
Surface Measurement ◽  
Time Interval ◽  
Portable Devices ◽  
Important Indicator ◽  
The Us ◽  
Respiratory Signal ◽  
Central Apnoea ◽  
Respiration Signal

The study's aim was to develop a non-contact, ultrasound (US) based respiration rate and respiratory signal monitor suitable for babies in incubators. Respiration rate indicates average number of breaths per minute and is higher in young children than adults. It is an important indicator of health deterioration in critically ill patients. The current incubators do not have an integrated respiration monitor due to complexities in its adaptation. Monitoring respiratory signal assists in diagnosing respiration rated problems such as central Apnoea that can affect infants. US sensors are suitable for integration into incubators as US is a harmless and cost-effective technology. US beam is focused on the chest or abdomen. Chest or abdomen movements, caused by respiration process, result in variations in their distance to the US transceiver located at a distance of about 0.5 m. These variations are recorded by measuring the time of flight from transmitting the signal and its reflection from the monitored surface. Measurement of this delay over a time interval enables a respiration signal to be produced from which respiration rate and pauses in breathing are determined. To assess the accuracy of the developed device, a platform with a moving surface was devised. The magnitude and frequency of its surface movement were accurately controlled by its signal generator. The US sensor was mounted above this surface at a distance of 0.5 m. This US signal was wirelessly transmitted to a microprocessor board to digitise. The recorded signal that simulated a respiratory signal was subsequently stored and displayed on a computer or an LCD screen. The results showed that US could be used to measure respiration rate accurately. To cater for possible movement of the infant in the incubator, four US sensors were adapted. These monitored the movements from different angles. An algorithm to interpret the output from the four US sensors was devised and evaluated. The algorithm interpreted which US sensor best detected the chest movements. An IoMT system was devised that incorporated NodeMcu to capture signals from the US sensor. The detected data were transmitted to the ThingSpeak channel and processed in real-time by ThingSpeak’s add-on Matlab© feature. The data were processed on the cloud and then the results were displayed in real-time on a computer screen. The respiration rate and respiration signal could be observed remotely on portable devices e.g. mobile phones and tablets. These features allow caretakers to have access to the data at any time and be alerted to respiratory complications. A method to interpret the recorded US signals to determine respiration patterns, e.g. intermittent pauses, were implemented by utilising Matlab© and ThingSpeak Server. The method successfully detected respiratory pauses by identifying lack of chest movements. The approach can be useful in diagnosing central apnoea. In central apnoea, respiratory pauses are accompanied by cessation of chest or abdominal movements. The devised system will require clinical trials and integration into an incubator by conforming to the medical devices directives. The study demonstrated the integration of IoMT-US for measuring respiration rate and respiratory signal. The US produced respiration rate readings compared well with the actual signal generator's settings of the platform that simulated chest movements.

scholarly journals Robotic Ultrasound Scanning With Real-Time Image-Based Force Adjustment: Quick Response for Enabling Physical Distancing During the COVID-19 Pandemic

2021 ◽  
Vol 8 ◽  
Author(s):  
Mojtaba Akbari ◽  
Jay Carriere ◽  
Tyler Meyer ◽  
Ron Sloboda ◽  
Siraj Husain ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Real Time ◽  
Close Contact ◽  
Image Features ◽  
Svm Classifier ◽  
Quick Response ◽  
Robot Arm ◽  
Noise Characteristics ◽  
The Us

During an ultrasound (US) scan, the sonographer is in close contact with the patient, which puts them at risk of COVID-19 transmission. In this paper, we propose a robot-assisted system that automatically scans tissue, increasing sonographer/patient distance and decreasing contact duration between them. This method is developed as a quick response to the COVID-19 pandemic. It considers the preferences of the sonographers in terms of how US scanning is done and can be trained quickly for different applications. Our proposed system automatically scans the tissue using a dexterous robot arm that holds US probe. The system assesses the quality of the acquired US images in real-time. This US image feedback will be used to automatically adjust the US probe contact force based on the quality of the image frame. The quality assessment algorithm is based on three US image features: correlation, compression and noise characteristics. These US image features are input to the SVM classifier, and the robot arm will adjust the US scanning force based on the SVM output. The proposed system enables the sonographer to maintain a distance from the patient because the sonographer does not have to be holding the probe and pressing against the patient's body for any prolonged time. The SVM was trained using bovine and porcine biological tissue, the system was then tested experimentally on plastisol phantom tissue. The result of the experiments shows us that our proposed quality assessment algorithm successfully maintains US image quality and is fast enough for use in a robotic control loop.

Epidemic Response: Follow-up and lessons learned from the US response to the evolving and conflicting risk information, focusing on education and clinical environments

2021 ◽  
Vol 65 (1) ◽  
pp. 1584-1587
Author(s):  
Alison G. Vredenburgh ◽  
Gail L. Sunderman ◽  
Rodrigo J. Daly Guris ◽  
Sreekanth R. Cheruku
Keyword(s):  
Real Time ◽  
Lessons Learned ◽  
Face To Face ◽  
The Us ◽  
Hospital Systems ◽  
Clinical Environments ◽  
New Type ◽  
Response Decisions ◽  
Epidemic Response

In this follow-up panel, we discuss what we have learned over the last year about responding to an epidemic or pandemic that has demonstrated a level of transmission unprecedented in the modern era. Two medical doctors that have worked on the front of this pandemic share their experiences transitioning from the “sharp end” of the response. Decisions about how to mitigate hazards have occurred at the personal, institutional, and health policy levels, in real-time, with frequent adaptation, and often in advance of concrete evidence. Over the course of the pandemic, hospital systems revised existing protocols to manage perceived risks in real time using emerging information from other centers. With the introduction of vaccines, there is a new type of risk perception. Is the vaccine perceived to be safe? Is there a disparity in perception among different population groups? That said, analyses are also complicated by emerging viral mutations with unclear implications. What factors increase or decrease public compliance with precautions? How are US education policymakers deciding about face-to-face classroom instruction? This panel includes a warnings expert, an expert on education policy, and two practicing physicians.

Monetary Policy and Real-Time Data: The Case of Europe, Asia and the US

2006 ◽  
pp. 165-182
Author(s):  
Franz Seitz ◽  
Christina Gerberding ◽  
Andreas Worms
Keyword(s):  
Monetary Policy ◽  
Real Time ◽  
Time Data ◽  
The Us ◽  
Real Time Data
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