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13th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (MEDPOWER 2022)

作者： N.S. Kelepouris A.S. Bouhouras N. Koltsaklis I. Panapakidis C. Tsiatsios G.C. Christoforidis Department of Electrical and Computer Engineering University of Western Macedonia Kozani Greece Energy & Environmental Policy Laboratory University of Piraeus Piraeus Greece Department of Electrical and Computer Engineering University of Thessaly Volos Greece

In this paper the problem of congestion management in the power grid under the application of the day-ahead dispatch schedule, is faced based on developing a day-ahead guideline regarding the required modifications to the power units' output to yield a more uniform loading to the grid's lines. These modifications result by comparing the dispatch schedule provided by an optimal power flow (OPF) analysis for the grid, under the objective function of power loss minimization, with the schedule for the day-ahead dispatch schedule. The point here is that the solution for the latter approach is based on an economical perspective while the former one on a technical one. The proposed approach is tested on the benchmarked 118 bus system which was modified to simulate the Greek transmission network. The day-ahead schedule is initially applied on the system to depict possible congestion issues via a power flow (PF) analysis. Then, an OPF analysis is applied in order to reschedule the power output of the power units, within their operational limits, aiming at power loss minimization. The results indicate that congestion mitigation in terms of lines' loading below their thermal limit could result under proper and guided alterations for the power units output.

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Economic Impact of New Pricing Policies on Solar PV Households in the Netherlands

Economic Impact of New Pricing Policies on Solar PV Househol...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Farshid Norouzi Aditya Shekhar Thomas Hoppe Pavol Bauer Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft The Netherlands Faculty of Technology Policy and Management Delft University of Technology Delft The Netherlands

The widespread adoption of solar photovoltaic (PV) technology as a prominent renewable energy source has significant implications for the economy of households and distribution system operators (DSOs). It is crucial to analyse these impacts in light of recent pricing policy changes, including Real-Time Pricing (RTP), Time-of-Use (TOU), and Feed-in Tariffs (FiT). This study analyses the impact of pricing policies based on actual load consumption, pricing rate, and PV generation data. An economic comparison of various scenarios for a typical household in the Netherlands is conducted by determining the optimal values for PV size. The findings suggest that transitioning to RTP policies reduces households’ economic advantages. The introduction of FiT further diminishes the financial benefits for households and increases the Payback period (PP). Moreover, the study reveals that imposing an export power limit of less than 3 kW can increase households’ energy costs.

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Valuing DER Location based on the Impact on Transmission Network: A Planning Tool

Valuing DER Location based on the Impact on Transmission Net...

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IEEE Green Technologies Conference (IEEE-Green)

作者： Sarangan Rajendran Visvakumar Aravinthan Al Tamimi Charles R. Yokley Electrical and Computer Engineering Department Wichita State University Wichita KS USA Transmission Planning and Policy Sunflower Electric Power Corporation Wichita KS USA

Distributed energy resources (DERs) are increasingly being considered as an attractive solution to the non-wire alternative problem, given their various benefits to the system. However, high levels of DER penetration can result in unanticipated electric grid operating conditions, as they are traditionally not considered in planning processes by the transmission utilities. Consequently, there arises a need to value DERs based on the impacts they have on the overall system as viewed from a transmission level. This paper presents three metrics to quantify the impacts caused by the addition of DERs to an existing system. The proposed approach employs a statistical approach to measure the shift of critical system parameters from normal operating conditions due to the addition of DERs. A test system developed based on the western Kansas region is used to analyze the impact of DERs and demonstrate the usefulness of the proposed method. The results provide additional insights on how value of DERs can be studied based on the candidate location of installation.

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Understanding the Transit Gap: A Comparative Study of On-Demand Bus Services and Urban Climate Resilience in South End, Charlotte, NC and Avondale, Chattanooga, TN

arXiv

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arXiv 2024年

作者： Hosseini, Sanaz Sadat Ardabili, Babak Rahimi Azarbayjani, Mona Pulugurtha, Srinivas Tabkhi, Hamed Department of Civil and Environmental Engineering University of North Carolina at Charlotte CharlotteNC United States Department of Public Policy University of North Carolina at Charlotte CharlotteNC United States School of Architecture University of North Carolina at Charlotte CharlotteNC United States Department of Electrical and Computer Engineering University of North Carolina at Charlotte CharlotteNC United States

Urban design significantly impacts sustainability, particularly in the context of public transit efficiency and carbon emissions reduction. This study explores two neighborhoods with distinct urban designs: South End, Charlotte, NC, featuring a dynamic mixed-use urban design pattern, and Avondale, Chattanooga, TN, with a residential suburban grid layout. Using the TRANSIT-GYM tool, we assess the impact of increased bus utilization in these different urban settings on traffic and CO2 emissions. Our results highlight the critical role of urban design and planning in transit system efficiency. In South End, the mixed-use design led to more substantial emission reductions, indicating that urban layout can significantly influence public transit outcomes. Tailored strategies that consider the unique urban design elements are essential for climate resilience. Notably, doubling bus utilization decreased daily emissions by 10.18% in South End and 8.13% in Avondale, with a corresponding reduction in overall traffic. A target of 50% bus utilization saw emissions drop by 21.45% in South End and 14.50% in Avondale. At an idealistic goal of 70% bus utilization, South End and Avondale witnessed emission reductions of 37.22% and 27.80%, respectively. These insights are crucial for urban designers and policymakers in developing sustainable urban landscapes. Copyright © 2024, The Authors. All rights reserved.

关键词： Urban transportation

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Optimal Restoration of a Power Distribution System During Extreme Events Considering Load Criticality

Optimal Restoration of a Power Distribution System During Ex...

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Annual North-American Power Symposium

作者： Adithya Melagoda Arun-Kaarthick Manoharan Mohd Abrar Rahman Visvakumar Aravinthan Al Tamimi Department of Electrical & Computer Engineering Wichita State University Wichita KS USA Transmission Planning & Policy Sunflower Electric Power Corporation Wichita KS USA

Recent natural and man-made disasters leading to sustained power outage has urged the system planners and policy makers for improving grid resiliency. This requires innovation across diverse facets ranging from better anticipation of such events to post event response. This work focuses on the problem of supporting the critical loads when the system is undergoing such an event. As a preliminary step towards the big picture, this work aims to develop a load criticality-based model to operable microgrid formation. A new firefly search inspired metaheuristic algorithm is developed in this work for microgrid formation with the objective of maximizing the critical load restoration with minimal switching operation. Numerical analysis is conducted on a modified Iowa state 240-bus distribution system and the results show the scalability and critical load restoration capabilities of the proposed algorithm.

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Using Technology to Improve Awareness, Convenience, and Communication about Neurodivergence in Higher Educational Institutes in Pakistan

Using Technology to Improve Awareness, Convenience, and Comm...

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IEEE International Conference on Multi Topic

作者： Ushna Batool Areeb Adnan Khan Urooj Siddiqui Neelma Bhatti Department of Computer Science DSSE Habib University Karachi Pakistan Department of Electrical and Computer Engineering DSSE Habib University Karachi Pakistan Department of Social Development & Policy AHSS Habib University Karachi Pakistan Computer Science DSSE Habib University Karachi Pakistan

ISBN: (数字)9798331507213

ISBN: (纸本)9798331507220

Awareness of neurodiversity in higher education is at the rise but institutions struggle to set up comprehensive frameworks that can effectively accommodate neurodivergent students. This deficiency undercuts attempts to establish inclusive learning settings, leaving students to deal with issues like academic stress, social isolation, and a lack of resources. This study peruse creative ways to bridge this gap by using technology to promote inclusivity, facilitate communication, and improve the accommodation process. We created an app prototype using a human-centered design methodology with the goals of raising awareness, easing accommodations, and boosting faculty-student communication. The findings provide beneficial data for educators, policymakers, and developers intending to use technology to build supportive and equitable learning environments.

关键词： Technological innovation Education Prototypes Organizations Software Communications technology Text to speech Stakeholders Usability Stress

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Design Considerations for Building Credible Security Testbeds: Perspectives from Industrial Control System Use Cases

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Journal of Cyber Security Technology 2021年第2期5卷 71-119页

作者： Ani, Uchenna P. Daniel Watson, Jeremy M. Green, Benjamin Craggs, Barnaby Nurse, Jason R. C. Department of Science Technology Engineering and Public Policy University College London United Kingdom Computing and Communications Lancaster University United Kingdom Department of Computer Science University of Bristol United Kingdom School of Computing University of Kent United Kingdom

This paper presents a mapping framework for design factors and an implementation process for building credible Industrial Control Systems (ICS) security testbeds. The security and resilience of ICSs has become a critical concern to operators and governments following widely publicised cyber security events. The inability to apply conventional Information Technology security practice to ICSs further compounds challenges in adequately securing critical systems. To overcome these challenges, and do so without impacting live environments, testbeds are widely used for the exploration, development, and evaluation of security controls. However, how a testbed is designed and its attributes, can directly impact not only its viability but also its credibility. Combining systematic and thematic analysis, and the mapping of identified ICS security testbed design attributes, we propose a novel relationship map of credibility-supporting design factors (and their associated attributes) and a process implementation flow structure for ICS security testbeds. The framework and implementation process highlight the significance of demonstrating some design factors such as user/experimenter expertise, clearly defined testbed design objectives, simulation implementation approach, covered architectural components, core structural and functional characteristics covered, and evaluations to enhance confidence, trustworthiness and acceptance of ICS security testbeds as credible. These can streamline testbed requirement definition, improve design consistency and quality while reducing implementation costs. © 2020 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Testbeds

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Virtual Co-Pilot: Multimodal Large Language Model-enabled Quick-access Procedures for Single Pilot Operations

arXiv

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arXiv 2024年

作者： Li, Fan Feng, Shanshan Yan, Yuqi Lee, Ching-Hung Ong, Yew Soon Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic University HKSAR Hong Kong Centre for Frontier AI Research A*STAR Singapore School of Public Policy and Administration Xi'an Jiaotong University Xi’an China School of Computer Science and Engineering Nanyang Technological University Singapore

Advancements in technology, pilot shortages, and cost pressures are driving a trend towards single-pilot and even remote operations in aviation. Considering the extensive workload and huge risks associated with single-pilot operations, the development of a Virtual Co-Pilot (V-CoP) is expected to be a potential way to ensure aviation safety. This study proposes a V-CoP concept and explores how humans and virtual assistants can effectively collaborate. A preliminary case study is conducted to explore a critical role of V-CoP, namely automated quick procedures searching, using the multimodal large language model (LLM). The LLM-enabled V-CoP integrates the pilot’s instruction and real-time cockpit instrumental data to prompt applicable aviation manuals and operation procedures. The results showed that the LLM-enabled V-CoP achieved high accuracy in situational analysis (90.5%) and effective retrieval of procedure information (86.5%). The proposed V-CoP is expected to provide a foundation for future virtual intelligent assistant development, improve the performance of single pilots, and reduce the risk of human errors in aviation. © 2024, CC BY-NC-SA.

关键词： Computational linguistics

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ENHANCING SYMBOLIC REGRESSION AND UNIVERSAL PHYSICS-INFORMED NEURAL NETWORKS WITH DIMENSIONAL ANALYSIS

arXiv

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arXiv 2024年

作者： Podina, Lena Darooneh, Diba Grewal, Joshveer Kohandel, Mohammad Cheriton School of Computer Science University of Waterloo Canada Department of Electrical and Computer Engineering University of Waterloo Canada Northville High School Public school in Northville MI United States Department of Applied Mathematics University of Waterloo Canada

We present a new method for enhancing symbolic regression for differential equations via dimensional analysis, specifically Ipsen’s and Buckingham π methods. Since symbolic regression often suffers from high computational costs and overfitting, non-dimensionalizing datasets reduces the number of input variables, simplifies the search space, and ensures that derived equations are physically meaningful. As our main contribution, we integrate Ipsen’s Method of dimensional analysis with Universal Physics-Informed Neural Networks. We also combine dimensional analysis with the AI Feynman symbolic regression algorithm to show that dimensional analysis significantly improves the accuracy of the recovered equation. The results demonstrate that transforming data into a dimensionless form significantly decreases computation time and improves accuracy of the recovered hidden term. For algebraic equations, using the Buckingham π Theorem reduced complexity, allowing the AI-Feynman model to converge faster with fewer data points and lower error rates. For differential equations, Ipsen’s Method was combined with Universal Physics-Informed Neural Networks (UPINNs) to identify hidden terms more effectively. These findings suggest that integrating dimensional analysis with symbolic regression can significantly lower computational costs, enhance model interpretability, and increase accuracy, providing a robust framework for automated discovery of governing equations in complex systems when data is limited. © 2024, CC BY.

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Deep Neural Network Ensembles for the Detection of Alzheimer's Disease Using Imbalanced Clock Drawing Test Images

Deep Neural Network Ensembles for the Detection of Alzheimer...

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IEEE Annual Computing and Communication Workshop and Conference (CCWC)

作者： Sai Santosh Reddy Danda Alper Kursat Uysal Tian Qin Anu Kumar Varshitha Sannareddy Mengyao Hu Richard Gonzalez Yi Lu Murphey Department of Electrical&Computer Engineering University of Michigan-Dearborn Dearborn USA Department of Computer Engineering Alanya Alaaddin Keykubat University Alanya Turkiye School of Public Health The University of Texas Health Science Center at Houston Houston United States Department of Psychology and Statistics University of Michigan Ann Arbor MI USA

ISBN: (数字)9798331507695

ISBN: (纸本)9798331507701

This paper explores innovative machine learning technologies for the detection of Alzheimer's Disease (AD) from large and imbalanced clock drawing test (CDT) images. We present a deep ensemble learning framework, 2Level MM-MD, which includes two-level ensemble of MultiModel deep neural networks (DNN) trained on MultiData blocks. The data blocks are generated by applying partition based and bootstrap statistical data resampling methods to the large but imbalanced CDT image data. To produce a more robust system that is better adapted to imbalanced CDT data, the 2Level MM-MD ensemble framework attempts to leverages both 1) the richness of large data blocks generated using effective data re-sampling schemes, and 2) multiple deep neural network systems that are trained on the resembled data blocks through transfer learning to produce a more robust system that is better adapted to more generalized CDT image domains. Three deep neural network models (EfficientNet, ResNet101, and ViT), along with six different sampling methods are used to generate re-balanced data blocks, and five different decision schemes are implemented and evaluated. The ensemble systems are trained and evaluated using a large CDT image dataset from Rounds 1 to 9 of the National Health and Aging Trends Study (NHATS), which contains over 47,723 CDT images, where 92% are class 0 (no dementia) and 8% are class 1 (probable dementia). The top classification system is a 2Level MM-MD system E5 with a two-level decision rule SoM. The system generated 0.67 Recall and 0.35 F1-Score on the test data. This represents a 123% improvement in Recall and a 25% improvement in F1-Score compared to the best baseline system, which is a classifier trained using EfficientNet with the training data balanced by oversampling the minority class.

关键词： Transfer learning Training data Artificial neural networks Aging Sampling methods Probabilistic logic Data models Ensemble learning Alzheimer's disease Clocks

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