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60th IEEE/IAS Industrial and Commercial Power Systems Technical Conference, I and CPS 2024

作者： Wang, Chenyang Liang, Xiaodong Kaur, Manpreet Manitoba Hydro Transmission & Civil Design Department WinnipegMB Canada University of Saskatchewan Department of Electrical and Computer Engineering SaskatoonSK Canada University of Manitoba Department of Electrical and Computer Engineering WinnipegMB Canada

ISBN: (纸本)9798350345308

The grounding system is an essential part of the transmission line system. In the last decade, more transmission lines have been constructed near urban areas that share the land with other public infrastructures, such as commercial lots, parks, playgrounds, walking trails, etc. This co-location raises safety concerns due to touch and step voltage hazards near transmission line structures under power line faulty conditions. In many countries, there is no national standard to tackle this concern and provide clear regulations. To overcome this issue, a probabilistic risk assessment method is utilized in this paper, which serves as a great tool to quantify this risk and make it possible to compare it with other common risks to develop acceptable criteria. A methodology is developed to determine the probability of risk, and each parameter used in the calculation is refined based on historical operational records and monitoring data. © 2024 IEEE.

关键词： Electric power transmission

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Preface to the Proceedings of the 8th Smart Data Smart Cities (SDSC) conference ISPRS Annals

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ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2024年第4/W4-2024期10卷 1-4页

作者： Pantazis, Dimos N. Karanikolas, Nikitas N. Vassilakopoulos, Michael Coors, Volker Voyiatzis, Ioannis Ellul, Claire Department of Surveying and Geoinformatics Engineering Research laboratory S.O.C.R.A.T.E.S. University of West Attica Greece Department of Informatics and Computer Engineering University of West Attica Greece Department of Electrical and Computer Engineering University of Thessaly Greece Germany Department of Civil Environmental & Geomatic Engineering University College London United Kingdom

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Effect of stator winding chording on the performance of five phase synchronous reluctance motor

Journal of Energy Systems

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Journal of Energy Systems 2024年第1期8卷 11-26页

作者： Umoh, Gideon David Obe, Desmond Obinna Mama, Benjamin Okwudilili Obe, Pauline Ijeoma Ugwuishiwu, Chikodili Helen Eneh, Hyacinth Agozie Obe, Emeka Simon Maritime Academy Electrical Engineering Department Akwa Ibom State Oron Nigeria James Cook University College of Science and Engineering QLD Australia University of Nigeria Civil Engineering Department Enugu State Nsukka Nigeria University of Nigeria Industrial Technical Education Department Enugu State Nsukka Nigeria University of Nigeria Computer Science Department Enugu State Nsukka Nigeria Botswana International University Electrical Computer and Telecommunications Engineering Department Palapye Botswana

The effect of winding chording on five-phase synchronous reluctance motor (SRM) modelled in phase variables is presented. The stator winding configuration is shifted a pole pitch from a full-pitch configuration to a 54 degrees over-full-pitched configuration incorporating the effect of 3rd harmonic of the air-gap magneto-motive force in the inductance equations. The models are monitored on starting, synchronism, loading, faults and loss of synchronism. These are considered simultaneously with vector potential, rotor speed, air-gap flux linkage and winding current. The phase variable (analytical) models have been simulated by using MATLAB/Simulink software while ANSYS Maxwell software has been used to simulate the finite element model (FEM) of the motor for corresponding chording ranges for comparison on direct online starting (DOL). Under all conditions considered in the work, the detailed results are presented and very close similarity is observed between the analytical and the nearly ideal FEM model for all chording ranges and the similarity is enhanced with increase in chording angle. © 2024 Published by peer-reviewed open access scientific journal, JES at DergiPark (https://***/jes)

关键词： Finite element method

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Employing Feature engineering for River Stage Forecasting to Improve Hybrid Model Performance 32

Employing Feature Engineering for River Stage Forecasting to...

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32nd International Conference on Software, Telecommunications and computer Networks, SoftCOM 2024

作者： Mihel, Anna Maria Pecnik, Spela Vrbancic, Grega Lerga, Jonatan Krvavica, Nino University of Rijeka Faculty of Engineering Department of Computer Engineering Rijeka Croatia University of Maribor Intelligent Systems Laboratory Faculty of Electrical Engineering and Computer Science Maribor Slovenia University of Rijeka Faculty of Civil Engineering Department of Hydrotechnics and Geotechnics Rijeka Croatia

ISBN: (纸本)9789532901382

Establishing early warning systems and efficient management of water resources in tidal reaches is crucial for achieving adequate flood protection. In tidal reaches, the river stage interacts non-linearly with tides (downstream) and discharge (upstream), making the modeling of river processes extremely complex. Data-driven methods have proven helpful for predicting the river stage parameter. This contrasts with existing numerical approaches, which suffer from several limitations. The aim of this study was to predict the river stage of the upstream part of the tidal river, where the influence of salinity is present during the summer months. Using the CNN-LSTM model trained on historical records of the discharge (station of the variable to be predicted), the river stage of three downstream stations, and the point of interest, the prediction was carried out up to 24 hours in advance. By incorporating feature engineering, we achieved an improvement in model results for the longest horizon, confirmed by standard performance metrics, and considered it efficient and effective for risk mitigation. Introducing feature engineering into the data preprocessing resulted in a predictive performance improvement of 0.98% for the Nash-Sutcliffe Efficiency (NSE) metric, 7.0% for the root mean squared error (RMSE) metric, and 7.25% for the mean absolute error (MAE) metric over the second and third-best scenarios using a spectrogram and time-series data. © 2024 University of Split, FESB.

关键词： Mean square error

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Hybrid Technique-based Optimal Energy Management in Smart Home Appliances

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IEIE Transactions on Smart Processing and Computing 2024年第5期13卷 425-434页

作者： Shirley, C.P. Depaa, R.A.B. Priya, A. Sarala, R. Solanki, Rajdeep Singh Malini, K.V. Venkatakrishna Reddy, Ch. Department of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India Department of Civil Engineering Dr. M.G.R Educational and Research Institute Maduravoyal Chennai95 India School of Architecture Koneru Lakshmaiah Educational Foundation Andhra Pradesh Guntur India Department of Computer Science and Engineering Velammal College of Engineering and Technology Madurai Rameshwaram High Road Viraganoor Madurai625009 India Department of Computer Science Medi-Caps University Indore India Department of Electrical and Electronics Engineering Sri Sairam College of Engineering Anekal India Department of Electrical and Electronics Engineering Chaitanya Bharathi Institute of Technology Hyderabad75 India

This manuscript presents a hybrid method for optimal energy management in smart home appliances. The proposed approach combines the Ebola Optimization Search Algorithm (EOSA) with the performance of spiking neural networks (SNN). The key objective of the proposed strategy is cost reduction through day-ahead load scheduling while also considering the best demand response (DR), and self-consumption of photovoltaic (PV). The EOSA method manages air conditioning (AC) and ensures thermal comfort. In addition, the SNN method was used to predict the optimal system control signal. Comparative analysis with existing systems, such as PSO, RFA, and BCO, showed that the proposed strategy resulted in 13% cost savings. The proposed system considered parameters, such as solar radiation, occupant presence, and electricity prices. The proposed technique is implemented in the MATLAB software, and the performance is compared with existing approaches. The efficiency of the proposed approach is higher than the existing techniques. © 2024 The Institute of Electronics and Information Engineers.

关键词： Demand response

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Automatic Transportation Mode Classification Using a Deep Reinforcement Learning Approach With Smartphone Sensors

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IEEE Access 2024年 12卷 514-533页

作者： Taherinavid, Siavash Moravvej, Seyed Vahid Chen, Yen-Lin Yang, Jing Ku, Chin Soon Yee, Por Lip Iran University of Science and Technology School of Civil Engineering Tehran13114-16846 Iran Isfahan University of Technology Department of Electrical and Computer Engineering Isfahan84156-83111 Iran National Taipei University of Technology Department of Computer Science and Information Engineering Taipei106344 Taiwan Universiti Malaya Faculty of Computer Science and Information Technology Department of Computer System and Technology Kuala Lumpur50603 Malaysia Universiti Tunku Abdul Rahman Department of Computer Science Kampar31900 Malaysia

The increasing dependence on smartphones with advanced sensors has highlighted the imperative of precise transportation mode classification, pivotal for domains like health monitoring and urban planning. This research is motivated by the pressing demand to enhance transportation mode classification, leveraging the potential of smartphone sensors, notably the accelerometer, magnetometer, and gyroscope. In response to this challenge, we present a novel automated classification model rooted in deep reinforcement learning. Our model stands out for its innovative approach of harnessing enhanced features through artificial neural networks (ANNs) and visualizing the classification task as a structured series of decision-making events. Our model adopts an improved differential evolution (DE) algorithm for initializing weights, coupled with a specialized agent-environment relationship. Every correct classification earns the agent a reward, with additional emphasis on the accurate categorization of less frequent modes through a distinct reward strategy. The Upper Confidence Bound (UCB) technique is used for action selection, promoting deep-seated knowledge, and minimizing reliance on chance. A notable innovation in our work is the introduction of a cluster-centric mutation operation within the DE algorithm. This operation strategically identifies optimal clusters in the current DE population and forges potential solutions using a pioneering update mechanism. When assessed on the extensive HTC dataset, which includes 8311 hours of data gathered from 224 participants over two years. Noteworthy results spotlight an accuracy of 0.88±0.03 and an F-measure of 0.87±0.02, underscoring the efficacy of our approach for large-scale transportation mode classification tasks. This work introduces an innovative strategy in the realm of transportation mode classification, emphasizing both precision and reliability, addressing the pressing need for enhanced classification mechanisms in an eve

关键词： Smartphones

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Paths, Proofs, and Perfection: Developing a Human-Interpretable Proof System for Constrained Shortest Paths 38

Paths, Proofs, and Perfection: Developing a Human-Interpreta...

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38th AAAI Conference on Artificial Intelligence, AAAI 2024

作者： Sidorov, Konstantin de Almeida Correia, Gonçalo Homem de Weerdt, Mathijs Demirović, Emir Algorithmics Group Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Netherlands Faculty of Civil Engineering and Geosciences Delft University of Technology Netherlands

ISBN: (纸本)1577358872

People want to rely on optimization algorithms for complex decisions but verifying the optimality of the solutions can then become a valid concern, particularly for critical decisions taken by non-experts in optimization. One example is the shortest-path problem on a network, occurring in many contexts from transportation to logistics to telecommunications. While the standard shortest-path problem is both solvable in polynomial time and certifiable by duality, introducing side constraints makes solving and certifying the solutions much harder. We propose a proof system for constrained shortest-path problems, which gives a set of logical rules to derive new facts about feasible solutions. The key trait of the proposed proof system is that it specifically includes high-level graph concepts within its reasoning steps (such as connectivity or path structure), in contrast to using linear combinations of model constraints. Using our proof system, we can provide a step-by-step, human-auditable explanation showing that the path given by an external solver cannot be improved. Additionally, to maximize the advantages of this setup, we propose a proof search procedure that specifically aims to find small proofs of this form using a procedure similar to A* search. We evaluate our proof system on constrained shortest path instances generated from real-world road networks and experimentally show that we may indeed derive more interpretable proofs compared to an integer programming approach, in some cases leading to much smaller proofs. Copyright © 2024, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Integer programming

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Towards an Optical Chemometric Sensor for Anti-Icing Agents on Asphalt Pavement 11

Towards an Optical Chemometric Sensor for Anti-Icing Agents ...

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11th International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2025

作者： Thörnberg, Benny Klein-Paste, Alex Zhang, Wei Department of Computer and Electrical Engineering Mid Sweden University Holmgatan 10 Sundsvall Sweden Department of Civil and Environmental Engineering NTNU Trondheim Norway

ISBN: (纸本)9789897587450

To ensure traffic safety during winter, chemical agents are typically used for de-icing and anti-icing. Smarter and more precise dispersion of chemicals, which considers local variations in concentration, has the potential to reduce the total amount applied. This paper presents a study of an optical chemometric sensor capable of measuring the NaCl concentration and the weight of the dispersed solution per square meter. The experiment was conducted in an indoor environment, where seven solutions of tap water and NaCl were poured onto a diffuse surface made of burned clay. Short-wave infrared light was illuminated onto the surface, and the light was diffusely reflected into a spectrometer after passing through the liquid layer twice. Absorption in the liquid layer alone can be extracted by subtracting the background and further modeled using Beer-Lambert's law. Both the concentration of NaCl and the amount of liquid can be computed by fitting an overdetermined equation system. Experimental results show a strong correlation between actual and computed concentrations, as well as between actual and computed liquid quantities. Suppression of ambient light, spectral variations of asphalt, harsh environments, dynamic range, and signal-to-noise ratio are among the challenges for outdoor chemometric sensing of asphalt pavements. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Asphalt pavements

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Multi-Objective Transmission Expansion: An Offshore Wind Power Integration Case Study

IEEE Transactions on Energy Markets, Policy and Regulation

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IEEE Transactions on Energy Markets, Policy and Regulation 2024年第4期2卷 519-535页

作者： Khanal, Saroj Graf, Christoph Liang, Zhirui Dvorkin, Yury Unel, Burcin Johns Hopkins University Department of Electrical and Computer Engineering BaltimoreMD21218 United States New York University School of Law Institute for Policy Integrity New YorkNY10012 United States StanfordCA94305 United States Johns Hopkins University Departments of Electrical and Computer Engineering and Civil and Systems Engineering BaltimoreMD21218 United States

Despite ambitious offshore wind targets in the U.S. and globally, offshore grid planning guidance remains notably scarce, contrasting with well-established frameworks for onshore grids. This gap, alongside the increasing penetration of offshore wind and other clean-energy resources in onshore grids, highlights the urgent need for a coordinated planning framework. Our paper describes a multi-objective, multistage generation, storage and transmission expansion planning model to facilitate efficient and resilient large-scale adoption of offshore wind power. Recognizing regulatory emphasis and, in some cases, requirements to consider externalities, this model explicitly accounts for negative externalities: greenhouse gas emissions and local emission-induced air pollution. Utilizing an 8-zone ISO-NE test system and a 9-zone PJM test system, we explore grid expansion sensitivities such as impacts of optimizing Points of Interconnection (POIs) versus fixed POIs, negative externalities, and consideration of extreme operational scenarios. Our results indicate that accounting for negative externalities necessitates greater upfront investment in clean generation and storage (balanced by lower expected operational costs). Optimizing POIs could significantly reshape offshore topology or POIs, and lower total cost. Finally, accounting for extreme operational scenarios typically results in greater operational costs and sometimes may alter onshore line investment. © 2024 IEEE.

关键词： Investments

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ComPSim: A Community based Smart Grid Testbed for Holistic Resilience Analysis 14

ComPSim: A Community based Smart Grid Testbed for Holistic R...

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14th IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2023

作者： Sreejith, Amulya Dhanapala, Prudhviraj Melagoda, Adithya Enderami, Seyyed Amin Aravinthan, Visvakumar Pahwa, Anil Natarajan, Balasubramaniam Kansas State University Department of Electrical & Computer Engineering United States Wichita State University Department of Electrical & Computer Engineering United States University of Kansas Department of Civil Environmental & Architectural Engineering United States

ISBN: (纸本)9781665455541

This paper presents a novel approach to designing a smart grid testbed, that advances the state of knowledge on power system resilience analysis by including the social aspects of the community in simulation. The proposed Community-based Power Simulation virtual testbed, termed ComPSim herein, integrates non-physical dimensions of the community into the smart grid infrastructure system. The ComPSim test bed can be applied to identify the social impacts of power system disruptions. The testbed takes into account diverse socioeconomic characteristics of the community, enabling targeted analysis and policy formulation. This research highlights the need for integrating community's social and economic facet into future infrastructure planning and decision efforts. © 2023 IEEE.

关键词： Smart power grids

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