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15th IFIP Wireless and Mobile Networking Conference, WMNC 2024

作者： Bouras, Christos Diasakos, Damianos Kokkinos, Vasileios Prodromos, Nikolaos Gkamas, Apostolos Pouyioutas, Philippos University of Patras Computer Engineering and Informatics Department Patras Greece University of Ioannina Department of Chemistry Ioannina Greece University of Nicosia Computer Science Department Nicosia Cyprus

ISBN: (纸本)9783903176683

The integration of drone technology with 5G networks presents novel opportunities for enhancing wireless communication systems. This paper explores the application of beamforming optimization techniques in dynamic environments, specifically focusing on moving drones in a simulated environment based on the DeepMIMO O1 scenario. By leveraging the unique properties of the O1 drone setup of DeepMIMO simulation environment, which simulates realistic urban mobility patterns at millimeter-wave (mmWave) frequencies, we propose a novel beamforming algorithm designed to optimize the signal quality and stability in highly mobile aerial networks. Key performance metrics used in this study include Signal-to-Noise Ratio (SNR), battery consumption, and power consumption of both the drones and the base station. Our findings indicate that the adaptive beamforming algorithm not only enhances the SNR and reduces power consumption but also optimizes battery usage compared to conventional beamforming methods. This study enhances the understanding of mmWave beamforming dynamics in aerial scenarios but also lays the groundwork for future advancements in drone-based communication networks. © 2024 IFIP.

关键词： 5G mobile communication systems

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Data-driven Predictive Maintenance Alerting Routine for utility-scale Photovoltaic Systems 3

Data-driven Predictive Maintenance Alerting Routine for util...

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3rd International Conference on Energy Transition in the Mediterranean Area, SyNERGY MED 2024

作者： Marangis, Demetris Livera, Andreas Makrides, George Georgiou, George E. University of Cyprus PV Technology Laboratory Department of Electrical and Computer Engineering Cyprus Efficient and Sustainable Energy Solutions PHAETHON Centre of Excellence for Intelligent Nicosia Cyprus

ISBN: (纸本)9798350375923

Predictive maintenance is crucial for optimizing the performance of photovoltaic (PV) systems by proactively addressing potential issues before they escalate. Even though many fault diagnosis methods have been proposed, a major challenge remains the lack of accurate predictive maintenance routines for utility-scale PV systems. The scope of this work is to address this fundamental challenge by proposing a data-driven predictive maintenance alerting routine (that leverages digital twin technologies and decision rules) for detecting and predicting PV system faults. The results demonstrated that the developed predictive maintenance routine yielded a sensitivity of 93.9% for PV utility-scale failure detection over a yearly test period. The findings of the predictive maintenance alerting model proved its capability to anticipate faults up to 10 days in advance, achieving a sensitivity of 83.3%. Finally, the predictive maintenance alerting system can be used by operation and maintenance teams for scheduling corrective actions and optimizing field activities. © 2024 IEEE.

关键词： Predictive maintenance

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Classifying Tomorrow's Currents: A Probabilistic Neural Network Approach to Forecasting Electricity Prices 3

Classifying Tomorrow's Currents: A Probabilistic Neural Netw...

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3rd International Conference on Energy Transition in the Mediterranean Area, SyNERGY MED 2024

作者： Loizidis, Stylianos Livera, Andreas Kyprianou, Andreas Georghiou, George E. University of Cyprus PV Technology Laboratory Department of Electrical and Computer Engineering Nicosia Cyprus Efficient and Sustainable Energy Solutions PH AET HON Centre of Excellence for Intelligent Nicosia Cyprus University of Cyprus Department of Mechanical and Manufacturing Engineering Nicosia Cyprus

ISBN: (纸本)9798350375923

This study introduces a probabilistic neural network model for classifying next-day electricity prices into negative or positive categories. It addresses the challenge of price volatility exacerbated by renewable energy integration, presenting significant risks for market participants. Through a comparative analysis with the traditional support vector machine with radial basis function kernel using the German Day-Ahead market data of 2020, the probabilistic neural network demonstrates superior accuracy and yielded promising electricity price forecasting results. This approach equips market participants with valuable insights for strategic planning and risk mitigation. © 2024 IEEE.

关键词： Neural network models

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Examining the economic feasibility of hybrid Photovoltaic - Battery Energy Storage System in public building with flexible demand: cyprus case study 3

Examining the economic feasibility of hybrid Photovoltaic - ...

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3rd International Conference on Energy Transition in the Mediterranean Area, SyNERGY MED 2024

作者： Chatzigeorgiou, Nikolas G. Makrides, George Theocharides, Spyros Georghiou, George E. University of Cyprus PV Technology Laboratory Department of Electrical and Computer Engineering Cyprus PHAETHON Centre of Excellence for Intelligent Efficient and Sustainable Energy Solutions Nicosia Cyprus

ISBN: (纸本)9798350375923

Photovoltaic - Battery Energy Storage Systems (PVBESS) are a promising solution against technical bottlenecks of high PV penetration. Public buildings are suitable for installation, although currently underexploited, while high BESS costs limit technology diffusion. This paper assesses the economic feasibility of PV-BESS in public buildings with flexible demand, through simulations showcasing BESS subsidisation impact and self-sufficiency contribution. The results derived that smaller PV-BESS sizes are more attractive investments, as larger systems are characterised by reduced profitability, while BESS subsidisation enhances system profitability. Shifting a small portion of load demand improves economic feasibility by decreasing BESS size, while combining PV production, energy storage, and energy flexibility is the optimal solution for public buildings against electricity prices. Finally, a trade-off between economic feasibility and energy self-sufficiency is observed. The results can be utilised by policymakers to design strategies for BESS promotion, while professionals can perform accurate system sizing, thus avoiding excess system capacities. © 2024 IEEE.

关键词： Battery storage

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(ω1,ω2)-temporal random hyperbolic graphs

arXiv

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arXiv 2024年

作者： Zambirinis, Sofoclis Papadopoulos, Fragkiskos Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Limassol3036 Cyprus

We extend a recent model of temporal random hyperbolic graphs by allowing connections and disconnections to persist across network snapshots with different probabilities, ω1 and ω2. This extension, while conceptually simple, poses analytical challenges involving the Appell F1 series. Despite these challenges, we are able to analyze key properties of the model, which include the distributions of contact and intercontact durations, as well as the expected time-aggregated degree. The incorporation of ω1 and ω2 enables more flexible tuning of the average contact and intercontact durations, and of the average time-aggregated degree, providing a finer control for exploring the effect of temporal network dynamics on dynamical processes. Overall, our results provide new insights into the analysis of temporal networks and contribute to a more general representation of real-world scenarios. Copyright © 2024, The Authors. All rights reserved.

关键词： Network theory (graphs)

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A NEW STEPSIZE STRATEGY FOR KORPELEVICH’S ALGORITHM SOLVING VARIATIONAL INEQUALITIES

Applied Set-Valued Analysis and Optimization

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Applied Set-Valued Analysis and Optimization 2024年第3期6卷 309-317页

作者： Trinh, Ngoc Hai Tran, Trung Duc Faculty of Mathematics and Informatics Hanoi University of Science and Technology Hanoi Viet Nam College of engineering and computer science VinUniversity Hanoi Viet Nam

In this paper, we propose two self-adaptive extragradient-like algorithms for solving pseudomonotone variational inequalities. We consider two cases: the mapping is Lipschitz continuous (with unknown modulus) and is not Lipschitz continuous. The step size in our algorithms can either increase or decrease at each step. This feature makes our algorithms more efficient. We also give some numerical examples to compare the performance of our algorithm with the existing one. ©2024 Applied Set-Valued Analysis and Optimization.

关键词： Variational techniques

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Vision-Based Navigation for a Small-Sized Drone: A Simple AI Strategy at IMAV'22

Vision-Based Navigation for a Small-Sized Drone: A Simple AI...

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2024 IEEE International Conference on Cybernetics and Innovations, ICCI 2024

作者： Farooq, Adil Nain Zukhraf, Syeda Zillay Shafi, Sadman Kamal, Mohsin Chumuang, Narumol University Of Cyprus Department Of Electrical And Computer Engineering Cyprus Penn State University Department Of Electrical Engineering United States National University Of Sciences And Technology School Of Electrical Engineering And Computer Science Pakistan Muban Chombueng Rajabhat University Department Of Digital Media Technology Thailand

ISBN: (纸本)9798350370096

Autonomous drone racing competitions serve as a testing ground for enhancing the perceptual, planning, and control aspects of micro unmanned aerial vehicles (MAVs). This study thoroughly outlines the strategy, methodology, and technical development of a lightweight collision avoidance module for small drones, employed during our participation in the IMAV 2022 Nanocopter AI Challenge held at TU Delft, The Nether-lands. Tailored for nano-sized drones, this competition presented challenges related to agile maneuvers, obstacle avoidance, and navigation in a dynamic indoor arena. We provide detailed insights into our obstacle avoidance algorithm, employing an AI computer vision approach and showcasing its robust performance in dynamic environments. The accuracy of the proposed strategy was verified through simulation testing, highlighting the effectiveness of our approach in a simulated Webots environment across diverse parameter settings. The shared insights aim to contribute significantly to the ongoing evolution of autonomous drone navigation. Moreover, the simulation of our proposed strategy can be seen on the YouTube video link: https://***/HVZPAfyf57M. © 2024 IEEE.

关键词： Drones

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Sizing and operation of hybrid photovoltaic - battery energy storage system in islanded power networks with high renewable energy curtailments 3

Sizing and operation of hybrid photovoltaic - battery energy...

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3rd International Conference on Energy Transition in the Mediterranean Area, SyNERGY MED 2024

作者： Chatzigeorgiou, Nikolas G. Makrides, George Theocharides, Spyros Georghiou, George E. University of Cyprus PV Technology Laboratory Department of Electrical and Computer Engineering Nicosia Cyprus PHAETHON Centre of Excellence for Intelligent Efficient and Sustainable Energy Solutions Nicosia Cyprus

ISBN: (纸本)9798350375923

Power networks are currently challenged by high renewable energy curtailments (REC), a countereffect of renewables' sporadic nature and high photovoltaic (PV) penetration in grids. This work aims to provide sizing and operation insights for battery energy storage systems (BESS) coupled with PVs, as a solution to mitigate REC, especially in islanded power networks. The derived REC analysis and simulation model results demonstrated the attractiveness of longer BESS-duration and quantified the examined asset's environmental and financial impact. Notably, the longer BESS-duration managed to utilise the available (curtailed) energy to the greatest extent and extended time utilisation. The obtained results provided insights for the practicality of BESS power and energy capacity, useful to policymakers, system operators, and investors for avoiding unnecessary or ineffective investments. © 2024 IEEE.

关键词： Hybrid power

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An Efficient and Robust Hand Gesture Recognition System of Sign Language Employing Finetuned Inception-V3 and Efficientnet-B0 Network

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computer Systems Science & engineering 2023年第9期46卷 3509-3525页

作者： Adnan Hussain Sareer Ul Amin Muhammad Fayaz Sanghyun Seo Department of Computer Science Islamia College UniversityPeshawar25120Pakistan Department of Computer Science and Engineering Chung-Ang UniversitySeoul06974Korea Department of Computer Engineering Cyprus International UniversityLefkosa99010Rep.of North Cyprus College of Art and Technology Chung-Ang.UniversityAnseong17546Korea

Hand Gesture Recognition(HGR)is a promising research area with an extensive range of applications,such as surgery,video game techniques,and sign language translation,where sign language is a complicated structured form of hand *** fundamental building blocks of structured expressions in sign language are the arrangement of the fingers,the orientation of the hand,and the hand’s position concerning the *** importance of HGR has increased due to the increasing number of touchless applications and the rapid growth of the hearing-impaired ***,real-time HGR is one of the most effective interaction methods between computers and *** a user-free interface with good recognition performance should be the goal of real-time HGR ***,Convolutional Neural Network(CNN)shows great recognition rates for different image-level classification *** is challenging to train deep CNN networks like VGG-16,VGG-19,Inception-v3,and Efficientnet-B0 from scratch because only some significant labeled image datasets are available for static hand gesture ***,an efficient and robust hand gesture recognition system of sign language employing finetuned Inception-v3 and Efficientnet-Bo network is proposed to identify hand gestures using a comparative small HGR *** show that Inception-v3 achieved 90%accuracy and 0.93%precision,0.91%recall,and 0.90%f1-score,respectively,while EfficientNet-B0 achieved 99%accuracy and 0.98%,0.97%,0.98%,precision,recall,and f1-score respectively.

关键词： Pretrained CNN hand gesture recognition transfer learning

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Techno-economic evaluation of Energy Community configurations based on the individual economic benefit of the members: the case of cyprus 3

Techno-economic evaluation of Energy Community configuration...

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3rd International Conference on Energy Transition in the Mediterranean Area, SyNERGY MED 2024

作者： Yiasoumas, Georgios Olympios, Andreas V. Georghiou, George E. University of Cyprus PV Technology Laboratory Department of Electrical and Computer Engineering Nicosia Cyprus Efficient and Sustainable Energy Solutions PHAETHON Centre of Excellence for Intelligent Nicosia Cyprus

ISBN: (纸本)9798350375923

Energy Communities (ECs) enable the participation of citizens in the energy transition, facilitating the shift towards a consumer-centric energy system. Given the voluntary and open nature of ECs, the participation of citizens can be challenging, especially in the early stages of development. This paper addresses this by evaluating the individual economic benefits of existing or potential EC members under different EC configurations. Three basic EC configurations were examined for the case of cyprus: (i) the EC acting as an electricity producer and exporter, (ii) the EC acting as an electricity producer for maximum self-consumption, and (iii) the EC members trading energy among themselves using an EC-based local electricity market. The results showcased the potential of ECs as an alternative to traditional RES residential schemes, while also highlighting the economic challenges associated with implementing such configurations. © 2024 IEEE.

关键词： cost allocation Energy Community Local electricity market net metering self-consumption

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