Electrical and Electronics Commons^™

Metaheuristic Optimization Techniques Used In Controlling Of An Active Magnetic Bearing System For High-Speed Machining Application, Suraj Suraj, Pabitra Kumar Biswas Pabitra Kumar Biswas, Sukanta Debnath, Anumoy Ghosh, Thanikanti Sudhakar Babu, Hossam Zawbaa, Salah Kemal

Articles

Smart control tactics, wider stability region, rapid reaction time, and high-speed performance are essential requirements for any controller to provide a smooth, vibrationless, and efficient performance of an in-house fabricated active magnetic bearing (AMB) system. In this manuscript, three pre-eminent population-based metaheuristic optimization techniques: Genetic algorithm (GA), Particle swarm optimization (PSO), and Cuckoo search algorithm (CSA) are implemented one by one, to calculate optimized gain parameters of PID controller for the proposed closed-loop active magnetic bearing (AMB) system. Performance indices or, objective functions on which these optimization techniques are executed are integral absolute error (IAE), integral square error (ISE), integral …

Performance Improvement Of Hybrid System Based Dfig-Wind/Pv/Batteries Connected To Dc And Ac Grid By Applying Intelligent Control, Younes Sahri, Salah Tamalouzt, Sofia Lalouni Belaid, Mohit Bajaj, Sherif S.M. Ghoneim, Hossam Zawbaa, Salah Kamel

Articles

One of the main causes of CO2 emissions is the production of electrical energy. Therefore, many researchers goal’s is to develop renewable power systems. This paper proposes a new intelligent control development of hybrid PV–Wind-Batteries. Neuro-Fuzzy Direct Power Control (NF-DPC) is invested in order to enhance system performance and generated currents quality. An improved MPPT algorithm based on Fuzzy Controller (FC) is invested for PV power optimization. In addition, a new Modified Fuzzy Direct Power Control (MF-DPC) is developed and applied to the grid side converter to control the active and reactive power by monitoring the involved active power flow …

Local Electricity Market Operation In Presence Of Residential Energy Storage In Low Voltage Distribution Network: Role Of Retail Market Pricing, Aziz Saif, Shafi K. Khadem Shafi K. Khadem, Michael Conlon, Brian Norton

Articles

Local Electricity Market (LEM) appears as a promising consumer-centric market-based approach that extends the self-consumption method, widely implemented in residential households, to collective self-consumption in the local energy communities, enabled through peer-to-peer (P2P) transactions. To facilitate the integration of LEM in the wholesale electricity market (WEM), it is paramount to comprehend the synergy of retail electricity pricing on the LEM operation hosted in the low-voltage distribution network (LVDN). The paper presents a co-simulation framework consisting of a local electricity market model coupled with a three-phase distribution network simulator to perform a holistic case study for a smart energy community in …

Nipuna: A Novel Optimizer Activation Function For Deep Neural Networks, Golla Madhu, Sandeep Kautish, Khalid Abdulaziz Alnowibet, Hossam Zawbaa, Ali Wagdy Mohamed

Articles

In recent years, various deep neural networks with different learning paradigms have been widely employed in various applications, including medical diagnosis, image analysis, self-driving vehicles and others. The activation functions employed in deep neural networks have a huge impact on the training model and the reliability of the model. The Rectified Linear Unit (ReLU) has recently emerged as the most popular and extensively utilized activation function. ReLU has some flaws, such as the fact that it is only active when the units are positive during back-propagation and zero otherwise. This causes neurons to die (dying ReLU) and a shift in …

Analysis Of Degradation Of Sb2se3 Thin Film Solar Cells Deploying A Time-Dependent Approach Linked With 1d-Amps Simulation, Ming-Lang Tseng, Malek Gassoumi, Nima Ghadiri

Articles

In this paper, we have developed a time-dependent model to study defect growth in the absorber layer of Sb2Se3 thin film solar cells. This model has been integrated with the AMPS-1D simulation platform to investigate the impact of increasing defect density at different positions within the Sb2Se3 layer on the electrical parameters of the solar cell. We adopted the Gloeckler standard model for thin films in AMPS to represent Sb2Se3 materials. The study focuses on tracking the degradation of device performance parameters as donor-like mid-gap states accumulate in the Sb2Se3 layer over time. We monitored the variation of key electrical …

Interpreting Energy Utilisation With Shapley Additive Explanations By Defining A Synthetic Data Generator For Plausible Charging Sessions Of Electric Vehicles, Prasant Kumar Mohanty, Gayadhar Panda, Malabika Basu, Diptendu Sinha Roy

Articles

Electric vehicles (EVs) are an effective solution for reducing reliance on non-renewable energy sources. However, the lack of charging infrastructure and concerns over their range are some of the biggest hurdles to adopting EVs. Charging infrastructure for EVs is, however, on the rise. Proper planning of charging stations vis-`a-vis road networks and related points of interest such as transportation hubs, schools, shopping centres, etc., alongside such roads become vital to laying out a plan for such infrastructure, particularly for developing countries like India where EV adoption is relatively in a nascent stage. Synthetic datasets can help overcome these hurdles and …

Lightnet: A Novel Lightweight Convolutional Network For Brain Tumor Segmentation In Healthcare, Dongyuan Wu, Junyi Tao, Zhen Qin, Rao Asad Mumtaz, Jin Qin, Linfang Yu, Jane Courtney

Articles

Diagnosis, treatment planning, surveillance, and the monitoring of clinical trials for brain diseases all benefit greatly from neuroimaging-based tumor segmentation. Recently, Convolutional Neural Networks (CNNs) have demonstrated promising results in enhancing the efficiency of image-based brain tumor segmentation. Most current work on CNNs, however, is devoted to creating increasingly complicated convolution modules to improve performance, which in turn raises the computing cost of the model. This work proposes a simple and effective feed-forward CNN, LightNet (Light Network). Based on multi-path and multi-level, it replaces traditional convolutional methods with light operations, which reduces network parameters and redundant feature maps. In the …

Optical Properties Of Periodically And Aperiodically Nanostructured P-N Junctions, Z. Taliashvili, E Łusakowska E Łusakowska, S. Chusnutdinow, A. Tavkhelidze, L. Jangidze, S. Sikharulidze, Nima Ghadiri, Z. Chubinidze, R. Melkadze

Articles

Recently, semiconductor nanograting layers have been introduced and their optical properties have been studied. Spectroscopic ellipsometry has shown that nanograting significantly modifies the dielectric function of c-Si layers. Photoluminescence spectroscopy reveals the emergence of an emission band with a remarkable peak structure. It has been observed that nanograting also alters the electronic and magnetic properties. In this study, we investigate the quantum efficiency and spectral response of Si p-n junctions fabricated using subwavelength grating layers and aperiodically nanostructured layers.

Energy-Aware Ai-Driven Framework For Edge-Computing-Based Iot Applications, Muhammad Zawish, Nouman Ashraf, Rafay Iqbal Ansari, Steven Davy

Conference papers

The significant growth in the number of Internet of Things (IoT) devices has given impetus to the idea of edge computing for several applications. In addition, energy harvestable or wireless-powered wearable devices are envisioned to empower the edge intelligence in IoT applications. However, the intermittent energy supply and network connectivity of such devices in scenarios including remote areas and hard-to-reach regions such as in-body applications can limit the performance of edge computing-based IoT applications. Hence, deploying state-of-the-art convolutional neural networks (CNNs) on such energy-constrained devices is not feasible due to their computational cost. Existing model compression methods, such as network …

Wind Energy Harvesting And Conversion Systems: A Technical Review, Sinhara M. H. D. Perera, Ghanim Putrus, Michael Conlon, Mahinsasa Narayana, Keith Sunderland

Articles

Wind energy harvesting for electricity generation has a significant role in overcoming the challenges involved with climate change and the energy resource implications involved with population growth and political unrest. Indeed, there has been significant growth in wind energy capacity worldwide with turbine capacity growing significantly over the last two decades. This confidence is echoed in the wind power market and global wind energy statistics. However, wind energy capture and utilisation has always been challenging. Appreciation of the wind as a resource makes for difficulties in modelling and the sensitivities of how the wind resource maps to energy production results …

Co-Design Of An Interactive Wellness Park: Exploring Design Requirements For A Multimodal Outdoor Physical Web Installation With Older Adults, Fatima Badmos

Academic Posters Collection

The global demographic landscape is experiencing a notable shift, characterised by a growing proportion of adults over 60. According to projections, the proportion of individuals aged 60 and above is expected to reach one-sixth of the global population by 2030. Furthermore, by 2050, this demographic is projected to exceed a staggering two billion people. Amidst this shift, there is an urgent need to develop interactive and innovative solutions to address older adults' unique challenges, particularly in outdoor physical activity.

A co-design methodology involving older adults’ participation from the idea generation to the application development process will be adopted to address …

Household Electricity Consumption: A Study On The Role Of Micro-Renewable Energy Systems In Vietnam, Luong Vinh Quoc Duy, Damien Cassells, Jim Hanly

Articles

Although nearly all households in Vietnam have connected to the national grid, electricity shortage in the residential sector is still an issue. One measure of residential electricity shortage is the micro-renewable energy system (micro-RES), but little is known about the drivers for household adoption of such system and whether the presence of a micro-RES can help to reduce household energy consumption. This paper examines the characteristics of households that have adopted a micro-RES and investigates whether the presence of micro-RES would result in a decrease in energy demand by using fixed-effects models. Analysis was carried out on the 2016 and …

(3-Aminopropyl) Triethoxysilane-Based Immobilization Of Pt/Wo3 On A Microfiber Sensor For High Sensitivity Hydrogen Sensing, Qiao Gao, Bin Liu, Juan Liu, Shengpeng Wan, Tao Wu, Xing-Dao He, Ping Lu, Jinhui Yuan, Renli Ma, Zabih Ghassemlooy, Gerald Farrell, Qiang Wu

Articles

A novel high stability hydrogen sensor based on a Pt/WO3 coated single-mode tapered-no-core single-mode (STNCS) fiber interferometer is proposed and experimentally studied. The STNCS structure is treated by (3-Aminopropyl) triethoxysilane (APTES) and then coated with Pt/WO3 nanorods. Compared to the traditional method of using poly (dimethylsiloxane) (PDMS) to adhere Pt/WO3 nanorods on the fiber surface, the APTES modified fiber forms strong covalent bonds with Pt/WO3 with stronger adhesion to the fiber surface, resulting in improved long-term stability. Experimental results show that the sensitivity of the sensor varies from -31.05 nm/% to -4.30 nm/% as the hydrogen concentration increases from 0 …

The Role Of Soc In Ensuring The Security Of Iot Devices: A Review Of Current Challenges And Future Directions, Hajar Bennouri, Abdiaziz Abdi, Iqbal Hossain, Alexandre Pujol

Conference papers

The growing popularity and deployment of Internet of Things (IoT) devices has led to serious security concerns. The integration of a security operations center (SOC) becomes increasingly important in this situation to ensure the security of IoT devices. In this article, we will present a summary of IoT device security issues, their vulnerabilities, a review of current challenges to keep these devices secure, and discuss the role that SOC can bring in protecting IoT devices while considering the challenges encountered and the directions to consider when implementing a reliable SOC for IoT monitoring.

Load-Adjusted Prediction For Proactive Resource Management And Video Server Demand Profiling, Obinna Izima, Ruairí De Fréin

Articles

To lower costs associated with providing cloud resources, a network manager would like to estimate how busy the servers will be in the near future. This is a necessary input in deciding whether to scale up or down computing requirements. We formulate the problem of estimating cloud computational requirements as an integrated framework comprising of a learning and an action stage. In the learning stage, we use Machine Learning (ML) models to predict the video Quality of Delivery (QoD) metric for cloud-hosted servers and use the knowledge gained from the process to make resource management decisions during the action stage. …

A Broadband Circularly Polarised Slot Antenna For Ambient Rf Energy Harvesting Applications, Khatereh Nadali, Patrick Mcevoy, Max Ammann

Conference papers

Energy harvesting is a potential source of power for integrating compact low-power and self-sustainable wireless devices in ambient backscatter communication systems and IoT networks. In this paper, an electrically small circularly polarised (CP) slot antenna for harvesting is proposed. The measured CP bandwidth for axial ratio values less than 3 dB is 990 MHz (1.7 GHz to 2.69 GHz), while the measured impedance bandwidth is 1,930 MHz (1.45 GHz to 3.38 GHz). The proposed structure can harvest energy from common radio frequency signal emitters operating in GSM 1800/1900, 3G/LTE 2100, 3G/LTE 2300, 4G/LTE 2500, and 2.4GHz Wi-Fi bands, which makes …

A Broadband Cp Elliptical-Slot Antenna For Ambient Rf Energy Harvesting, Khatereh Nadali, Patrick Mcevoy, Max Ammann

Conference papers

In this paper, a compact broadband CPW-fed circularly polarised elliptical-slot antenna with an inverted- L tuning stub is proposed. The antenna impedance is optimized for broadband operation from 1.62 GHz to 2.97 GHz. The measured CP bandwidth is 934 MHz (1.747-2.681 GHz), that covers common wireless communication bands GSM 1800, GSM 1900, 3G/LTE 2100, 3G/LTE 2300, 4G/LTE 2500, and 2.4GHz Wi-Fi bands. This makes the designed antenna an appropriate candidate for ambient RF energy harvesting purposes.

Optimization Based On Movable Damped Wave Algorithm For Design Of Photovoltaic/ Wind/ Diesel/ Biomass/ Battery Hybrid Energy Systems, Mohammed Kharrich, Salah Kamel, Mamdouh Abdel-Akher, Ahmad Eid, Hossam Zawbaa, Jonghoon Kim

Articles

The actual energetic situation has several challenges such as pollution, the rarefaction of fossil fuel and the dangers of nuclear. Renewable sources are proposed as a solution and suggested, such as a cost-effectiveness system. The paper deals with the problem of feeding a domestic load with electricity which should respect the ecologies factors, so this work is a design problem of the hybrid renewable energy systems; PV/biomass, PV/diesel/battery, PV/wind/diesel/battery, and wind/diesel/battery to choose the best one of them which feed the load with the lowest cost. The study’s goal is to design a microgrid system by the minimization of the …

Efficient Flatness Based Energy Management Strategy For Hybrid Supercapacitor/Lithium-Ion Battery Power System, Salam J. Yaqoob, Seydali Ferahtia, Adel Obed, Hegazy Rezk, Naseer Tawfeeq Alwan, Hossam Zawbaa, Salah Kamel

Articles

This article offers a flatness theory-based energy management strategy (FEMS) for a hybrid power system consisting of a supercapacitor (SC) and lithium-ion battery. The proposed FEMS intends to allocate the power reference for the DC/DC converters of both the battery and SC while attaining higher effciency and stable DC bus voltage. First, the entire system model is analyzed theoretically under the differential flatness approach to reduce the model order as a at system. Second, the proposed FEMS is validated under different load conditions using MATLAB/Simulink. Thus, this FEMS provides high-quality energy to the load and reduces the fluctuations in the …

Optimal Design Of Photovoltaic, Biomass, Fuel Cell, Hydrogen Tank Units And Electrolyzer Hybrid System For A Remote Area In Egypt, Abd El-Sattar Abd El-Sattar, Salah Kamel, Hamdy M. Sultan, Hossam Zawbaa, Francisco Jurado

Articles

In this paper, a new isolated hybrid system is simulated and analyzed to obtain the optimal sizing and meet the electricity demand with cost improvement for servicing a small remote area with a peak load of 420 kW. The major configuration of this hybrid system is Photovoltaic (PV) modules, Biomass gasifier (BG), Electrolyzer units, Hydrogen Tank units (HT), and Fuel Cell (FC) system. A recent optimization algorithm, namely Mayfly Optimization Algorithm (MOA) is utilized to ensure that all load demand is met at the lowest energy cost (EC) and minimize the greenhouse gas (GHG) emissions of the proposed system. The …

Enhanced Chaotic Manta Ray Foraging Algorithm For Function Optimization And Optimal Wind Farm Layout Problem, Fatima Dadqaq, Rachid Ellaia, Mohammed Ouassaid, Hossam Zawbaa, Salah Kamel

Articles

Manta ray foraging optimization (MRFO) algorithm is relatively a novel bio-inspired optimization technique directed to given real-world engineering problems. In this present work, wind turbines layout (WTs) inside a wind farm is considered a real nonlinear optimization problem. In spite of the better convergence of MRFO, it gets stuck into local optima for large problems. The chaotic sequences are among the performed techniques used to tackle this shortcoming and improve the global search ability. Therefore, ten chaotic maps have been embedded into MRFO. To affirm the performance of the suggested chaotic approach CMRFO, it was First assessed using the IEEE …

Hosting A Community-Based Local Electricity Market In A Residential Network, Aziz Saif, Shafi K. Khadem, Michael Conlon, Brian Norton

Articles

This paper presents the potential of building a local electricity market (LEM) to boost the deployment of the local energy communities, centred around active customers with distributed energy resources (DERs). To conduct a comprehensive and detailed study on different cases with reduced computational burdens, this paper adopts a simplified modelling approach where the market and network model simulations are performed in a cascaded, decoupled fashion. This allows achieving the optimal LEM output for the energy community with different DER assets that are not bounded by the network constraints. The investigation involves quantifying the benefits brought by LEM to energy communities …

The Environmental Aspects Of Renewable Energy Consumption And Structural Change In Sweden: A New Perspective From Wavelet-Based Granger Causality Approach, Tomiwa Sunday Adebayo, Ridwan Lanre Ibrahim, Ephraim Bonah Agyekum, Hossam Zawbaa, Salah Kamel

Articles

The current paper assessed the time-frequency analysis interrelationship between CO2 emissions and financial development, economic growth, renewable energy use, structural change, and non-renewable energy use in Sweden. We utilized a quarterly dataset stretching from 1980-2019. In order to unlock these interrelationships, we leverage wavelet tools (wavelet-based Granger causality and wavelet coherence). The wavelet-based Granger causality (WGC) test accounts for the issue of multiple time scales in a time series analysis. Another uniqueness of the WGC lies in its resistance to distribution assumption and misspecification in a time series model. Additionally, the wavelet coherence estimator instantaneously evaluates correlation and causality among …

A Survey Of Machine Learning Techniques For Video Quality Prediction From Quality Of Delivery Metrics, Obinna Izima, Ruairí De Fréin, Ali Malik

Articles

A growing number of video streaming networks are incorporating machine learning (ML) applications. The growth of video streaming services places enormous pressure on network and video content providers who need to proactively maintain high levels of video quality. ML has been applied to predict the quality of video streams. Quality of delivery (QoD) measurements, which capture the end-to-end performances of network services, have been leveraged in video quality prediction. The drive for end-to-end encryption, for privacy and digital rights management, has brought about a lack of visibility for operators who desire insights from video quality metrics. In response, numerous solutions …

Optimal Placement Of Fuses And Switches In Active Distribution Networks Using Value-Based Minlp, N. Gholizadeh, S.H. Hosseinian, M. Abedi, Hamed Nafisi, P. Siano

Articles

Contingency conditions in distribution networks create financial losses for different parts of the system including electricity customers, electricity retailers, distributed generation (DG) units, etc. Therefore, protective device allocation methods have been introduced in recent years to enhance the reliability of the power system. In this study, a new formulation is proposed to find the optimal places of sectionalizing switches and fuses while taking the financial loss of both electricity customers and DG units into account. The current method has the flexibility to consider DG effect on any location of the network and its islanded operation in case of contingencies. Moreover, …

Grammatical Evolution For Detecting Cyberattacks In Internet Of Things Environments, Hasanen Alyasiri, John Clark, Ali Malik, Ruairí De Fréin

Conference papers

The Internet of Things (IoT) is revolutionising nearly every aspect of modern life, playing an ever greater role in both industrial and domestic sectors. The increasing frequency of cyber-incidents is a consequence of the pervasiveness of IoT. Threats are becoming more sophisticated, with attackers using new attacks or modifying existing ones. Security teams must deal with a diverse and complex threat landscape that is constantly evolving. Traditional security solutions cannot protect such sys- tems adequately and so researchers have begun to use Machine Learning algorithms to discover effective defence systems. In this paper, we investigate how one approach from the …

Flying Free: A Research Overview Of Deep Learning In Drone Navigation Autonomy, Thomas Lee, Susan Mckeever, Jane Courtney

Articles

With the rise of Deep Learning approaches in computer vision applications, significant strides have been made towards vehicular autonomy. Research activity in autonomous drone navigation has increased rapidly in the past five years, and drones are moving fast towards the ultimate goal of near-complete autonomy. However, while much work in the area focuses on specific tasks in drone navigation, the contribution to the overall goal of autonomy is often not assessed, and a comprehensive overview is needed. In this work, a taxonomy of drone navigation autonomy is established by mapping the definitions of vehicular autonomy levels, as defined by the …

An Lpc Pole Processing Method For Enhancing The Identification Of Dominant Spectral Features, Jin Xu, Mark Davis, Ruairí De Fréin

Articles

This paper proposes a new time-resolved spectral analysis method based on a modification to the linear predictive coding (LPC) method for enhancing the identification of the dominant frequencies of a signal. The method described here is based on a z-plane analysis of the LPC poles. These poles are used to produce a series of reduced order filter transfer functions which can accurately identify and estimate the frequency of the dominant spectral features. The standard LPC method has been shown to suffer from a sensitivity to noise and its performance is dependent on the filter order. The proposed method can …

A Two-Level Information Modelling Translation Methodology And Framework To Achieve Semantic Interoperability In Constrained Geoobservational Sensor Systems, Paul Stacey

Doctoral

As geographical observational data capture, storage and sharing technologies such as in situ remote monitoring systems and spatial data infrastructures evolve, the vision of a Digital Earth, first articulated by Al Gore in 1998 is getting ever closer. However, there are still many challenges and open research questions. For example, data quality, provenance and heterogeneity remain an issue due to the complexity of geo-spatial data and information representation.

Observational data are often inadequately semantically enriched by geo-observational information systems or spatial data infrastructures and so they often do not fully capture the true meaning of the associated datasets. Furthermore, data …

Using Case Studies In Engineering Ethics Education: The Case For Immersive Scenarios Through Stakeholder Engagement And Real Life Data, Diana Adela Martin, Eddie Conlon, Brian Bowe

Articles

Our contribution is part of a broader study conducted in cooperation with the national accreditation body Engineers Ireland that examined the conceptualisation and education of ethics in engineering programmes in Ireland. The paper is a qualitative examination of the use of case studies in engineering ethics education and includes 23 engineering programmes from 6 higher education institutions in Ireland. The qualitative study aims to determine (RQ1) how cases are selected, (RQ2) the goals envisioned for engineering ethics case instruction, (RQ3) the characteristics of the scenarios employed and (RQ4) the preferred application by instructors. A first finding notes the diverse set …