Electrical and Electronics Commons^™

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 …

Model-Based Cognitive Communications For Low-Power Wireless Networks, Indika Sanjeewa Abeywickrama Dhanapala

Theses

Our world is increasingly being instrumented with low-power wireless networks that deliver data for diverse application domains such as energy management, health and well-being, security, and other Internet of Things services. As these wireless networks operate in the unlicensed radio spectrum while co-existing with various other communication networks, their communication reliability and energy efficiency are affected by the radio environment. Because of this vulnerability to radio interference, low-power wireless networks may be unable to deliver their application requirements and be inefficiently consuming energy, functioning as a low-dependability network. The situation is exacerbated in indoor environments such as office and residential …

Modeling And Control Of Direct-Conversion Hybrid Switched-Capacitor Dc-Dc Converters, Ziyu Xia

Dartmouth College Ph.D Dissertations

Efficient power delivery is increasingly important in modern computing, communications, consumer and other electronic systems, due to the high power demand and thermal concerns accompanied by performance advancements and tight packaging. In pursuit of high efficiency, small physical volume, and flexible regulation, hybrid switched-capacitor topologies have emerged as promising candidates for such applications. By incorporating both capacitors and inductors as energy storage elements, hybrid topologies achieve high power density while still maintaining soft charging and efficient regulation characteristics. However, challenges exist in the hybrid approach. In terms of reliability, each flying capacitor should be maintained at a nominal `balanced' voltage …

The Design Of Cmos Front-End Amplifiers For Electrical Impedance Applications, Yueh-Ching Teng

Dartmouth College Ph.D Dissertations

Electrical Impedance Tomography (EIT) is a medical imaging methodology that does not need any kind of ionizing radiation. It is significantly cheaper and smaller than Computerized Tomography (CT) or Magnetic Resonance Imaging (MRI). These advantages make EIT particularly suitable for emerging applications like the continuous medical imaging and telemonitoring of organ function. Current bench-top EIT systems are bulky and require shielded cables to interface with measurement electrodes. The cable introduces parasitic capacitances which shunt the desired signals and degrade the accuracy of the measurements. A EIT system based on application-specific integrated circuits (ASICs) can reduce the parasitic and stray capacitance …

Magic: The Gathering Card Virtualizer, Vincent Garbonick, Jacen C. Conlan, Jaret A. Varn

Williams Honors College, Honors Research Projects

Any well-versed Magic: The Gathering (MTG) player or collector knows how difficult it can be to keep track of all cards in their collection. Some spend hours searching for that one specific card, and others are constantly scouring the internet for how much their collection costs. However, this issue does not only affect casual fans. Resale companies spend hours a day determining the costs of cards, and tournament judges painstakingly check players’ decks to ensure they are not cheating. To assist with these struggles, the design team proposed to create the MTG Card Virtualizer. This device scans MTG playing cards …

Smart Kettlebell, Cole Russell, Patrick Davis, Ryan Deboer, Isaac Stecker

Williams Honors College, Honors Research Projects

The purpose of design team 08’s senior design project is to create and implement a workout device that will be able to calculate the caloric expenditure, repetitions, and length of a workout. Once the duration of a workout is completed, the user metrics will be communicated from the kettlebell system to a user application via Bluetooth. The caloric expenditure will be used using the data that is provided from the accelerometer. The duration of the workout will be controlled using a push button that is connected to the kettlebell system that will allow for the start and stop of a …

Hardware In The Loop Implementation And Simulations Of A Wave Energy Converter Using Typhoon Hil And Speedgoat, Pranav Nair

Dissertations, Master's Theses and Master's Reports

Several studies have indicated that electricity production is the prime source of greenhouse emissions, more than flying and driving combined. Hence, over the past few decades, there has been a significant rise in the need for clean energy to achieve the targets in emissions reduction. It has been observed that the share of renewable energy sources in the percentage of total electricity production is rising, but, according to climate experts, the transition needs to speed up. Hence, it is significant to study and develop underutilized renewable energy sources.

One of these underutilized renewable energy sources is wave energy. It has …

An Improvement In Protection Coordination And Criteria Settings For Bhutanese Power System, Cheten Tshering

Chulalongkorn University Theses and Dissertations (Chula ETD)

Overcurrent and ground fault relay coordination have been studied for a pilot 132/33/11 kV Substation in Bhutan. The calculated settings as well as the existing settings have been simulated and the critical findings and recommendations are made. The methodology of overcurrent and ground fault relay coordination are also proposed. Similarly, the criteria settings for differential relay have been discussed along with the compensation in respect of CT ratio, vector correction, magnetic inrush and zero sequence filtering. The pickup setting followed by 1st and 2nd slope biasing has been discussed. Further, the distance relay setting has been analysed whereby the parameters …

Classification Of Cardiac Arrhythmias Based On Overlapped Ecg Image With Lightweight Neural Network, Khaing Su Thway

Chulalongkorn University Theses and Dissertations (Chula ETD)

This dissertation presents the classification of different types of cardiac arrhythmias, including Atrial Fibrillation (AF), Normal Sinus Rhythm (NSR), Premature Atrial Contraction (PAC), and Premature Ventricular Contraction (PVC), using a lightweight neural network. A novel ECG data transformation method, referred to as transforming into overlapped ECG images, has been developed and utilized as input images for our neural network. During the transformation process, individual heartbeats within a 30-second time frame are cropped based on heart rate calculations. These resulting beats are then overlapped with respect to the x and y axis limits, generating distinctive images representing different arrhythmia types examined …

Genetic Algorithm Based Deep Multi-Route Self-Attention For Single Image Super-Resolution, Nisawan Ngambenjavichaikul

Chulalongkorn University Theses and Dissertations (Chula ETD)

Image restoration, such as single image super-resolution (SISR), is a long-established low-level vision issue that intends to regenerate high-resolution (HR) images from low-resolution (LR) input counterparts. While state-of-the-art image super-resolution models are based on the well-known convolutional neural network (CNN), many self-attention-based or transformer-based experiment attempts have been conducted. They have shown promising performance on vision problems. A powerful baseline model based on the swin transformer adopts the shifted window approach. It enhances the capability by restricting the model to compute the self-attention function only on non-superimpose local windows while enabling cross-window relations. However, the architecture design is manually fixed. …

A Linear Matrix Inequality Approach To Design State Feedback Control For Non-Polynomial Nonlinear Systems, Phing Lim

Chulalongkorn University Theses and Dissertations (Chula ETD)

This thesis aims to design a state feedback controller for non-polynomial systems with bounded control inputs. The problem formulation begins by transforming the non-polynomial systems into polynomial systems. This can be done by defining non-polynomial terms as new state variables with algebraic constraints satisfying the non-polynomial properties. This method avoids the approximation of the recast polynomial systems. Then we design the state feedback control based on the extended Lyapunov stability theorem and the quadratic performance criterion. Two state feedback control laws are proposed: Theorem 1 for static Lyapunov matrix variables and Theorem 2 for polynomial ones. For Theorem 1, the …

Effect Of Drop-Out Layers Inside Recurrent Neural Networks In Household Load Forecast Application, Sanaullah Soomro

Chulalongkorn University Theses and Dissertations (Chula ETD)

Ensuring precise power load forecasting is highly important in planning the secure, steady, and cost-effective functioning of the power system. Grid planning and decision-making can be based on accurate long- and short-term power load forecasting. Recently, machine learning techniques have gained widespread adoption for both long- and short-term power load forecasting. Specifically, the Long Short-Term Memory (LSTM) is customized for time series data analysis. This research proposes an LSTM model for forecasting the power load of a single house containing electrical appliances over the next 20 days. We conducted a comparative analysis of the impact of dropout layers in load …

Performance Analysis Of Jpeg Xr With Deep Learning-Based Image Super-Resolution, Taingliv Min

Chulalongkorn University Theses and Dissertations (Chula ETD)

The demand for efficient high-level image and video codec compression has widely increased. Conventional image compression methods such as JPEG XR use a high quantization parameter (QP) to produce a highly compressed file for any given image. However, higher QP has unpleasing artifacts that lead to perceptual quality degradation. A feasible solution to tackle this limitation is to reduce the high-resolution image size by downsampling it before encoding it with JPEG XR. Then, the super-resolution algorithm is applied to the resultant low-resolution image to reconstruct the high-resolution result. In this research, we downsample the input image before JPEG XR. Then, …

Deep Consecutive Attention Network For Video Super-Resolution, Talha Saleem

Chulalongkorn University Theses and Dissertations (Chula ETD)

In the video application, slow motion is visually attractive and gets more attention in video super resolution. To generate the high-resolution (HR) slow motion video frames from the low-resolution (LR) frames, two sub-tasks are required, including video super-resolution (VSR) and video frame interpolation (VFI). However, the interpolation approach is not successful to extract low level feature attention to get the maximum advantage from the property of space-time relation. To this extent, we propose a deep consecutive attention network-based method. The multi-head attention and an attentive temporal feature module are designed to achieve better prediction of interpolation feature frame. Bi-directional deformable …

Applications Of Deep Learning Framework And Localization To Intelligent Radio Spectrum Monitoring, Truong Thanh Le

Chulalongkorn University Theses and Dissertations (Chula ETD)

In this thesis, the author proposed an intelligent radio spectrum monitoring system with implemented deep learning framework. Deep learning is a powerful method to handle hard tasks automatically. The system uses the RTL-SDR USB dongle as the sensor to collect the spectrum data. This dongle is a low-cost device that can measure the signal from 500kHz to 1700MHz. The maximum bandwidth of measurement is 2MHz. The main functions of this system are to collect the spectrum data and then detect the representation signals and extract their characteristics, such as bandwidth, center frequency, modulation type, and capacity. The modulation classification task …

Functional Split In 5g Cloud Radio Access Network Using Particle Swarm Optimization, Wai Phyo

Chulalongkorn University Theses and Dissertations (Chula ETD)

The Cloud Radio Access Network (C-RAN) is an innovative approach that has the potential to significantly reduce the expenses of setting up and operating wireless networks. C-RAN's placement of RAN functions, which strives to reduce bandwidth utilization and computation costs, is a critical component. In this study, our main goal is to reduce the costs associated with functionally placing the RAN while accounting for the computational expense and the front-haul bandwidth usage among various users. To achieve this, we propose to apply Particle Swarm Optimization (PSO) to achieve effective allocation of computational resources and the front-haul bandwidth, ensuring an efficient …