Electrical and Computer Engineering Commons^™

Data-Driven Approaches For Enhancing Power Grid Reliability, Behrouz Sohrabi

Electronic Theses and Dissertations

This thesis explores the transformative potential of data-driven approaches in addressing key operational and reliability issues in power systems. The first part of this thesis addresses a prevalent problem in power distribution networks: the accurate identification of load phases. This study develops a data-driven model leveraging consumption measurements from smart meters and corresponding substation data to reconstruct topology information in low-voltage distribution networks. The proposed model is extensively tested using a dataset with more than 5,000 real load profiles, demonstrating satisfactory performance for large-scale networks. The second part of the thesis pivots to a crucial safety concern: the risk and …

Consensus-Based Active And Reactive Power Control And Management Of Microgrids, Shruti Singh

Electronic Theses and Dissertations

Microgrids incorporating distributed generation and renewable energy sources offer potential solutions to the energy crisis while modernizing traditional grids. Despite cost-effectiveness in some technologies, financial support remains crucial for expensive ones like PV, fuel cells, and storage technologies. Microgrids bring economic benefits, efficiency, reduced emissions, and improved power quality. Their success hinges on cost reductions in renewables, storage, reliability, and energy management systems, enabling operation both with and without the utility grid.

Economic Dispatch optimizes system costs, considering all constraints. Various methods tackle this problem, including quadratic convex functions, Lagrangian relaxation, and quadratic programming. For microgrids with distributed generators, seamless …

Unsupervised Learning Algorithm For Noise Suppression And Speech Enhancement Applications, Abdullah Zaini Alsheibi

Electronic Theses and Dissertations

Smart and intelligent devices are being integrated more and more into day-to-day life to perform a multitude of tasks. These tasks include, but are not limited to, job automation, smart utility management, etc., with the aim to improve quality of life and to make normal day-to-day chores as effortless as possible. These smart devices may or may not be connected to the internet to accomplish tasks. Additionally, human-machine interaction with such devices may be touch-screen based or based on voice commands. To understand and act upon received voice commands, these devices require to enhance and distinguish the (clean) speech signal …

Ad-Corre: Adaptive Correlation-Based Loss For Facial Expression Recognition In The Wild, Ali Pourramezan Fard, Mohammad H. Mahoor

Electrical and Computer Engineering: Faculty Scholarship

Automated Facial Expression Recognition (FER) in the wild using deep neural networks is still challenging due to intra-class variations and inter-class similarities in facial images. Deep Metric Learning (DML) is among the widely used methods to deal with these issues by improving the discriminative power of the learned embedded features. This paper proposes an Adaptive Correlation (Ad-Corre) Loss to guide the network towards generating embedded feature vectors with high correlation for within-class samples and less correlation for between-class samples. Ad-Corre consists of 3 components called Feature Discriminator, Mean Discriminator, and Embedding Discriminator. We design the Feature Discriminator component to guide …

Learning Approach For Fast Approximate Matrix Factorizations, Haiyan Yu

Electronic Theses and Dissertations

Efficiently computing an (approximate) orthonormal basis and low-rank approximation for the input data X plays a crucial role in data analysis. One of the most efficient algorithms for such tasks is the randomized algorithm, which proceeds by computing a projection XA with a random projection matrix A of much smaller size, and then computing the orthonormal basis as well as low-rank factorizations of the tall matrix XA. While a random matrix A is the de facto choice, in this work, we improve upon its performance by utilizing a learning approach to find an adaptive projection matrix A from a set …

Mechanisms Of Sensory Adaptation In The Primate Visual System, Boris Isaac Peñaloza Rojas

Electronic Theses and Dissertations

Under ecological conditions, the luminance impinging on the retina varies within a dynamic range of 220 dB. Stimulus contrast can also vary drastically within a scene, and eye movements leave little time for sampling luminance. In addition, the amount of information reaching our visual system far exceeds the brain’s information processing capacity. Given the limited dynamic range of its neurons and its limited capacity in processing visual information in real-time, the brain deploys both structural and functional solutions that work in tandem to adapt to the surroundings. In this work, employing visual psychophysics and computational neuroscience, we study the mechanisms …

Deep Siamese Neural Networks For Facial Expression Recognition In The Wild, Wassan Hayale

Electronic Theses and Dissertations

The variation of facial images in the wild conditions due to head pose, face illumination, and occlusion can significantly affect the Facial Expression Recognition (FER) performance. Moreover, between subject variation introduced by age, gender, ethnic backgrounds, and identity can also influence the FER performance. This Ph.D. dissertation presents a novel algorithm for end-to-end facial expression recognition, valence and arousal estimation, and visual object matching based on deep Siamese Neural Networks to handle the extreme variation that exists in a facial dataset. In our main Siamese Neural Networks for facial expression recognition, the first network represents the classification framework, where we …

Optimized Trajectory Generation For Car-Like Robots On A Closed Loop Track, Tyler Friedl

Electronic Theses and Dissertations

This thesis presents a method for generating an optimized path through a given track. The path is generated by choosing waypoints throughout the track then iteratively optimizing the position of these waypoints. The waypoints are then connected by optimized paths represented by curvature polynomials. The end result is a path through the track represented as a spline of curvature polynomials. This method is applied to multiple simulated tracks and the results are presented. By generating and representing the paths in the continuous domain, the method has improved computational efficiency from many of the discrete methods used to generate an optimal …

Data-Centric Situational Awareness And Management In Intelligent Power Systems, Xiaoxiao Dai

Electronic Theses and Dissertations

The rapid development of technology and society has made the current power system a much more complicated system than ever. The request for big data based situation awareness and management becomes urgent today. In this dissertation, to respond to the grand challenge, two data-centric power system situation awareness and management approaches are proposed to address the security problems in the transmission/distribution grids and social benefits augmentation problem at the distribution-customer lever, respectively.

To address the security problem in the transmission/distribution grids utilizing big data, the first approach provides a fault analysis solution based on characterization and analytics of the synchrophasor …

Photoelectrochemical Water Splitting For Hydrogen Production With Metal Oxide (Hematite And Cupric Oxide) Based Photocatalysts, Houwen Tang

Electronic Theses and Dissertations

Solar hydrogen is one ideal energy source to replace fossil fuel, as it is sustainable and environmentally friendly. Solar hydrogen can be generated in a number of ways. Photoelectrochemical (PEC) water splitting is one of the most promising methods for solar-to-chemical energy conversion. In this research project, metal oxide-based photocatalysts, especially hematite (fÑ-Fe2O3) and cupric oxide (CuO), were investigated for use as electrodes in PEC water splitting for solar hydrogen production.

In our research project of hematite-based electrodes, we started with the incorporation of transition metal, particularly titanium (Ti), in hematite thin films to modify the valence and …

Toward A Distributed Actuation And Cognition Means For A Miniature Soft Robot, Xiaoting Yang

Electronic Theses and Dissertations

This thesis presents components of an on-going research project aimed towards developing a miniature soft robot for urban search and rescue (USAR). The three significant contributions of the thesis are verifying the water hammer actuation previous work, developing an estimator of water hammer impulse direction from hose shape, and creating the infrastructure for distributed cognitive networks. There are many technical issues in designing soft robots, in terms of perception, actuation, cognition, power, physical structure and so on. We are focusing on actuation and cognition issues in this thesis. We investigated water hammer actuation as an alternative system which provides a …

Fabrication Of Silicon Photovoltaic Micro-Particles For Low-Cost Solar Energy Generation, Siddhartha Kala

Electronic Theses and Dissertations

The relatively high cost of the high quality semiconductor materials (typically silicon) and complex conventional techniques for the fabrication of solar cells result in the overall high cost of the commercially available solar cells. Although, research in the field of solar technologies has been going on for a long time, but, utilization of solar energy still remains limited to a very few applications, owing to the high manufacturing costs and lower efficiency. In this work we present a new solar technology based on silicon photovoltaic micro-particles and demonstrate a fabrication technique for such particles. The photovoltaic micro-particles can be manufactured …