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Open Access Theses & Dissertations

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Full-Text Articles in Electrical and Electronics

Microgrid Assessment And Ml-Based Power System Faults Detection Leveraging Real-Time Co-Simulation, Diego Normando Gandara Mendez Dec 2025

Microgrid Assessment And Ml-Based Power System Faults Detection Leveraging Real-Time Co-Simulation, Diego Normando Gandara Mendez

Open Access Theses & Dissertations

The rapid growth of distributed energy resources (DERs) and the increasing reliance on data-driven decision making have reshaped the operational challenges of modern electric power systems. As microgrids become more prominent in distribution networks, utilities require methods that unify planning, control, and real-time situational awareness to ensure resilient operation under faulted or uncertain conditions. The goal of this MSEE thesis is to design and validate a latency-aware ML framework for rapid, reliable fault detection in distribution grids. To achieve the goal of the thesis, there are three specific objectives. Objective 1 evaluates optimized microgrid configurations under varying DER levels and …


Unmixing In Very High Spatial Resolution Hyperspectral Images, Ana C. Chavez Lopez Dec 2025

Unmixing In Very High Spatial Resolution Hyperspectral Images, Ana C. Chavez Lopez

Open Access Theses & Dissertations

Hyperspectral Imaging (HSI) captures hundreds of contiguous narrow wavelength bands across the optical region of the electromagnetic spectrum collecting the spectral signature of materials in the field of view of the sensor enabling detailed analysis of each pixel's spectral signature. Satellite or airborne remote sensing systems often capture imagery with low to moderate spatial resolution (LMSR). At these resolutions, the measured spectral signature is a mixture of the signatures of the materials within a single pixel. This mixing of spectral information makes analysis and material identification difficult. Hyperspectral unmixing is an analysis technique that decomposes a pixel's spectrum into constituent …


Simulation, Modeling, And Economical Optimization Of Small Modular Reactors For Flexible Power System Operations, Javier Bejarano Dec 2025

Simulation, Modeling, And Economical Optimization Of Small Modular Reactors For Flexible Power System Operations, Javier Bejarano

Open Access Theses & Dissertations

The transition toward a low-carbon and increasingly renewable electric grid has heightened the need for generation technologies that can deliver both stability and operational flexibility. Small Modular Reactors (SMRs), with their modularity, reduced geographical footprint, and capacity for flexible operation, have emerged as promising resources for supporting modern power systems. However, a comprehensive evaluation of their technical performance across steady-state conditions, fault-induced disturbances, and economically optimized dispatch is necessary to understand their role in future grid architectures. This thesis provides an assessment of SMR capabilities using benchmark test systems, data-driven forecasting, dynamic simulation, and unit commitment modeling to evaluate how …


Computational Methods For Complex Electromagnetic Geometries And Media, Edgar Bustamante Dec 2025

Computational Methods For Complex Electromagnetic Geometries And Media, Edgar Bustamante

Open Access Theses & Dissertations

Additive manufacturing has enabled electromagnetic devices with increasingly complex geometries, but existing numerical tools remain limited in their ability to model and design such structures. This dissertation presents two major advancements that address these restrictions in the finite-difference frequency-domain method (FDFD) and the spatially-variant lattice algorithm (SVLA). These two numerical methods provide a foundation for future exploration in the simulation, optimization, and realization of next-generation electromagnetic devices. First, a general bianisotropic FDFD formulation based on the vector wave equation is presented that enables practical modeling of metamaterials using effective medium homogenized parameters rather than explicitly resolving subwavelength metamaterial features. The …


Further Insights Into The Network Link Outlier Factor's (Nlof) Light-Load Penalty, Sunday Oluwaleke Ogundele Dec 2025

Further Insights Into The Network Link Outlier Factor's (Nlof) Light-Load Penalty, Sunday Oluwaleke Ogundele

Open Access Theses & Dissertations

This research investigates the performance of the Network Link Outlier Factor with Most Likely Links (NLOF:MLL), under varying network load conditions. Earlier studies reported that the NLOF:MLL algorithm experienced a noticeable drop in fault-localization accuracy when operating in lightly loaded networks. To further examine this limitation, 240 experiments were carried out to observe how the algorithm responds as overall network load increases. The evaluation focused on the classification performance metrics: precision, recall, and F1-score. The results show that NLOF:MLL’s effectiveness improves as network load increases but that the rate of improvement slows progressively, eventually stabilizing in a pattern consistent with …


Development And Optimization Of A Deep Level Transient Spectroscopy System, Samuel Ruiz Dec 2025

Development And Optimization Of A Deep Level Transient Spectroscopy System, Samuel Ruiz

Open Access Theses & Dissertations

Deep-level transient spectroscopy (DLTS) remains one of the most widely used techniques for identifying electrically active defects that affect leakage current, carrier lifetime, and overall reliability in semiconductor devices. Legacy boxcar or capacitance meter implementations, however, often struggle with limited signal-to-noise ratio, labor-intensive data collection, and poor adaptability across diverse material systems. This thesis presents the design and optimization of a semi-automated, lock-in-amplifier-based DLTS platform. By pairing a Zurich HF2LI with PID-controlled cryogenic sweeps, precision signal generation, and MATLAB driven acquisition and processing scripts, the system will (i) enhance SNR through phase-sensitive detection, programmable low pass filtering, and parasitics calibration; …


Image And Signal Processing Methods For Clinical Decision Support: Reference-Based Lung Segmentation On Chest X-Rays And Ecg-Based Study Of Acute Hyperkalemia Using Machine Learning, Basavarajaiah Shanmukhayya Totada Dec 2025

Image And Signal Processing Methods For Clinical Decision Support: Reference-Based Lung Segmentation On Chest X-Rays And Ecg-Based Study Of Acute Hyperkalemia Using Machine Learning, Basavarajaiah Shanmukhayya Totada

Open Access Theses & Dissertations

ABSTRACT

Study-I: An Image Processing Pipeline for Reference Guided Lung Region Detection in Chest Radiographs with Shape Similarity Matching Accurate and reliable segmentation of the lung region in chest X-ray (CXR) images is essential for computer-aided diagnosis (CAD) systems, particularly in the early detection and monitoring of lung disorders. Traditional segmentation techniques often rely on manual annotations, limiting scalability and adaptability. The proposed reference-guided approach selects the most similar healthy CXRs dynamically, ensuring flexibility while benefiting from dataset-specific reference images. Building upon prior approaches that utilize shape similarity-based selection and SIFT-flow, this study introduces a fully automated segmentation pipeline that …


Line Outage Impact Factors: A New Approach To Line Outage Detection With Machine Learning, Daniel Flores Aug 2025

Line Outage Impact Factors: A New Approach To Line Outage Detection With Machine Learning, Daniel Flores

Open Access Theses & Dissertations

Electric power systems have become one of our most critical infrastructures as we've grown dependent on electricity for everyday tasks. Ensuring power systems provide reliable service is a priority that can be affected by disturbance events. A common event is transmission line outages, where a line in the system becomes disconnected due to varying forms of physical damage. If an outage isn't detected in time, other lines in the system may overload, causing cascading failures that leave many customers without power. Therefore, having a power system that can automatically detect outages is crucial for reliability, as it promotes real-time response …


Towards Mitigation Of The Light Network Load Performance Penalty Of The Network Link Outlier Factor (Nlof), Jaime Merin Guzman May 2025

Towards Mitigation Of The Light Network Load Performance Penalty Of The Network Link Outlier Factor (Nlof), Jaime Merin Guzman

Open Access Theses & Dissertations

Detecting and localizing faults in communication networks is critical to maintaining reliable and efficient network operations. The Network Link Outlier Factor with Most Likely Link (NLOF: MLL) algorithm has demonstrated its potential to automate this task but suffers from significant performance degradation under low network load conditions, where limited network flow data reduces its ability to localize faults. This thesis proposes and evaluates the performance of a synthetic traffic generation algorithm to be used with NLOF:MLL. This algorithm strategically injects synthetic flows that supplement the insufficient real network flows, thereby improving NLOF:MLL's performance under low-load conditions. Specifically, we select network …


Generative Ai For 3d Printed Antenna Design, Jennifer Ann Chavez May 2025

Generative Ai For 3d Printed Antenna Design, Jennifer Ann Chavez

Open Access Theses & Dissertations

This research explores the integration of generative artificial intelligence (AI) with a physics-informed particle swarm optimizer (PSO) to develop 3D printable microstrip patch antennas. A neural network was trained on a dataset of microstrip patch antenna geometries and their corresponding performance metrics: return loss and gain. The PSO used a fitness function prioritizing low return loss in potential antennas, eventually yielding novel antenna geometries with parasitic components. 3D printing constraints were also hard coded into the framework, thus preventing any geometries being generated that cannot be fabricated. When simulated using Ansys HFSS, the AI generated microstrip patch antennas exceeded the …


Inference Per Joule: A Performance Metric For Artificial Intelligence In Space Applications, Eduardo Macias Zugasti May 2025

Inference Per Joule: A Performance Metric For Artificial Intelligence In Space Applications, Eduardo Macias Zugasti

Open Access Theses & Dissertations

The use of artificial intelligence (AI) has grown exponentially in recent years. This growth is driven in part by the significant advancements in computing capabilities, which have also increased exponentially. Computers have not only become more powerful but also smaller in size, thanks to the evolution of transistor technology. These developments have enabled AI to become a widely accessible tool, even in recreational activities such as image creation and entertainment videos.

More recently, the use of AI has extended to space applications, where it can enhance and optimize various tasks. However, space conditions pose significant challenges for conventional computers due …


3d Printing Metal Horn Antennas Using Periodic And Aperiodic Perforated Designs For Directed Energy Applications, Alexis Valencia Jan 2025

3d Printing Metal Horn Antennas Using Periodic And Aperiodic Perforated Designs For Directed Energy Applications, Alexis Valencia

Open Access Theses & Dissertations

In the past decade, Additive Manufacturing (AM) has proven to be groundbreaking yet reliable technology. Not only has it revolutionized the way we approach problems in research, design, and production but it has enabled burgeoning discoveries and methods due to the technologyâ??s efficiency, speed, and low manufacturing cost. One area that benefits greatly from this includes radio frequency (RF) devices like horn antennas. At the moment, most horn antennas produced by conventional manufacturing are expensive, heavy, and limited in customization, yet they are necessary for various systems like satellite communication, radar, radio astronomy, and more. 3D printing technology would alleviate …


Developing A Bioengineered Nanoparticle For Improving Oral Absorption Of Iron Supplements., Mila Biswas Dec 2024

Developing A Bioengineered Nanoparticle For Improving Oral Absorption Of Iron Supplements., Mila Biswas

Open Access Theses & Dissertations

Iron deficiency (ID) and iron deficiency anemia (IDA) are widespread nutritional issues, affecting millions globally. Conventional iron supplements often suffer from low absorption rates and gastrointestinal side effects. We investigated β-glucan derivatives as potential carriers to enhance iron absorption and mitigate these drawbacks. This study explored a novel β-glucan-based carrier system loaded with ferrous sulfate heptahydrate. In-vitro studies demonstrated sustained iron stability for over six hours in simulated gastric fluids due to the carrier's affinity for stomach mucin. Particle size analysis and scanning electron microscopy (SEM) images confirmed this specific binding. Additionally, drug release studies revealed a pH-dependent release profile, …


Chipless 3d Microfluidic Rf Sensing, Sheikh Dobir Hossain Dec 2024

Chipless 3d Microfluidic Rf Sensing, Sheikh Dobir Hossain

Open Access Theses & Dissertations

Effective management of the cold chain is essential to uphold the quality and safety of products vulnerability to physical factors like temperature, humidity, pressure, etc., including perishable foods, pharmaceuticals, and vaccines. Chipless Radio Frequency Identification (RFID) sensors have become increasingly favored as a viable technology for tracking, inventory, and sensing industries due to their wireless and non-line of sight (NLOS) situations, straightforward fabrication, cost efficiency, and adaptability to challenging environmental conditions. However, there is still a need for advancements in RFID sensors to make them promise for cold chain applications. Integration of flexibility and non-volatile memory into the existing RFID …


Dynamic Optimization Of Directed Energy Deposition Build Conditions Using Real-Time Monitoring Via Closed-Loop Control, Callan Herberger Dec 2024

Dynamic Optimization Of Directed Energy Deposition Build Conditions Using Real-Time Monitoring Via Closed-Loop Control, Callan Herberger

Open Access Theses & Dissertations

Directed Energy Deposition (DED) is an additive manufacturing process that is being rapidly adopted by industry and is well suited for the fabrication of complex components in various metal alloys. DED provides unique benefits such as design flexibility, the potential for in-situ alloying, and an open environment that allows for unobstructed monitoring within the build chamber. Despite these benefits, fully exploiting additive manufacturing's (AM) potential remains a complex task for designers. This dissertation presents a framework for controlling Directed Energy Deposition process variables through in-situ monitoring. An exploration into modifying AM build conditions through the development and implementation of a …


Uncovering The Light Network Load Performance Penalty Of The Network Link Outlier Factor (Nlof), Michelle Lara Dec 2024

Uncovering The Light Network Load Performance Penalty Of The Network Link Outlier Factor (Nlof), Michelle Lara

Open Access Theses & Dissertations

This thesis evaluates the effectiveness of the Network Link Outlier Factor with Most Likely Link (NLOF: MLL) algorithm under varying network load conditions. Repeated simulation experiments using Mininet were conducted for four different network-wide load levels: 100 Mbps, 500 Mbps, 1 Gbps, and 5 Gbps. Using statistical inference, our experimental results indicate that NLOF: MLL is ineffective under light load conditions (i.e., 100Mbps load) due to the limited network flow data available for its learning process. This limitation highlights a key challenge in applying the algorithm to lightly loaded networks. A preliminary algorithm was proposed to address this light-load performance …


Advancing Grid Modernization Through Data-Driven Resilience Modeling And Hosting Capacity Of Distributed Energy Resources, Oscar Samuel Acosta Dec 2024

Advancing Grid Modernization Through Data-Driven Resilience Modeling And Hosting Capacity Of Distributed Energy Resources, Oscar Samuel Acosta

Open Access Theses & Dissertations

This Ph.D. dissertation focuses on advancing the integration of distributed energy resources (DERs) through concepts surrounding their impacts on power system stability, resilience, and hosting capacity (HC). This dissertation addresses crucial topics in renewable energy deployment, transient fault response, and dynamic modeling. The work begins with the development of renewable energy source (RES) models tailored for offsetting residential heating, ventilation, and air conditioning~(HVAC) and commercial cooling loads. These models utilize solar photovoltaic (PV) and wind energy systems to produce scalable frameworks adapted across diverse climates and building types in application of a partial-load targeting methodology. The dissertation then transitions from …


Towards A Spaceworthy Cots Graphics Processing Unit: Hardware Performance Counter Based Symptomatic Fault Detection, Antonio E. Teijeiro Dec 2023

Towards A Spaceworthy Cots Graphics Processing Unit: Hardware Performance Counter Based Symptomatic Fault Detection, Antonio E. Teijeiro

Open Access Theses & Dissertations

Ionizing radiation remains an obstacle to bringing graphics processing units (GPU) to space. Since radiation-hardened GPU chips are technically infeasible at the moment, an emphasis has been placed on the adaptation of commercial-off-the-shelf (COTS) GPUs to the space domain. At present, GPU error detection methods require redundant computation. This thesis work explores the utilization of hardware performance counters, special registers useful for monitoring internal GPU hardware events, for symptom-based, lightweight error detection. Hardware performance counters are successfully utilized for the detection of anomalous single event upsets in the L0 instruction cache, the load store unit, the arithmetic and logic unit, …


Diverse Impacts Of Commercial Ev Charging Load Infrastructure On Electric Power Grid, Antonio Avila Dec 2023

Diverse Impacts Of Commercial Ev Charging Load Infrastructure On Electric Power Grid, Antonio Avila

Open Access Theses & Dissertations

With the rising prominence of electric vehicles (EVs) in the transportation sector, this thesis delves into the critical nexus between commercial EVs, charging infrastructure, and their consequential impacts on the power grid. As commercial EVs, particularly medium and heavy-duty variants, gain traction as viable alternatives in the commercial transportation landscape, understanding the intricacies of their charging requirements becomes paramount. This thesis critically examines the technological and logistical dimensions of the charging infrastructure for supporting commercial EVs, evaluating the consequential implications on the power grid and proposing strategies for mitigation through the utilization of Distributed Energy Resources (DERs). In tandem with …


Development Of Metaheuristic Algorithms For The Efficient Allocation Of Power Flow Control Devices, Eduardo Jose Castillo Fatule Dec 2023

Development Of Metaheuristic Algorithms For The Efficient Allocation Of Power Flow Control Devices, Eduardo Jose Castillo Fatule

Open Access Theses & Dissertations

No abstract provided.


Enhancing Power System Flexibility Through Efficient Integration Of Facts And Electric Vehicles, Izaz Zunnurain Dec 2023

Enhancing Power System Flexibility Through Efficient Integration Of Facts And Electric Vehicles, Izaz Zunnurain

Open Access Theses & Dissertations

The global transition towards a cleaner and sustainable energy landscape has led to the integration of renewable energy sources and electric vehicles (EVs) into the modern power system, along with their complexities. Due to the high penetration of renewable energy sources and rapid growth of EVs, the power grid often experiences congestion, increasing the overall operating cost of the power system and directly jeopardizing the power stability and quality of the grid. A flexible and resilient power infrastructure that can accommodate the intermittency of renewable energy sources and the adoption of EVs is very much required to ensure the reliability …


Inkjet-Printed Electrochemical Sensors For Lead Detection, Annatoma Arif Aug 2023

Inkjet-Printed Electrochemical Sensors For Lead Detection, Annatoma Arif

Open Access Theses & Dissertations

This PhD dissertation research has developed a simple, miniaturized, sensitive, selective, reproducible, and disposable 3D (inkjet printed – additive manufacturing technology) gold (Au) plated electrochemical sensor (ECS) on shape memory polymer (SMP) for aqueous lead detection. This technology has shown promising performance in the application of electrochemical sensing (lead (II) detection) due to increased effective electrode surface area (7.25 mm^2 ± 0.15 mm^2) despite miniaturizing lateral surface area (4.19 mm^2). The design, fabrication processes, optimization including bismuth functionalization, evaluation, uncertainty analysis, and cost analysis of the novel SMP based inkjet printed Au plated sensor have been delineated in this manuscript …


Metal Additive Microfabrication Of Semiconductor Packages With Inbuilt Thermal Management System, Bhushan Lohani Aug 2023

Metal Additive Microfabrication Of Semiconductor Packages With Inbuilt Thermal Management System, Bhushan Lohani

Open Access Theses & Dissertations

Moore’s law describes the development capabilities in electronics manufacturing. Although his estimation held for decades, at present, the doubling of components every two years seems to be approaching a halt. The assessment was based on the miniaturization of transistors to create space for more. Miniaturization led to higher component density, decreased cost, lowered power consumption, and compactness. However, it also came with high current density, increased Joule heating, and reduced critical charge. One of the limiting factors is the heat generated from such devices, which is heavily discussed in International Roadmap for Devices and Systems (IRDS) and International Technology Roadmap …


Addressing The Challenged Of Dcop Based Decision-Making Algorithms In Modern Power Systems, Luis Daniel Ramirez Burgueno May 2023

Addressing The Challenged Of Dcop Based Decision-Making Algorithms In Modern Power Systems, Luis Daniel Ramirez Burgueno

Open Access Theses & Dissertations

Natural disasters have been determined as the leading cause of power outages, causing not only huge economic losses, but also the interruption of crucial welfare activities and the arise of security concerns. Because of the later, decision-making considering grid modernization, power system economics, and system resiliency has been a crucial theme in power systemsâ?? research. The need to better withstand catastrophic events and reducing the dependency of bulky generating units has propelled the development and better management of behind-the-meter generation or distributed energy resources (DERs). DERs can assist in the grid in different manners, not only by meeting energy demand …


Cyber-Physical Production Systems And Their Practical Integration And Application With Simio Software, Jose Carlos Garcia Marquez Basaldua May 2023

Cyber-Physical Production Systems And Their Practical Integration And Application With Simio Software, Jose Carlos Garcia Marquez Basaldua

Open Access Theses & Dissertations

Industry 4.0 comprises a diverse array of technologies and components that are revolutionizing the manufacturing industry, from Digital Twins, Cyber-Physical Systems and Augmented Reality. The elements that englobe Industry 4.0 vary from framework to framework. Nevertheless, there are similarities in the available literature on what constitutes Industry 4.0. Some of the most critical components specified by the available literature include Digital Twins and Cyber-Physical Systems. A Factory Digital Twin is a virtual representation of a production system that can mimic the behavior of the physical asset. Moreover, a digital twin must have synchronization with its physical twin (i.e., production floor), …


Hybrid Model For Making Decision Methods In Wireless Sensor Networks Through Neuro-Fuzzy Inference System, Martha Lucia Torres Dec 2022

Hybrid Model For Making Decision Methods In Wireless Sensor Networks Through Neuro-Fuzzy Inference System, Martha Lucia Torres

Open Access Theses & Dissertations

Considering the complexity and multiple alternatives for technology decisions in Wireless Sensor Networks (WSNs), a multicriteria selection method (MCDM) is an appropriate approach for choosing the best option in technical projects. Purely quantitative decision-making procedures have currently been created based on client requirements and recommendations from industry professionals in many domains. In this context, implementation and operational costs could be increasing due to technical problems and additional processes. In order to prevent future difficulties and obtain a more accurate technology selection, a new method was being developed to involve qualitative and quantitative parameters taken from real scenarios and technical literature …


Optimized Learning Using Fuzzy-Inference-Assisted Algorithms For Deep Learning, Miroslava Barua Dec 2022

Optimized Learning Using Fuzzy-Inference-Assisted Algorithms For Deep Learning, Miroslava Barua

Open Access Theses & Dissertations

For years, researchers in Artificial Intelligence (AI) and Deep Learning (DL) observed that performance of a Deep Learning Network (DLN) could be improved by using larger and larger datasets coupled with complex network architectures. Although these strategies yield remarkable results, they have limits, dictated by data quantity and quality, rising costs by the increased computational power, or, more frequently, by long training times on networks that are very large. Training DLN requires laborious work involving multiple layers of densely connected neurons, updates to millions of network parameters, while potentially iterating thousands of times through millions of entries in a big …


Processes & Toolchain For Automation Of Hybrid Direct-Write 3d Printing, Gilbert Thomas Carranza Dec 2022

Processes & Toolchain For Automation Of Hybrid Direct-Write 3d Printing, Gilbert Thomas Carranza

Open Access Theses & Dissertations

Hybrid 3D printing has evolved from a means to rapidly prototype devices to a fully viable means of manufacturing final products. In particular, electronic and electromagnetic devices have been a focus of hybrid 3D printing multi material structures. However, while the hardware capabilities have been around for years, the software capabilities have only begun to catch up. A process and toolchain for hybrid 3D printing is critically needed.This work details a process and toolchain for hybrid 3D printing metal dielectric structures. In it, a basic slicing algorithm is shown along with off-axis printing and conformal printing for arbitrary curvatures. These …


A High Performance Software Intensive Testbed For Rapid Prototyping And Controlled Testing Of Lte And Wi-Fi Radio Frequency Signals, Mirza Mohammad Maqbule Elahi Aug 2022

A High Performance Software Intensive Testbed For Rapid Prototyping And Controlled Testing Of Lte And Wi-Fi Radio Frequency Signals, Mirza Mohammad Maqbule Elahi

Open Access Theses & Dissertations

Long Term Evolution or LTE has gained interest for new applications that can benefit society including mobile broadband services like 802.11 or Wi-Fi. Both LTE and Wi-Fi uses similar modulation technique Orthogonal Frequency Division Multiplexing or OFDM. 6GHz sub carrier bands are crowded with LTE users. As wireless communications technology continues to develop, LTE technology in unlicensed bands (LTE-U) is a viable solution to the lack of spectrum resources. The competition between LTE-U and Wi-Fi will seriously impair their communication quality, so the friendly coexistence of both become an important research topic. This paper discusses the use of a software-defined …


Diverse Effects Of Ev Charging Infrastructure On Electric Power Distribution Systems, Travis Michael Moore Newbolt Aug 2022

Diverse Effects Of Ev Charging Infrastructure On Electric Power Distribution Systems, Travis Michael Moore Newbolt

Open Access Theses & Dissertations

The advanced technology of today has allowed for an avenue into cleaner forms of energy that will not only protect our environment but also continue to advance our society. Among the many forms of clean energy, electric vehicles (EV) have the potential to mitigate our consumption of fossil fuels in vehicle transportation industries. In the U.S. for 2021, EVs account for approximately 700,000 registrations. That number is projected to increase to 2 million by 2030. Although EVs do reduce the number of emissions when compared to an internal combustion engine, they do however shift the responsibility to utility companies to …