Power and Energy 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 …

Fair Fault-Tolerant Approach For Access Point Failures In Networked Control System Greenhouses, Mohammed Ali Yaslam Ba Humaish

Theses and Dissertations

Greenhouse Networked Control Systems (NCS) are popular applications in modern agriculture due to their ability to monitor and control various environmental factors that can affect crop growth and quality. However, designing and operating a greenhouse in the context of NCS could be challenging due to the need for highly available and cost-efficient systems. This thesis presents a design methodology for greenhouse NCS that addresses these challenges, offering a framework to optimize crop productivity, minimize costs, and improve system availability and reliability. It contributes several innovations to the field of greenhouse NCS design. For example, it recommends using the 2.4GHz frequency …

Poster: Optimising Electric Vehicle Charging Infrastructure In Dublin Using Geecharge, Alexander Mutiso Mutua, Ruairí De Fréin, Ali Malik, Kibanza Eliel, Sahbane Marco, Pantel Maxime

Conference papers

Range anxiety is a significant challenge affecting electric vehicles use as drivers fear running out of charge without finding a charging point on time. We develop methods to optimise the distribution of charging points. EV portacharge and GEECharge solutions distribute charging points in a city by considering the population density and Points Of Interest (POI) or road traffic. This paper focuses on (1) developing and evaluating methods to distribute Charging Points (CPs) in Dublin city; (2) optimising CP allocation; (3) visualising paths in the graph network to show the most used roads and points of interest; (4) describing a way …

Deep Learning Based Power System Stability Assessment For Reduced Wecc System, Yinfeng Zhao

Doctoral Dissertations

Power system stability is the ability of power system, for a giving initial operating condition, to reach a new operation condition with most of the system variables bounded in normal range after subjecting to a short or long disturbance. Traditional power system stability mainly uses time-domain simulation which is very time consuming and only appropriate for offline assessment.

Nowadays, with increasing penetration of inverter based renewable, large-scale distributed energy storage integration and operation uncertainty brought by weather and electricity market, system dynamic and operating condition is more dramatic, and traditional power system stability assessment based on scheduling may not be …

Designing Intelligent Energy Efficient Scheduling Algorithm To Support Massive Iot Communication In Lora Networks, Jui Mhatre

Master of Science in Computer Science Theses

We are about to enter a new world with sixth sense ability – “Network as a sensor -6G”. The driving force behind digital sensing abilities is IoT. Due to their capacity to work in high frequency, 6G devices have voracious energy demand. Hence there is a growing need to work on green solutions to support the underlying 6G network by making it more energy efficient. Low cost, low energy, and long-range communication capability make LoRa the most adopted and promising network for IoT devices. Since LoRaWAN uses ALOHA for multi-access of channels, collision management is an important task. Moreover, in …

Round Trip Time Measurement Over Microgrid Power Network, Yasin Emir Kutlu, Ruairí De Fréin, Malabika Basu, Ali Malik

Conference papers

A focus of the Power Systems and Networking communities is the design and deployment of Microgrid (MG) integration systems that ensure that quality of service targets are met for load sharing systems at different endpoints. This paper presents an integrated Microgrid testbed that allows Microgrids endpoints to share their current, voltage and power values using a Network Published Shared Variable (NPSV) approach. We present Round Trip Time (RTT) measurements for time sensitive Microgrid control traffic in the presence of varying background traffic as an example quality of service measurement. Numerical results are presented using a range of different background traffic …

Power Amplifier Based On Composite Injection-Voltaic Transistors, Nodira Batirdjanovna Alimova

Chemical Technology, Control and Management

The problem of high-current radio engineering devices is related to the fact that the use of high-power transistors and other semiconductor devices is limited by such a phenomenon as a secondary breakdown, in which there is a sharp decrease in the voltage on the device with simultaneous internal current lacing, and the device fails. To solve the problem of secondary breakdown, schemes have been proposed that operate stably at reverse voltage values 4-5 times higher than usual and at power dissipation 2-3 times higher than the maximum allowable power for an individual device. The problem is proposed to be solved …

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …

Optimising Electric Vehicle Charging Infrastructure In Dublin Using Geecharge, Alexander Mutua Mutiso, Ruairí De Fréin, Ali Malik, Eliel Kibanza, Marco Sahbane, Maxime Pantel

Conference papers

Range anxiety poses a hurdle to the adoption of Electric Vehicles (EVs), as drivers worry about running out of charge without timely access to a Charging Point (CP). We present novel methods for optimising the distribution of CPs, namely, EV portacharge and GEECharge. These solutions distribute CPs in Dublin, in this paper, by considering the population density and Points Of Interest (POIs) or road traffic. The object of this paper is to (1) develop and evaluate methods to distribute CPs in Dublin city; (2) optimise CP allocation; (3) visualise paths in the graph network to show the most used roads …

Survey Of Routing Techniques-Based Optimization Of Energy Consumption In Sd-Dcn, Mohammed Nsaif, Gergely Kovásznai, Ali Malik, Ruairí De Fréin

Articles

The increasing power consumption of Data Center Networks (DCN) is becoming a major concern for network operators. The object of this paper is to provide a survey of state-of-the-art methods for reducing energy consumption via (1) enhanced scheduling and (2) enhanced aggregation of traffic flows using Software-Defined Networks (SDN), focusing on the advantages and disadvantages of these approaches. We tackle a gap in the literature for a review of SDN-based energy saving techniques and discuss the limitations of multi-controller solutions in terms of constraints on their performance. The main finding of this survey paper is that the two classes of …

Smart Power Outlet, Kyrolos Melek, Joseph M. Garro, Ethan G. Frese, Madison Britton

Williams Honors College, Honors Research Projects

With an ever-increasing demand on the electrical grid and an increase in electrical consumer goods per household, effective power management and monitoring for home users is a must. The objective of this project is to create a consumer outlet and companion phone application. The power outlet will measure power draw on each socket and report these measurements via an embedded system, wirelessly, to the application. The application will then allow for setting custom power draws at which an individual socket will switch off if exceeded and will display how much a given outlet or individual socket is costing per unit …

Application Of Conventional Feedforward And Deep Neural Networks To Power Distribution System State Estimation And State Forecasting, James Paul Carmichael

Theses and Dissertations--Electrical and Computer Engineering

Classical neural networks such as feedforward multilayer perceptron models (MLPs) are well established as universal approximators and as such, show promise in applications such as static state estimation in power transmission systems. This research investigates the application of conventional neural networks (MLPs) and deep learning based models such as convolutional neural networks (CNNs) and long short-term memory networks (LSTMs) to mitigate challenges in power distribution system state estimation and forecasting based upon conventional analytic methods. The ability of MLPs to perform regression to perform power system state estimation will be investigated. MLPs are considered based upon their promise to learn …

Enhancing Traffic Safety In Unpredicted Environments With Integration Of Adas Features With Sensor Fusion In Intelligent Electric Vehicle Platform With Implementation Of Environmental Mapping Technology, David S. Obando Ortegon

Electronic Theses and Dissertations

A major objective on society is to reduce the number of accidents and fatalities on the road for drivers, and pedestrians. Therefore, the automotive engineering field is working on this problem through the development and integration of safety technologies such as advanced driving assistance systems. For this reason, this work was intended to develop and evaluate the performance of different ADAS features and IV technologies under unexpected scenarios. This by the development of safety algorithms applied to the intelligent electric vehicle designed and built in this work, through the use of ADAS sensors based on sensor fusion. Evaluation of AEB, …

Machine Learning Approach To Investigate Ev Battery Characteristics, Shayan Falahatdoost

Major Papers

The main factor influencing an electric vehicle’s range is its battery. Battery electric vehicles experience driving range reduction in low temperatures. This range reduction results from the heating demand for the cabin and recuperation limits by the braking system. Due to the lack of an internal combustion engine-style heat source, electric vehicles' heating system demands a significant amount of energy. This energy is supplied by the battery and results in driving range reduction. Moreover, Due to the battery's low temperature in cold weather, the charging process through recuperation is limited. This limitation of recuperation is caused by the low reaction …

Material Characterization And Comparison Of Sol-Gel Deposited And Rf Magnetron Deposited Lead Zirconate Titanate Thin Films, Katherine Lynne Miles

Mechanical Engineering ETDs

Lead zirconate titanate (PZT) has been a material of interest for sensor, actuator, and transducer applications in microelectromechanical systems (MEMS). This is due to their favorable piezoelectric, pyroelectric and ferroelectric properties. While various methods are available to deposit PZT thin films, radio frequency (RF) magnetron sputtering was selected to provide high quality PZT films with the added capability of batch processing. These sputter deposited PZT films were characterized to determine their internal film stress, Young’s modulus, composition, and structure. After characterization, the sputtered PZT samples were poled using corona poling and direct poling methods. As a means of comparison, commercially …

Agglomerative Hierarchical Clustering With Dynamic Time Warping For Household Load Curve Clustering, Fadi Almahamid, Katarina Grolinger

Electrical and Computer Engineering Publications

Energy companies often implement various demand response (DR) programs to better match electricity demand and supply by offering the consumers incentives to reduce their demand during critical periods. Classifying clients according to their consumption patterns enables targeting specific groups of consumers for DR. Traditional clustering algorithms use standard distance measurement to find the distance between two points. The results produced by clustering algorithms such as K-means, K-medoids, and Gaussian Mixture Models depend on the clustering parameters or initial clusters. In contrast, our methodology uses a shape-based approach that combines Agglomerative Hierarchical Clustering (AHC) with Dynamic Time Warping (DTW) to classify …

Models And Machine Learning Techniques For Improving The Planning And Operation Of Electricity Systems In Developing Regions, Santiago Correa Cardona

Doctoral Dissertations

The enormous innovation in computational intelligence has disrupted the traditional ways we solve the main problems of our society and allowed us to make more data-informed decisions. Energy systems and the ways we deliver electricity are not exceptions to this trend: cheap and pervasive sensing systems and new communication technologies have enabled the collection of large amounts of data that are being used to monitor and predict in real-time the behavior of this infrastructure. Bringing intelligence to the power grid creates many opportunities to integrate new renewable energy sources more efficiently, facilitate grid planning and expansion, improve reliability, optimize electricity …

Improving The Programmability Of Networked Energy Systems, Noman Bashir

Doctoral Dissertations

Global warming and climate change have underscored the need for designing sustainable energy systems. Sustainable energy systems, e.g., smart grids, green data centers, differ from the traditional systems in significant ways and present unique challenges to system designers and operators. First, intermittent renewable energy resources power these systems, which break the notion of infinite, reliable, and controllable power supply. Second, these systems come in varying sizes, spanning over large geographical regions. The control of these dispersed and diverse systems raises scalability challenges. Third, the performance modeling and fault detection in sustainable energy systems is still an active research area. Finally, …

Developing A Miniature Smart Boat For Marine Research, Michael Isaac Eirinberg

Computer Engineering

This project examines the development of a smart boat which could serve as a possible marine research apparatus. The smart boat consists of a miniature vessel containing a low-cost microcontroller to live stream a camera feed, GPS telemetry, and compass data through its own WiFi access point. The smart boat also has the potential for autonomous navigation. My project captivated the interest of several members of California Polytechnic State University, San Luis Obispo’s (Cal Poly SLO) Marine Science Department faculty, who proposed a variety of fascinating and valuable smart boat applications.

Total Sky Imager Project, Ryan D. Maier, Benjamin Jack Forest, Kyle X. Mcgrath

Mechanical Engineering

Solar farms like the Gold Tree Solar Farm at Cal Poly San Luis Obispo have difficulty delivering a consistent level of power output. Cloudy days can trigger a significant drop in the utility of a farm’s solar panels, and an unexpected loss of power from the farm could potentially unbalance the electrical grid. Being able to predict these power output drops in advance could provide valuable time to prepare a grid and keep it stable. Furthermore, with modern data analysis methods such as machine learning, these predictions are becoming more and more accurate – given a sufficient data set. The …

Deep Learning For Load Forecasting With Smart Meter Data: Online And Federated Learning, Mohammad Navid Fekri

Electronic Thesis and Dissertation Repository

Electricity load forecasting has been attracting increasing attention because of its importance for energy management, infrastructure planning, and budgeting. In recent years, the proliferation of smart meters has created new opportunities for forecasting on the building and even individual household levels. Machine learning (ML) has achieved great successes in this domain; however, conventional ML techniques require data transfer to a centralized location for model training, therefore, increasing network traffic and exposing data to privacy and security risks. Also, traditional approaches employ offline learning, which means that they are only trained once and miss out on the possibility to learn from …

Data-Driven Control, Modeling, And Forecasting For Residential Solar Power, Akansha Singh Bansal

Doctoral Dissertations

Distributed solar generation is rising rapidly due to a continuing decline in the cost of solar modules. Most residential solar deployments today are grid-tied, enabling them to draw power from the grid when their local demand exceeds solar generation and feed power into the grid when their local solar generation exceeds demand. The electric grid was not designed to support such decentralized and intermittent energy generation by millions of individual users. This dramatic increase in solar power is placing increasing stress on the grid, which must continue to balance its supply and demand despite the potential for large solar fluctuations. …

Spectrum Sensing With Energy Detection In Multiple Alternating Time Slots, Călin Vlădeanu, Alexandru Marţian, Dimitrie C. Popescu

Electrical & Computer Engineering Faculty Publications

Energy detection (ED) represents a low complexity approach used by secondary users (SU) to sense spectrum occupancy by primary users (PU) in cognitive radio (CR) systems. In this paper, we present a new algorithm that senses the spectrum occupancy by performing ED in K consecutive sensing time slots starting from the current slot and continuing by alternating before and after the current slot. We consider a PU traffic model specified in terms of an average duty cycle value, and derive analytical expressions for the false alarm probability (FAP) and correct detection probability (CDP) for any value of K . Our …

An Efficient Ar Model-Based Method For The Detection Of Forced Oscillations In Power Networks: Implementation And Analysis, Maria Waleska Suarez

Graduate Theses, Dissertations, and Problem Reports

An active research topic is the detection of various oscillations that may lead to instability and potential disruption in the operation of a power network. Forced Oscillations (FOs) play a unique role in power system stability among various oscillations. They are perturbances that change the system’s state and are caused for many reasons, including but not limited to persistent load changes and oscillatory load or generation, fault, triplane, and other mechanical anomalies. These factors can hugely affect the power grid by either increasing or decreasing the amplitude, causing corrupt modes leading to blackouts, affecting the equipment involved, delivering poor power …

Enhanced Security Utilizing Side Channel Data Analysis, Michael Taylor

Computer Science and Engineering Theses and Dissertations

The physical state of a system is affected by the activities and processes in which it is tasked with carrying out. In the past there have been many instances where such physical changes have been exploited by bad actors in order to gain insight into the operational state and even the data being held on a system. This method of side channel exploitation is very often effective due to the relative difficulty of obfuscating activity on a physical level. However, in order to take advantage of side channel data streams one must have a detailed working knowledge of how a …

Deep Learning For High-Impedance Fault Detection And Classification, Khushwant Rai

Electronic Thesis and Dissertation Repository

High-Impedance Faults (HIFs) are a hazard to public safety but are difficult to detect because of their low current amplitude and diverse characteristics. Supervised machine learning techniques have shown great success in HIF detection; however, these approaches rely on resource-intensive signal processing techniques and fail in presence of non-HIF disturbances and even for scenarios not included in training data. This thesis leverages unsupervised learning and proposes a Convolutional Autoencoder framework for HIF Detection (CAE-HIFD). In CAE-HIFD, Convolutional Autoencoder learns only from HIF signals by employing cross-correlation; consequently, eliminating the need for diverse non-HIF scenarios in training. Furthermore, this thesis proposes …

Smart E-Bike Conversion Kit And Helmet, Megan West, Marena Trujillo, Hossein Asghari

Honors Thesis

With many state governments across the United States implementing shutdowns to prevent the spread of COVID-19, many bike retailers have seen dramatic increases in bike sales. Electric bicycles (e-bikes) have become increasingly popular as the public searches for alternatives to public transportation. Unfortunately, e-bike users assume some risk by riding bikes that are faster than conventional bicycles. While kits to convert conventional bicycles to e-bikes exist, no “smart” e-bike/helmet kit specifically designed to keep the user safe is currently available on the market. To mitigate risks, a smart e-bike conversion kit with multiple novel safety features, including auditory and visual …

Data Forgery Detection In Automatic Generation Control: Exploration Of Automated Parameter Generation And Low-Rate Attacks, Yatish R. Dubasi

Computer Science and Computer Engineering Undergraduate Honors Theses

Automatic Generation Control (AGC) is a key control system utilized in electric power systems. AGC uses frequency and tie-line power flow measurements to determine the Area Control Error (ACE). ACE is then used by the AGC to adjust power generation and maintain an acceptable power system frequency. Attackers might inject false frequency and/or tie-line power flow measurements to mislead AGC into falsely adjusting power generation, which can harm power system operations. Various data forgery detection models are studied in this thesis. First, to make the use of predictive detection models easier for users, we propose a method for automated generation …

Digital Twin-Based Cooperative Control Techniques For Secure And Intelligent Operation Of Distributed Microgrids, Ahmed Aly Saad Ahmed

FIU Electronic Theses and Dissertations

Networked microgrids play a key role in constructing future active distribution networks for providing the power system with resiliency and reliability against catastrophic physical and cyber incidents. Motivated by the increasing penetration of renewable resources and energy storage systems in the distribution grids, utility companies are encouraged to unleash the capabilities of the distributed microgrid to work as virtual power plants that can support the power systems. The microgrids nature is transforming the grid and their control systems from centralized architecture into distributed architectures. The distributed networked microgrids introduced many benefits to the future smart grids, it created many challenges …

Análisis En Un Sistema De Almacenamiento De Energía Basado En Hidrogeno Para Una Agrupación De Pozos Petroleros Con Penetración De Energía Solar, Jostin Esteban Martinez Rodriguez, Guillermo Humberto Ramirez Camacho

Ingeniería Eléctrica

El uso de las energías renovables hoy en día toma gran importancia, ya que estas permiten obtener energía de formas que se consideran limpias, a diferencia de las formas convencionales para realizar este mismo proceso, en las cuales se generan emisiones por el uso de combustibles fósiles. Un ejemplo de esto son las centrales termoeléctricas e hidroeléctricas, en donde la primera emite grandes cantidades de gases efecto invernadero, y la segunda produce problemáticas asociadas con la afectación en el ecosistema, ya que es necesario inundar grandes extensiones de terreno, afectando flora y fauna sin tener presente los cambios en el …