Engineering Commons^™

Digital Twin For Hvac Load And Energy Storage Based On A Hybrid Ml Model With Cta-2045 Controls Capability, Rosemary E. Alden, Evan S. Jones, Huangjie Gong, Abdullah Al Hadi, Dan Ionel

Power and Energy Institute of Kentucky Faculty Publications

Building modeling, specifically heating, ventilation, and air conditioning (HVAC) load and equivalent energy storage calculations, represent a key focus for decarbonization of buildings and smart grid controls. Widely used white box models, due to their complexity, are too computationally intensive to be employed in high resolution distributed energy resources (DER) platforms without simulation time delays. In this paper, an ultra-fast one-minute resolution Hybrid Machine Learning Model (HMLM) is proposed as part of a novel procedure to replicate white box models as an alternative to widespread experimental big data collection. Synthetic output data from experimentally calibrated EnergyPlus models for three existing …

Forecast Of Community Total Electric Load And Hvac Component Disaggregation Through A New Lstm-Based Method, Huangjie Gong, Rosemary E. Alden, Aron Patrick, Dan Ionel

Power and Energy Institute of Kentucky Faculty Publications

The forecast and estimation of total electric power demand of a residential community, its baseload, and its heating ventilation and air-conditioning (HVAC) power component, which represents a very large portion of a community electricity usage, are important enablers for optimal energy controls and utility planning. This paper proposes a method that employs machine learning in a multi-step integrated approach. An LSTM model for total electric power at the main circuit feeder is trained using historic multi-year hourly data, outdoor temperature, and solar irradiance. New key temperature indicators, TmHAVC, corresponding to the standby zero-power operation for HVAC systems for summer cooling …

Prostacyclin Promotes Degenerative Pathology In A Model Of Alzheimer’S Disease, Tasha R. Womack, Craig T. Vollert, Odochi Ohia-Nwoko, Monika Schmitt, Saghi Montazari, Tina L. Beckett, David Mayerich, M. Paul Murphy, Jason L. Eriksen

Molecular and Cellular Biochemistry Faculty Publications

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that is the most common form of dementia in aged populations. A substantial amount of data demonstrates that chronic neuroinflammation can accelerate neurodegenerative pathologies. In AD, chronic neuroinflammation results in the upregulation of cyclooxygenase and increased production of prostaglandin H2, a precursor for many vasoactive prostanoids. While it is well-established that many prostaglandins can modulate the progression of neurodegenerative disorders, the role of prostacyclin (PGI2) in the brain is poorly understood. We have conducted studies to assess the effect of elevated prostacyclin biosynthesis in a mouse model of AD. Upregulated prostacyclin expression …

Recent Advances Of Wind-Solar Hybrid Renewable Energy Systems For Power Generation: A Review, Pranoy Roy, Jiangbiao He, Tiefu Zhao, Yash Veer Singh

Electrical and Computer Engineering Faculty Publications

A hybrid renewable energy source (HRES) consists of two or more renewable energy sources, such as wind turbines and photovoltaic systems, utilized together to provide increased system efficiency and improved stability in energy supply to a certain degree. The objective of this study is to present a comprehensive review of wind-solar HRES from the perspectives of power architectures, mathematical modeling, power electronic converter topologies, and design optimization algorithms. Since the uncertainty of HRES can be reduced further by including an energy storage system, this paper presents several hybrid energy storage system coupling technologies, highlighting their major advantages and disadvantages. Various …

Evaluation Of The Accuracy Of Different Pv Estimation Models And The Effect Of Dust Cleaning: Case Study A 103 Mw Pv Plant In Jordan, Loiy Al-Ghussain, Moath Abu Subaih, Andres Annuk

Mechanical Engineering Graduate Research

The estimation of PV production has been widely investigated previously, where many empirical models have been proposed to account for wind and soiling effects for specific locations. However, the performance of these models varies among the investigated sites. Hence, it is vital to assess and evaluate the performance of these models and benchmark them against the common PV estimation model that accounts only for the ambient temperature. Therefore, this study aims to evaluate the accuracy and performance of four empirical wind models considering the soiling effect, and compare them to the standard model for a 103 MW PV plant in …

Highly-Individualized Physical Therapy Instruction Beyond The Clinic Using Wearable Inertial Sensors, Samir A. Rawashdeh, Ella Reimann, Timothy L. Uhl

Physical Therapy Faculty Publications

Musculoskeletal conditions, often requiring rehabilitation, affect one-third of the U.S. population annually. This paper presents rehabilitation assistive technology that includes body-worn motion sensors and a mobile application that extends the reach of a physical rehabilitation specialist beyond the clinic to ensure that home exercises are performed with the same precision as under clinical supervision. Assisted by a specialist in the clinic, the wearable sensors and user interface developed allow the capture of individualized exercises unique to the patient’s physical abilities. Beyond the clinical setting, the system can assist patients by providing real-time corrective feedback to repeat these exercises through a …

Application Of Deep Neural Networks To Distribution System State Estimation And Forecasting, James P. Carmichael, Yuan Liao

Electrical and Computer Engineering Faculty Publications

Classical neural networks such as feedforward multi-layer 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. The dynamic nature of distributed generation (i.e. solar and wind), vehicle to grid technology (V2G) and false data injection attacks (FDIAs), may pose significant challenges to the application of classical MLPs to state estimation (SE) and state forecasting (SF) in power distribution systems. This paper investigates the application of conventional neural networks (MLPs) and deep learning based models such as convolutional neural networks (CNNs) and long-short term networks …

Application Of Deep Neural Networks To Distribution System State Estimation And Forecasting, James P. Carmichael, Yuan Liao

Electrical and Computer Engineering Faculty Publications

Classical neural networks such as feedforward multi-layer 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. The dynamic nature of distributed generation (i.e. solar and wind), vehicle to grid technology (V2G) and false data injection attacks (FDIAs), may pose significant challenges to the application of classical MLPs to state estimation (SE) and state forecasting (SF) in power distribution systems. This paper investigates the application of conventional neural networks (MLPs) and deep learning based models such as convolutional neural networks (CNNs) and long-short term networks …

The Effects Of Reference-Command Preview On The Strategies That Humans Use In Command-Following Tasks, Amelia J. S. Sheffler

Theses and Dissertations--Mechanical Engineering

This thesis presents results from an experiment in which 22 human subjects each interact with a dynamic system 40 times over a one-week period. For each interaction, a subject performs a command-following task, where the reference command is the same for all 22 subjects but different on each trial. The subjects are divided into 2 groups of 11 subjects. One group performs the command-following task without reference-command preview. The other group is provided with 1-s preview of the reference command. The experimental results are used to examine the effects of reference-command preview. For the group with 1-s reference-command preview, the …

Experimental Comparison Of Two Sampled-Data Adaptive Control Algorithms For Rejecting Sinusoidal Disturbances, William Grayson Woods

Theses and Dissertations--Mechanical Engineering

We review two adaptive control algorithms that address the problem of rejecting sinusoids with known frequencies that act on an unknown asymptotically stable linear time-invariant system. We present modifications to the algorithms that address the problems of sensor noise and actuator saturation. We demonstrate the effectiveness of the algorithms and compare the performance of the algorithms via numerical simulation and experimental testing.

Determining Power System Fault Location Using Neural Network Approach, Edward O. Ojini

Theses and Dissertations--Electrical and Computer Engineering

Fault location remains an extremely pivotal feature of the electric power grid as it ensures efficient operation of the grid and prevents large downtimes during fault occurrences. This will ultimately enhance and increase the reliability of the system. Since the invention of the electric grid, many approaches to fault location have been studied and documented. These approaches are still effective and are implemented in present times, and as the power grid becomes even more broadened with new forms of energy generation, transmission, and distribution technologies, continued study on these methods is necessary. This thesis will focus on adopting the artificial …

Formation Control With Bounded Controls And Collision Avoidance: Theory And Application To Quadrotor Unmanned Air Vehicles, Zachary S. Lippay

Theses and Dissertations--Mechanical Engineering

This dissertation presents new results on multi-agent formation control and applies the new control algorithms to quadrotor unmanned air vehicles. First, this dissertation presents a formation control algorithm for double-integrator agents, where the formation is time varying and the agents’ controls satisfy a priori bounds (e.g., the controls accommodate actuator saturation). The main analytic results provide sufficient conditions such that all agents converge to the desired time-varying relative positions with one another and the leader, and have a priori bounded controls (if applicable). We also present results from rotorcraft experiments that demonstrate the algorithm with time-varying formations and bounded controls. …

Parametric Average-Value Modeling, Simulation, And Characterization Of Machine-Rectifier Systems, Isuje Ojo

Theses and Dissertations--Electrical and Computer Engineering

There are many techniques for modeling and simulation of synchronous machine-rectifier systems. The more common approaches are the detailed and average-value modeling techniques. The detailed simulation technique takes into account the details of the diode switching and is both very accurate and very expensive in terms of computational resources. To alleviate this disadvantage, the average-value modeling technique is often utilized. In this approach, the details of diode switching are neglected or averaged. In that light, the work presented herein proposes a unique saliency-sensitive parametric average-value model (SSPAVM) of the synchronous machine-rectifier system. This model extends existing parametric average-value models to …

An Electrochemical-Mechanical Investigation Of Next Generation Lithium Metal Electrode And Solid Electrolyte, Andrew Meyer

Theses and Dissertations--Chemical and Materials Engineering

Lithium-ion batteries (LIBs) are a staple in today’s society. From our cellphones, laptops, power tools, the ever-growing electric vehicle, and many more application, LIBs are more important to us than most realize. They provide the best combination of both high-energy and high-power density compared to other battery types such as Ni-Cd, Ni-MH, or the lead acid batteries used in our cars. Plus, LIBs are much safer. However, as new technologies grow and are developed, the demand for higher energy and power density, better safety, lower costs, and longer life increases. One way to achieve the ever-increasing demands is to replace …

Three Dimensional Photonics Structures: Design And Applications, Mansoor Sultan

Theses and Dissertations--Electrical and Computer Engineering

Photonics is an emerging technology for light control, emission, and detection. Photonic devices control photons the same way electronic circuits control electrons in active or passive mode depending on the energy requirement of the device. This dissertation will discuss the design, fabrication, testing of photonic structures with applications including imaging and renewable energy. First, we developed a novel lithography method for fluoropolymer resist based on variable pressure electron beam lithography (VP-EBL). VP-EBL proves to be an efficient method for patterning a widely used, but challenging to process, fluoropolymer, Teflon AF. However, rather than solely mitigating charging, the ambient gas is …

A Computational Exploration Of The Scandate Cathode Surface, Shankar Miller-Murthy

Theses and Dissertations--Chemical and Materials Engineering

The exact surface configuration of scandate cathodes has been a point of contention for the materials community for a long time. Without proper understanding of it and the related structures and emission mechanisms, scandate cathodes remain patchy and unreliable emitters. Thus, density functional theory techniques were applied to various potential surface arrangements and found that there are several low-energy surfaces with low work functions that incorporate a scandium interlayer between tungsten and oxygen or otherwise have a scandium-on-tungsten structure. Furthermore, it was discovered that adding a monolayer of scandium directly to a tungsten surface is surprisingly favorable, thermodynamically. While none …

Protocols And Architecture For Privacy-Preserving Authentication And Secure Message Dissemination In Vehicular Ad Hoc Networks, Shafika Showkat Moni

Theses and Dissertations--Computer Science

The rapid development in the automotive industry and wireless communication technologies have enhanced the popularity of Vehicular ad hoc networks (VANETs). Today, the automobile industry is developing sophisticated sensors that can provide a wide range of assistive features, including accident avoidance, automatic lane tracking, semi-autonomous driving, suggested lane changes, and more. VANETs can provide drivers a safer and more comfortable driving experience, as well as many other useful services by leveraging such technological advancements. Even though this networking technology enables smart and autonomous driving, it also introduces a plethora of attack vectors. However, the main issues to be sorted out …

Models And Optimal Controls For Smart Homes And Their Integration Into The Electric Power Grid, Huangjie Gong

Theses and Dissertations--Electrical and Computer Engineering

Smart homes can operate as a distributed energy resource (DER), when equipped with controllable high-efficiency appliances, solar photovoltaic (PV) generators, electric vehicles (EV) and energy storage systems (ESS). The high penetration of such buildings changes the typical electric power load profile, which without appropriate controls, may become a “duck curve” when the surplus PV generation is high, or a “dragon curve” when the EV charging load is high. A smart home may contribute to an optimal solution of such problems through the energy storage capacity, provided by its by battery energy storage system (BESS), heating, ventilation, and air conditioning (HVAC) …

Modeling Human Control Behavior In Command-Following Tasks, Sajad Koushkbaghi

Theses and Dissertations--Mechanical Engineering

Humans interact with a variety of complex dynamic systems on a daily basis. However, they are often the lesser understood component of human-in-the-loop (HITL) systems. In this dissertation, we present the results of two HITL experiments to investigate the control strategies that humans use when performing command-following tasks. The first experiment is designed to investigate the control strategies that humans use to interact with nonlinear dynamic systems. Two groups of human subjects interact with a dynamic system and perform a command-following task. One group interacts with a linear time-invariant (LTI) dynamic system and the other group interacts with a Wiener …

Sizing Considerations For Ev Dynamic Wireless Charging Systems With Integrated Energy Storage, Donovin Lewis, Huangjie Gong, Gregory D. Erhardt, Rong Zeng, Omer Onar, Veda Prakash Galigekere, Burak Ozpineci, Dan Ionel

Power and Energy Institute of Kentucky Faculty Publications

Roadways with dynamic wireless charging systems (DWCS) enable charge-sustaining in-motion EV charging, which can reduce charging idle time while increasing range capabilities. Spatially distributed transmitter coils are controlled in response to traffic load that varies significantly minute to minute with high power levels, very short charging time, and low system utilization like wind turbine power. Traffic load estimation and localized analysis may guide effective sizing and topology adoption for feasible and scalable DWCS deployment. DWCS traffic load approximation is reviewed with measured Automated Traffic Recorder (ATR) data and statistical distributions being used to create a synthetic load analyzed using proposed …

Energy-Efficient And Secure Hardware Using Adiabatic Logic And Non-Volatile Mtj Devices, Zachary Kahleifeh

Theses and Dissertations--Electrical and Computer Engineering

Internet of Things (IoT) is a collection of devices that exchange data through a network to implement complex applications. IoT devices increase the quality of life of their user base which has a wide variety such as the medical field, consumer electronics, and the manufacturing sector. However, IoT devices have several challenges that need to be overcome namely, security and energy consumption. The threat vector that IoT devices face is growing and includes the following threats, the leakage of information through a side-channel attack known as the Correlation Power Analysis (CPA), authentication, piracy, etc. A side-channel attack is an attack …

Hourly Dispatching Wind-Solar Hybrid Power System With Battery-Supercapacitor Hybrid Energy Storage, Pranoy Kumar Singha Roy

Theses and Dissertations--Electrical and Computer Engineering

This dissertation demonstrates a dispatching scheme of wind-solar hybrid power system (WSHPS) for a specific dispatching horizon for an entire day utilizing a hybrid energy storage system (HESS) configured by batteries and supercapacitors. Here, wind speed and solar irradiance are predicted one hour ahead of time using a multilayer perceptron Artificial Neural Network (ANN), which exhibits satisfactory performance with good convergence mapping between input and target output data. Furthermore, multiple state of charge (SOC) controllers as a function of energy storage system (ESS) SOC are developed to accurately estimate the grid reference power (P_Grid,ref) for each dispatching period. …

Multi-Physics And Artificial Intelligence Models For Digital Twin Implementations Of Residential Electric Loads, Steven Poore, Rosemary E. Alden, Huangjie Gong, Dan M. Ionel

Power and Energy Institute of Kentucky Faculty Publications

Heating, ventilation, and air-conditioning (HVAC) and electric water heating (EWH) represent residential loads. Simulating these appliances for electric load forecasting, demand response (DR) studies, and human behavior analysis using physics-based models and artificial intelligence (AI) can further advance smart home technology. This paper explains the background of residential load modeling, starting with the concept of digital twin (DT) as well as the different types of methods. Two major types of appliance load monitoring (ALM) and their advantages/disadvantages are then discussed. This is followed by a review of multiple studies on residential load modeling, particularly for HVAC, EWH, and human behavior. …

Large-Scale Modeling And Dr Control Of Electric Water Heaters With Energy Star And Cta-2045 Control Types In Distribution Power Systems, Huangjie Gong, Evan S. Jones, A. H. M. Jakaria, Aminul Huque, Ajit Renjit, Dan Ionel

Power and Energy Institute of Kentucky Faculty Publications

The paper proposes a generalized energy storage (GES) model for battery energy storage systems (BESS), electric water heaters (EWH) and heating, ventilation, and air-conditioning (HVAC) systems to enable demand response control complying to Energy Star and CTA-2045 standards. The demand response control has been implemented in the DER integration testbed, which was originally developed by EPRI, to demonstrate that the “energy content” and “energy take” for BESS and EWH with mixing valve technology are comparable for typical residential ratings. A distribution power system was modeled using the modified IEEE 123-bus feeder system, measured residential loads, and EWH power simulated based …

Stochastic Battery Soc Model Of Ev Community For V2g Operations Using Cta-2045 Standards, Huangjie Gong, Rosemary E. Alden, Dan Ionel

Power and Energy Institute of Kentucky Faculty Publications

An electric vehicle (EV) battery has large energy storage capacity in the context of residential total usage, and the potential to provide large energy reserves for Home energy Management (HEM) systems. In an electric distribution system, groups of EVs could provide vehicle-to-grid (V2G) service in response to control signals and enable virtual power plant (VPP) operation of the car batteries. The CTA-2045 standards were considered for integration of the EV controls into the HEM system for maximal interoperability with other appliances, such as residential battery, electric water heater, and heating, ventilation, and air conditioning (HVAC) system. The power distribution system …

Development Of Dc Circuit Breakers For Medium-Voltage Electrified Transportation, Trevor Morgan Arvin

Theses and Dissertations--Electrical and Computer Engineering

Medium-voltage DC (MVDC) distribution is an enabling technology for the electrification of transportation such as aircraft and shipboard. One main obstacle for DC distribution is the lack of adequate circuit fault protection. The challenges are due to the rapidly rising fault currents and absence of zero crossings in DC systems compared to AC counterparts. Existing DC breaker solutions lack comprehensive consideration of energy efficiency, power density, fault interruption speed, reliability, and implementation cost.

In this thesis, two circuit topologies of improved DC circuit breakers are developed: the resonant current source based hybrid DC breaker (RCS-HDCB) and the high temperature superconductor …

Improving Network Policy Enforcement Using Natural Language Processing And Programmable Networks, Pinyi Shi

Theses and Dissertations--Computer Science

Computer networks are becoming more complex and challenging to operate, manage, and protect. As a result, Network policies that define how network operators should manage the network are becoming more complex and nuanced. Unfortunately, network policies are often an undervalued part of network design, leaving network operators to guess at the intent of policies that are written and fill in the gaps where policies don’t exist. Organizations typically designate Policy Committees to write down the network policies in the policy documents using high-level natural languages. The policy documents describe both the acceptable and unacceptable uses of the network. Network operators …

Explainable Data-Driven Motor Condition Monitoring And Fault Disgnosis, Yuming Wang

Theses and Dissertations--Electrical and Computer Engineering

Industrial motors are widely used in various fields such as power generation, mining, and manufacturing. Motor faults and time-consuming maintenance process will lead to serious economic losses in this context. To monitor motor faults and detect motor conditions, different types of sensors that can test vibration and current signals are mounted on motors. However, the main challenge was how to use information gained by sensors to analyze or diagnose motor conditions.

Machine learning is a popular technology in recent years, and it's very suitable for crunching and analyzing data. As an important subset of machine learning, deep learning is suitable …

Synthesizing Dysarthric Speech Using Multi-Speaker Tts For Dsyarthric Speech Recognition, Mohammad Soleymanpour

Theses and Dissertations--Electrical and Computer Engineering

Dysarthria is a motor speech disorder often characterized by reduced speech intelligibility through slow, uncoordinated control of speech production muscles. Automatic Speech recognition (ASR) systems may help dysarthric talkers communicate more effectively. However, robust dysarthria-specific ASR requires a significant amount of training speech is required, which is not readily available for dysarthric talkers.

In this dissertation, we investigate dysarthric speech augmentation and synthesis methods. To better understand differences in prosodic and acoustic characteristics of dysarthric spontaneous speech at varying severity levels, a comparative study between typical and dysarthric speech was conducted. These characteristics are important components for dysarthric speech modeling, …

Laptop Recycling Case Study: Estimating The Contained Value And Value Recovery Process Feasibility Of End-Of-Life Consumer Electronics, Zebulon Hart

Theses and Dissertations--Mining Engineering

Work has been done to establish, through the development and use of novel assay techniques and analysis metrics, the contained value of a sampling of laptop computers (as an analog for myriad e-waste sources). This work has conceptualized e-waste as an alternative to geologic-origin complex metallic ores and has likewise evaluated the feasibility of value recovery from e-waste sources in a similar manner to an ore. The application of conventional and novel mineral separation techniques to e-waste recycling processes has been evaluated and positive results are demonstrated. Further, this work has demonstrated the ability to identify the presence of base …