Engineering Commons^™

Generation Expansion Planning: Transitioning Toward Decarbonization With A Focus On Reliability And Dunkelflaute, Taraneh Ghanbarzadeh, Daryoush Habibi, S. M.Muslem Uddin, Asma Aziz

Research outputs 2022 to 2026

Modern power systems increasingly rely on variable renewable energy sources, supported by energy storage systems and gas power plants, to meet decarbonization targets. However, the high penetration of renewables introduces significant uncertainty due to their weather-dependent nature, posing challenges to system reliability. This paper proposes a probabilistic, multi-level generation expansion planning framework that integrates reliability assessments, with a particular emphasis on the role of energy storage systems. A novel probabilistic approach is also introduced to model the Dunkelflaute phenomenon and evaluate its impact on system reliability. Additionally, the study explores the influence of regulatory mechanisms — referred to as embedded …

A Light-Dependent Resistor Based Embedded Image Acquisition System For Use In Low-Resolution Application-Specific Data Processing, Connor Best

Journal of Undergraduate Research at Minnesota State University, Mankato

This paper proposes an efficient hardware-based approach to image acquisition & processing to replace complex camera systems in simple industrial & commercial applications.

Environment Mapping And Gps-Based Trailer Parking Using Low-Cost Peripheral Sensors And Post-Processing Algorithms, Connor Best

Journal of Undergraduate Research at Minnesota State University, Mankato

This paper explores the merit of software data optimization through two practical examples: environment mapping & GPS navigation.

Model-Based Assessment Of Ocean Monitoring Temporal And Spatial Resolution Requirements For Acoustic Operations, William K. Stevens, Martin Siderius

Electrical and Computer Engineering Faculty Publications and Presentations

Understanding present and future ocean conditions is essential for the effective planning and execution of a wide range of naval and commercial acoustic operations. The four-dimensional structure of temperature and salinity}from the ocean surface to the seabed}is a critical factor influencing acoustic transmission properties. Modern numerical ocean modeling systems consist of three primary components: ocean observations, a numerical forecasting model, and a data assimilation system. Of the tens of millions of global ocean observations assimilated daily, the majority derive from satellite-based surface measurements. In stark contrast, subsurface water column measurements number only in the thousands per day. This disparity highlights …

Teaching Machine Learning To Undergraduate Electrical Engineering Students, Gerald L. Fudge, Anika Rimu, William Zorn, July Ringle, Cody Barnet

Faculty Publications

Proficiency in machine learning (ML) and the associated computational math foundations have become critical skills for engineers. Required areas of proficiency include the ability to use available ML tools and the ability to develop new tools to solve engineering problems. Engineers also need to be proficient in using generative artificial intelligence (AI) tools in a variety of contexts, including as an aid to learning, research, writing, and code generation. Using these tools properly requires a solid understanding of the associated computational math foundation. Without this foundation, engineers will struggle with developing new tools and can easily misuse available ML/AI tools, …

Strategies For Obtaining High-Performance Li-Ion Solid-State Electrolytes For Solid-State Batteries, Yi-Cheng Deng, Zi-Chang You, Geng-Zhong Lin, Guo Tang, Jing-Hua Wu, Zhi-Min Zhou, Xiang-Chun Zhuang, Li-Xuan Yang, Zhen-Jie Zhang, Zhao-Yin Wen, Xia-Yin Yao, Chang-Hong Wang, Qian Zhou, Guang-Lei Cui, Ping He, Hui Li, Xin-Ping Ai

Journal of Electrochemistry

With the widespread adoption of lithium-ion batteries (LIBs), safety concerns associated with flammable organic electrolytes have become increasingly critical. Solid-state lithium batteries (SSLBs), with enhanced safety and higher energy density potential, are regarded as a promising next-generation energy storage technology. However, the practical application of solid-state electrolytes (SSEs) remains hindered by several challenges, including low Li⁺ ion conductivity, poor interfacial compatibility with electrodes, unfavorable mechanical properties and difficulties in scalable manufacturing. This review systematically examines recent progress in SSEs, including inorganic types (oxides, sulfides, halides), organic types (polymers, plastic crystals, poly(ionic liquids) (PILs)), and the emerging class of soft …

High-Voltage Solid-State Lithium Batteries: A Review Of Electrolyte Design, Interface Engineering, And Future Perspectives, Cheng Yang, Zi-Xin Liang, Ming-Yun Zhang, Ming-Zhe Chen, Kai Zhang, Li-Min Zhou

Journal of Electrochemistry

Solid-state lithium batteries have become a research hotspot in the field of large-scale energy storage due to their excellent safety performance. The development of high-voltage positive electrode materials matched with lithium metal anode have advanced the energy density of solid-state lithium batteries close to or even exceeding that of lithium batteries based on a liquid electrolyte, which is expected to be commercialized in the future. However, in high voltage conditions (> 4.3 V), the decomposition of electrolyte components, structural degradation, and interface side reactions significantly reduce battery performance and hinder its further development. This review summarizes the latest research progress …

Development Trends And Priority Research Fields Of Electrochemical Discipline In The 15th Five Year Plan Period, Lin Zhuang, Wen-Bin Cai, Heng-Xing Ji, Qing Li, Gong-Wei Wang, Sen Xin, Qing Zhao, Fang-Yi Cheng, Yu-Guo Guo, Lan-Qun Mao, Yang Tian, Fei Wu, Li-Min Zhang, Yan Xiang, Jin-Song Hu, Rui Cao, Li Xiao, Hua-Bing Tao, Wei Xing, Dong-Ping Zhan, Hong-Gang Liao, Mei-Ling Xiao, Bin Ren, Zhang-Quan Peng, Rui Wen, Xiang Wang, Yue-Feng Song, Hou-Fu Lv, Bao-Yu Xia, Guo-Xiong Wang, Jun Cheng, Zhi-Pan Liu, Min Zhou, Bing Huang, Cun-Pu Li, Yu-Qin Zou, Shuang-Yin Wang, Hai-Bo Lin, Zi-Dong Wei

Journal of Electrochemistry

In fulfillment of the national science-and-technology development agenda, the Department of Chemical Sciences of the National Natural Science Foundation of China (NSFC) convened the Strategic Symposium on the Fifteenth Five-Year (2026–2030) Development Plan for Electrochemistry held in Xiamen on 29 August, 2025—the culminating year of the Fourteenth Five-Year (2021–2025) Development Plan. More than forty leading experts in the field of electrochemistry participated with spanning nine thematic fronts: Interfacial Electrocatalysis, Interfacial Electrochemistry for Energy Storage, Bioelectrochemistry, Electrochemistry of Hydrogen Energy, Electrochemical Micro-/Nano-Manufacturing, Operando Electrochemical Characterization, Electro-Thermal Coupling Catalysis, Theoretical and Computational Electrochemistry, and Electrochemical Synthesis. The forum assembled China’s foremost electrochemical …

A Radiation-Hardened 4-Bit Flash Adc With Compact Fault-Tolerant Logic For Seu Mitigation, Fnu Naveed, Jeff Dix

Electrical Engineering and Computer Science Faculty Publications and Presentations

This paper presents a radiation-hardened 4-bit flash analog-to-digital converter (ADC) implemented in a 22 nm fully depleted silicon-on-insulator (FD-SOI) process for high-reliability applications in radiation environments. To improve single-event upsets (SEU) tolerance, the design introduces a compact fault-tolerant logic scheme based on Dual Modular Redundancy (DMR), offering reliability comparable to Triple Modular Redundancy (TMR) while using two storage nodes instead of three, and a simple XOR-based check in place of a majority voter. A distributed sampling architecture mitigates SEU vulnerabilities in the input path, while thin-oxide devices are used in analog-critical circuits to enhance total ionizing dose (TID) resilience. Post-layout …

Design And Implementation Of A Cross-Platform, Modular Electronic-Nose System, Kaushika Rudraraju

USF Tampa Graduate Theses and Dissertations

Electronic noses (e-noses) are a subject of great research. They are useful in multiple platforms and serve a great purpose in both studies and safety. This thesis presents a portable, modular e-nose platform that spans the full pipeline from sensing to visualization, with emphasis on scalability, repeatability, and straightforward integration. The hardware is organized as swappable sensor modules each hosting multiple commercial sensors and local signal-conditioning networked to a master microcontroller via structured communication protocols. High-resolution acquisition, time alignment, and efficient streaming to a host enable reliable logging and analysis. A controlled exposure chamber and a repeatable sampling protocol (baseline-exposure-purge …

Development And Validation Of A Composite Digital Balance Score For Spinocerebellar Ataxia: A Prospective Study., James Mcnames, Vrutangkumar V. Shah, Hannah L. Casey, Kristen L. Sowalsky, Mahmoud El-Gohary, Delaram Safarpour, Patricia Carlson-Kuhta, Jeremy D. Schmahmann, Liana S. Rosenthal, Susan Perlman, Multiple Additional Authors

Electrical and Computer Engineering Faculty Publications and Presentations

Clinical trials in spinocerebellar ataxia are currently limited by the large sample sizes required by available clinical endpoints. We aimed to devise a digital composite measure of standing and walking balance using wearable inertial sensors that would require smaller sample sizes. The new score is called the Score of Integrated Balance in Ataxia (SIBA).

Measures To Improve The Structure And Operating Principle Of Perovsite Light-Emitting Devices, Latofat Utkir Qizi Shuhratova, Rustam Rashidovich Kabulov, Farrux Anvar Ugli Akbarov, Anvar Akbarovich Alimov

Technical science and innovation

Since the discovery of the unique properties of perovskite materials, these materials have been used as active layers in various optoelectronic devices. In particular, perovskite-based light-emitting diodes (LEDs) have attracted the attention of many researchers as a highly efficient and versatile technology for lighting and display devices. Perovskite-based LEDs allow for tunable light emission and can be manufactured at low cost and with flexible fabrication technology. These advantages make them suitable for use in devices ranging from modern displays to wearable electronics. Despite their potential, solving problems such as material stability and industrial scale is one of the current challenges …

Methodology For Creating An Intelligent Mechatron Module Based On A Synergistic Approach, Nurbek Rustamovich Matyokubov, Temurbek Omonboyevich Rakhimov

Technical science and innovation

This article is devoted to the methodology of creating an intelligent mechatron module based on a synergistic approach. Creating a multi-coordinate intelligent mechatron module and expanding the functional capabilities of the controlled object based on them, allows to optimize the dynamic characteristics. Also, the methodology for creating an intelligent mechatronic module based on a synergistic approach allows for the integration of electrical, magnetic, and mechanical components into a single circuit, the integration of technical parameter modification, and the integration of processing functions into a single information-measuring module. In addition, the article proposes a Eurorhythm scheme for expressing how …

The Method Of Power Networks Mode Optimization In Basis Of Genetic Algorithm, Tulkin Shernazarovich Gayibov, Gulnaz Makhmutovna Turmanova

Technical science and innovation

One of the main tasks solved in planning short-term and managing operational modes of electric power systems (EPS) is the optimization of their network modes on the adjustable parameters. For modern complex EPS, this task is often characterized by the multi-extremality of the objective function, the appearance of discontinuous functions, the presence of initial information of a probabilistic and partially uncertain nature. In such conditions, solving the problem by traditional algorithms using mainly linear and nonlinear programming methods, Lagrange, gradient, etc., is associated with a number of difficulties in simplifying them and bringing them to a convenient form for calculations. …

Comparative Assessment Of Battery And Hydrogen Energy Storage In A Grid-Connected Heat-Electricity Integrated Microgrid, Naglaa Elsherbiny, Mohamed Elgamal, Islam Ismael, Akram Elmitwally

Mansoura Engineering Journal

Given the significant challenges of conventional power systems, including high emissions and operational costs, transitioning to microgrids (MGs) is increasingly critical. This paper presents a comprehensive evaluation of three energy management strategies for a grid-connected, heat-electricity integrated MG: (i) a base case without storage, (ii) a battery-based energy storage system (B-BESS), and (iii) a hydrogenbased energy storage system (H-BESS) comprising an electrolyzer (ELC), hydrogen tank (HT), and fuel cell (FC). This study optimizes operational profit and emissions reduction by integrating renewable energy and heat recovery mechanisms. Simulation results show that, compared to the base case, both B-BESS and H-BESS significantly …

Climate Change Projections Through Optimized Machine Learning And Deep Learning Models: A Comprehensive Analysis, Hala H. Youssef, Salma S. Mohammed, Hanan M. Amer, Abeer T. Khalil

Mansoura Engineering Journal

One major worldwide issue that has far-reaching effects on environmental stability and the avoidance of natural disasters is climate change. Developing efficient mitigating strategies depends on precise climate change forecasts. To predict important climate change indicators, including temperature fluctuations, greenhouse gas (CO2, N2O, CH4, and SF6) emissions, population dynamics, sea level changes, Arctic Sea ice extent, and Antarctica mass, this study evaluated the predictive capabilities of several Machine Learning (ML) and Deep Learning (DL) techniques. The set of machine learning algorithms includes Multiple Linear Regression (MLR), K-Nearest Neighbors (KNN), Support Vector Machines (SVMs), Artificial Neural Networks (ANN), Random Forest (RF), …

An Integrated Pcb-Based Heating And Auto-Ranging Platform For Volatile Organic Compound (Voc) Detection Using Carbon Nanotube Based Sensors, Thomas Kalach

USF Tampa Graduate Theses and Dissertations

This thesis presents the development, characterization, and integration of a novel low-cost, high-dynamic-range sensor platform for the detection of volatile organic compounds (VOCs), leveraging the unique electrical properties of carbon nanotube (CNT) thin films. The platform introduces a fully integrated auto-ranging analog front-end circuit capable of real-time resistance measurement spanning over eight orders of magnitude ranging from tens of ohms to hundreds of megaohms, without compromising signal resolution or precision. This was achieved through a digitally controlled, multi-path feedback architecture and controllable current source.

To further enhance sensor performance, the system incorporates a copper trace heater beneath the sensor array, …

Calving As A Source Of Acute And Persistent Kinetic Energy To Enhance Submarine Melting Of Tidewater Glaciers, M. F. Shaya, J. D. Nash, E. C. Pettit, J. M. Amundson, R. H. Jackson, D. A. Sutherland, Dylan Winters

Electrical and Computer Engineering Faculty Publications and Presentations

Calving icebergs at tidewater glaciers release large amounts of potential energy. This energy—in principle—could be a source for submarine melting, which scales with near‐terminus water temperature and velocity. Because near‐terminus currents are challenging to observe or predict, submarine melt remains a key uncertainty in projecting tidewater glacier retreat and sea level rise. Here, we study one submarine calving event at Xeitl Sít’ (LeConte Glacier), Alaska, to explore the effect of calving on ice melt, using a suite of autonomously deployed instruments beneath, around, and downstream of the calving iceberg. Our measurements captured flows exceeding 5 m/s and demonstrate how potential …

Performance Analysis Of Power System Dynamic Stability Of The Nigerian 330kv Transmission Network, Charles Evuarherhe Ikeyin, Benjamin Olabisi Akinloye

Al-Bahir

Nigeria's power sector faces persistent challenges, including dynamic instability, poor voltage regulation, and frequent grid collapses, primarily driven by reactive power deficits and transmission distances exceeding 200 km in northern regions. To bridge critical research gaps, this study employs a rigorous, multi-method approach through comprehensive EMTP-RV (Electromagnetic Transients Program) analysis of Nigeria’s 330kV 52-bus grid, PV curve-based vulnerability indexing to identify cascade-critical buses, and a novel Cost-benefit Pareto framework for optimal capacitor placement. Methodology was validated against IEEE (Institute of Electrical and Electronics Engineers) 14-bus benchmarks. Validated against IEEE 14-bus benchmarks, simulations revealed severe voltage instability in northern …

Resilience Oriented Distribution System Service Restoration Considering Overhead Power Lines Affected By Hurricanes, Kehkashan Fatima, Hussain Shareef, Flavio Costa

Michigan Tech Publications

In recent years, there has been an increase in the frequency of severe weather events (like hurricanes). These events are responsible for most power outages in power distribution systems (PDSs). Particularly susceptible to storms are overhead PDSs. In this study, the dynamic Bayesian network (DBN)-based failure model was developed for different hurricane scenarios to predict the line failure of overhead lines. Based on the outcomes of the DBN model, a service restoration model was formulated to maximize restored loads and minimize power losses using Particle Swarm Optimization (PSO)-based distributed generation (DG) integration and system reconfiguration. Three different case studies based …

Non-Invasive Way For Detection Of Neonatal Jaundice Using Gbr, Priti V. Bhagat, Mukesh Raghuwanshi, Ashutosh D. Bagde

Chulalongkorn Medical Journal

Background: Neonatal jaundice is a common condition in newborns due to excess levels of bilirubin. The traditional method for bilirubin testing is invasive, i.e., through blood tests only, which is painful to infants. Therefore, this study uses machine learning algorithms to develop a non-invasive way to detect neonatal jaundice.

Objectives: Design a computer-aided support system to detect neonatal jaundice using machine learning algorithm.

Methods: The gradient-boosting regression model is used to predict the bilirubin level. Gradient Boosting is a robust boosting algorithm that combines several weak learners into strong learners, in which each new model is trained to minimize the …

Trustworthy Navigation With Variational Policy In Deep Reinforcement Learning, Karla Bockrath, Liam Ernst, Rohaan Nadeem, Bryan Joseph Pedraza, Dimah Dera

Electrical and Computer Engineering Faculty Publications

Introduction: Developing a reliable and trustworthy navigation policy in deep reinforcement learning (DRL) for mobile robots is extremely challenging, particularly in real-world, highly dynamic environments. Particularly, exploring and navigating unknown environments without prior knowledge, while avoiding obstacles and collisions, is very cumbersome for mobile robots.

Methods: This study introduces a novel trustworthy navigation framework that utilizes variational policy learning to quantify uncertainty in the estimation of the robot’s action, localization, and map representation. Trust-Nav employs the Bayesian variational approximation of the posterior distribution over the policy-based neural network’s parameters. Policy-based and value-based learning are combined to guide the robot’s actions …

Authenticating Electronic Devices Via Multi Tone Analysis, Carl Bohman Jr., Aaron Jennings, Christian Eakins, Mark B. Skouson, Richard Ott, Jamin Mccue

AFIT Patents

Methods and systems for authenticating electronic devices via multi tone analysis. A method for authenticating a device under test (DUT) of a type of DUT includes imparting voltage tones to the DUT. The voltage tones are proximate a frequency of interest that is associated with the type of DUT. Using a measurement response of the DUT to the voltage tones, an electronic signature of the DUT is determined. The DUT is determined to be authentic when the electronic signature of the DUT substantially matches an electronic signature of an authority DUT of the type of DUT.

Maximum Likelihood Symbol Timing Algorithm Based On Cyclic Prefix For Ofdm Systems, Kwame S. Ibwe

Tanzania Journal of Engineering and Technology (TJET)

In this paper, a blind symbol synchronization algorithm is presented for orthogonal frequency-division multiplexing (OFDM) systems, and a timing function based on the redundancy of the cyclic prefix (CP) is introduced. The existing algorithms rely on the prior knowledge of the channel energy distribution i.e. channel power profile. In practical environment the channel power profile is unknown to the receiver and its statistics are expected to be highly changing. Nevertheless, the use of pilot symbols in channel profile estimation reduces efficiency as data subcarriers are used to carry pilots instead of payload. In this paper a timing function that accounts …

Techno-Economic Analysis Of Hybrid Pv-Wind-Diesel Generator Swarm Grid For Rural Electrification In Tanzania, Ibrahim Mwammenywa

Tanzania Journal of Engineering and Technology (TJET)

Remote, rural, and off-grid communities, particularly in Sub-Saharan Africa (SSA), face significant challenges in securing reliable and affordable electricity. While solutions such as solar home systems (SHSs) and diesel generators (DGs) have been adopted by some individuals, their deployment is often not optimized to meet the full load demand. This study addresses this challenge by proposing a hybrid swarm grid (HSG) design that integrates photovoltaic (PV), wind energy, and diesel generators (DGs). Utilizing MATLAB/Simulink and HOMER, the HSG is modeled and optimized for a typical SSA village, incorporating real-world variables such as load demand profiles, solar irradiance, and wind patterns. …

Adoption Of Agrivoltaics In Developing Countries: A Review On Challenges, Opportunities And Future Prospects, Abdi J. Athumani, Pater Makolo

Tanzania Journal of Engineering and Technology (TJET)

This paper provides a review of agrivoltaics technology and how it has been applicable in developing countries, including African countries. Agrivoltaics, the integration of agricultural production with photovoltaic energy generation, offers promising solutions to water- energy-food nexus in developing countries. This technology offers the dual benefit of increasing agricultural productivity while generating clean energy, which is very important for regions facing frequent electricity shortages and declining agricultural yields due to climate change. However, despite its potential, the adoption of agrivoltaics in developing nations remains limited in comparison to developed countries due to financial, technical and policy constraints. This paper explores …

Optimal Location And Sizing Of Facts Devices To Improve Voltage Profiles On A 132 Kv Mwanza-Musoma-Nyamongo Transmission Line, Peter Makolo

Tanzania Journal of Engineering and Technology (TJET)

Recently, utility companies have desired to supply quality, stable and reliable power to customers, and ensure they meet the demand. Flexible AC Transmission Systems (FACTS) dynamic compensator devices such as Static Synchronous Compensator (STATCOM), Static VAr Compensator (SVC) and Unified Power Flow Controller (UPFC) are an impeccable choice, however, cost is one of the limiting factors following these technologies. In addition, using FACTS devices in the system requires a detailed steady state, dynamic and optimisation analysis to effectively meet the purpose and ensure reduced cost. This paper proposes using an optimised FACTS device to improve voltage profile, power transfer, system …

Investigating The Harmonic Content Of A Pwm Inverter With Varying Modulation Index, Peter Makolo

Tanzania Journal of Engineering and Technology (TJET)

Photovoltaic energy is a clean and endless vital renewable energy. In order to generate electricity from solar energy an inverter is required to transform the direct current into alternating current. Also, with the emerging of new ultra-high voltage direct current transmission technology, the rectification and inverters play a great role. Most three-phase two-level inverters draw harmonics that cause heat dissipation, waveform distortions hence affect the electrical loads. Knowing that Total Harmonic Distortion content of voltage source inverter is important and must be within the allowable range. Several schemes are suggested to mitigate the distortion in order to produce as much …

Towards Autonomous Energy Management: Machine Learning For Effective Auditing And Optimization, Sameh O. Abdellatif, Sherif Ashraf, Mira Mohsen

Electrical Engineering

This study presents a fully automated procedure for energy management and auditing, applicable to a diverse range of residential and commercial loads, leveraging machine learning techniques across three key phases: load classification, benchmarking, and smart monitoring. The model effectively categorizes energy loads based on consumption patterns, establishes performance benchmarks through historical data analysis, and employs real-time monitoring to identify inefficiencies and predict future energy usage. Evaluating the model through four distinct case studies demonstrates its capability to optimize energy consumption in a techno-economic manner, achieving significant energy savings of 34.73 MWh/year for essential loads in Egypt, 215.67 MWh/year for HVAC …

Developing A Low-Temperature Pathway For The Synthesis Of Two-Dimensional Ws2 Nanosheets, Akhil Potdar

Holster Scholar Projects

Since their discovery in 2004, two-dimensional (2D) materials have attracted great attention due to their unique mechanical, electrical, and chemical properties. However, their integration into devices is limited by the high temperatures required for crystalline growth, which prevents the use of flexible and biocompatible substrates like polymers for biomedical and next-generation electronic devices. This project aims to therefore develop a low-temperature synthesis process for two-dimensional tungsten disulfide (WS₂), a material particularly promising due to its tunable bandgap and biocompatibility. We propose that by first depositing an intermediate tungsten oxide film (WOx) via Hollow Cathode Plasma-Assisted Atomic Layer Deposition (HCP-ALD) and …