Power and Energy Commons^™

Enhanced Cuckoo Search-Based Optimization For Single Distributed Generation Placement And Sizing In Radial Distribution Systems, Samson Oladayo Ayanlade, Abdulrasaq Jimoh, Richard Oladayo Olarewaju, Ignatius Kema Okakwu, Israel O. Adejumobi, Joseph B. Samson, Oluwadare A. Adebisi, Oluwadare O. Akinrogunde

Al-Bahir

This paper presents an Enhanced Cuckoo Search Algorithm (ECSA) to optimally place and size Distributed Generation (DG) in radial distribution systems to minimize real power loss within operating constraints. The proposed ECSA has exponentially decaying adaptive Lévy flights, constraint-aware solution repair with dynamic penalty coefficients, and diversity-directed stochastic replacement to enhance search robustness and convergence speed. It was tested with 30 independent runs on the IEEE 33-bus, IEEE 69-bus, and a practical Nigerian 32-bus distribution network. The simulations show that the ECSA lowers the active power loss of the IEEE 33-bus system from 201.58 kW to 102.75 kW (49.03%), and …

Quantifying And Integrating Community Hardship Into Two-Stage Stochastic Grid Reliability Optimization With Battery Storage, Fredrica Arthur

LSU Master's Theses

Traditional reliability planning for conventional distribution systems is largely utility-oriented, with a focus on collective system performance metrics like Expected Energy Not Supplied (EENS), where implicitly all unserved energy is considered of equal weight in terms of post-outage economic hardship. Yet, it is well understood that extended outage durations cause an uneven level of hardship to socioeconomically disadvantaged communities. This thesis proposes a community-informed reliability planning framework where the hardship caused by outages is explicitly considered in the battery energy storage system (BESS) location and sizing problem. First, a hardship-weighted Energy Not Supplied (WENS) measure is proposed, where income, education, …

Availability Model To Evaluate Ai Data Centers’ Role In Grid Stability, Troy Mcsimov, Trevor S. Kunz, Jeffrey Billo

SMU Data Science Review

The United States has made it clear; it is imperative that the US wins the global AI race. This paper focuses on one of the most challenging puzzle pieces surfaced at the POWER Data Center conference (San Antonio, Sept. 30.); for Electric Reliability Council of Texas (ERCOT) the limiting factor is not generation alone but the need to balance generation and load to preserve grid reliability.

The regulatory landscape fundamentally changed with the passage of Texas Senate Bill 6 in June 2025, which mandates new large loads must "contribute to the recovery of the interconnecting electric utility’s costs" (Texas Legislature, …

Reducing Range Anxiety Through Predictive Modeling Of Ev Battery Degradation, Caleb Thornsbury, Christian Castro, Bivin Sadler

SMU Data Science Review

Electric Vehicles (EV) range anxiety remains one of the top barriers for broader adoption. Range anxiety can be attributed to battery pack age and degradation over time. This paper plans to explore how to address this issue by creating a machine learning model that can predict degradation based on usage, temperature, battery chemistry, charging habits and exploring whether other factors tie into range degradation. This research will be using real world charging data along with lab tested chemistry data to build a model that can be chemistry specific for degradation. This paper will help perspective used-EV buyers learn about battery …

Sustainabake, Kevin Kunta Swanson Ii

Electrical Engineering

This senior project outlines the development of an oven that utilizes renewable energy to operate safely and effectively. It aims to test building an oven using mostly basic hardware students acquired during their time at Cal Poly and provide a starting point for those interested in creating a solar-powered oven. As our society continues to innovate and increasingly relies on electricity, it is important to place more emphasis on how we can make our lives sustainable to take care of our environment without introducing excessive pollutants. Food preparation is a daily activity that typically involves significant energy consumption, making this …

Current Research Progress On Electrode Materials For All-Vanadium Redox Flow Batteries, Wen-Qi Wang, Jie Jin, Li-Min Wang, Xin-Yue Liu, Tao Cheng, Yong Hou, Han Xue, Zhi-Yu Wang, Bo Liu, Jia-Bao Liu, Xu-Bin Lu

Journal of Electrochemistry

The redox active species in all-vanadium redox flow batteries (VRFBs) reside in the electrolyte, while the heterogeneous reactions occur on the electrode surface; the electrode is therefore the decisive platform for dynamic adsorption, electron transfer, and ion conversion, especially for the VO²⁺/VO₂⁺ and V²⁺/V³⁺ couples. One of the major challenges for VRFBs is the slow charge transfer in VO²⁺/VO₂⁺ and V²⁺/V³⁺ reactions, mainly caused by poor catalytic performance of electrodes and weak adhesion of catalysts to electrodes. This review focuses on the key challenges and recent …

Strategic Research On Rebco High-Temperature Superconducting Tapes, Tianping Ying, Dongliang Wang, Pengtao Yang, Lin Zhao, Zhongtang Xu, Ziyi Liu, Chao Yao, Yanwei Ma, Xingjiang Zhou, Jinguang Cheng, Zhong Fang

Bulletin of Chinese Academy of Sciences (Chinese Version)

High-temperature superconducting materials, represented by REBCO (REBa2Cu3O7-δ, where RE denotes rare-earth elements), are of significant strategic importance in fields such as energy, healthcare, and large-scale scientific facilities due to their excellent performance in the liquid nitrogen temperature range. However, they still face severe challenges in long-tape uniformity, production cost, and engineering reliability. Future development must shift toward a “material-processing-application” collaborative innovation model, aiming at enhancing flux pinning, optimizing the interfaces and mechanical properties of the multilayer structure, and integrating scalable and intelligent fabrication technologies to promote the low-cost and stable production of high-performance tapes. This study analyzes the core application …

Machine Learning In Peak Demand Forecasting: Foundations, Trends, And Insights, Shuang Dai, Fanlin Meng, Hongsheng Dai, Qian Wang, Xizhong Chen, Wenlei Bai, Peizhi Shi, Richard Allmendinger, Yuchen Zhang, Jian Liu

Electrical and Computer Engineering Faculty Research & Creative Works

Peak demand forecasting involves predicting the maximum electricity demand within a specific period, which plays a key role in maintaining the efficiency and stability of power systems. The rapid evolution of power systems, driven by advanced metering infrastructure, local energy applications such as electric vehicles, and the increasing adoption of intermittent renewable energy, has introduced greater randomness and reduced predictability in peak demand. Given the pressing need to address more diverse implementation requirements across different contexts, accurate and reliable peak demand forecasting has become increasingly important. To the best of our knowledge, this study is the first to provide a …

Development Status And Existing Problems Of Ion-Solvation Membranes For Electrolysis Of Water, Zheng-Yuan Zhou, Yu-Tao Sun, Zheng-Bang Liu, Chuan-Zheng Wang, Yong-Nan Zhou, Xi Luo, Tian-Chi Zhou, Jin-Li Qiao

Journal of Electrochemistry

Ion-solvaing membranes (ISMs) have received extensive attention in recent years as a key component in electrochemical energy conversion and storage devices. This article provides an overview of structural composition, performance advantages, research progress, ion conduction mechanism and existing issues of ISMs, primarily classifying them according to the matrix structure. A detailed analysis of performance enhancement methods, key performance indicators of ISMs and performance influencing factors is also presented. The article contributes to further optimizing the design and application of ion-solvation membranes, providing theoretical support for the development of fields such as hydrogen production through electrolysis of water and electrochemical energy …

Iron-Involved Orr Electrocatalysts Under The Lens Of In-Situ/Operando Mössbauer Spectroscopy, Sumbal Farid, Jun-Hu Wang

Journal of Electrochemistry

Exploring cost-effective and efficient catalysts for oxygen reduction reaction (ORR) poses a significant challenge, especially in the pursuit of alternatives to precious metals like platinum. Significant advancements have driven electrochemists to develop efficient ORR catalysts using abundant materials, particularly iron (Fe)-based, known for their exceptional performance in ORR. While the crucial function of Fe in boosting ORR catalytic activity is recognized, the connection between material attributes and catalytic performance remains enigmatic. Understanding the dynamic processes involved in oxygen electrocatalysis is paramount for designing precious-metals-free ORR electrocatalysts. Mössbauer spectroscopy stands out as a powerful technique for deciphering the structural characteristics of …

The Ntp Anode For Aqueous Sodium Ion Batteries: Recent Advances And Future Perspectives, Ming-Li Wang, Xue-Ying Su, Zheng-Xiang Shan, Shu-Zhe Yang, Heng-Rui Guo, Hao Luo, Dong-Liang Chao

Journal of Electrochemistry

Aqueous sodium-ion batteries (ASIBs) have attracted great attention in aqueous batteries due to their merit of high safety. However, the constrained work potential and insufficient chemical stability of anode materials in aqueous electrolytes hinder the large-scale application of ASIBs. Sodium titanium phosphate, NaTi₂(PO₄)₃ (NTP), is considered one of the most promising anode materials for ASIBs due to its excellent electrochemical performance and tunable structure. Recently, great achievements have been made in the development of NTP, however, a comprehensive review of existing studies is still lacking. This article firstly introduces the basic properties of NTP and …

Carbon Supported Octahedral Ptni Nanoparticles (Oct-Ptni/C) As A Cathode Catalyst For Proton Exchange Membrane Fuel Cells (Pemfcs) With Improved Activity And Durability, Zi-Wei Feng, Hai-Zhong Chen, Xiao Duan, Ling Tang, Yun-Kun Zhao, Long Huang

Journal of Electrochemistry

Proton exchange membrane fuel cells (PEMFCs) are considered as a promising renewable power source. However, the massive commercial application of PEMFCs has been greatly hindered by their high expense and less-satisfied performance mainly due to the sluggish oxygen reduction reaction (ORR) kinetics even on state-of-the-art Pt catalyst. Octahedral PtNi nanoparticles (oct-PtNi NPs) with excellent ORR activity in a half-cell have been widely studied, while their performance in membrane electrode assembly (MEA) has much less reported. Herein, we investigated the MEA performance using the carbon supported oct-PtNi NPs (oct-PtNi/C) as the cathode catalyst. Under the mild acid washing condition, the surface …

Ai Data Center Dynamic Load Effects On Current Transformer Saturation, Sergio A. Hernandez

Electrical Engineering Theses

AI data centers can produce rapid changes in electrical demand that may influence current transformer performance during faults. This study evaluates the effect of an AI data center transient on CT saturation during single line-to-ground faults using a 400 V, 60 Hz grid connected inverter model in MATLAB/Simulink. The normal condition transient produced a maximum RMS current rate of approximately 211 A/ms, which was used along with the maximum power condition to define fault inception cases. A MATLAB time-domain CT model then swept the fault current DC offset coefficient to determine the minimum offset required for CT saturation. The calculated …

Localized Air Pollution Impacts From Data Centers In Northern Virginia, Damian Pitt, Ivan Suen, Ellie Plisko

Institute for Sustainable Energy and Environment Publications and Presentations

This report examins the extent of air pollution emissions resulting from the use of backup generators at data centers in Northern Virginia, including both actual current emissions and potential future emissions, and how those emissions totals compare to other sources of air pollution in the Northern Virginia region. It also examines how exposure to data center emissions correlates with demographic characteristics such as race, income, and education.

We while the air pollution emissions from individual data centers is minor, the collective impact from the 100+ such facilities in the Northern Virginia region is significant. Notably, the cumulative emissions exposure in …

Ammonia Synthesis By Nanosecond Pulsed Atmospheric Pressure Plasma Jets Impinging On Water, Zach Caudell, Lynnet Rich, Olga Pakhomova, Chunqi Jiang

Bioelectrics Publications

Developing energy-efficient technologies for carbon-neutral ammonia (NH₃) synthesis is critical for decentralized fertilizer production and global decarbonization. This study investigates generating NH₃ from water using a nanosecond pulsed atmospheric pressure plasma jet (ns‑APPJ) operating in either N₂ or dry air. The plasma jet reactor employed approximately 250 ns, up-to-22 kV pulses at 500 Hz to sustain a nonequilibrium discharge impinging directly on static liquid water. The kinetics, energy efficiency, and product selectivity of NH3 formation were quantified as functions of the pulse voltage, repetition frequency (PRF), and gas flow rate. NH₃ production increased linearly with treatment time and scaled strongly …

Validating A Low-Cost Radio Frequency Characterization Framework For Development-Grade Software-Defined Radios In Short-Duration Cubesat Missions, Thomas Wayne Francois

Masters Theses

Software-defined radios (SDRs) and CubeSat platforms have reduced the cost and complexity of space-based communication systems, enabling broader participation in satellite missions. While low-cost radio hardware is increasingly accessible, the ability to characterize and validate its performance remains constrained by the high cost and limited access to traditional RF test equipment. This disparity creates a challenge for small satellite development teams, which must characterize communication-system technical performance with limited access to laboratory-grade instrumentation.

This thesis presents a low-cost RF characterization framework for assessing key radio-frequency performance metrics using readily available hardware and measurement techniques. The approach integrates frequency translation, SDR-based …

From Comparison To Integration: Building Energy Simulation Tool Variability And The Case For Intelligent Retrofit Workflows, Amir Safari, Dalya Ismael, Mahsa Safari, James Freihaut

Engineering Technology Faculty Publications

As the urgency to address climate change and modernize energy infrastructure grows, the building sector plays a key role in improving energy efficiency and reducing carbon emissions. This study evaluates five energy retrofit strategies for Building 101 at The Navy Yard in Philadelphia, comparing two real-world proposals from energy service companies with three simulation-based packages derived from Building Energy Simulation (BES) tools. The study examined whether advanced BES tools provide greater accuracy and decision-making value compared to simpler alternatives. Electricity savings ranged from 5 % to 40 %, gas savings from 29.7 % to 61 %, and annual cost reductions …

Multi-Period Coordinated Planning Of Xfcs In Coupled Tn-Pdn Networks: Integrating Demand Charge Reduction And Pre-Existing Infrastructure, Waqas Ur Rehman, Siyuan Wang, Liheng Lv, Jonathan W. Kimball, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

The widespread adoption of electric vehicles (EVs) and transportation electrification is encumbered by two chief barriers: i) the limited driving range of EVs in the market today and ii) inadequate charging infrastructure support. This paper aims to address the latter bottleneck and proposes a strategic multi-period coordinated planning model to optimally site and size battery energy storage system (BESS) assisted extreme fast charging stations in a highway transportation network and solar systems in a power distribution network. The proposed approach accounts for pre-existing charging stations, the increasing EV penetration levels, decreasing technology costs, and technological advancements in the future and …

Nash Equilibrium Strategies For Multicluster Pursuit–Evasion Game With Disturbances: A Prescribed-Time Convergence Approach, Lei Xue, Xian Yu, Yongbao Wu, Jian Liu, Changyin Sun, D. C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article investigates the problem of prescribed-time Nash equilibrium (NE) seeking for a multicluster pursuit–evasion game (PEG) subject to external disturbances. To mitigate the impact of disturbances and reach the NE within a user-defined prescribed time, a prescribed-time disturbance observer (PTDO) is devised to estimate and compensate for them. Based on this observation, a novel control algorithm is developed, which facilitates collaboration among multiple pursuers to capture multiple evaders within the prescribed time. It is theoretically demonstrated that the designed algorithm ensures prescribed-time convergence to the NE of the multicluster PEG with disturbances. Finally, numerical simulations are conducted to verify …

Event-Based Predefined-Time Synchronization For Complex Networks With Deception Attacks: An Asynchronously Intermittent Strategy, Lei Xue, Jiong Yu, Haoyu Zhou, Yongbao Wu, Jian Liu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article studies the practical predefined-time synchronization (PPTS) for complex networks (CNs) under deception attacks based on the asynchronously intermittent event-triggered control (AIE-TC). Notably, AIE-TC effectively integrates the advantages of asynchronously intermittent control (AIC) and event-triggered control, where AIC provides each subsystem node with independent control and rest intervals. Besides, all synchronization errors of the CNs converge to an adjustable neighborhood within the predefined time by designing a bounded time-varying function into the controller. Moreover, this article considers that the transmission network is subjected to stochastic deception attacks modeled by a Markov process, which captures the state-driven dynamic transition characteristics …