A part of the Center mission is to administer interdisciplinary seed grants (ISGs) to strengthen the generation of preliminary results in support of the pursuit of external funding to ensure self-sustainability of the center. Application requirements encourage interdisciplinary proposals, promote student participation, and ensure effective use of seed funds.
The 2024 ISG round prioritizes early stage submissions focused on advancing the field of energy sector cybersecurity, as well as other topics within the mission of the DOE Office of Cybersecurity, Energy Security and Emergency Response to "strengthen the security and resilience of the U.S. energy sector from cyber, physical, and climate-based risks and disruptions." Please see more here: https://www.energy.gov/ceser/about-us
New calls for ISG grants with respective dates will be announced here.
M. K. Ghantasala (MAE, CEAS), R. Guda (Chemistry, CAS), Novel polyoxometalate based Catalytic Materials for Proton Exchange Membrane fuel cells. Design and optimization of new catalyst layers without depending on platinum-group metal (PGM)-based electrocatalysts for polymer electrolyte fuel cells is the key in reducing the cost and making fuel cell technology commercially viable for large range of applications ranging from generating electrical power to transportation. In this direction, we propose to develop polyoxometalate (POM) based catalysts with low cost, first group transition metals Mn/Co/Ni into carbon-based substrates. The proposed research involves chemical synthesis of the catalyst materials including POM with chosen metal on to graphene/graphene oxide/reduced graphene oxide (with and without nitrogen doping) supports. These catalysts will be analyzed for structure, microstructure, porosity using X-ray Diffraction, Raman Spectroscopy, Fourier Transform Infrared Spectroscopy and Brunauer–Emmett–Teller (BET) measurement for surface porosity evaluation and adsorption properties. These are correlated to the measured electrochemical I-V characteristics. These catalyst materials will be prepared in the ink form for making layered structures onto the membrane. This will facilitate the evaluation of an assembled single fuel cell and its potential use in engineering applications. This project mainly involves three important components viz., Chemical synthesis, Materials Characterization and engineering evaluation of its performance, requiring expertise in chemistry and engineering.
R. Meyer (MAE, CEAS), S. Bhattacharjee, Electric Vehicle Charging Data Falsification Attacks Utilizing Behavioral Models. A charging station (CS) and its associated electric vehicle supply equipment (EVSE) and charging electric vehicle (EV) interactions are potential targets for data falsification attacks since CSs are typically unmanned public facilities that are connected to the internet. We propose to develop a charging data falsification attack simulator that includes a dynamic battery model, EV battery energy management system, and EVSE and CS controller. An EV battery behavioral model form is proposed to capture the essential dynamics of the charging process without overly complex mathematics. Specific EV battery behavioral models will be developed from thousands of charge sessions in ACN-Data, a publicly available database. The EV battery energy management system is taken from the literature. The CS controller associated with the ACN-Data minimizes the product of the time while being charged and the maximum allowed current that can be drawn summed over all EVs connected to the CS. The minimization is subject to a maximum possible current that can be supplied by an EVSE, the energy requested by each EV, and CS infrastructure limits. Both physical exploits and cyber exploits are considered for data falsification attacks on the CS (EVSE) and EV side. Three attacker intents are given: delaying full charge (or charge degradation attack), EV battery health damage, and grid instability. The primary path to these intents is manipulations of the EV current sensor, EVSE current sensor, maximum allowable current that an EV can draw as determined by the CS controller, and departure time. These values will be incorporated into attack strategies that include data order aware, incremental ramp strategy, sensor saturation and replay. Further, attacks on the EV side will be upper bounded from a single vehicle to those currently using the CS, and attack scale is irrelevant. This approach will identify severity of attacks on operations as a function of the compromised devices. The ultimate output of this early investigation is a novel simulator of data falsification attacks at a CS that is derived from real-world vehicle and CS interaction data.
Pablo Gomez (ECE, CEAS), R. Meyer (MAE, CEAS), Computational Analysis and Optimized Modeling of Geomagnetically Induced Currents in Power Transformers. A Geomagnetic storm is a type of space weather event in which the Earth’s magnetic field interacts with magnetic solar material. This interaction produces variations in the Earth’s magnetic field that result in corresponding variations in the electric field according to Faraday’s law. Electric fields produced by a geomagnetic storm are commonly known as geoelectric fields. When these fields interact with conducting paths of large extension, such as power lines, pipelines, or railways, they produce what is known as Geomagnetically induced currents (GIC).This project aims to better understand the effect of GIC on power transformers. For this purpose, this project involves a) investigating the most important electromagnetic and electrothermal features of the transformer model for its utilization in the evaluation of GIC effects within itself and in its interaction with the grid; b) developing a computational approach that enables the seamless integration between a previously implemented methodology for calculation of GIC signatures, and the optimized transformer model; and c) evaluating the sensitivity of GIC effects on the transformer to the level of detail in the geomagnetic event, transformer, power grid, and ground models, with a focus on heat increase and distribution, introduction of harmonics, and power imbalance of the grid due to reactive power absorption by the transformer.
S. Roy (MAE, CEAS), X. Shao (CCE, CEAS), Power and Structural Analysis of Floating Wind Turbines Through Computational Fluid Dynamic Simulation and Hybrid Simulation. As a renewable energy source, wind is considered to be the most potential energy provider. Offshore floating wind turbines (FWT) are rapidly growing popularity to efficiently harvest the wind energy. FWT is exposed to environmental loads including wind and wave, the combination of which creates complex dynamic condition. In addition, extreme environmental loading should be considered in FWT design for reliable structure and efficient power generation. Proper power and structural analysis of FWT require consideration of both aerodynamic and structural loads through combination of numerical and experimental simulations. Therefore, it is imperative to develop innovative and advanced analysis methods, which can be numerical, experimental or a combination of both (i.e., hybrid simulation), to estimate structural responses under combined loads. Although a reliable analytical procedure is the ultimate goal of many researches due to less cost, time and effort associated with such procedure, experimental investigation remains to be an indispensable mean to study these complex dynamics that provides direct insight on structures’ performance and realistic response data. The numerical modeling and simulation through computational fluid dynamic will be validated through experimental outcome. This validated model can be used to measure extreme condition which are experimentally difficult to achieve. In this proposed research the goal is to develop a power and structural analysis method of FWT considering multiple environmental loads. The numerical models will be generated using experimental measured data to validate with the measured experimental condition. Calculated numerical load will be used to analyze structural response. Then, distributed real-time hybrid simulation (dRTHS) method and the associate testing platform will be employed to further understand FWT’s dynamic responses under combined wind and wave loads and to validate the FTW numerical models and simulation method developed.
S. Bhattacharjee (CS, CEAS), P. Gomez (ECE, CEAS), Real-time evaluation of cybersecurity threats to photovoltaic inverter grid-support functions. The high deployment of distributed energy resources (DER), such as wind turbines, photovoltaic systems, and energy storage units, is a great ally to combat climate change and strengthen the electric grid during the increasingly common major weather events. However, DER interconnection, combined with the ongoing transition to a digital power grid, also poses substantial cybersecurity threats. Thus, addressing cybersecurity challenges must be a key priority over the next decades for DER owners, operators, developers, software and hardware vendors, and aggregators. Cyberattacks on power grids have been increasing worldwide, while recent studies have shown vulnerabilities in existing communication protocols. Still, sufficient guidelines and procedures do not exist to date to help DER stakeholders adopt and implement procedures to secure the data and communications of DERs. This project aims to contribute to the understanding of the type and severity of potential cybersecurity attacks to the grid-support functionalities of photovoltaic (PV) systems interconnected to the AC distribution grid via inverters. For this purpose, a cybersecurity testbed will be developed that allows appropriate integration and combined operation of the main hardware components after investigation of the most important features required for real-time modeling and simulation of the electrical, control, and communication layers of PV-grid interconnection via smart inverters. Then, this testbed will be utilized to study the cybersecurity vulnerabilities of grid-tied smart PV inverters in its main grid-support functions, namely voltage support via active/reactive power control, frequency control, and fault ride-through (voltage/frequency). Further work will involve a systematic study of coordinated data falsification attacks on voltage, current and frequency measurements as received by different algorithms running on grid-support PV inverter controllers. Finally, recommendations on cyberattack mitigation strategies results will be provided.
Please contact the ISG committee chair, Dr. Richard Meyer, if you have any questions about this opportunity: