Impact of Hybrid Energy Storage System Topology on Performance: Exploration for Hydropower Hybrids

We investigate the technical performance of six HESS topologies integrated with run-of-river (ROR) hydropower to provide frequency support. We choose ROR hydropower because there are 23 GW of installed ROR hydropower in the U.S. and integrating these plants with energy storage could boost their contribution to grid services. We focus on HESSs composed of batteries and ultra-capacitors because batteries are cost effective for storing energy but degrade more quickly as a function of cycling. In contrast, ultra-capacitors can be cycled millions of times and are cost effective for quick injections of power. We find that active HESS topologies demonstrate the best overall improvement to grid frequency during a contingency while adhering to the power ramping limits of the HESS devices. Future work will investigate other services to identify if one HESS topology performs best for all services of interest or, more likely, different HESS topologies are best suited for specific services

Local Properties and Differential Forms of Smooth Map and Tangent Bundle

In this paper, some basic properties of differential forms of smooth map and tangent bundle are developed.  More details can be found in the full paper.

Multi-agent estimation and control of cyber-physical systems

Doctor of PhilosophyElectrical and Computer EngineeringBalasubramaniam NatarajanA cyber-physical system (CPS) typically consists of networked computational elements that control physical processes. As an integral part of CPS, the widespread deployment of communicable sensors makes the task of monitoring and control quite challenging especially from the viewpoint of scalability and complexity. This research investigates two unique aspects of overcoming such barriers, making a CPS more robust against data explosion and network vulnerabilities. First, the correlated characteristics of high-resolution sensor data are exploited to significantly reduce the fused data volume. Specifically, spatial, temporal and spatiotemporal compressed sensing approaches are applied to sample the measurements in compressed form. Such aggregation can directly be used in centralized static state estimation even for a nonlinear system. This approach results in a remarkable reduction in communication overhead as well as memory/storage requirement. Secondly, an agent based architecture is proposed, where the communicable sensors (identified as agents) also perform local information processing. Based on the local and underdetermined observation space, each agent can monitor only a specific subset of global CPS states, necessitating neighborhood information exchange. In this framework, we propose an agent based static state estimation encompassing local consensus and least square solution. Necessary bounds for the consensus weights are obtained through the maximum eigenvalue based convergence analysis and are verified for a radial power distribution network. The agent based formulation is also applied for a linear dynamical system and the consensus approach is found to exhibit better and more robust performance compared to a diffusion filter. The agent based Kalman consensus filter (AKCF) is further investigated, when the agents can choose between measurements and/or consensus, allowing the economic allocation of sensing and communication tasks as well as the temporary omission of faulty agents. The filter stability is guaranteed by deriving necessary consensus bounds through Lyapunov stability analysis. The states dynamically estimated from AKCF can be used for state-feedback control in a model predictive fashion. The effect of lossy communication is investigated and critical bounds on the link failure rate and the degree of consensus that ensure stability of the agent based control are derived and verified via simulations

Open Source High Fidelity Modeling of a Type 5 Wind Turbine Drivetrain for Grid Integration

The increasing integration of renewable energy resources in evolving bulk power system (BPS) is impacting the system inertia. Type-5 wind turbine generation has the potential to behave like a traditional synchronous generator and can help improve system inertia. Hydraulic torque converter (TC) and gearbox with torque limiting feature are integral parts of a Type-5 wind turbine unit. High fidelity model of Type-5 wind turbine including these core components is not openly and widely available for grid integration and transient stability studies. This hinders appropriate assessment of Type-5 wind power plant's contribution to bulk grid resilience. This work develops a TC model based on those generally used in automobile's transmission system. Moreover, the concept of torsional coupling is leveraged to integrate the TC and gearbox system dynamics. The entire integrated model will be open sourced and publicly available for grid integration studies.Comment: This manuscript is originally submitted to Journal of Physic

Mathematical Formulation of Inverse Scattering and Korteweg-De Vries Equation

Inverse scattering refers to the determination of the solutions of a set of differential equations based on known asymptotic solutions, that is, the solution of Marchenko equation. Marchenko equation was derived using integral equation. The potential function derived from eigenvalues and scattering data seems to be the inverse method of scattering problem. The reflection coefficient with one pole and zero reflection coefficients has been chosen to solve inverse scattering problem. Again this paper deals with the connection between inverse scattering and the Korteweg-de Vries equation and describes variety of examples with Korteweg-de Vries equation: the single-soliton solution, the two-soliton solution and finally the N-soliton solution. Throughout the work, the primary objective is to study some mathematical techniques applied in analyzing the behavior of soliton in the KdV equations. Keywords: Marchenko equation, KdV equation, Solitons, Scattering, Inverse Scattering, Canal

Bengali Fake Review Detection using Semi-supervised Generative Adversarial Networks

This paper investigates the potential of semi-supervised Generative Adversarial Networks (GANs) to fine-tune pretrained language models in order to classify Bengali fake reviews from real reviews with a few annotated data. With the rise of social media and e-commerce, the ability to detect fake or deceptive reviews is becoming increasingly important in order to protect consumers from being misled by false information. Any machine learning model will have trouble identifying a fake review, especially for a low resource language like Bengali. We have demonstrated that the proposed semi-supervised GAN-LM architecture (generative adversarial network on top of a pretrained language model) is a viable solution in classifying Bengali fake reviews as the experimental results suggest that even with only 1024 annotated samples, BanglaBERT with semi-supervised GAN (SSGAN) achieved an accuracy of 83.59% and a f1-score of 84.89% outperforming other pretrained language models - BanglaBERT generator, Bangla BERT Base and Bangla-Electra by almost 3%, 4% and 10% respectively in terms of accuracy. The experiments were conducted on a manually labeled food review dataset consisting of total 6014 real and fake reviews collected from various social media groups. Researchers that are experiencing difficulty recognizing not just fake reviews but other classification issues owing to a lack of labeled data may find a solution in our proposed methodology

Evaluation of rK-39 strip test using urine for diagnosis of visceral leishmaniasis in an endemic area in Bangladesh

Diagnosis of visceral leishmaniasis (VL) by demonstration of parasites in tissue smears obtained from bone marrow, spleen or lymph nodes is risky, painful, and difficult. The rK-39 strip test is widely used for the diagnosis of VL using blood/serum samples in endemic countries. The aim of the study was to evaluate the rK-39 strip test using urine sample as a non-invasive means for the diagnosis of VL. The rk-39 strip test was performed using urine from 100 suspected VL cases along with 25 disease control (malarial febrile cases) and 50 healthy control (from endemic and non-endemic areas). All the VL suspected cases were positive with the rK-39 strip test using serum. The sensitivity and specificity of the rK-39 strip test using urine samples was 95% and 93.3%, respectively, compared to serum based rK-39 test. The findings suggest that the urine based rK-39 test could be a practical and efficient tool for the diagnosis of VL patients in rural areas, particularly where resources are limited

Integration of Large-Scale Electric Vehicles into Utility Grid: An Efficient Approach for Impact Analysis and Power Quality Assessment

Electric vehicles (EVs) have received massive consideration in the automotive industries due to their improved performance, efficiency and capability to minimize global warming and carbon emission impacts. The utilization of EVs has several potential benefits, such as increased use of renewable energy, less dependency on fossil-fuel-based power generations and energy-storage capability. Although EVs can significantly mitigate global carbon emissions, it is challenging to maintain power balance during charging on-peak hours. Thus, it mandates a comprehensive impact analysis of high-level electric vehicle penetration in utility grids. This paper investigates the impacts of large-scale EV penetration on low voltage distribution, considering the charging time, charging method and characteristics. Several charging scenarios are considered for EVs’ integration into the utility grid regarding power demand, voltage profile, power quality and system adequacy. A lookup-table-based charging approach for EVs is proposed for impact analysis, while considering a large-scale integration. It is observed that the bus voltage and line current are affected during high-level charging and discharging of the EVs. The residential grid voltage sag increases by about 1.96% to 1.77%, 2.21%, 1.96 to 1.521% and 1.93% in four EV-charging profiles, respectively. The finding of this work can be adopted in designing optimal charging/discharging of EVs to minimize the impacts on bus voltage and line current