Dynamical System and Parameter Identification for Power Systems

The complexity of dynamical analysis has been growing to suffice the understanding and modeling of dynamical systems. Besides its nonlinearity and high-dimensionality, the dynamics of power systems contain uncertainty that complicates its analysis. Recently, dynamical modeling has been categorized into three types: white-box, black-box, and gray-box. White-box modeling has the accessibility of all system components. Black-box modeling has the observability of the system measurements without knowing the actual system. Gray-box modeling has the observability of the system measurements with the reachability to some of the system components. The scope of this dissertation focuses on black-box and gray-box models to achieve practical system and parameter identification of power system applications. Dynamic Mode Decomposition (DMD) is a black-box method that has been proposed by the fluid community. It is a free-equation model identification technique and it has proven its practicality in various fields including brain modeling, fluid experiments, video separation, flows around a train, and financial trading strategies. Our work reviews the DMD algorithm and implements it for mode identification and signal reconstruction in three power system-related applications: RLC circuit dynamics, phasor measurement unit (PMU) measurements of an unknown system, and AC voltage waveform polluted by harmonics. In the first two applications, we compare DMD with Eigensystem Realization Algorithm (ERA) and present that the two methods have the same accuracy level. The last application shows that DMD can also work as fast Fourier transformation (FFT), which can identify harmonics and their magnitudes in the analyzed system. The standard DMD is unable to identify real-world measurement data captured by phasor measurement units (PMUs) because they are noisy. In our research, we enhance DMD performance by data stacking that increases the rank of the data matrix. Correspondingly, DMD accurately identifies the system eigenvalues and eigenvectors. The eigensystem components reveal the details of the dynamics and reconstruct the signals in the time-evolving format. While data stacking raises the computation cost, we further implement a randomization technique for DMD to radically reduce the size of the data matrix. The randomized DMD (rDMD) has high accuracy and efficiency. Our work shows that the identified mode shapes (eigenvectors) of the DMD/rDMD can recognize the oscillation mode type whether it is local or interarea. PMU data from three real-world oscillation events are used for demonstration. Also, we compare both DMD and rDMD with the classical identification methods including Prony, Matrix Pencil, and Eigensystem Realization Algorithm. The second part of this dissertation focuses on gray-box dynamical modeling for parameter identification. The two classical parameter identification methods are the prediction error method (PEM) and the similarity matrix technique. These methods are nonlinear and require a good initial guess of parameters that must be in the domain of convergence. Recently, two new methods have been developed by the system identification community. These methods start from the two conventional methods, make computing improvement by taking into consideration the low-rank characteristic of data, and formulate the estimation problems as rank-constraint optimization problems. Furthermore, the rank-constraint optimization problems are converted to difference of convex programming (DCP) problems and solved by convex iteration. The new convexification technique leads to more accurate parameter estimation. Our work presents the four methods and implements the problem formulations and solving algorithms for synchronous generator and inverter-based resource (IBR) dynamic model parameter estimation

Locomotor Behavior Analysis in Spinal Cord Injured Macaca radiata after Predegenerated Peripheral Nerve Grafting—A Preliminary Evidence

Introduction: Primate animal models are being utilized to explore novel therapies for spinal cord injuries. This study aimed to evaluate the efficiency of the transplantation of predegenerated nerve segments in unilateral spinal cord-hemisected bonnet monkeys’ (Macaca radiata) locomotor functions using the complex runways. Materials and Methods: The bonnet monkeys were initially trained to walk in a bipedal motion on grid and staircase runways. In one group of trained monkeys, surgical hemisection was made in the spinal cord at the T12-L1 level. In the other group, hemisection was induced in the spinal cord, and the ulnar nerve was also transected at the same time (transplant group). After one week, the hemisected cavity was reopened and implanted with predegenerated ulnar nerve segments obtained from the same animal of the transplant group. Results: All the operated monkeys showed significant deficits in locomotion on runways at the early postoperative period. The walking ability of operated monkeys was found to be gradually improved, and they recovered nearer to preoperative level at the fourth postoperative month, and there were no marked differences. Conclusion: The results demonstrate that there were no significant improvements in the locomotion of monkeys on runways after the delayed grafting of nerve segments until one year later. The failure of the predegenerated nerve graft as a possible therapeutic strategy to improve the locomotion of monkeys may be due to a number of factors set in motion by trauma, which could possibly prevent the qualities of regeneration. The exact reason for this ineffectiveness of predegenerated nerve segments and their underlying mechanism is not known

IMMUNIZATION COVERAGE AND HESITANCY IN SAUDI ARABIA

One of the greatest contributions to public health is vaccination. The majority of affluent nations have high rates of childhood vaccination, indicating that vaccination is still largely regarded as a public health policy in these nations. But there might be many individuals who are under-vaccinated. The rise of VPD outbreaks, such as measles, poliomyelitis, and pertussis, and under- or non-vaccinated communities have been linked in several nations. The World Health Organization (WHO) has identified vaccine hesitancy as one of the top 10 health hazards for 2019. Recently, there have been reports of vaccine reluctance in Saudi Arabia. Currently, the need for awareness campaigns about the benefits of vaccination is needed more than ever. In this review we will be looking at immunization hesitancy in Saudi Arabia, its definition, factors, and possible solutions

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population