Browsing by Author "Elsayed, Suzan"

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    An Optimal Asynchrophasor in PMU Using Second Order Kalman Filter
    (2021-11-15) Alqahtani, Nayef Mohammed S; Zohdy, Mohamed; Ganesan, Subramaniam; Kobus, Christopher; Elsayed, Suzan
    Phasor Measurement Units (PMU) are very costly according to energy regulator and utility companies. Utility operators work on alternative solutions to reduce the error rate and operation costs of PMU. In this paper, we sought to optimize the PMU to reduce the level of error using Second-Order Kalman Filter (SOKF). Consequently, this optimization is based on minimizing the number of errors when receiving the signal from access points or from the main access point. We derived a simple mathematical model to estimate the phase coming from the PMU.PMUs provide Global Positioning System (GPS) time stamped synchronized measurements of voltage and currents with the phase angle of the system at certain points along the grid system. Those synchronized data measurements were extracted in form of amplitude and phase from various locations of the power grid to monitor and control the power system conditions. A PMU device is a crucial part of the power equipment in terms of the cost and operative point of view. However, such ongoing development and improvement to PMUs' principal work is essential to the network operators to enhance the grid quality and the operating expenses. A MATLAB model was created to implement the proposed method in the presence of Gaussian and non-Gaussian noise. It is based on an Asyncrhophasor technique resulting in a phase error minimization when receiving the signal from access point or from the main access point. The results show the proposed SOKF method outperforming the existing model as tested using Mean Square Error (MSE). The SOKF method was replaced with a synchronization unit into the PMU structure to clarify the significance of the proposed new PMU. This paper's proposed method leads to lower costs and less complex techniques to optimize the performance of PMU using SOKF
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    Interactive Module for Medical Student Education in Type I Renal Tubular Acidosis
    (2025) Patel, Het; Nappo, Emelie-jo; Naik, Akshata; Elsayed, Suzan
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    Optimization Approaches for Optimal Power Flow Problems in Renewable Energy Grids
    (2021-11-15) Alzahrani, Abdullah Mohammed A; Zohdy, Mohamed; Alaweh, Shadi; Monroe, Ryan; Elsayed, Suzan
    In recent years, the global energy crisis confronting humanity is attributable to a deficiency in classical energy sources whereas the energy demands are widespread growth. In overcoming this crisis, increasing the efficiency of energy and sustainability are becoming significantly crucial. Therefore, the integration of various renewable energy resources into the traditional electrical grid is quite a challenging issue due to their intermittent nature. In this dissertation, the main focus is on the operational stage optimization problem considering the optimal power flow (OPF) problem to economically meet time-varying consumer demands. This brings a new level of complexity to the OPF problem that needs to be addressed by new and more performant optimization algorithms. One promising area of research that will be followed in this work is the use of heuristic optimization algorithms. These have been used both alone or in hybrid combinations of two optimization algorithms to compensate for the weaknesses of each.Due to nonlinearity introduced by alternating current power flow equations, this research focuses on improving the non-linear of the OPF problem for an electrical power grid that includes different energy sources along with thermal plants as energy generators. This dissertation illustrates how to improve the numerical stability of the proposed optimization approach by considering different variables to avoid ill-conditioned numerical operations. The proposed optimization approach, on the other hand, is able to deal with non-convex problems with multiple local optima, and also it is able to deal with the additional complexity of the hybrid power grid. This dissertation aimed at improving the use of stand-alone and hybrid AC/DC microgrid systems by minimizing some issues, e.g., global warming emissions and the increasing cost of power systems and losses during the entire time horizon. In this work, some assumptions have been made by considering line constraints on the network to theoretically prove that the performance of the polynomial optimization problem relaxation can satisfy the original power flow equations. Finally, the performance of the proposed algorithm has been examined on different electrical power networks with various power system sizes, such as IEEE 5, 14, and 30 bus. The outcomes of the experiments proved the adaptability of the algorithm when considering large-scale electrical power networks. In addition, this proposed algorithm has been compared with some exiting optimization algorithms given in the literature for similar power systems, where it shows the effectiveness of this proposed method. This achievement will strengthen the use of this convexification approach in its applications on large-scale systems to reduce energy expenses and network system losses.