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Öğe An accurate efficiency calculation for PMSG utilized in renewable energy systems(Department of Agribusiness, Universitas Muhammadiyah, 2023) Hamodat, Zaid; Hussein, Ismail Khudhur; Nasir, Bilal AbdullahConsidering the importance of optimizing renewable energy systems, this paper aims at calculating the exact efficiency of a stand-alone wind turbine connected to a synchronous generator with permanent magnet excitation (PMSG). By accounting for mechanical and electrical losses (copper losses, stray load losses, iron core losses, friction losses, windings losses, and magnetizing saturation effect), the study investigates the impact of wind speed on the generator's performance and efficiency in addition to the impact of losses on the overall efficiency of (PMSG). The simulation of the PMSG dynamic model 8. 5 × (10)3 V․A is executed using MATLAB/Simulink, employing a simplified equivalent circuit that accurately represents the PMSG's behavior under steady-state conditions with resistive loads. Wind speeds of 12 and 14 meters/second are chosen as fixed values to demonstrate the effect of varying wind speed on efficiency. The obtained results reveal the influence of wind speed on the PMSG efficiency. The presented findings contribute to the understanding of PMSG performance and can aid in optimizing the stand-alone wind turbine systems, they also show that the wind had an effect on the efficiency values that were obtained (97.86% at 12m/s and 97.91% at 14 m/s), while the effect of losses was very few around 3%. However, the obtained results are very good compared to previous studies to show the accuracy and validity of the suggested dynamic model.Öğe Automated generation control of multiple area electrical system with an availability-based tariff pricing scheme regulated by whale optimized fuzzy PID controller(Altınbaş Üniversitesi, Lisansüstü Eğitim Enstitüsü, 2021) Hamodat, Zaid; Cansever, GalipBu araştırmada, kullanılabilirliğe dayalı tarife (ABT) fiyatlandırma şeması ile çok alanlı elektrik enerjisi sistemlerinde otomatik üretim kontrolünü yönetmek için balina optimizasyonlu bir bulanık PID denetleyici geliştirilmiştir. Bu çalışmanın amacı, gerçek zamanlı yük ve frekans değişim koşulları ile çok alanlı elektrik enerjisi sisteminin güç üretim maliyetlerini, alan kontrol hatalarını (ACE'ler) ve marjinal maliyetlerini en aza indirmektir. Hidrotermal, buhar santrali ve gaz santrali dahil olmak üzere birbirine bağlı üç alanlı elektrik enerjisi sisteminin güç üretimi, bağlantı hattındaki güç sapması ve frekansı sapması, titizlikle ölçülecek ve analiz edilecektir. Balina optimizasyonundan elde edilen çıktıya bağlı olarak, bulanık PID denetleyicisi, bağlantı hattındaki gücün sapmasını ve birbirine bağlı üç alanlı elektrik enerjisi sisteminin frekans sapmasını düzenler. Önerilen optimizasyonun, yani balina için optimize edilmiş bulanık PID denetleyicisinin güvenilirliği ve uygunluğu, parçacık sürüsü optimizasyonu ve genetik algoritmalar gibi halihazırda sunulan yöntemlere karşı araştırılır.Öğe Automated generation control of multiple-area electrical system with an availability-based tariff pricing scheme regulated by whale optimized fuzzy PID controller(Hindawi, 2021) Hamodat, Zaid; Cansever, Galip; Cansever, GalipIn this research, a whale-optimized fuzzy PID controller was developed to manage automatic generation control in multiple-area electrical energy systems with an availability-based tariff (ABT) pricing scheme. The objective of this work is to minimize the power production costs, area control errors (ACEs), and marginal costs of the multiple-area electrical energy system with real-time load and frequency variation conditions. The generation of power, deviation of power in the tie line, and deviation of frequency of the interconnected three-area electrical energy system, including the hydrothermal steam power plant and gas power plant, will be measured and analyzed rigorously. Based on the output from the whale optimization, the fuzzy PID controller regulates the deviation of power in the tie line and the deviation of frequency of the interconnected three-area electrical energy system. The reliability and suitability of the proposed optimization, i.e., whale-optimized fuzzy PID controller, are investigated against already presented methods such as particle swarm optimization and genetic algorithms.Öğe Control and management of microgrid based solar charger using GWO algorithm(Institute of Electrical and Electronics Engineers Inc., 2022) Al-Bazi, Mohammed Hikmat; Hamodat, ZaidAs the green energy development revolution continues, the use of microgrids powered by renewable energy sources such as solar, wind, and fuel cells is becoming more popular and effective. On the other hand, the variability and wide dynamic range of renewable energy sources necessitate the use of battery energy storage systems in microgrids. To maximize the efficiency of microgrids, intelligent energy management and battery sizing must be used to maximize renewable energy sources and minimize the use of conventional fuel in these complex systems. The grey wolf optimization (GWO) technique is presented in this article as a novel technique for meeting these requirements via a probabilistic approach.Öğe Control and management of solar PV grid using scada system(Institute of Electrical and Electronics Engineers Inc., 2022) Abdulsalam, Abdulsalalm Bouaisha; Alsaadi, Hajir Adil Jasim; Hamodat, ZaidThe design and construction of a supervisory control and data acquisition (SCADA) system for remote control and monitoring of grid-connected inverters are described in this thesis. As the number of battery energy storage systems linked to the grid increases, the number of inverters connected to the power system increases as well. Utility providers' capacity to monitor and control any inverters linked to the grid is critical for network stability, enhancing power quality, and maintaining stable energy pricing. critical aspects that must be included in a low-cost SCADA system for grid-tied inverters to ensure its effectiveness Several SCADA systems were evaluated throughout the inquiry to discover if they could be used to meet the standards. The SCADA system has been significantly improved based on test results, and a server based on the Internet of Things (IoT) has been retained as the system's primary component. To be successful, the SCADA system required automatic management of the inverter, taking into account changes in energy pricing and fluctuations in renewable energy generation over time. This was important to optimize the economic benefits of the inverter. The results indicate that the SCADA system created met the research's requirements and that the wind prediction algorithm maximized the project's economic advantages.Öğe Design and implementation of LUO converter with MPPT controller based on photovoltaic system(Springer Science and Business Media Deutschland GmbH, 2024) Al-Yosif, Rasha; Hamodat, ZaidThe contentious nature of the topic of energy management may be traced back to the negative effects on the surrounding environment that are caused by the use of nonrenewable energy supplies. In spite of this, there has been a lot of discussion on whether or not we should continue to rely on fossil fuels to meet the ever-increasing need for energy throughout the world. Both the greenhouse effect and global warming may be traced back to actions taken by humans, most notably the burning of fossil fuels. This is especially true of the greenhouse effect. The interaction of these two fundamental systems may be directly responsible for the recent shifts that have been seen in the climate of the Earth. The capability of the proposed system to evaluate the effects of variations in radiation and temperature was investigated. It has been shown that the fuzzy maximum power point tracking approach can reliably detect the maximum power point with an accuracy that ranges from 96.4% to 99.3%. This demonstrates how successful the method is as a responsive system that can easily adjust to varying amounts of input in a short amount of time.Öğe Design of power control circuit for grid-connected PV system-based neural network(Department of Agribusiness, Universitas Muhammadiyah Yogyakarta, 2024) Rajab Al-Jaboury, Omar N.; Hamodat, Zaid; Daoud, Raid W.This research explores the application of neural networks in managing grid- photovoltaic (PV) systems. this paper aims to improve the performance and reliability of PV systems using artificial intelligence capabilities, specifically neural networks. The main emphasis of this system is to control active and reactive power and to track the maximum power point (MPPT). This study introduces an intelligent control technique for fuel cell distributed generation (DG) grid connection inverters. The algorithm allows for the management of both active and reactive power for the unit. The algorithm provides local reactive power compensation, making it economically viable. The controller modeling and performance validation are conducted using MATLAB/Simulink and Sim power system blocks, demonstrating its capacity for enhancing power factor. This makes fuel cell technology a clean, highly controllable, and economically viable option for DG systems. The system maximizes the energy extraction of PV panels and maintains them at their ideal PowerPoint across various environmental conditions. It also raises the voltage from 260 volts to 350 volts. Simulations and practical evaluations validate the proposed control system. The obtained results indicate that the total harmonic distortion (THD) of the grid current under operating conditions was less than 1.86%. This demonstrates significant improvements in the efficiency and reliability of PV systems. The neural network controller shows remarkable flexibility and the ability to quickly adapt to fluctuations in load and radiation, which contributes to developing a more sustainable and stable energy network.Öğe Enhancing smart grid stability with the implementation of heuristic algorithms(Institute of Electrical and Electronics Engineers Inc., 2022) Abdulqader, Qutada Jihad; Abdulazeez, Mshhain Ghazi; Hamodat, ZaidThe smart grid, one of the most technologically advanced systems in existence today, is responsible for balancing supply and demand (DR). Residential customers have a significant influence on the overall operation of the conventional power system due to their high levels of energy consumption. HEM is a system designed to assist consumers in monitoring, regulating, and decreasing their energy use. With the use of HEM, appliances may be designed so that their consumption is changed to match the quantity of available supply. Recent advances in artificial intelligence have facilitated the attainment of these goals (AI). Heuristic approaches include optimization techniques such as wind-driven optimization (WDO), genomics optimization (GA), and binary particle swarm optimization (BPSO) (BPSO). Simulations are used to evaluate scheduling alternatives based on parameters such as cost, peak-to-average ratio (PAR), and an equally distributed power demand pattern throughout the system. Simulation results indicate that the WDO-based HEM outperforms both the BPSO and the GA algorithms.Öğe Forecasting annual solar power output from geographic location(Institute of Electrical and Electronics Engineers Inc., 2022) Al-Dabbagh, Nayyef Sami Nayyef; Al-Musawi, Sura Saadi Jaafar; Hamodat, ZaidPower determining of environmentally friendly power plants is an exceptionally dynamic examination field, as dependable data about the future power age takes into consideration a protected activity of the power framework and assists with limiting the functional expenses of these energy sources. AI calculations have demonstrated to be exceptionally strong in anticipating errands, like financial time series or discourse acknowledgment. Using random forest regression method, daily mean solar output generation can yield promising result rather than conventional NWP model for forecasting. Using that in practice also the goal was to create a user-friendly application, with easy access, to provide accurate forecasting regarding saving and conservation. This paper's goal was accomplished in three stages: To begin with, make an AI model that predicts the yearly energy result of an expected sun based establishment. From that point onward, make a model that predicts establishment costs. Carrying out these models on an easy to use web application that shows clients the amount they can hope to save money on their yearly energy bill by changing to sun oriented. The random forest model out-performs its other rivals and also conventional models, thus providing a better suited model to run with for forecasting.Öğe Improvement of solar energy efficiency using solar tracking and artificial intelligence(Institute of Electrical and Electronics Engineers Inc., 2022) Alwakeel, Hussein Mohammed Ali Hammood; Abed, Qader Farhan Abed; Hamodat, ZaidNumerous kinds of solar producing devices, such as concentrators and flat-plate arrays, need that the sun be followed in order to function. The experimental technique used to model the process that must be handled or the plant with unknown characteristics is an essential part of process identification. This article aims to find and simulate a two-Axis solar tracking system utilizing artificial neural networks. In order to manage the placement of the solar tracker, a fuzzy logic controller with and without self-Tuning scaling factors has been researched and implemented. To establish which kind of controller was best in terms of performance, logic controllers were compared with proportional integral and derivative controllers. We used a number of tools and software, including MATLAB and Simulink, as well as real-Time workshop equipment, to construct the environment.Öğe Iot techniques for disaster prediction and prevention(2023) Abdullah, Mustafa Hadi; Hamodat, ZaidNatural catastrophes such as landslides, floods, fires, and volcanic eruptions, as well as the damage produced by these events, are global issues that result in financial and human losses. This problem is exacerbated by changes in the planet's environmental conditions and is primarily evident in metropolitan areas. Because of pollution and a lack of planning, the deterioration of the ecosystem is more pronounced in these areas, damaging the ecology and influencing the local climate. As a result, this initiative makes three major contributions: (i) the use and evaluation of new IoT standards and emerging technologies in conjunction with WSN for the collection and distribution of data in natural environments, (ii) the use of the collected data for the prediction of natural disasters using Machine Learning (ML) techniques, with a case study on the characteristics of rivers and rainfall in Iraq and Turkey, and (iii) the proposal of an IoT-based and ML-based fault-tolerant architecture for the system.Öğe Optimal voltage stability from a scada based solar array and using ACO algorithm(Institute of Electrical and Electronics Engineers Inc., 2022) Mohammed, Ramzi Qasim; Hamodat, ZaidSolar PV-DG (PV-DG) in the power system is an extremely intriguing alternative due to the advantages of clean energy consumption and distributed generation. Nonetheless, it is necessary to investigate the best placement and size of a PV-DG in order to meet the power grid's needs while also analyzing solar energy's potential. Recent research on PV-DG allocation is reviewed from two perspectives: (1) the DG itself, including optimization methodologies and objectives, and (2) the methodology for estimating PV potential. As a result of this review, holes in previous research were discovered, and a novel strategy was developed to address them. The authors are certain that their effort will contribute to resolving the power system's difficulties. Additionally, it adds to the expansion of solar energy use in poor nations.Öğe Power quality enhancement in hybrid grid using FACTS device(Institute of Electrical and Electronics Engineers Inc., 2022) Al-Anbagi, Mohammed; Hamodat, ZaidThis work presents a mathematical model and control process of a three-phase VSC static synchronous compensator (STATCOM) in a hybrid grid made up of a 100 KW PV plant and a traditional power source. This approach is used to address the issues caused by the presence of both reactive and resistive loads at the common coupling point (PCC). The suggested control approach controls the STATCOM in a way that forces the source quadrature current component to zero, allowing only the active current component to be pulled from the source while the STATCOM satisfies the harmonic and reactive current requirements of the non-linear load. This approach will reduce the reactive power driven from the grid and eventually increase the transmission capacity and enhance the grid stability.Öğe SVC based smart grid management of renewable energy resources(Institute of Electrical and Electronics Engineers Inc., 2022) Mohammed, Mohammed Kareem; Niyef, Seyef Mohamad; Hamodat, ZaidA smart grid system can compensate for reactive power that changes in real time by using a TCLC compensator. When combined with SVCs such as a fixed capacitor-thyristor controlled reactor (FCTCR) that generates low order harmonic current, TCLCs have the potential to be significantly more effective than currently available static variable compensators (SVCs). Considerations for reactive power compensation and harmonic current rejection are taken into account while generating the TCLC parameters in this research. The generalized instantaneous reactive power theory is used as an additional control mechanism. TCLC is demonstrated to be more successful in compensating for dynamic reactive power than traditional FC-TCR and FC-TCR+PPF parallel configurations, as well as other related modeling and experimental results.Öğe Three phase fault location and nature determination using smart intelligent technique(Institute of Electrical and Electronics Engineers Inc., 2022) Mohammed, Ayoob Jasim; Hamodat, Zaid; Hammoodi, Yazen FawwazElectrical power is being generated using fuel-based turbines in large amounts for maintaining the huge demand. The cost of maintaining the power system is being added to that of power generation. It is reported that losses due to faults in distribution sub systems are major as compared with generation cost. Protection of power system is vital for cost reduction and economical worthiness. It has also vital impact of quality of service given to the consumers through minimizing the fluctuation time. In this paper, three phase fault detection and isolation is being performed using artificial neural network.Öğe Voltage stability control in hybrid systems using AI(Institute of Electrical and Electronics Engineers Inc., 2022) Al-Gbur, Fadhaa Zaid Khalaf; Al Yosif, Rasha Khalied Lrehaem; Hamodat, ZaidThis paper presents an optimization-based strategy for increasing the voltage stability of power systems while needing fewer measurements. By using a Ward reduction-based network that collects data only from critical locations, it is possible to increase the system's overall loadability, hence improving overall performance. A hybrid state estimator is used to more accurately estimate the system states of the reduced network by taking into account recent changes in the surrounding environment. Utilizing a predictive-corrector primal-dual interior point approach, it is important to improve the loadability margin over a specific critical margin. Gauss-Newton optimization is used to compare the optimized voltages to the objective values in order to establish the control settings. When combined with the aforementioned methodologies, the IEEE 30-bus and IEEE 118-bus test systems have shown success.
