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    Enhancing smart grid efficiency: a modified ANN-LSTM approach for energy storage and distribution optimization
    (Institute of Electrical and Electronics Engineers Inc., 2023) Mohammed, Ramzi Qasim; Abdulrazzaq, Mohammed Majid; Mohammed, Ayoob Jasim; Mardikyan, Kevork; Çevik, Mesut
    The smart grid represents a paradigm shift in energy management, aiming to optimize energy storage and distribution while accommodating the growing demand for renewable energy sources. In this paper, we investigate the application of a modified Artificial Neural Network with Long Short-Term Memory (ANN-LSTM) in addressing the multifaceted challenges of the smart grid. Through rigorous experimentation and simulation, the ANN-LSTM is evaluated in four diverse scenarios, including normal operation, fluctuating renewable energy, peak demand, and grid instability. The results showcase the model's exceptional predictive accuracy, low Mean Squared Error (MSE), and rapid response times, outperforming other models, such as Support Vector Machine (SVM), Convolutional Neural Network (CNN), Decision Tree (DT), and Fuzzy Logic. Our findings underscore the ANN-LSTM's potential to revolutionize energy storage and distribution in the smart grid, ushering in a new era of efficiency, sustainability, and resilience in energy management.
  • [ X ]
    Öğe
    Study and analysis of PV system behavior during disturbances
    (Institute of Electrical and Electronics Engineers Inc., 2023) Mohammed, Ramzi Qasim; Mardikyan, Kevork; Çevik, Mesut
    The utilization of renewable energy sources has drawn attention because of the population's fast increase and growing worry over global warming. Renewable energy sources greatly improve the environment by lowering carbon emissions and generating cost-effective electricity. Solar energy is the most widely used renewable energy source. PV panels are becoming more affordable, have a bright commercial future, and are good for the environment. Recently, the PV solar system has drawn a lot of attention, especially in comparison to other renewable energy sources. The renewable energy source systems are intended to function normally within a set of operating parameters, but they may experience failures that alter their operational performance and behavior. The performance and behavior of a PV hybrid grid-connected system under disturbances, such as a quick change in load or a rapid change in applied irradiations, temperature and also fault conditions will be studied, analyzed, and discussed in this papers. The MATLAB Simulink application will be used to display the modeling of PV system results. In this papers the P&O MPPT technique-based power management of PV batteries is vulnerable to a number of eventualities, including dust impairing PV efficiency and raising temperature and failures. The results show that, the PV system's output power decreases as the temperature rises, but the output efficiency also suffers from dust buildup. The second goal is the direct proportion between PV current and irradiance. Different cases are proposed in this work to verify the energy management system. The results were within IEEE harmonic standards when the LC filter is used in this work.