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Keyword: Artificial Neural Network

Original Article
A New Control Scheme for Three-level Shunt Active Filter Using Artificial Neural Network Controllers to Eliminate the Current Harmonics and Compensate Reactive Power

The increased use of nonlinear devices in the industry has resulted in the direct increase of harmonic distortion in power systems during these last years. Active filter systems are proposed to mitigate current harmonics generated by nonlinear loads. The conventional scheme based on two-level voltage source inverter controlled by a hysteresis controller has several disadvantages […]

Original Article
Estimating Parallel Transmission Line Fault Using Phasor Measurement Unit based Artificial Neural Network

In a parallel transmission line, fault line, fault location, and classification have been identified separately. Since fault location takes more calculation time, it is unfit for protection purposes. Thus, this paper presented a new scheme that estimates the faulted line, fault location, and type of fault in a parallel transmission line, with the help of […]

Original Article
Hybrid Techniques for Short Term Load Forecasting

Short Term Load Forecasting (STLF) is the projection of system load demands for the next day or week. Because of its openness in modeling, simplicity of implementation, and improved performance, the ANN-based STLF model has gained traction. The neural model consists of weights whose optimal values are determined using various optimization approaches. This paper uses […]

Original Article
An Investigation on the Soft Computing Method Performance of the Optimizing Energy Consumption Cost

During peak demand hours, hydroelectric energy is one of the most significant sources of energy. Power sector restructuring has increased competition among the country’s electricity providers. Estimating the future price of energy is critical for producers in order to enhance investment profit and make better use of resources. One of the most significant technologies of […]

Original Article
A Sliding Mode Controller for Prediction of the Maximum Power Point Tracking of Hybrid Renewable Sources

The integration of a fuel cell and solar cell into a generator system presents an effective solution to numerous energy-related challenges. This system consists of solar panels, fuel cells, voltage converters, and a battery or supercapacitor. The performance of this electricity generation system is influenced by various factors, including load nature, system connection, and energy […]