Classification of Fault Using Artificial Neural Network and Power Quality Improvement Using DVR in a PV Integrated Hybrid Power System
Kumaresh Pal, Ashok Kumar Akella, Kumari Namrata, Subhendu Pati
Abstract
Renewable energy is a type of energy that lasts for lifetime and creates a stable and sustainable environment for living things. Making power generation to the degree of extent in the revitalization of technology is critical for developing an unconventional society. PV solar systems are incorporated to improve system reliability, and we have designed a PV-based Hybrid Power Generation System to cause the least amount of damage to the electrical system. The type of fault that occurred must be swiftly and properly identified. Artificial Neural Networks (ANN) is one of the most effective method for classifying transmission line defects. In addition an ingenious Dynamic Voltage Restorer is accomplished in the Hybrid Power System in this work to provide distortion-free power generation. The simulations were run in MATLAB/Simulink, and the results-oriented performance was proven conclusively.