Compensation of active and reactive power in PV- WIND battery system by using ANN technique

Abstract

This paper proposes the improvement of PV-WE system's energy usage and the battery energy storage system (BESS). PV, BESS. Surveillance, tension management, frequency control, energy distribution, power quality and artificial intelligence techniques (AI). The aim is to increase the power quality of the grid-connected PV-BESS system. In order to increase energy quality, technology is continually explored and evaluated. The PV-BESS system is built for the microgrid, which offers benefits including continuous supply, efficient load content and effective electricity utilisation. The flow of energy from source to source is controlled by ANN. The development of the MPPT algorithm for validation of the proposed approach is using an artificial neural network (ANN) technique. An extensive research and data finding demonstrates that output is accuracy with the ANN-based MPPT output. This study therefore proposes a new way for assessing the performance at a specific site of the microgrid. The power translation systems are therefore handled in an active and reactive manner taking into consideration their circumstances and limitations.