Radial basis function neural network MPPT controller-based microgrid for hybrid stand-alone energy system used for irrigation

Abstract

Purpose

The main purpose of this controller is to carryout irrigation by the farmers with renewable energy resources.

Design/methodology/approach

The proposed design includes the Deep learning based intelligent stand-alone energy management system used for irrigation purpose. The deep algorithm applied here is Radial basis function neural network which tracks the maximum power, maintains the battery as well as load system.

Findings

The Radial Basis Function Neural Network algorithm is used for carrying out the training process. In comparison with other conventional algorithms, this algorithm outperforms by higher efficiency and lower tracking time without oscillation.

Research limitations/implications

It is little complex to implement the hardware setup of neural network in terms of training process but the work is under progress.

Practical implications

The practical hardware implementation is under progress.

Social implications

If controller are implemented in a real-time environment, definitely it helps the human-less farming and irrigation process.

Originality/value

If this system is implemented in real-time environment, every farmer gets benefitted.

Citation

R., J. and Rajesh, K. (2023), "Radial basis function neural network MPPT controller-based microgrid for hybrid stand-alone energy system used for irrigation", Circuit World, Vol. 49 No. 2, pp. 251-266. https://doi.org/10.1108/CW-03-2022-0076