Title: Retrospection and investigation of ANN-based MPPT technique in comparison with soft computing-based MPPT techniques for PV solar and wind energy generation system

Authors: Sunita Chahar; Dinesh Kumar Yadav

Addresses: Department of Electrical Engineering, Rajasthan Technical University Kota, Rajasthan, India ' Department of Electrical Engineering, Rajasthan Technical University Kota, Rajasthan, India

Abstract: This article discusses the previously available research and summarises the state of knowledge of soft computing artificial neural network (ANN)-based control techniques for renewable energy systems. In recent years, wind and photovoltaic (PV) solar energy systems have been developed as key renewable energy sources. The main issue is to operate these energy sources for maximum power output in abrupt changes in environmental conditions. Besides different types of conventional control techniques, the soft computing-based control system has proved efficient in extracting the highest available output. There are few articles available in the literature on ANN-based control systems in wind energy systems, however, sufficient research has been carried out for the ANN-based maximum power extraction techniques for PV solar. This article highlights the important features such as better controllability and performance of ANN-based control techniques in comparison with the other types of soft computing-based-tactics for PV solar and wind energy systems.

Keywords: traditional algorithm; novel algorithm; hybrid algorithm; artificial neural network; ANN; solar photovoltaic; wind; renewable; maximum power point tracking.

DOI: 10.1504/IJMMNO.2024.143230

International Journal of Mathematical Modelling and Numerical Optimisation, 2024 Vol.14 No.1/2, pp.69 - 83

Received: 14 Jan 2023
Accepted: 25 Feb 2023
Published online: 11 Dec 2024 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article