Neural Network Based Energy Management Control for PV/Wind Hybrid System with Battery Storage

  • L. M. Waghmare, Sangita B. Patil

Abstract

An intelligent energy management control for hybrid renewable energy sources (HRES) like PV-wind is proposed for the standalone power generation systems. While considering the various kind of renewable resources Energy management control will be essential. A power management control (PMC) system is a computer aided tool commonly worn to monitor, measure and control the performance of generation and transmission system. In this paper hybrid photovoltaic/wind with battery storage is implemented. The energy balance between photovoltaic (PV) and wind is made superior by the artificial neural network (ANN) controller. In this approach Multi-layer feed forward network is used for carrying out the process of the hybrid renewable energy resources. The Levenberg Marquardt algorithm is an interconnection of perceptron’s in which the data and calculation will flow in an accurate direction from input to output. It is quite simple and easy to resolve the different operating modes of the hybrid system according to the time and varying weather conditions. The process is implemented through MATLAB then the attained results are displayed and the comparison results are carried out with fuzzy logic controller and the obtained results shows the feasibility of the proposed system.  

Published
2020-06-01
How to Cite
L. M. Waghmare, Sangita B. Patil. (2020). Neural Network Based Energy Management Control for PV/Wind Hybrid System with Battery Storage. International Journal of Control and Automation, 13(02), 1396 - 1412. Retrieved from https://sersc.org/journals/index.php/IJCA/article/view/32918
Section
Articles