Title: Artificial neural network-based multiport DC-DC converter for simultaneous power management

Authors: B. Ashok Kumar; G. Angeline Ezhilarasi

Addresses: VIT University, Chennai, India ' School of Electrical Engineering, VIT University, Chennai, India

Abstract: In the paper, artificial neural network (ANN) is proposed for providing the optimal operation of multiport DC-DC converter. Here, the proposed controller is utilised to achieve the simultaneous power management of multiple renewable energy sources, which can be of different types and capacities. The photovoltaic (PV) and wind turbine generator (WTG) are considered as the sources and these are associated with the converter. The main objective of the paper is to achieve the simultaneous power management through the utilisation of multiport DC-DC converter with ANN controller. The input of the proposed controller is error voltage and the output is control pulses. The proposed method is implemented in MATLAB/Simulink platform and their performances are evaluated. The performance of the proposed method is compared with the base controller and PI controller. Then the efficiency of the converter is also determined to evaluate simultaneous power management of the converter.

Keywords: multiport DC-DC converter; artificial neural network; ANN; PI controller; voltage; wind turbine generator; WTG; photovoltaic; PV.

DOI: 10.1504/IJPELEC.2020.110753

International Journal of Power Electronics, 2020 Vol.12 No.4, pp.461 - 492

Received: 16 Sep 2017
Accepted: 06 Jun 2018
Published online: 29 Oct 2020 *

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