Nonlinear Model Predictive Control Using Relevance Vector Machine for Maximum Power Point Tracking of Photovoltaic Arrays

24 Pages Posted: 20 Apr 2018

See all articles by Germin Nisha M.

Germin Nisha M.

St. Xavier’s Catholic College of Engineering - Department of Electrical and Electronics Engineering

Monisha M

St. Xavier’s Catholic College of Engineering - Department of Electrical and Electronics Engineering

Snow J Steggela

St. Xavier’s Catholic College of Engineering - Department of Electrical and Electronics Engineering

Promodhini S

St. Xavier’s Catholic College of Engineering - Department of Electrical and Electronics Engineering

Date Written: April 6, 2018

Abstract

This paper proposes the control of photovoltaic (PV) array Maximum Power Point Tracker (MPPT) through Nonlinear Model Predictive Control (NMPC) strategy which uses Relevance Vector Machines (RVM) regression model. Another Relevance Vector Regression (RVR) model is employed to offer the reference Maximum Power Point (MPP) trajectory to the model predictive control system by predicting the maximum power point current and voltage of the nonlinear PV module at different operating conditions. The above control algorithm is speeded up by simplifying the optimization problem by Finite Control Set Model Predictive Control (FCS-MPC) technique. Thus an improved system performance is guaranteed by an accurate predictive model and simple control algorithm. The obtained simulation results show the superiority of the proposed method compared to deterministic sparse kernel learning Least squares support vector machines (LS-SVM) based model predictive control (MPC) and state space model based NMPC.

Keywords: Photovoltaic arrays; Relevance vector machines; Maximum power point tracking; Nonlinear model predictive control; Finite control set model predictive control

Suggested Citation

M., Germin Nisha and M, Monisha and Steggela, Snow J and S, Promodhini, Nonlinear Model Predictive Control Using Relevance Vector Machine for Maximum Power Point Tracking of Photovoltaic Arrays (April 6, 2018). International Conference on Energy Efficient Technologies for Sustainability (ICEETS) 2018. Available at SSRN: https://ssrn.com/abstract=3165947

Germin Nisha M. (Contact Author)

St. Xavier’s Catholic College of Engineering - Department of Electrical and Electronics Engineering ( email )

Nagercoil
India

Monisha M

St. Xavier’s Catholic College of Engineering - Department of Electrical and Electronics Engineering ( email )

Nagercoil
India

Snow J Steggela

St. Xavier’s Catholic College of Engineering - Department of Electrical and Electronics Engineering ( email )

Nagercoil
India

Promodhini S

St. Xavier’s Catholic College of Engineering - Department of Electrical and Electronics Engineering ( email )

Nagercoil
India

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