MPPT of Photovoltaic Systems Using Sensorless Current-Based Model Predictive Control

Morcos Metry, Mohammad B. Shadmand, Robert Balog, Haitham Abu-Rub

Research output: Contribution to journalArticle

57 Citations (Scopus)

Abstract

Variability in the solar irradiance level and ambient temperature of photovoltaic (PV) systems necessitates the use of maximum power point tracking (MPPT) of PV systems to ensure continuous harvesting of maximum power. This paper presents a sensorless current (SC) MPPT algorithm using model predictive control (MPC). The main contribution of this paper is the use of model-based predictive control principle to eliminate the current sensor that is usually required for well-known MPPT techniques such as perturb and observe (P&O). By predicting the PV system states in horizon of time, the proposed method becomes an elegant, embedded controller that allows faster response and lower power ripple in steady state than the conventional P&O technique under rapidly changing atmospheric conditions. This becomes possible without requiring expensive sensing and communications equipment and networks for direct measurement of solar irradiation changes. The performance of the proposed SC-MPC-MPPT with reduced load sensitivity is evaluated on the basis of industrial European Efficiency Test, EN 50530, that assesses the performance of PV systems under dynamic environmental conditions. The proposed control technique is implemented experimentally using dSPACE DS1007 platform to verify the simulation results.

Original languageEnglish
Article number7726069
Pages (from-to)1157-1167
Number of pages11
JournalIEEE Transactions on Industry Applications
Volume53
Issue number2
DOIs
Publication statusPublished - 1 Mar 2017

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Keywords

  • Maximum power point tracking (MPPT)
  • photovoltaic systems
  • predictive control
  • solar energy
  • solar power generation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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