Efficiency improvement of the maximum power
point tracking for PV systems using support vector
machine technique
الباحث الأول:
Ameer A. Kareim
الباحثين الآخرين:
Muhamad Bin Mansor
المجلة:
IOP Publishing
تاريخ النشر:
None
مختصر البحث:
Abstract. The aim of this paper is to improve efficiency of maximum power point tracking
(MPPT) for PV systems. The Support Vector Machine (SVM) was proposed to achieve the
MPPT controller. The theoretical, the perturbation and observation (P&O), …
Abstract. The aim of this paper is to improve efficiency of maximum power point tracking
(MPPT) for PV systems. The Support Vector Machine (SVM) was proposed to achieve the
MPPT controller. The theoretical, the perturbation and observation (P&O), and incremental
conductance (IC) algorithms were used to compare with proposed SVM algorithm. MATLAB
models for PV module, theoretical, SVM, P&O, and IC algorithms are implemented. The
improved MPPT uses the SVM method to predict the optimum voltage of the PV system in
order to extract the maximum power point (MPP). The SVM technique used two inputs which
are solar radiation and ambient temperature of the modeled PV module. The results show that
the proposed SVM technique has less Root Mean Square Error (RMSE) and higher efficiency
than P&O and IC methods.
