A MPPT-Based ANN Controller Applied To PV Pumping System

被引：0

作者：

Bouselham, L. ^{[1
]}

Hajji, M. ^{[1
]}

Hajji, B. ^{[1
]}

Bouali, H. ^{[1
]}

机构：

[1] ENSA UMP, BP 669, Oujda 60000, Morocco

来源：

PROCEEDINGS OF 2016 INTERNATIONAL RENEWABLE & SUSTAINABLE ENERGY CONFERENCE (IRSEC' 16) | 2016年

关键词：

PV Pumping System; MPPT; Artificial Neural Network (ANN); Partial Shading Conditions; Global Maximum Power Point (GMPP); POWER POINT TRACKING; OPTIMIZATION;

D O I：

暂无

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

This paper introduces a maximum power point method (MPPT) based on an artificial neural network (ANN) and a scanning algorithm. The proposed MPPT is applied to pumping system. The system is composed of solar generator, boost converter and centrifugal pump load driven by a DC motor. A complete simulation of the system is developed in MATLAB/SIMULINK under different weather conditions. The results obtained verify that the ANN controller shows a significant improvement in the power extraction performance especially in terms of tracking efficiency, when compared with modified Perturb and observe controller, and consequently the quantity of the pumped water gained by the ANN method is higher.

引用

页码：86 / +

页数：7

共 14 条

[1] A novel MPPT method for PV systems with irradiance measurement [J].