Maximum Power Point Tracking for Photovoltaic Systems Using Adaptive Extremum Seeking Control

被引：0

作者：

Li, Xiao ^{[1
]}

Li, Yaoyu ^{[2
]}

Seem, John E. ^{[3
]}

Lei, Peng ^{[1
]}

机构：

[1] Univ Wisconsin, 3200 N Cramer St, Milwaukee, WI 53211 USA

[2] Univ Texas Dallas, Richardson, TX 75083 USA

[3] Johnson Controls Inc, Building Efficiency Res, Milwaukee, WI 53209 USA

来源：

2011 50TH IEEE CONFERENCE ON DECISION AND CONTROL AND EUROPEAN CONTROL CONFERENCE (CDC-ECC) | 2011年

关键词：

NONLINEAR DYNAMIC-SYSTEMS;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

To maintain the maximum achievable efficiency for the photovoltaic (PV) systems, it is crucial to achieve the maximum power point tracking (MPPT) operation for realistic illumination conditions. This paper presents the application of the adaptive extremum seeking control (AESC) scheme to the PV MPPT problem. A state-space model is derived for the PV system with buck converter. The AESC is used to maximize the power output by tuning the duty ratio of the pulse-width modulator (PWM) of the DC-DC buck converter. To address the nonlinear PV characteristics, the radial basis function (RBF) neural network is used to approximate the unknown nonlinear I-V curve. The convergence of the system to an adjustable neighborhood of the optimum is guaranteed by utilizing a Lyapunov-based adaptive control method. The performance of the controller is verified through simulations.

引用

页码：1503 / 1508

页数：6

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