# Maximum Power Point Tracking Using Fuzzy Logic Control

Wissenschaftliche Studie 2004 8 Seiten

## Leseprobe

ABSTRACT: This paper proposes an intelligent control method for the maximum power point tracking (MPPT) of a photovoltaic system under variable temperature and insolation conditions. This method uses a fuzzy logic controller applied to a DC-DC converter device. The different steps of the design of this controller are presented together with its simulation. The PV system that I chose to simulate to apply my techniques on it is stand-alone PV water pumping system. Results of this simulation are compared to those obtained by the system without MPPT. They show that the system with MPPT using fuzzy logic controller increase the efficiency of energy production from PV.

Keywords: Photovoltaic (PV), Maximum power point tracking (MPPT), Fuzzy Logic Control (FLC), MATLAB/SIMULINK.

## I. INTRODUCTION

In our Arabian nation peopled areas is very small comparing to total area because fresh water resources concentrate in these areas. Now, the existing fresh water almost enough for our needs, but in the near future with increasing in people numbers it will be huge problem. On the other hand we have shining sun all the year, so we can use stand alone PV-powered water pumping system to get water in non peopled areas. Unfortunately the actual energy conversion efficiency of PV module is rather low. So to overcome this problem and to get the maximum possible efficiency, the design of all the elements of the PV system has to be optimized.

In order to increase this efficiency, MPPT controllers are used. Such controllers are becoming an essential element in PV systems. A significant number of MPPT control have been elaborated since the seventies, starting with simple techniques such as voltage and current feedback based MPPT to more improved power feedback based MPPT such as the perturbation and observation (P&O) technique or the incremental conductance technique [1-2]. Recently intelligent based controls MPPT have been introduced.

In this paper, an intelligent control technique using fuzzy logic control is associated to an MPPT controller in order to improve energy conversion efficiency.

## II. MAXIMUM POWER POINT TRACKING ALGORITHMS

When a PV module is directly coupled to a load, the PV module's operating point will be at the intersection of its I-V curve and the load line which is the I-V relationship of load. For example in Figure 1, a resistive load has a straight line with a slope of 1/Rload as shown in Figure 2. In other words, the impedance of load dictates the operating condition of the PV module. In general, this operating point is seldom at the PV module's MPP, the optimal adaptation occurs only at one particular operating point, called Maximum Power Point (MPP) and noted in our case Pmax.

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Figure 1 PV module is directly connected to a (variable) resistive load [5].

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Figure 2 I-V curves of BP SX 150S PV module [14] and various resistive loads simulated with the MATLAB model (1KW/m2, 25oC) [5].

To overcome this problem, it is necessary to add an adaptation device, MPPT controller with a DC-DC Cük converter, between the source and the load, (Figure 3), [3].

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Figure 3 Block diagram of the proposed PV water pumping sysytem.

Furthermore the location of the MPP in the I-V plane is not known beforehand and always changes dynamically depending on irradiance and temperature [6, 7]. For example, figure 4 shows a set of PV I-V curves under increasing irradiance at the constant temperature (25 oC), and figure 5 shows the I-V curves at the same irradiance values but with a higher temperature (50 oC). There are observable voltage shifts where the MPP occurs. So, the MPPT controller is also required to track the new modified maximum power point in its corresponding curve whenever temperature and/or insolation variation occurs.

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Figure 4 I-V curves for vaiying irradiance and a trace ofMPPs (25 oC) [5],

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Figure 5 I-V curves for varying irradiance and a trace of MPPs (50 oC) [5].

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