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.
Inhaltsverzeichnis (Table of Contents)
- I. INTRODUCTION
- II. MAXIMUM POWER POINT TRACKING ALGORITHMS
- Maximum power point tracking algorithms:
- III. FUZZY LOGIC MPPT CONTROLLER
- A) Fuzzification
- B) Inference Method
- C) Defuzzification
- D) Fuzzy Logic Control Simulation in MATLAB/SIMULINK
- IV. SIMULATION OF PV WATER PUMP SYSTEM WITH MPPT
Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)
This paper investigates the implementation of an intelligent control method for maximizing the power output of a photovoltaic (PV) system under varying environmental conditions. This method utilizes a fuzzy logic controller (FLC) to regulate a DC-DC converter, aiming to enhance the efficiency of energy production from the PV system. The paper focuses on a stand-alone PV water pumping system, simulating its performance under various scenarios.
- Maximum Power Point Tracking (MPPT) for PV Systems
- Fuzzy Logic Control for MPPT Applications
- Simulation and Analysis of a Stand-Alone PV Water Pumping System
- Efficiency Enhancement of PV Systems through Intelligent Control
- Comparison of MPPT Performance with and without Fuzzy Logic Control
Zusammenfassung der Kapitel (Chapter Summaries)
The introduction highlights the significance of PV water pumping systems for water access in areas with limited freshwater resources. It addresses the challenge of low energy conversion efficiency in PV modules and introduces the need for MPPT controllers to optimize system performance. The paper then delves into various MPPT algorithms, including voltage, current, and power-based methods, outlining their strengths and limitations.
Chapter III focuses on the implementation of a fuzzy logic MPPT controller. It details the design of the controller, including the fuzzification process, inference method, defuzzification, and simulation in MATLAB/SIMULINK. The chapter explains the role of input variables (error and change of error) and output variable (duty ratio) in the FLC.
Chapter IV presents the simulation of the PV water pumping system with MPPT using MATLAB/SIMULINK. The simulation incorporates atmospheric conditions and compares the system's performance with and without MPPT. It analyzes the impact of the FLC on energy production and water pumping rates, demonstrating the efficiency improvements achieved through intelligent control.
Schlüsselwörter (Keywords)
The paper focuses on the development and application of fuzzy logic control for maximum power point tracking (MPPT) in photovoltaic (PV) systems, particularly in the context of stand-alone PV water pumping systems. Key concepts include fuzzy logic, MPPT algorithms, DC-DC converters, MATLAB/SIMULINK simulations, and energy efficiency optimization. The paper aims to enhance the performance of PV systems under varying environmental conditions, contributing to the field of renewable energy technologies.
- Citar trabajo
- Mohamed Ezzat Salem (Autor), 2004, Maximum Power Point Tracking Using Fuzzy Logic Control, Múnich, GRIN Verlag, https://www.grin.com/document/174104
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