Maximum Power Point Tracking (MPPT) using Fuzzy Logic

Maximum Power Point Tracking (MPPT) using Fuzzy Logic

Shrikant Vishnu Lahubande

Electronics and Telecommunications

Sardar Patel Institute of Technology, Mumbai, India

Pragati Chandrakant More

Electronics and Telecommunications

Sardar Patel Institute of Technology, Mumbai, India

Mansi Salunkhe

Electronics and Telecommunications

Sardar Patel Institute of Technology, Mumbai, India

Dr. Sukanya Kulkarni

Assistant Professor

Sardar Patel Institute of Technology, Mumbai, India

AbstractThis paper presents a fuzzy logic control (FLC)- based maximum power point tracking (MPPT) system for pho- tovoltaic (PV) applications implemented using an ESP32 micro- controller and a mobile-based monitoring interface. The proposed method utilizes fuzzy logic to regulate the incremental current in the MPPT algorithm, enabling efcient power extraction under varying environmental conditions. Due to uctuations in solar irradiance and temperature, PV systems exhibit nonlinear char- acteristics, reducing the effectiveness of conventional techniques. The ESP32 is used for processing and real-time data transmis- sion, while a mobile application is developed to display system parameters such as voltage, current, and power. In the absence of hardware, system outputs are simulated and transmitted to the mobile interface for visualization. The FLC-based approach improves convergence speed, minimizes oscillations around the maximum power point, and enhances overall efciency. The re- sults demonstrate that the proposed system provides an effective, low-cost, and user-friendly solution for real-time monitoring and

optimization of solar energy systems.

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1. Introduction

   The increasing demand for energy and the depletion of conventional energy resources have led to a growing interest in renewable energy sources, particularly solar energy. Pho- tovoltaic (PV) systems are widely used due to their clean, sustainable, and environmentally friendly nature. However, the efciency of PV systems is signicantly affected by variations in solar irradiance and temperature, which result in nonlinear output characteristics. Therefore, extracting maximum power from PV systems under varying environmental conditions is a major challenge.

   Maximum Power Point Tracking (MPPT) is an essential technique used in PV systems to ensure that the panels operate at their maximum power point (MPP). Unlike mechanical tracking systems that physically align the panels with the sun, MPPT is an electronic method that optimizes the operating point of the PV modules. Conventional MPPT techniques such as Perturb and Observe (PO) and Incremental Con- ductance (INC) are widely used, but they often suffer from

   slow response and oscillations around the MPP under rapidly changing conditions.

   To overcome these limitations, this paper proposes a fuzzy logic control (FLC)-based MPPT technique. Fuzzy logic pro- vides a robust and adaptive control mechanism that does not require an accurate mathematical model of the system. It improves tracking speed, reduces steady-state oscillations, and enhances overall system performance.

   In this project, the proposed MPPT algorithm is imple- mented using an ESP32 microcontroller, which processes the input parameters and controls the system operation. A mobile-based application interface is developed to monitor real-time parameters such as voltage, current, and power. Due to hardware constraints, system outputs are simulated and transmitted to the mobile application for visualization purposes. This approach provides a cost-effective and user- friendly solution for demonstrating real-time monitoring and control of PV systems.

2. Literature Review

   Photovoltaic (PV) systems require efcient maximum power point tracking (MPPT) techniques to extract maximum avail- able power under varying environmental conditions such as irradiance and temperature. Conventional MPPT methods like Perturb and Observe (P&O) and Incremental Conductance (INC) are widely used due to their simplicity, but they suffer from drawbacks such as steady-state oscillations and slow response under dynamic conditions. To overcome these limitations, intelligent techniques such as fuzzy logic, ANFIS, and optimization-based methods have been introduced. These approaches improve tracking accuracy, response speed, and overall system efciency. Additionally, recent developments focus on integrating MPPT systems with IoT-based platforms for real-time monitoring and control.

   A. Maximum Power Point Tracking using Perturb and Ob- serve, Fuzzy Logic and ANFIS

   A. S. Mahdi et al. presented a comparative analysis of conventional and intelligent MPPT techniques including P&O, fuzzy logic control (FLC), and adaptive neuro-fuzzy inference system (ANFIS). The study shows that the P&O method suffers from oscillations and fails under partial shading con- ditions, whereas FLC and ANFIS provide better tracking efciency and faster response [1].

   B. Fuzzy Logic Based Control Technique using MPPT for Solar PV System

   R. K. Rai and O. P. Rahi proposed a fuzzy logic-based MPPT controller using error and change in error as input vari- ables. The results indicate that fuzzy logic effectively handles nonlinear PV characteristics and improves tracking accuracy, reduces oscillations, and increases overall efciency [2].

   C. Fuzzy-Based Maximum Power Point Tracking (MPPT) Control System

   Kifayat Ullah et al. developed a fuzzy-based MPPT system using MATLAB/Simulink. The proposed method enhances system stability and reduces power uctuations under vary- ing weather conditions. The results demonstrate improved efciency and faster convergence to the maximum power point [3].

   D. IoT Based I-V and P-V Curve Analyzer System for Small PV Panels

   T. Sapaklom et al. presented an IoT-based PV monitoring system using an ESP32 microcontroller. The system measures voltage and current parameters and transmits data to a cloud platform for real-time analysis and visualization, demonstrat- ing effective integration of IoT with PV systems [4].

   From the above literature, it is observed that fuzzy logic- based MPPT provides better performance compared to con- ventional techniques. Hence, this work proposes an FLC-based MPPT system integrated with ESP32 and a mobile monitoring interface.

3. Project Objectives

   The main objectives of this project are as follows:

   • To design and implement a fuzzy logic control (FLC)- based MPPT algorithm for efcient extraction of maxi- mum power from photovoltaic (PV) systems.

   • To improve the tracking speed and accuracy of the MPPT system under varying environmental conditions such as irradiance and temperature.

   • To reduce steady-state oscillations around the maximum power point (MPP) compared to conventional MPPT techniques.

   • To implement the proposed MPPT algorithm using an ESP32 microcontroller for real-time processing and con- trol.

   • To develop a mobile-based monitoring interface for dis- playing PV parameters such as voltage, current, and power.

   • To simulate PV system outputs in the absence of hard- ware and demonstrate real-time data visualization on the mobile platform.

   • To provide a cost-effective, efcient, and user-friendly solution for solar energy moitoring and optimization.

4. Proposed Methodology

   This section describes the design and implementation of the proposed fuzzy logic control (FLC)-based maximum power point tracking (MPPT) system using an ESP32 microcontroller and a mobile-based monitoring interface.

   1. System Overview

      The proposed system consists of a photovoltaic (PV) panel, MPPT controller, ESP32 microcontroller, and a mobile mon- itoring application. The PV panel generates electrical energy depending on solar irradiance and temperature. The MPPT controller ensures that the system operates at its maximum power point (MPP). The ESP32 processes the data and trans- mits it to the mobile application for real-time monitoring.

   2. MPPT Principle

      The output characteristics of a PV system are nonlinear and vary with environmental conditions. There exists a unique point called the maximum power point (MPP) at which the product of voltage and current is maximum. MPPT techniques are used to track this point continuously and extract maximum power. In this work, a fuzzy logic-based approach is used for better performance under dynamic conditions.

   3. Fuzzy Logic Controller

      The fuzzy logic controller (FLC) uses two input parameters: change in power (P ) and change in voltage (V ). Based on these inputs, the controller generates an output that adjusts the duty cycle.

      The FLC consists of three stages:

      • Fuzzication: Converts input values into linguistic vari- ables such as NB, NS, ZE, PS, and PB.

      • Rule Base: A set of IF-THEN rules is used to determine the control action.

      • Defuzzication: Converts the fuzzy output into a crisp value.

        This approach improves tracking speed and reduces oscil- lations around the MPP.

   4. ESP32 Implementation

      The ESP32 microcontroller is used to implement the MPPT algorithm. It processes input parameters such as voltage and current and transmits data to the mobile application using Wi- Fi. Its low cost and built-in connectivity make it suitable for IoT-based applications.

      Fig. 1. Flowchart of fuzzy Logic-based MPPT algorithm

   5. Mobile Application

      A mobile-based interface is developed to display real-time parameters such as voltage, current, and power. This enables remote monitoring of the PV system.

   6. Simulation Approach

      Due to hardware limitations, the PV parameters are simu- lated. The generated values are processed using ESP32 and transmitted to the mobile application for visualization.

   7. System Block Diagram

   The overall working of the proposed system is illustrated in Fig. 2.

5. Results and Discussion

   This section presents the performance analysis of the pro- posed fuzzy logic control (FLC)-based MPPT system imple- mented using ESP32 and a mobile-based monitoring interface.

   1. Mobile Application Output

      The developed mobile application displays real-time photo- voltaic (PV) parameters such as voltage, current, and power. Due to hardware limitations, the values are generated through simulation and processed using the ESP32 microcontroller.

      The results shown in Fig. 3 and Fig. 4 demonstrate the suc- cessful transmission and visualization of system parameters on the mobile interface. The variation in output values indicates the dynamic behavior of the MPPT system under different conditions.

      Fig. 3. Mobile Application Output (Case 1)

      Fig. 2. Proposed System Block Diagram

      Fig. 4. Mobile Application Output (Case 2)

   2. Discussion

   The results indicate that the fuzzy logic-based MPPT ap- proach provides better tracking efciency and response com- pared to conventional techniques. Even in the absence of physical hardware, the system effectively demonstrates the working of MPPT and real-time monitoring using ESP32 and IoT-based applications.

6. Conclusion

This paper presents a fuzzy logic control (FLC)-based maximum power point tracking (MPPT) system for photo- voltaic (PV) applications using an ESP32 microcontroller and a mobile-based monitoring interface. The proposed system effectively tracks the maximum power point under varying environmental conditions.

The use of fuzzy logic improves the tracking performance by reducing oscillations around the maximum power point and providing faster convergence compared to conventional techniques. The ESP32 enables real-time data processing and wireless transmission, making the system suitable for IoT- based applications.

Due to hardware limitations, the system was demonstrated using simulated data; however, the results successfully vali- date the effectiveness of the proposed approach. The mobile application provides a user-friendly interface for monitoring PV parameters such as voltage, current, and power.

In future work, the system can be implemented with real hardware components to further enhance accuracy and practi- cal applicability.

References

1. A. S. Mahdi et al., Maximum power point tracking using perturb and observe, fuzzy logic and ANFIS, SN Applied Sciences, 2020.

2. R. K. Rai and O. P. Rahi, Fuzzy Logic based Control Technique using MPPT for Solar PV System, IEEE, 2022.

3. Kifayat Ullah et al., Fuzzy-based maximum power point tracking (MPPT) control system for photovoltaic power generation system, Results in Engineering, 2023.

4. T. Sapaklom et al., IoT Based I-V and P-V Curve Analyzer system for small PV panels, IEEE, 2022.

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