Design and hardware implementation of highly efficient fuzzy logic based MPPT controller for PV applications

This project is basically based on new maximum power point (MPP) tracking (MPPT) methodology with an adaptive fuzzy logic (FL) technique for controlling photovoltaic (PV) systems. The proposed methodology will be designed and implemented in this project. The main advantage of the proposed adaptive F

Project Title

Design and hardware implementation of highly efficient fuzzy logic based MPPT controller for PV applications

Project Area of Specialization

Electrical/Electronic Engineering

Project Summary

This project is basically based on new maximum power point (MPP) tracking (MPPT) methodology with an adaptive fuzzy logic (FL) technique for controlling photovoltaic (PV) systems. The proposed methodology will be designed and implemented in this project. The main advantage of the proposed adaptive FL-based MPPT (AFL-MPPT) algorithm is simple, accurate, and provides faster convergence to optimal operating point. The effectiveness and feasibility variations of the proposed AFL-MPPT methodology are validated with considering various operating conditions at slow and fast change of solar radiation. The FL control has the capability to enable an accurate and better performance as compare to conventional HC method. Additionally, dual MPPT method using fuzzy and P&O method was introduced. This method has achieved a good performance regarding adaptively with the operating point. However, higher complexity and slower performance are obtained, especially in fast changing irradiance conditions. The modified sine-cosine optimized MPPT method will be presented with using adaptive FL method. MATLAB/Simulink software will be used for design and simulation .Additionally, experimental results will be performed while using digital oscilloscope, DC power supply, inductive load, sensors, DC-DC boost converter and DSP board for verifying the feasibility of the proposed AFL-MPPT methodology. 

Project Objectives

Main objective of the research would be as under:

1. To regulate a panel array to be of higher voltage than the battery bank.
2. To achieve the maximum power from thepanel array at low irradiation during cloudy weather conditions.
3. To ensure the loads receive maximum current to be used by quickly charging the battery.
4. To reduce the complexity of the PV module and to get the output of the system with higher efficiency.

Project Implementation Method

The above procedure can be summarized by following 5 stages:

Step 1: To Design an adaptive fuzzy based MPPT controller by applying current and voltages as inputs at different ratings.

Step 2: Selection of the sensors that sense the applied power in DC-DC boost converter as the rated output power.

Step 3: Performance of fuzzy based MPPT controller in MATLAB/Simulink. Simulated method controls unregulated waves to regulated results of PV panel.

Step 4: The prototype experiment observes the actual performances of components as compare to simulated performance at the output by using fuzzy logic algorithm technique.

Step 5: This algorithm FL based MPPT tracking energy from the solar panel at the different weather conditions and partial shading.

Benefits of the Project

The main benefits in the proposed  FL-MPPTmethod are accurate and adaptive tracking performance of the operating maximum power extraction point of the solar PV system, and the mitigation of power fluctuations in transient and steady state operating points. Moreover, the proposed AFL-MPPT method achieves faster MPPT convergence with simple implementation. The pro-posed AFL-MPPT controller can effectively overcome the demerits of the existing MPPT methods The boost dc-dc power converter represents the first stage, wherein the maximum available energy is harvested from the PV module. The boost power converter possesses the benets of voltage boosting, less component, and continuous current of the solar PV panel side. The control of this stage is composed of the MPPT and the PWM modulator that transfers theMPPT signal to gating pulses for the boost dc-dc converter.

Technical Details of Final Deliverable

Solar energy and other renewables like geothermal, biomass, photovoltaic (PV), and wind energy can minimize the emissions of the CO2 and other harmful gases resulting from fossil fuel. Recently, the yearly growth rates of PV generation systems have been largely increased attaining total generation of 402 GW in 2017 compared with total generation of 303 GW in 2016. It is expected that the increase PV generation penetration levels continues and achieves between 1760 to 2500 GW by the year 2030. 

Being available everywhere, continual decrease in their cost per watt, and environmental friendly have made wide spreading of PV system in comparison with the other renewable energy
sources. Concerns of energy efficiency and better energy harvesting have been arisen in order to maximize their power densities, and to reduce the cost of their generated kWh. The most conventional and effective technique for better energy efficiency of PV systems is the maximum
power point tracking (MPPT) control This is due to the fluctuating nature of PV generation. The output power of PV systems is highly dependent on their operating irradiance and ambient temperature. The nonlinear nature of solar PV panels and the climate conditions result in quite complicated tracking behavior. Therefore, FL-based MPPT methods can be employed for tracking the MPP in the solar PV system with simplified implementation and less required data. The 75W PV module is selected in this project as a case study. The simulation of the PV panel is performed using MATLAB/Simulink   110 series connected solar PV cells. The mathematical models and detailed analysis of PV modelling can be found.

Final Deliverable of the Project

Hardware System

Core Industry

Energy

Other Industries

Core Technology

Clean Tech

Other Technologies

Sustainable Development Goals

Affordable and Clean Energy, Reduced Inequality, Sustainable Cities and Communities

Required Resources

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