𝐇𝐲𝐛𝐫𝐢𝐝 𝐍𝐞𝐮𝐫𝐚𝐥 𝐍𝐞𝐭𝐰𝐨𝐫𝐤 𝐏𝐎 𝐌𝐏𝐏𝐓 𝐟𝐨𝐫 𝐒𝐨𝐥𝐚𝐫 𝐏𝐕 𝐒𝐲𝐬𝐭𝐞𝐦 𝐢𝐧 𝐌𝐀𝐓𝐋𝐀𝐁

𝐇𝐲𝐛𝐫𝐢𝐝 𝐍𝐞𝐮𝐫𝐚𝐥 𝐍𝐞𝐭𝐰𝐨𝐫𝐤 𝐏𝐎 𝐌𝐏𝐏𝐓 𝐟𝐨𝐫 𝐒𝐨𝐥𝐚𝐫 𝐏𝐕 𝐒𝐲𝐬𝐭𝐞𝐦 𝐢𝐧 𝐌𝐀𝐓𝐋𝐀𝐁

𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧

𝐇𝐲𝐛𝐫𝐢𝐝 𝐍𝐞𝐮𝐫𝐚𝐥 𝐍𝐞𝐭𝐰𝐨𝐫𝐤 𝐏𝐎 𝐌𝐏𝐏𝐓 for a 𝐒𝐨𝐥𝐚𝐫 𝐏𝐕 𝐒𝐲𝐬𝐭𝐞𝐦 is designed to improve maximum power extraction from a photovoltaic panel under changing irradiation conditions.

This MATLAB Simulink model combines the fast prediction capability of a 𝐍𝐞𝐮𝐫𝐚𝐥 𝐍𝐞𝐭𝐰𝐨𝐫𝐤 MPPT with the practical tracking behavior of the 𝐏𝐎 MPPT algorithm. The hybrid controller helps reduce oscillation and improves tracking response compared with individual PO and NN MPPT methods.

MATLAB Implementation of Hybrid NN-PO MPPT for Solar PV System

₹4,127.00₹2,063.50

Buy Now

𝐒𝐲𝐬𝐭𝐞𝐦 𝐎𝐯𝐞𝐫𝐯𝐢𝐞𝐰

The system includes a 𝐬𝐨𝐥𝐚𝐫 𝐏𝐕 𝐩𝐚𝐧𝐞𝐥, 𝐛𝐨𝐨𝐬𝐭 𝐜𝐨𝐧𝐯𝐞𝐫𝐭𝐞𝐫, 𝐥𝐨𝐚𝐝, 𝐍𝐍 𝐌𝐏𝐏𝐓, 𝐏𝐎 𝐌𝐏𝐏𝐓, hybrid selection logic, and PWM generator.

𝐒𝐥. 𝐍𝐨.	𝐒𝐲𝐬𝐭𝐞𝐦 𝐏𝐚𝐫𝐭	𝐃𝐞𝐬𝐜𝐫𝐢𝐩𝐭𝐢𝐨𝐧
01	Solar PV Panel	Converts solar irradiation into electrical power
02	Boost Converter	Increases PV voltage and controls power flow
03	Neural Network MPPT	Predicts maximum power point voltage
04	PO MPPT	Tracks maximum power using voltage and current variation
05	Hybrid Controller	Combines NN and PO duty cycle outputs
06	PWM Generator	Generates switching pulses for the boost converter
07	Load	Receives regulated power from the PV system

𝐏𝐕 𝐏𝐚𝐧𝐞𝐥 𝐒𝐩𝐞𝐜𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧

𝐏𝐚𝐫𝐚𝐦𝐞𝐭𝐞𝐫	𝐕𝐚𝐥𝐮𝐞
PV Panel Rating	250 W
Open Circuit Voltage	37.3 V
Voltage at Maximum Power Point	30.7 V
Short Circuit Current	8.6 A
Current at Maximum Power Point	8.1 A

𝐖𝐨𝐫𝐤𝐢𝐧𝐠 𝐏𝐫𝐨𝐜𝐞𝐬𝐬

• The 𝐏𝐕 𝐩𝐚𝐧𝐞𝐥 receives changing irradiation and temperature inputs.

• The generated PV voltage and current are measured.

• The 𝐍𝐞𝐮𝐫𝐚𝐥 𝐍𝐞𝐭𝐰𝐨𝐫𝐤 MPPT provides a duty cycle based on PV behavior.

• The 𝐏𝐎 𝐌𝐏𝐏𝐓 algorithm calculates another duty cycle using PV voltage and current changes.

• Both outputs are combined using hybrid logic.

• The final duty cycle is given to the 𝐏𝐖𝐌 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐨𝐫.

• The boost converter switching is controlled to extract maximum power from the PV panel.

𝐂𝐨𝐧𝐭𝐫𝐨𝐥 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲

The model supports different MPPT operating modes using manual selection switches.

𝐌𝐨𝐝𝐞	𝐎𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧
Hybrid NN + PO Average Mode	NN duty cycle and PO duty cycle are added and averaged
Change-in-Power Based Hybrid Mode	PO is selected when power change is high; NN is selected when power change is low
PO Only Mode	Only the PO MPPT duty cycle is applied
NN Only Mode	Only the Neural Network MPPT duty cycle is applied

𝐇𝐲𝐛𝐫𝐢𝐝 𝐒𝐞𝐥𝐞𝐜𝐭𝐢𝐨𝐧 𝐋𝐨𝐠𝐢𝐜

𝐂𝐨𝐧𝐝𝐢𝐭𝐢𝐨𝐧	𝐒𝐞𝐥𝐞𝐜𝐭𝐞𝐝 𝐌𝐏𝐏𝐓
Change in power greater than 0.02	PO MPPT
Change in power less than or equal to 0.02	Neural Network MPPT

This selection helps the controller respond properly during sudden irradiation changes while maintaining smoother power tracking during stable conditions.

𝐒𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐒𝐞𝐭𝐮𝐩

The irradiation is varied step by step to test the MPPT controller performance under different solar conditions.

𝐒𝐥. 𝐍𝐨.	𝐈𝐫𝐫𝐚𝐝𝐢𝐚𝐭𝐢𝐨𝐧	𝐏𝐕 𝐏𝐨𝐰𝐞𝐫 𝐑𝐞𝐟𝐞𝐫𝐞𝐧𝐜𝐞
01	1000 W/m²	Around 250 W
02	800 W/m²	Around 199.9 W
03	600 W/m²	Around 149.6 W
04	400 W/m²	Around 98.9 W
05	200 W/m²	Around 48 W

𝐒𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐑𝐞𝐬𝐮𝐥𝐭𝐬

The hybrid NN-PO MPPT method is tested and compared with 𝐏𝐎 𝐌𝐏𝐏𝐓 and 𝐍𝐍 𝐌𝐏𝐏𝐓.

𝐈𝐫𝐫𝐚𝐝𝐢𝐚𝐭𝐢𝐨𝐧	𝐇𝐲𝐛𝐫𝐢𝐝 𝐍𝐍-𝐏𝐎 𝐏𝐨𝐰𝐞𝐫 𝐎𝐮𝐭𝐩𝐮𝐭
1000 W/m²	Around 249 W
800 W/m²	Around 198 W
600 W/m²	Around 148 W
400 W/m²	Around 98 W
200 W/m²	Around 48 W

𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 𝐂𝐨𝐦𝐩𝐚𝐫𝐢𝐬𝐨𝐧

𝐌𝐏𝐏𝐓 𝐌𝐞𝐭𝐡𝐨𝐝	𝐎𝐛𝐬𝐞𝐫𝐯𝐞𝐝 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞
PO MPPT	Takes more time to reach the maximum power point and shows higher oscillation
NN MPPT	Reaches faster than PO, but shows more oscillation at low irradiation
Hybrid NN-PO MPPT	Provides faster tracking, reduced oscillation, and better maximum power extraction

𝐊𝐞𝐲 𝐅𝐞𝐚𝐭𝐮𝐫𝐞𝐬

• 𝐇𝐲𝐛𝐫𝐢𝐝 𝐍𝐍-𝐏𝐎 MPPT control for solar PV system

• MATLAB Simulink implementation with boost converter

• Supports 𝐍𝐍, 𝐏𝐎, and hybrid MPPT operating modes

• Tested under changing irradiation from 1000 W/m² to 200 W/m²

• Reduced oscillation compared with normal PO MPPT

• Better tracking response during irradiation variation

• Simple switching logic for MPPT mode selection

• Suitable for solar PV power electronics learning and research

𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

• Solar PV maximum power point tracking study

• MATLAB Simulink-based renewable energy analysis

• Boost converter control for PV systems

• Neural Network-based MPPT testing

• Hybrid MPPT algorithm comparison

• Power electronics controller design

• Renewable energy simulation and performance evaluation

𝐖𝐡𝐲 𝐇𝐲𝐛𝐫𝐢𝐝 𝐍𝐍-𝐏𝐎 𝐌𝐏𝐏𝐓?

The 𝐏𝐎 𝐌𝐏𝐏𝐓 method is simple and widely used, but it can show oscillation near the maximum power point. The 𝐍𝐞𝐮𝐫𝐚𝐥 𝐍𝐞𝐭𝐰𝐨𝐫𝐤 𝐌𝐏𝐏𝐓 method gives faster response, but it may have power variation under some conditions.

The 𝐇𝐲𝐛𝐫𝐢𝐝 𝐍𝐍-𝐏𝐎 𝐌𝐏𝐏𝐓 combines both methods to improve the overall tracking performance. It gives smoother operation, better transition behavior, and improved power extraction from the PV panel.

𝐒𝐄𝐎 𝐊𝐞𝐲𝐰𝐨𝐫𝐝𝐬

Hybrid NN PO MPPT MATLAB, Neural Network MPPT Simulink, Solar PV MPPT MATLAB, PO MPPT for Solar PV, Hybrid MPPT Algorithm, Boost Converter MPPT Control, MATLAB Simulink Solar PV System, Renewable Energy MPPT Simulation, Neural Network Solar PV MPPT, Solar PV Power Tracking

𝐂𝐨𝐧𝐜𝐥𝐮𝐬𝐢𝐨𝐧

The 𝐇𝐲𝐛𝐫𝐢𝐝 𝐍𝐞𝐮𝐫𝐚𝐥 𝐍𝐞𝐭𝐰𝐨𝐫𝐤 𝐏𝐎 𝐌𝐏𝐏𝐓 for Solar PV System in MATLAB is a useful model for understanding advanced MPPT control. By combining 𝐍𝐍 𝐌𝐏𝐏𝐓 and 𝐏𝐎 𝐌𝐏𝐏𝐓, the system improves tracking response and reduces oscillation under changing irradiation conditions.

This model is highly useful for students, researchers, and engineers who want to study 𝐬𝐨𝐥𝐚𝐫 𝐏𝐕 𝐩𝐨𝐰𝐞𝐫 𝐭𝐫𝐚𝐜𝐤𝐢𝐧𝐠, 𝐛𝐨𝐨𝐬𝐭 𝐜𝐨𝐧𝐯𝐞𝐫𝐭𝐞𝐫 𝐜𝐨𝐧𝐭𝐫𝐨𝐥, and 𝐢𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐭 𝐌𝐏𝐏𝐓 𝐚𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬 in MATLAB Simulink.