Enhanced adaptive control techniques for extracting maximum power from photovoltaic system.

Area of Science:

• Renewable Energy Systems
• Control Systems Engineering
• Power Electronics

Background:

• Photovoltaic (PV) systems require robust maximum power point tracking (MPPT) to maintain stable grid integration despite environmental fluctuations like irradiance and temperature changes.
• Conventional MPPT methods may struggle with real-time adaptation to dynamic environmental conditions, impacting overall system efficiency and reliability.

Purpose of the Study:

• To investigate and compare the performance of four adaptive MPPT controllers for grid-connected PV systems.
• To introduce and evaluate novel SP-API and SMAPA-based PI controllers for PV MPPT, alongside MRFO-optimized PID and API controllers.
• To assess the controllers' adaptability to uniform and partial shading conditions without relying on large datasets.

Main Methods:

• Implementation of four adaptive MPPT controllers: MRFO-optimized PID, API, SP-API, and SMAPA-based PI, integrated with the incremental conductance (IC) algorithm.
• Evaluation using two case studies on a grid-connected PV system: simulating daily variations and partial shading scenarios.
• Comparative analysis of controller performance based on efficiency, dynamic response, ripples, and energy losses.

Main Results:

• The SMAPA-based PI controller achieved the highest efficiency (approx. 99.8%) with minimal ripples and energy losses (approx. 0.2%).
• The SP-API controller demonstrated strong performance, closely following the SMAPA controller.
• Conventional PID and API controllers exhibited weaker dynamic responses and higher energy losses compared to the novel adaptive controllers.

Conclusions:

• SMAPA and SP-API controllers offer superior adaptability and stability for MPPT in PV systems, outperforming conventional methods.
• These novel adaptive controllers are promising for reliable grid integration of PV systems, especially under challenging environmental conditions.
• Real-time adaptation capabilities of SP-API and SMAPA eliminate the need for extensive datasets, simplifying implementation.