A New and Improved Sliding Mode Control Design Based on a Grey Linear Regression Model and Its Application in Pure...

Area of Science:

• Renewable Energy Systems
• Control Theory
• Power Electronics

Background:

• Sliding Mode Control (SMC) is popular for photovoltaic (PV) systems due to its robustness, but suffers from slow convergence and chattering.
• Traditional Maximum Power Point Tracking (MPPT) algorithms struggle with multi-peaked power-voltage curves caused by partial shading.
• Existing limitations in PV control can lead to suboptimal system performance and power generation.

Purpose of the Study:

• To develop a novel control strategy for PV systems that improves MPPT accuracy and sine wave quality.
• To address the limitations of conventional SMC and MPPT algorithms, particularly under partial shading conditions.
• To enhance the transient and steady-state performance of PV inverters.

Main Methods:

• Implementation of a new and improved sliding mode control (NISMC) integrated with a grey linear regression model (GLRM).
• Utilizing the GLRM for accurate prediction of global state points in PV systems.
• Employing NISMC for both MPPT and high-quality pure sine wave generation in PV inverters.

Main Results:

• The proposed GLRM-based NISMC ensures faster finite system state convergence with reduced chattering and steady-state errors.
• The strategy demonstrates superior tracking performance for inverter output voltage during steady-state and transient conditions.
• The system complies with IEEE standards for voltage sag/swell (IEEE 1159-2019) and total harmonic distortion (THD < 8% per IEEE 519-2014).

Conclusions:

• The GLRM-based NISMC effectively enhances MPPT performance and sine wave quality in PV systems.
• The proposed control strategy overcomes the limitations of traditional methods, offering improved system efficiency and stability.
• Experimental validation confirms the robustness and effectiveness of the NISMC strategy under various operating conditions.