A New and Improved Sliding Mode Control Design Based on a Grey Linear Regression Model and Its Application in Pure Sine Wave Inverters for Photovoltaic Energy Conversion Systems

A new and improved sliding mode control (NISMC) with a grey linear regression model (GLRM) facilitates the development of high-quality pure sine wave inverters in photovoltaic (PV) energy conversion systems. SMCs are resistant to variations in internal parameters and external load disturbances, resulting in their popularity in PV power generation. However, SMCs experience a slow convergence time for system states, and they may cause chattering. These limitations can result in subpar transient and steady-state performance of the PV system. Furthermore, partial shading frequently yields a multi-peaked power-voltage curve for solar panels that diminishes power generation. A traditional maximum power point tracking (MPPT) algorithm in such a case misclassifies and fail to locate the global extremes. This paper suggests a GLRM-based NISMC for performing MPPT and generating a high-quality sine wave to overcome the above issues. The NISMC ensures a faster finite system state convergence along with reduced chattering and steady-state errors. The GLRM represents an enhancement of the standard grey model, enabling greater accuracy in predicting global state points. Simulations and experiments validate that the proposed strategy gives better tracking performance of the inverter output voltage during both steady state and transient tests. Under abrupt load changing, the proposed inverter voltage sag is constrained to 10% to 90% of the nominal value and the voltage swell is limited within 10% of the nominal value, complying with the IEEE (Institute of Electrical and Electronics Engineers) 1159-2019 standard. Under rectified loading, the proposed inverter satisfies the IEEE 519-2014 standard to limit the voltage total harmonic distortion (THD) to below 8%.