Performance Enhancement of Power Converters for PV-Based Microgrid using Model Predictive Control

Abstract

PV-based renewable energy systems are integrated in microgrids (MGs) throughout power electronic converters. During external disturbances of abrupt load variation and PV generation fluctuation, controllers play the most key role in regulating the system performance. In this paper, a proposed combination control method of model predictive control (MPC) and sliding mode control (SMC) for moderating the power converters is presented. The interlinking inverter is controlled via applying MPC while DC-DC converter is controlled by SMC. MPC is well known as most reliable and modern approach for non-linear systems to compensate noise and handle modeling inaccuracies for efficient load voltage profile. On the other hand, SMC is considered as the most stable controller with highly robust operation for DC-DC converters. Intermittency nature of renewable energy systems and abrupt load variation have a severe impact on load voltage quality. Keeping in view the sophisticated control attributes of MPC and SMC, inner and outer control loops with primary droop control are designed for interlinking converter by using MPC while SMC is designed for the DC-DC boost converter. Controller performance is analyzed through simulations with fluctuating generation, and variable loads. Unlike conventional cascaded PI controller, proposed MPC strategy is simple, robust with fast dynamic response.