UPQC with Model Predictive Control Implementation

In this paper, we explore the implementation of Unified Power Quality Conditioner (UPQC) using Model Predictive Control (MPC) methodology, providing detailed analysis and technical insights. UPQC represents an advanced power quality controller that integrates both voltage and current regulation capabilities, featuring broad application domains in power systems. The control algorithm for UPQC requires sophisticated techniques and advanced computational capabilities, hence we focus on the application of Model Predictive Control to enhance UPQC's performance and control precision. From an implementation perspective, MPC employs a receding horizon optimization approach where the control system predicts future system behavior over a finite horizon and computes optimal control actions by solving quadratic programming problems at each sampling interval. We will discuss UPQC's operational principles, including its role and applications in power grids. The implementation typically involves discrete-time modeling of power converters, where the MPC controller calculates optimal switching states for voltage source converters (VSCs) by minimizing cost functions that incorporate reference tracking errors and switching frequency constraints. Key functions include grid synchronization algorithms using phase-locked loops (PLLs), voltage/current reference generation, and constraint handling for safe operation of power semiconductor devices. Through reading this paper, you will gain deeper understanding of UPQC control methodologies and the working principles of power quality conditioning, with practical insights into real-time implementation aspects such as processor selection for MPC computation, sampling rate determination, and anti-windup strategies for actuator saturation scenarios.