Set-based Anomaly Detection and Interpolating Predictive Regulation of UPQC for Power Distribution Quality Improvement

This paper investigates the monitoring and predictive control of unified power quality conditioner to improve power quality in a power distribution system. The proposed strategy is composed of a set-based anomaly monitoring method and an interpolating predictive regulation method. The novelty of such strategy consists of two aspects. On the one hand, the set-based anomaly monitoring scheme features a user-defined output observation set given to characterize the different severity levels of harmonic effects that the user can tolerate. On the other hand, a linear constrained linear programming control method based on interpolation optimization is designed to achieve fast predictive regulation of unified power quality conditioner. Simulation studies on a single-phase power distribution system are given to validate that the proposed strategy is able to guarantee the quality of power distribution, whether the supply voltage/load current has harmonics or sags/swells problems.