Power quality improvement of smart microgrids using EMS-based fuzzy controlled UPQC

Abstract

The prevalent power quality problems in smart microgrids and power distribution systems are voltage sag, voltage swell, and harmonic distortion. The achievement of pure sinusoidal waveform with proper magnitude and phase is currently a great research and development concern. The aim of this paper is to evaluate and mitigate the smart microgrid harmonics, voltage sag, and voltage swell throughout a 24-h cycle, taking into consideration the variation in solar power generation due to changes in irradiation received by photovoltaic cells, the variation in wind power generation due to changes in wind speed, and the variation of linear and nonlinear load profiles during the day’s cycle. The mitigation of the power quality issues manifested in current harmonics, voltage sag, and voltage swell is achieved through the implementation of a new fully fuzzy controlled unified power quality conditioner (UPQC). It is controlled by an energy management system (EMS). This paper introduces a new control system for the UPQC using full fuzzy logic control. Moreover, fuzzy control is used in current control instead of proportional integral controllers so that it has acceptable performance over a wide range of operating points. The novel approach of an EMS-connected UPQC activates the UPQC at the required time only into the grid. This approach has many benefits by increasing the UPQC lifetime. The effect of the proposed system on the aforementioned issues has been validated through simulation by MATLAB/Simulink. The results are compared with those obtained by conventional methods. The results verify the superior performance of the proposed UPQC to mitigate the problems of current total harmonic distortions, voltage sag, and voltage swell under different operating conditions during the monitoring period.

Voltage Quality Enrichment using Transformerless Dynamic Voltage Compensator based on Asymmetrical Multilevel Inverter

“…Error voltage D and Q axis as per Equations (17)(18) is converted to and quantities Equations (20)(21) by following inverse Park transformation matrix Equation ( 19)…”