Unity Power Factor Operation in Microgrid Applications Using Fuzzy Type 2 Nested Controllers

• Main Authors: Awad, H. (Author), Bayoumi, E.H.E (Author), De Santis, M. (Author), Ibrahim, A.M (Author)
• Format: Article
• Language: English
• Published: MDPI 2023
• Subjects: boost converter; Fuzzy type 2; microgrids; unity power factor
• Online Access: View Fulltext in Publisher; View in Scopus

 Featured Application: This work introduces a Fuzzy-Type-2 controller to address the issue of the low-power factor operation of microgrids. The power factor is an essential index for economic and technical operations. The proposed method can be applied to improve the power factor in microgrids using deterministic optimization to obtain the controller parameters. The issue of low-power factor operation microgrids was reported for several layouts. Although numerous power factor improvement strategies have been applied and tested, various concerns remain to be addressed such as transient performance, simplicity of implementation, and satisfying the power-quality standards. The presented research aimed to design and implement controllers that can improve the transient response of microgrids due to changes in the load demand and achieve a near-unity power factor at the AC grid side, to which the DC microgrid is connected. Due to the nonlinear nature of microgrids, as they rely on power electronics converters, a Fuzzy type 2 controller was designed, implemented, and tested. The focus was given to improving the power factor of the DC microgrids. The validation of the proposed technique was verified by comparing its performance with Fuzzy type 1 and autotuned conventional PI controllers. To achieve the set aims, two nested control loops were designed with an inner current loop and an outer voltage loop. Besides MATLAB/Simulink simulations, a 10 kHz-sampling dSPACE platform was used to implement the suggested system. Two operational scenarios were tested: (1) a step change in the DC link voltage and (2) a change in the AC load (increase and decrease) at the output of the power inverter, connected to the DC grid. The simulation and experimental results confirmed that the proposed Fuzzy type 2 controller performed better than the other two techniques regarding the dynamic response, steady-state error, and compliance with power quality standards. Conventional approaches develop controllers using a linearized model, which limits the model accuracy and ignores higher-order variability. The method employs the nonlinear model. Fuzzy type 2 can better approximate high-precision problems than Fuzzy type 1. © 2023 by the authors.