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

Author:

Awad Hilmy1,Ibrahim Amr M.2,De Santis Michele3ORCID,Bayoumi Ehab H. E.4

Affiliation:

1. Department of Electrical Technology, Faculty of Technology and Education, Helwan University, Cairo 11715, Egypt

2. Department of Electrical Power and Machines Engineering, Ain Shams University, Cairo 11517, Egypt

3. Department of Engineering, Niccolò Cusano University, 00166 Roma, Italy

4. Department of Mechanical Engineering, Faculty of Engineering, The British University in Egypt (BUE), El Sherouk, Cairo 11837, Egypt

Abstract

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.

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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