Nonlinear Load Sharing and Voltage Compensation of Microgrids Based on Harmonic Power-Flow Calculations Using Radial Basis Function Neural Networks

Abstract

A new decentralized hierarchical control scheme is presented to improve power sharing of multidistributed energy resources microgrids including nonlinear and sensitive loads. In this systems, electronically coupled distributed energy resources are responsible to perform the compensation to reduce the voltage harmonics at the point-of-common coupling. The proposed control scheme adds a new virtual impedance scheme, power calculation unit, and also a complementary loop to improve small- and large-signal stability margins and includes detailed modeling for all hierarchical control levels (either for grid-connected or islanded modes). Compared to conventional virtual impedance methods that add only line current feedforward terms to the voltage reference, here, the line current and voltage at the point-of-common coupling regulate the virtual impedance at fundamental and harmonic frequencies, respectively. So, mismatches in the feeder and line impedances are compensated. Moreover, a power calculation method based on harmonic power flow is presented, which exploits the nonlinear mapping ability of radial basis function neural networks to solve harmonic power flow and obtain voltage harmonics and active and reactive powers. To show the effectiveness of the proposed control scheme, offline time-domain simulation studies have been done on a test microgrid by MATLAB/SIMULINK software and verified experimentally using OPAL-RT real-time digital simulator.