Power sharing enhancement through a decentralized droop-based control strategy in an islanded microgrid

Abstract

A decentralized intelligent droop-based control strategy is proposed in this paper for the enhancement of equal active and reactive power sharing in an islanded inverter-based microgrid. Droop control is mostly preferred because it does not need communication facilities for its implementation. However, the presence of different feeder impedances for the different distributed generators (DGs) in a microgrid make reactive power sharing inaccurate. Furthermore, as a result of considerable load changes and different droop characteristics for the DGs, the inverter's output voltage and frequency are altered and these in turn alter the reactive and active power sharing respectively. With these conditions, the generalized droop control (GDC) strategy fails to effectively share load reactive and active power among the DGs. In order to extenuate these challenges, this paper presents a nonlinear autoregressive exogenous neural network droop-based control (NARX-NN DBC) strategy which does not depend on the varying line impedances, droop gains for the different DGs and is less affected by fluctuating loads in the grid. A microgrid, made up of two DGs and a load is modelled in MATLAB/Simulink environment and validation of the proposed control strategy is done through many simulations. Within the simulation runtime, NARX-NN DBC yielded a maximum frequency percentage deviation of 0.46% from the nominal value of 50 Hz whereas GDC yielded 0.62%. Regarding the voltage, NARX-NN DBC gave maximum deviation of 0.026% meanwhile GDC gave 0.079% from the nominal value for 380 V. In addition, during 0.57–0.64 s with load active power demand of 4.6 kW, NARX-NN DBC registered 0.43% power sharing error whereas GDC registered 6.5%. On the other hand, during 0.57–0.64 s, with 5kVAr load power demand, NARX-NN DBC registered 0.2% whereas, GDC registered 2%. These obtained results clearly show that NARX-NN DBC strategy has a better performance compared to GDC strategy with respect to power sharing in an autonomous microgrid.