Control measures for ancillary services in microgrids with renewable energy resources

Increased integration of renewable resources with high variability poses unique challenges to the reliable and secure operation of microgrids, namely: (a) flicker and voltage fluctuations and (b) frequency deviations. This dissertation deals with the development of control measures for ancillary services in microgrids with renewable energy resources and concentrates on reactive power/voltage control and frequency regulation in microgrids with substantial wind generation. The proposed research and results of the simulations are presented in five separate papers as follows:;The first paper addresses the frequency deviations produced by variations in generated wind power by the addition of a small supercapacitor at the DC link of a doubly fed induction generator (DFIG). The proposed method investigates the power variations in the range of 0.1--1 Hz and simultaneously balances the maximum power point tracking as well as output power smoothing objectives.;The second paper proposes a novel reactive power control strategy for DFIG wind systems by coordinating the grid and rotor side converters. The central idea is to derive the generator reactive power reference signal from the grid side converter control loop and to eliminate internal reactive power loops.;The last three papers address the issue of voltage regulation noted in IEEE-1547. The third paper proposes a voltage sensitivity based scheme to achieve voltage regulation in microgrids. The proposed method is local and can be implemented without any interference with other devices.;The performance of the classical control of DFIG wind systems is based on the decoupled proportional-integral (PI) control loops which can be degraded by uncertainties. The fourth and fifth papers employ a nonlinear sliding mode control scheme and directly control the output power of a DFIG wind system.;The performance of the proposed methods is illustrated on the IEEE-13 bus distribution network. Dynamic models are considered for the DFIG, converters and internal controllers. Stochastic fluctuations in wind speed are modeled with NREL Turbsim while accounting for tower shadow and wind shear. Dynamic simulations (in PSCAD/EMTDC and Matlab/Simulink) are presented to assess the performance of the proposed control systems with limiting frequency deviation, voltage fluctuation compensation and control system robustness.