Open AccessA finite time adaptive back‐stepping sliding mode control for instantaneous active‐reactive power dynamics based DFIG‐wind generation towards improved grid stability
Author(s) -
Parida Tanmoy,
Dhar Snehamoy,
Nayak Niranjan
Publication year - 2020
Publication title -
wind energy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.743
H-Index - 92
eISSN - 1099-1824
pISSN - 1095-4244
DOI - 10.1002/we.2557
Subject(s) - control theory (sociology) , backstepping , controller (irrigation) , wind power , microgrid , islanding , ac power , terminal sliding mode , grid , engineering , distributed generation , computer science , control engineering , sliding mode control , adaptive control , nonlinear system , voltage , mathematics , renewable energy , control (management) , geometry , electrical engineering , artificial intelligence , agronomy , biology , physics , quantum mechanics
Abstract In this paper, a low computational, robust nonlinear feedback control is proposed as independent distributed generation controller (IDGC) for doubly fed induction generator (DFIG) based wind power generation system (WPGS). WPGS integration as distributed generation (DG) to grid point of common coupling (PCC) is reflecting high power loss profile in terms of low frequency oscillations under grid operational contingencies and have high instability hazard under unbounded uncertainties like unintentional islanding operation. Thus, to improve the stability margin of DFIG‐WPGS integration fast DG dynamic relations are obtained, where instantaneous active‐reactive power ( P ‐ Q ) formulation is proposed to avoid unnecessary phase locked loop (PLL) angle (ω) estimation. The feedback path is designed with proposed finite time adaptive backstepping sliding mode control (FTABSMC) for IDGC operation according to ISA‐95 standards. The FTABSMC is ensured with bounded/unbounded uncertainty handling capability by incorporating backstepping based dynamic error profile depletion and with enhanced stability margin by finite time sliding surface based error trajectory to equilibrium. Further, the adaptive sliding surface estimation is proposed in terms of dynamic uncertainty (energy fluctuation) for robust unbounded uncertainty handling. The stability improvement is established with small‐signal (SS) based closed loop analysis of considered DFIG‐WPGS. The uncertainty handling capability is presented thought rigorous case studies in MATLAB based simulation environment and TMS 320 digital signal processor (DSP) based processor‐in‐loop (PIL) validation.