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Robust estimation based nonlinear higher order sliding mode control strategies for PMSG-WECS

Nazir Awais, Khan Safdar Abbas, Khan Malak Adnan, Alam Zaheer, Khan Imran, Irfan Muhammad, Rehman Saifur, Nowakowski Grzegorz

Bulletin of the Polish Academy of Sciences. Technical Sciences

2023

Vol. 71, nr 5

art. no. e147063

The wind energy conversion systems (WECS) suffer from an intermittent nature of source (wind) and the resulting disparity between power generation and electricity demand. Thus, WECS are required to be operated at maximum power point (MPP). This research paper addresses a sophisticated MPP tracking (MPPT) strategy to ensure optimum (maximum) power out of the WECS despite environmental (wind) variations. This study considers a WECS (fixed pitch, 3KW, variable speed) coupled with a permanent magnet synchronous generator (PMSG) and proposes three sliding mode control (SMC) based MPPT schemes, a conventional first order SMC (FOSMC), an integral back-stepping-based SMC (IBSMC) and a super-twisting reachability-based SMC, for maximizing the power output. However, the efficacy of MPPT/control schemes rely on availability of system parameters especially, uncertain/nonlinear dynamics and aerodynamic terms, which are not commonly accessible in practice. As a remedy, an off-line artificial function-fitting neural network (ANN) based on Levenberg-Marquardt algorithm is employed to enhance the performance and robustness of MPPT/control scheme by effectively imitating the uncertain/nonlinear drift terms in the control input pathways. Furthermore, the speed and missing derivative of a generator shaft are determined using a high-gain observer (HGO). Finally, a comparison is made among the stated strategies subjected to stochastic and deterministic wind speed profiles. Extensive MATLAB/Simulink simulations assess the effectiveness of the suggested approaches.

A new fuzzy design for switching gain adaptation of sliding mode controller for a wind energy conversion system using a doubly fed induction generator

Horch Mohamed, Chemidi Abdelkarim, Baghli Lotfi, Kadi Sara

Archives of Electrical Engineering

2023

Vol. 72, nr 1

273--291

The paper proposes a newrobust fuzzy gain adaptation of the sliding mode (SMC) power control strategy for the wind energy conversion system (WECS), based on a doubly fed induction generator (DFIG), to maximize the power extracted from the wind turbine (WT). The sliding mode controller can deal with any wind speed, ingrained nonlinearities in the system, external disturbances and model uncertainties, yet the chattering phenomenon that characterizes classical SMC can be destructive. This problem is suitably lessened by adopting adaptive fuzzy-SMC. For this proposed approach, the adaptive switching gains are adjusted by a supervisory fuzzy logic system, so the chattering impact is avoided. Moreover, the vector control of the DFIG as well as the presented one have been used to achieve the control of reactive and active power of the WECS to make the wind turbine adaptable to diverse constraints. Several numerical simulations are performed to assess the performance of the proposed control scheme. The results show robustness against parameter variations, excellent response characteristics with a reduced chattering phenomenon as compared with classical SMC.

Evaluation of wind energy potential for four sites in Ireland using the Weibull distribution model

Jamdade P. G., Jamdade S. G.

Journal of Power Technologies

2015

Vol. 95, nr 1

48--53

Wind speed is receiving greater attention in the design and study of wind energy conversion systems (WECS). Using meteorological data, this paper studies the availability of wind energy potential at four sites in Ireland: Malin Head, Dublin Airport, Belmullet and Mullingar. An analysis is made of mean wind speed data collected at a height of 50 m above ground level at each site over a period of seven years. A two parameter Weibull distribution model is used to analyze wind speed pattern variations. Weibull parameters are calculated by the Least Squares Method (LSM). The results relating to wind energy potential are given in terms of the density function. Analysis shows that coastal sites of Ireland such as Malin Head, Dublin Airport and Belmullet have good wind power potential.