Abstract
The wind turbine’s operation is affected by the wind speed variations, which cannot be followed by the wind turbine due to the large moment of the power plant’s inertia. The method proposed in this paper belongs to the wind turbine power curves (WTPC) approach, which expresses the power curve of the permanent magnet synchronous generator (PMSG) by a set of mathematical equations. The WTPC research papers published before now have not taken into consideration the total power plant inertia at time-variable wind speeds, when the wind turbine’s optimal operation is very difficult to be reached, and its efficiency is thus threatened. The study is based on a wind turbine having a large moment of total inertia, and demonstrates, through extensive simulation results, that the optimal values of the PMSG’s power can be determined based on the kinetic motion equation. This PMSG’s optimal power represents an ideal time-varying curve, and the wind turbine should be controlled so as to closely follow it. For this purpose, proportional integral (PI) and proportional integral derivative (PID) type-based control methods were implemented and analyzed, so that the PMSG’s power oscillations could be reduced, and the PMSG’s angular speed value made comparable to the optimal one, meaning that the wind turbine operates within the optimal operation area, and is efficient. The simulations are actually the numerical solutions obtained by using the Scientific Workplace simulation environment, and they are based on the wind speed measurements collected from a wind farm located in Dobrogea, Romania.
Highlights
Renewable energy has become a very important research area during the last few decades, and wind farms are a resource-efficient option for generating electric energy
The main drawback, though, is that the wind resources are affected by wind volatility, and sudden wind speed variations lead to the unstable operation of the wind turbine [1]
The wind speed is a time-varying function, and in order to operate within the optimal area from the energy point of view, the angular speed of the permanent magnet synchronous generator (PMSG) must follow the wind speed variation in time, because the PMSG’s optimal angular speed is directly proportional to the wind speed value, as was shown in [3]
Summary
Renewable energy has become a very important research area during the last few decades, and wind farms are a resource-efficient option for generating electric energy. A number of methods have been proposed in the literature for WTPC modelling, as follows: parametric models, parameter estimation, data preprocessing, evaluation of model, and nonparametric models (i.e., the artificial neural networks method and the fuzzy logic method, this one being used when the data collected from the wind farms is voluminous, and usually contains errors). Determination of the coefficients of these equations requires fitting the data to the mathematical model [13] All these methods, PSF, OT, TSR, P&O, artificial intelligence techniques and WTPC, at some level fail in the proper detection of the maximum power point. A list containing the main variables used in this paper is provided by Table A2 in Appendix
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