Robust Predictive Control Scheme for Permanent-Magnet Synchronous Generators Based Modern Wind Turbines

Abstract

In this article, a deadbeat predictive control (DB-PC) strategy for permanent-magnet synchronous generators (PMSGs)-based modern wind turbines is proposed. The main advantages of the DB-PC technique are its excellent dynamics and its constant switching frequency. However, the main idea of DB-PC is obtaining the actuation voltage for the next sample from the mathematical model of the generator. Therefore, the DB-PC is highly sensitive to mismatches in the parameters of the PMSG. In order to obviate this problem, a disturbance estimator (extended Kalman filter (EKF)) is employed in this work to enhance the robustness of the proposed DB-PC scheme by estimating the total disturbance due to parameter mismatches and adding it to the calculation of the actuation voltage. Furthermore, the same EKF observe the rotor speed and position of the PMSG, i.e., mechanical sensors are not required. Moreover, the EKF is able to reduce the harmonic distortion in the stator currents of the PMSG. The proposed DB-PC strategy is implemented in the laboratory. The experimental results proved the superiority of the proposed DB-PC strategy over the traditional DB-PC technique.

Wind energy conversion technologies and engineering approaches to enhancing wind power generation: A review

“…The step-up transformer can be avoided in PMSG WECSs by adjusting the power converters at a MV scale. In general, the main advantages and disadvantages of the full-scale power converter PMSG technologies are the following [ 8 , 9 , 59 , 60 , 94 ]: Outperforming energy harvesting efficiency and no fatigue load on mechanical subsystems due to implementation of full-load (0–100%) application. Autonomous real and reactive power regulation help to maintain outstanding FRT capability.…”

“…For instance, a wind farm model with unspecified number of turbines was studied to maximize its power production based on the optimization of blade pitch angle and tip speed ratio by researcher in [ 61 ], and power maximization of 0.4–1.4% was reported. Similarly, DFIG, and PMSG turbine technologies-based power maximization were independently studied in [ 161 ] and [ 60 ] with different layout models, where power production of 2% and 20% were claimed to be maximized respectively. Furthermore, axial induction factor [ 162 ], and yaw angle –and– blade pitch angle [ 163 ] were considered to be optimized as the control inputs in aiming to maximize the power production of two wind farms with different layout models, and varying scales and ranges of increments indicating 2–8% and 30.4–33.2% were respectively reported to be achieved.…”

“…Furthermore, the fusions could also possibly be made between soft and soft controls, whereas the hard and soft combinations were characterized in some studies [ 57 , 58 ] as more efficient strategies. Similarly, model-based predictive control (MBPC) was prevalently demonstrated by the recent research works [ 59 , 60 , 61 ] as the advanced strategy having appealing features, which can be utilized to develop efficient and cost-effective power smoothing system. In general, the ultimate goal of implementing these strategies (including hybrid and MBPC) are to establish the stringent power control systems that eventually meet advanced operation requirements (power reliability, FRT capability, maximum power production, overall cost optimization) for WECS technologies.…”

Convergence analysis of nonlinear model predictive control based on fractional Hammerstein model

“…The intermediate signal ỹ(k), which is usually assumed to The nonlinearity f (.) is usually represented by a polynomial expression (6).…”

“…In the last decades, NMPC is considered one of the most successful control schemes. It coped in several areas such as thermal [1] [2], hydraulic [3] [4], mechanical [5] [6]. However, Its application is still limited because of the inaccuracy of the models.…”