Continuous-time tube-based explicit model predictive control for collective pitching of wind turbines

Lasheen, Ahmed; Saad, M. S.; Emara, Hassan M.; El-Shafei, A.

doi:10.1016/j.energy.2016.11.002

Cited by 27 publications

(7 citation statements)

References 14 publications

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“…However, there exists a huge calculation burden to search for the optimal solution by enumerating all the vertices of W in the prediction horizon. Thus, an efficient tube method is incorporated to solve the min-max optimization problem (22) to reduce the calculation burden [20]. The controller is evaluated at discrete time instants t k = t 0 + k∆t, k = 0, 1, .…”

Section: Robust Mpcmentioning

confidence: 99%

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A Comparative Study of Robust MPC and Stochastic MPC of Wind Power Generation System

2022

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In this paper, a complete comparison analysis of two advanced control algorithms, namely robust model predictive control (MPC) and stochastic MPC, is performed in order to optimize the operation of a wind power generation system (WPGS). The power maximization often conflicts with the mechanical load experienced by the turbine in the full-load region (i.e., the higher the power extracted, the higher the load) under the wind speed disturbance, thereby leading to high maintenance cost resulting from the fatigue damage. Thus, a typical 5 MW wind turbine operating in a high-speed region is considered to guarantee system security and economy. The robust MPC is designed by utilizing the min–max framework to track steady-state optimum operating reference trajectory with the deterministic constraint of output power, while the stochastic MPC is constructed by incorporating the invariant set theory to also ensure the system security subjecting to the probabilistic constraint of output power. The relation between the constraints and the implications on optimal performance are also studied. Comprehensive simulations on a mechanism model and FAST simulator are carried out to demonstrate the validation of the two control methods under various scenarios. It is discovered that when wind speed in the near future can be predicted and utilized in controller design, the stochastic MPC can effectively reduce the maintenance cost by suppressing the constraint violation rate compared to robust MPC with a similar energy utilization due to the incorporation of the stochastic characteristics of wind speed.

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Section: Robust Mpcmentioning

confidence: 99%

“…Ref. [20] utilized a continuous-time robust MPC based on the tube method to ensure the robustness of a nonlinear WPGS operating above the rated wind speed.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of Robust MPC and Stochastic MPC of Wind Power Generation System

2022

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“…However, allowing for system controls is to compute the optimal control action with the advantage of using MPC. The procedure of wind energy conversion systems discrete-time MPC according to controllers has been suggested to control [97].…”

Section: Summary Of the Pitch Control Mechanism Of Vawtmentioning

confidence: 99%

Pitch Control Mechanism in Various Type of Vertical Axis Wind Turbines: A Review

Rathore

Agrawal

Baredar

2021

J. Vib. Eng. Technol.

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Purpose Due to rising interest in wind energy harvesting offshore as well as in the urban environment, vertical axis wind turbines (VAWTs) have recently received renewed interest. Their omnidirectional ability makes them a very fascinating choice for use with the frequently varying wind directions. Therefore, the main concern is reducing vibration of the turbine blade as well as wind tower, self-starting at low wind speed, and stability issues at very high wind speed for VAWT. Methods In this paper presents a detailed overview of various pitch control configurations in VAWT to avoid vibration, self-starting problem w.r.t. wind speed. Conclusion Various research work carried out in this field has been studied critically and according to the number of blades choose effective pitch control mechanism to control the vibration and rotation speed of wind turbine.

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“…For a WECS, there are many constraints that should be satisfied to ensure equipment safety of the system. Specifically, constraints Equations (7), (8) and (15) are considered as hard constraints while Equations (5), (14) and (17) can be treated as soft constraints that may be relaxed for sufficiently short time periods.…”

Section: Model Predictive Control Strategiesmentioning

confidence: 99%

“…The main objective of the feedback control layer is to drive a WECS to track the optimal reference trajectories. In the feedback control layer, different control algorithms have been explored including the classical proportional integral (PI) control [5,6], linear quadratic Gaussian (LQG) approach [7,8], robust control [9,10], and model predictive control (MPC) [11][12][13][14][15]. Among these algorithms, MPC has become more and more popular because of its ability to account for state and input constraints as well as optimality considerations explicitly in the evaluation of control actions.While the framework of MPPT and MPC has been successful, it primarily focuses on tracking the optimal operating references which are different for different operating modes (partial load and full load).…”

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confidence: 99%

A Comparative Study of MPC and Economic MPC of Wind Energy Conversion Systems

Cui

Liu

et al. 2018

Energies

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In this work, we perform a comprehensive comparative study of two advanced control algorithms-the classical tracking model predictive control (MPC) and economic MPC (EMPC)-in the optimal operation of wind energy conversion systems (WECSs). A typical 5 MW wind turbine is considered in this work. The tracking MPC is designed to track steady-state optimal operating reference trajectories determined using a maximum power point tracking (MPPT) algorithm. In the design of the tracking MPC, the entire operating region of the wind turbine is divided into four subregions depending on the wind speed. The tracking MPC tracks different optimal reference trajectories determined by the MPPT algorithm in these subregions. In the designed EMPC, a uniform economic cost function is used for the entire operating region and the division of the operating region into subregions is not needed. Two common economic performance indices of WECSs are considered in the design of the economic cost function for EMPC. The relation between the two economic performance indices and the implications of the relation on EMPC performance are also investigated. Extensive simulations are performed to show the advantages and disadvantages of the two control algorithms under different conditions. It is found that when the near future wind speed can be predicted and used in control, EMPC can improve the energy utilization by about 2% and reduce the operating cost by about 30% compared to classical tracking MPC, especially when the wind speed varies such that the tracking MPC switches between operating subregions. It is also found that uncertainty in information (e.g., future wind speed, measurement noise in wind speed) may deteriorate the performance of EMPC.Energies 2018, 11, 3127 2 of 23 capture as much energy as possible from the wind; when the WECS is operated in the full load mode, the typical control objective is to regulate the blade pitch angle to maintain both the output power and the generator speed at their rated values to ensure the safety of the equipment [2]. The operation of a WECS may switch between these two operating modes frequently due to the variation of wind speed. This poses great challenges in the controller design for WECSs.In the literature, many control strategies have been proposed for the control of WECSs with the purpose of either maximizing wind energy capture or maintaining the system at rated power. When a WECS operates in partial load mode, the maximum power point tracking (MPPT) is one of the most effective approaches for extracting energy from wind. Existing research studies primarily focus on three MPPT algorithms, namely, tip speed ratio (TSR) control, hill-climb search (HCS) control, and power signal feedback control [3,4]. In these algorithms, the optimal steady-state reference trajectories are calculated. These reference trajectories are then sent to the feedback control layer. The main objective of the feedback control layer is to drive a WECS to track the optimal reference trajectories. In the feedback control lay...

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Continuous-time tube-based explicit model predictive control for collective pitching of wind turbines

Cited by 27 publications

References 14 publications

A Comparative Study of Robust MPC and Stochastic MPC of Wind Power Generation System

A Comparative Study of Robust MPC and Stochastic MPC of Wind Power Generation System

Pitch Control Mechanism in Various Type of Vertical Axis Wind Turbines: A Review

A Comparative Study of MPC and Economic MPC of Wind Energy Conversion Systems

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