Energy capture efficiency enhancement of wind turbines via stochastic model predictive yaw control based on intelligent scenarios generation

Song, Dongran; Li, Ziqun; Wang, Lei; Jin, Fangjun; Huang, Chaoneng; Xia, Erdong; Rizk‐Allah, Rizk M.; Yang, Jian; Su, Mei; Joo, Young Hoon

doi:10.1016/j.apenergy.2022.118773

Cited by 50 publications

(16 citation statements)

References 44 publications

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“…In recent years, some improved yaw control techniques [23][24][25][26][27][28] are presented to implement the YCB of PMSG-/DFIG-based WTs DGSs in grid-connected applications. In [23], a multi-step prediction model-based advanced MPC technique is proposed for the yaw control of a horizontal-axis WT.…”

Section: Control Techniques For Yaw Control Block (Ycb)mentioning

confidence: 99%

“…To realize an improved yaw control, the finite set SMPYC is designed based on the optimal scenarios. As compared to the traditional baseline model predictive yaw control [23], the efficiency of energy capture is improved by 0.26−0.43% and the yaw time ratio is reduced by 0.35−1.58% using the proposed ISG‐based SMPYC [27]. Furthermore, it offers an improved efficiency of energy capture by 0.29% and a reduced rate of yaw time by 0.1% compared with the SMPYC using random method other than ISG.…”

Section: Control Techniques For Grid‐connected Pmsg‐ and Dfig‐based W...mentioning

confidence: 99%

“…For an accurate wind direction prediction, an ISG‐SMPYC technique is proposed in [27]. The upgraded bonobo optimizer, that is, an improved co‐evolution bonobo optimizer is used for ISG to solve the designed optimization problem.…”

Section: Control Techniques For Grid‐connected Pmsg‐ and Dfig‐based W...mentioning

confidence: 99%

“…The YCB adjusts the WT rotor direction to always face the wind in order to obtain an increased power, reduced loads under the yaw misalignment and a minimized wake effect [21,22]. In the grid-connected WTs DGSs, the YCB can be applied using the modern control techniques, such as model predictive control (MPC) [23], light detection and ranging (LIDAR)-based economic MPC (EMPC) [24], LIDAR-based two-level EMPC (TL-EMPC) [25], adaptive control [26], intelligent scenarios generation-based stochastic model predictive yaw control (ISG-SMPYC) [27] and non-linear MPC (NMPC) [28]. In the grid-connected PMSG-/DFIG-based WTs gen-eration systems, the MSC/RSC are used to control the active power (P) generated by the PMSG/DFIG, respectively [10,29].…”

Section: Introductionmentioning

confidence: 99%

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A state‐of‐the‐art comprehensive review of modern control techniques for grid‐connected wind turbines and photovoltaic arrays distributed generation systems

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This paper presents a state-of-the-art comprehensive review of the modern control techniques for the widely recommended two distributed generation systems (DGSs) using permanent magnet synchronous generator (PMSG)-and doubly-fed induction generator (DFIG)-based wind turbines (WTs) and photovoltaic (PV) arrays in grid-connected applications. The already published review papers individually study each DGS and also lack a systematic discussion on the control techniques without any suitable classification. This makes it difficult to study the comparatively improved performance of each control technique and comprehensively understand the control requirements of overall DGSs. Unlike existing literature, this paper first distinctively presents the generalized control configurations for both DGSs in the form of control blocks (CBs). Second, the modern control techniques suggested for each DGS are uniquely classified based on the CBs. Third, each CB is studied in detail considering its required control operation for the particular DGS component and recently proposed control techniques for its implementation. Furthermore, a detailed data analysis and comparative graphical illustrations are provided to appropriately study the merits and demerits of every state-of-the-art control technique. Finally, the useful future research directions are presented to realize improved hardware components and control techniques for the grid-connected WTs and PV arrays DGSs.

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Section: Control Techniques For Yaw Control Block (Ycb)mentioning

confidence: 99%

Section: Control Techniques For Grid‐connected Pmsg‐ and Dfig‐based W...mentioning

confidence: 99%

Section: Control Techniques For Grid‐connected Pmsg‐ and Dfig‐based W...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A state‐of‐the‐art comprehensive review of modern control techniques for grid‐connected wind turbines and photovoltaic arrays distributed generation systems

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show abstract

“…In [19], a multi-stage stochastic programming has been for the optimal dispatch of generation and reserve where the uncertainties have been described by a scenario tree, while the optimal network decision has been considered as a decision tree. Song et al [20] have proposed a strategy for the improvement of the energy capture efficiency of wind turbines by using a stochastic model predictive yaw control (SMPYC). To do this, the authors of this reference have described the intermittent characteristics of predicted wind direction by intelligent scenarios generation (ISG).…”

Section: Introductionmentioning

confidence: 99%

Hybrid Chaotic Maps-Based Artificial Bee Colony for Solving Wind Energy-Integrated Power Dispatch Problem

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A chance-constrained programming-based optimization model for the dynamic economic emission dispatch problem (DEED), consisting of both thermal units and wind turbines, is developed. In the proposed model, the probability of scheduled wind power (WP) is included in the set of problem-decision variables and it is determined based on the system spinning reserve and the system load at each hour of the horizon time. This new strategy avoids, on the one hand, the risk of insufficient WP at high system load demand and low spinning reserve and, on the other hand, the failure of the opportunity to properly exploit the WP at low power demand and high spinning reserve. The objective functions of the problem, which are the total production cost and emissions, are minimized using a new hybrid chaotic maps-based artificial bee colony (HCABC) under several operational constraints, such as generation capacity, system loss, ramp rate limits, and spinning reserve constraints. The effectiveness and feasibility of the suggested framework are validated on the 10-unit and 40-unit systems. Moreover, to test the robustness of the suggested HCABC algorithm, a comparative study is performed with various existing techniques.

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Non-centralised coordinated optimisation for maximising offshore wind farm power via a sparse communication architecture

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Joo³

2022

Applied Energy

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Energy capture efficiency enhancement of wind turbines via stochastic model predictive yaw control based on intelligent scenarios generation

Cited by 50 publications

References 44 publications

A state‐of‐the‐art comprehensive review of modern control techniques for grid‐connected wind turbines and photovoltaic arrays distributed generation systems

A state‐of‐the‐art comprehensive review of modern control techniques for grid‐connected wind turbines and photovoltaic arrays distributed generation systems

Hybrid Chaotic Maps-Based Artificial Bee Colony for Solving Wind Energy-Integrated Power Dispatch Problem

Non-centralised coordinated optimisation for maximising offshore wind farm power via a sparse communication architecture

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