scholarly journals A Wind Farm Active Power Dispatch Strategy Considering the Wind Turbine Power-Tracking Characteristic via Model Predictive Control

Processes ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. 530 ◽  
Author(s):  
Wei Li ◽  
Dean Kong ◽  
Qiang Xu ◽  
Xiaoyu Wang ◽  
Xiang Zhao ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Wind Turbines ◽  
Control Strategy ◽  
Wind Farm ◽  
Control Object ◽  
Automatic Generation ◽  
Active Power ◽  
Tracking Performance ◽  
Equivalent Model

In this paper, an industrial application-oriented wind farm automatic generation control strategy is proposed to stabilize the wind farm power output under power limitation conditions. A wind farm with 20 units that are connected beneath four transmission lines is the selected control object. First, the power-tracking dynamic characteristic of wind turbines is modeled as a first-order inertial model. Based on the wind farm topology, the wind turbines are grouped into four clusters to fully use the clusters’ smoothing effect. A method for frequency-domain aggregation and approximation is used to obtain the clusters’ power-tracking equivalent model. From the reported analysis, a model predictive control strategy is proposed in this paper to optimize the rapidity and stability of the power-tracking performance. In this method, the power set-point for the wind farm is dispatched to the clusters. Then, the active power control is distributed from the cluster to the wind turbines using the conventional proportional distribution strategy. Ultra-short-term wind speed prediction is also included in this paper to assess the real-time performance. The proposed strategy was tested using a simulated wind farm based on an industrial wind farm. Good power-tracking performance was achieved in several scenarios, and the results demonstrate that the performance markedly improved using the proposed strategy compared with the conventional strategy.

scholarly journals A non-centralized predictive control strategy for wind farm active power control: A wake-based partitioning approach

2020 ◽  
Vol 150 ◽  
pp. 656-669
Author(s):  
Sara Siniscalchi-Minna ◽  
Fernando D. Bianchi ◽  
Carlos Ocampo-Martinez ◽  
Jose Luis Domínguez-García ◽  
Bart De Schutter
Keyword(s):  
Power Control ◽  
Predictive Control ◽  
Control Strategy ◽  
Wind Farm ◽  
Active Power ◽  
Active Power Control

scholarly journals Active power control strategy of wind farm considering fatigue load of wind turbines

2021 ◽  
Vol 7 ◽  
pp. 1466-1476
Author(s):  
Jie Zhao ◽  
Yudi Fang ◽  
Yuqin He ◽  
Junjun Fang ◽  
Libin Wen ◽  
...  
Keyword(s):  
Power Control ◽  
Wind Turbines ◽  
Control Strategy ◽  
Wind Farm ◽  
Active Power ◽  
Fatigue Load ◽  
Active Power Control

scholarly journals The Active Frequency Control Strategy of the Wind Power Based on Model Predictive Control

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Ya-ling Chen ◽  
Yin-peng Liu ◽  
Xiao-fei Sun
Keyword(s):  
Model Predictive Control ◽  
Power Control ◽  
Wind Turbine ◽  
Output Power ◽  
Predictive Control ◽  
Wind Turbines ◽  
Control Strategy ◽  
Frequency Control ◽  
Frequency Deviation ◽  
Load Shedding

In this paper, an active frequency control strategy of wind turbines based on model predictive control is proposed by using the power margin of wind turbines operating in load shedding mode. The frequency response model of the microgrid system with the load shedding of the wind turbines is used to predict the output power and system frequency deviation of the wind turbine. According to the prediction information, the output power control signal of the model predictive controller in the wind turbine can be optimized. On this basis, a wind turbine active participation frequency control strategy based on model predictive control is designed by rolling prediction and optimization. The wind turbine power control signal after the strategy is used to adjust the output power of the wind turbine and balance the change of the active power of the system to reduce the frequency deviation.

scholarly journals Bi-Level Model Predictive Control for Optimal Coordination of Multi-Area Automatic Generation Control Units under Wind Power Integration

Processes ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. 669
Author(s):  
Xia ◽  
Liu
Keyword(s):  
Model Predictive Control ◽  
Wind Power ◽  
Predictive Control ◽  
Control Strategy ◽  
Automatic Generation ◽  
Frequency Stability ◽  
Automatic Generation Control ◽  
Level Model ◽  
Generation Control ◽  
Tie Line

With the high degree of wind power penetration integrated into multi-area AC/DC interconnected power grids, the frequency regulation capacity of automatic generation control (AGC) units is not sufficient in the wind power-penetrated area, making it difficult to effectively suppress the frequency stability caused by the fluctuation of wind power. Therefore, a coordinated control strategy for AGC units across areas based on bi-level model predictive control is proposed in this paper to achieve resource sharing. The control scheme uses economic model predictive control to realize steady power optimal allocation of the AGC units across areas in the upper layer and distributed model predictive control to realize dynamic frequency optimization control of the multi-area AGC units in the lower layer. Taking a three-area AC/DC interconnected power grid with a wind farm as an example, the simulation results show that, compared with model predictive control using tie-line frequency bias control (TBC) mode, the proposed control strategy can not only effectively maintain tie-line safety and frequency stability, but can also reduce the regulation cost of multi-area AGC units.

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