Hierarchical Model Predictive Control Strategy Based on Dynamic Active Power Dispatch for Wind Power Cluster Integration

For the volatility and intermittency of intermittent new energy like wind power, traditional dispatch model and technology are severely challenged. According to the characteristics that the prediction accuracy of wind power increases as time scale increases, this paper presents a multi-time scale active power dispatch model based on the traditional dispatch model, and proposes an active power dispatch hierarchical predicting control method on the base of model predictive control and multilevel hierarchical control during industrial control course. Finally, it gets the online rolling dispatch model and strategy for the access of intermittent energy.

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Battery energy storage sizing based on a model predictive control strategy with operational constraints to smooth the wind power

International Journal of Electrical Power & Energy Systems ◽

10.1016/j.ijepes.2019.105471 ◽

2020 ◽

Vol 115 ◽

pp. 105471 ◽

Cited By ~ 11

Author(s):

Minjian Cao ◽

Qingshan Xu ◽

Xiaoyang Qin ◽

Jilin Cai

Keyword(s):

Energy Storage ◽

Model Predictive Control ◽

Wind Power ◽

Predictive Control ◽

Control Strategy ◽

Battery Energy Storage ◽

Battery Energy ◽

Operational Constraints

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

Processes ◽

10.3390/pr7080530 ◽

2019 ◽

Vol 7 (8) ◽

pp. 530 ◽

Cited By ~ 3

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.

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Adaptive Multi-Model Switching Predictive Active Power Control Scheme for Wind Generator System

Energies ◽

10.3390/en13061329 ◽

2020 ◽

Vol 13 (6) ◽

pp. 1329 ◽

Cited By ~ 2

Author(s):

Hongwei Li ◽

Kaide Ren ◽

Shuaibing Li ◽

Haiying Dong

Keyword(s):

Power Generation ◽

Model Predictive Control ◽

Power Control ◽

Wind Power ◽

Predictive Control ◽

Control Method ◽

Measured Data ◽

Active Power ◽

Wind Power Generation ◽

Active Power Control

To deal with the randomness and uncertainty of the wind power generation process, this paper proposes the use of the clustering method to complement the multi-model predictive control algorithm for active power control. Firstly, the fuzzy clustering algorithm is adopted to classify actual measured data; then, the forgetting factor recursive least square method is used to establish the multi-model of the system as the prediction model. Secondly, the model predictive controller is designed to use the measured wind speed as disturbance, the pitch angle as the control variable, and the active power as the output. Finally, the parameters and measured data of wind generators in operation in Western China are adopted for simulation and verification. Compared to the single model prediction control method, the adaptive multi-model predictive control method can yield a much higher prediction accuracy, which can significantly eliminate the instability in the process of wind power generation.

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

Processes ◽

10.3390/pr7100669 ◽

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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