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Research on multi time scale active power optimal scheduling strategy of wind power cluster based on model predictive control
Lu Peng, Ye Lin, Tang Yong, Zhang Cihang, Zhong Wuzhi, sun baohao, Zhai bingxu, Qu Ying, Liu Xinyuan doi: 10.13334/j.0258-8013.pcsee.190188
One
The background of the project is large-scale and cluster wind power development and grid connection, which brings great challenges to the safe and economic operation of the power system. In order to better cope with the impact of the randomness and volatility of wind power on the active power balance of the system, based on the wind power prediction information, it has become an urgent problem to develop a refined active power scheduling scheme of wind power cluster.
Two
The problems and significance of this paper are as follows: (1) the accuracy of active power prediction of wind power cluster is low. The prediction accuracy of active power of wind power cluster can not meet the requirements of fine scheduling of active power; (2) the deviation of active power scheduling of wind power cluster is large. At present, the fixed proportion power allocation method adopted by wind power cluster will bring deviation to multi time scale "synchronous" and "asynchronous" scheduling, and affect the fine scheduling level of active power of wind power cluster. The so-called synchronous scheduling is that the active power up and down scheduling instructions are consistent with the trend of wind farm output power up and down; asynchronous scheduling is just the opposite of synchronous scheduling.
Three
The main content of this paper is to establish the trend set of the output power of the wind power cluster based on the combined prediction of the variable weight of the active power of the wind power cluster, to formulate the dynamic clustering strategy of the active power of the wind power cluster, to give the priority order of the active power output of the wind power cluster, to control the active power of the wind power cluster in the way of "synchronous" scheduling and "asynchronous" scheduling, and to fine schedule the wind power cluster Control provides decision information.
In the pre dispatch stage, the active power of wind power is used as the scheduling object, and the active power dispatching plan of the wind turbine cluster is established at the early stage with a time resolution of 1H. Based on the predictive value of the active power of the wind power cluster, considering the output power characteristics of the wind power cluster and the output power constraints of the tie line, with the goal of maximizing the absorption of wind power, the active power of the wind power cluster in each period is optimized, and the hourly generation plan value is formulated to reach the wind power dispatching center.
In the daily rolling scheduling stage, the active power scheduling plan of wind power cluster in the next day is made every 1H, the implementation optimization period is 1H, and the resolution of sampling point is 15min. Based on the ultra short term power value of wind power cluster, a rolling scheduling strategy for the active power of wind power cluster in the day is established to track the minimum deviation of the daily plan value, and the output power of wind power cluster is calculated.
In the real-time correction stage, based on the daily hourly scheduling plan and considering the active power fluctuation error, the output active power of wind power cluster is corrected once every 5min, and the optimized time domain is 15min.
The overall idea of this paper is shown in Figure 1.
Figure 1 multi time scale active power optimization scheduling block diagram of wind power cluster based on model predictive control
When the output power of wind power is greater than the planned value, the dispatching center will not expect the wind power cluster to output more active power. If the active power is forced to adjust, the reverse regulation of power will occur. On the one hand, the fluctuation of output power will be increased, on the other hand, the deviation of active power command will be caused 。
When the output power value of the wind power cluster is less than the scheduling plan value, the scheduling Department expects the wind power cluster to increase the active power of the wind power. At this time, if the active power of the wind power cluster shows a downward trend, it can not keep up with the upward order of the scheduling plan at the same time. If the upward order is enforced, it is bound to cause the loss of the generation index of the wind power cluster. In order to avoid the above situation, it is necessary to adjust the upward priority Wind power cluster with group changing trend. Considering the output power characteristics of wind power cluster, the synchronous asynchronous strategy of wind power cluster power change trend is established, and the priority of active power scheduling of wind power cluster is divided. Table 1 shows the division results.
Table 1 dynamic clustering output power priority of synchronous asynchronous scheduling mode
When the predicted output power of the ultra short term wind power cluster is greater than the scheduled value, it can be seen from Figure 2 that the model predictive control (MPC The scheduling mode of control (MPC) is stable, because the MPC scheduling method takes into account the prediction information of the power output of the ultra short term wind power cluster. On the other hand, it optimizes the fluctuation of the active power daily dispatching plan of the wind power cluster effectively by rolling optimization and error feedback correction, and improves the stationarity of the active power output.
Figure 2 active power of wind power cluster when ultra short term forecast value is greater than dispatching value
When the predicted value of the output power of the ultra short term wind power cluster is less than the scheduled value, the wind farm operates in the "maximum power tracking mode" to meet the scheduling needs. It can be seen from Figure 3 that the MPC based scheduling strategy can also track the planned value well when the predicted power value of the whole ultra short term wind power cluster is less than the scheduled value, and this method has significant advantages.
Fig. 3 wind power cluster active power when the ultra short term forecast value is less than the dispatching value
Four
Conclusion (1) in order to reduce the deviation between the predictive value of active power and the scheduling value of wind power cluster, an optimal scheduling method based on model predictive control is proposed.
(2) The synchronous asynchronous scheduling mode is established, the trend set of active power change is constructed, and the dynamic clustering strategy of active power of wind power cluster is formulated, which makes the active power scheduling mode of wind power plant more reasonable and refined.
(3) Based on the MPC rolling optimization strategy, the change of active power of wind power cluster is transformed into control variable, and the measured value is used for feedback correction to smooth the scheduling results, which is conducive to reduce the impact of wind power uncertainty on active power scheduling.
Citation information
Lu Peng, Ye Lin, Tang Yong, et al. Research on multi time scale active power optimal scheduling strategy of wind power cluster based on model predictive control [J]. Journal of China Electrical Engineering, 2019, 39 (22): 6572-6582
LU Peng, YE Lin, TANG Yong，et al. Multi-time Scale Active Power Optimal Dispatch in Wind Power Cluster Based on Model Predictive Control[J]. Proceedings of the CSEE, 2019，39 (22): 6572-6582 (in Chinese)．
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Author brief introduction
The power system operation and control team led by Professor Ye Lin of China Agricultural University is mainly engaged in power system automation, power grid security and stability analysis considering large-scale wind power / solar energy access, new energy power prediction and spatio-temporal correlation algorithm, active power control strategy of regional wind farms based on power prediction information, electromagnetic transient modeling and real-time simulation of power systems and regions Scientific research work in the field of wind power resource refinement assessment. In recent years, he has presided over more than 30 research projects of the National Natural Science Foundation of China, key research projects of science and technology of the Ministry of education, doctoral program of the Ministry of Education (Doctoral Program), Huo Yingdong Young Teacher Award (Fund), research projects of the Beijing Natural Science Foundation, science and technology projects of the headquarters of the State Grid Corporation, etc, Participated in 2 national key R & D Program projects, published high-level research papers in top academic journals at home and abroad, 36 papers were included in SCI, 83 papers were included in EI, 19 national invention patents and 39 computer software copyrights were authorized, and 6 provincial and ministerial science and technology awards were obtained.
Lu Peng (1989), male, Ph.D. candidate, mainly engaged in power system operation and control, new energy power generation technology, participated in one research project of NSFC, one national key R & D plan project and one science and technology project of headquarters of State Grid Corporation of home appliances as main personnel, published more than 10 papers and applied for three invention patents.
Ye Lin (1968), male, Humboldt scholar of Germany, excellent talents of the Ministry of education in the new century, winner of Huo Yingdong Youth Fund (priority funding), the first leading professor and doctoral supervisor in the field of electrical engineering of China Agricultural University, with research direction of power system automation and new energy power generation technology. From 2000 to 2003, he was engaged in scientific research in the University of Karlsruhe (Kit), Germany, and from 2004 to 2007, he worked in the engineering department / Cavendish Laboratory of Cambridge University, UK. In recent years, he has successively presided over 6 research projects of the National Natural Science Foundation of China (including 1 NSFC British Royal Society RS international cooperation and exchange fund project), 2 national key R & D Program projects, key research projects of science and technology of the Ministry of education, Doctoral Program Fund (Doctoral Program) of the Ministry of education, Huo Yingdong Young Teacher Award (Fund) project and Beijing Natural Science Fund More than 30 research projects and science and technology projects of the headquarters of State Grid Corporation of China. In recent years, IEEE Transactions on power systems, IEEE Transactions on smart grid, IEEE Transactions on sustainable energy, applied energy, renewable Energy, China Journal of electrical engineering, power system automation, power grid technology and other top academic journals at home and abroad published high-level research papers, which were included in 26 SCI papers, 63 EI papers, 15 national invention patents and 39 computer software copyrights. As the editorial board member of power system automation, power system protection and control, power and energy progress, power engineering technology, protection & control of modern power systems, UK IOP engineering research express, UK IET energy systems integration and other journals. In 2000, he was awarded by Alexander von Humboldt Stiftung / foundation, the highest honor of the German government (Humboldt scholar in Germany); in 2008, he was selected into the New Century Excellent Talents funding plan of the Ministry of education; he was awarded the second prize of the 2012 excellent achievement award of scientific research (science and Technology) Natural Science Award of the Ministry of education and the second prize of 2019 China Electric Power Science and technology progress.
Editor in charge: Qiu Liping
Reviewed by: Qiao Baoyu
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