Abstract
With the real-time changes of wind speed and operating conditions, it is a challenge to fully tap the active power regulation ability and improve the control performance of automatic generation control (AGC) in a wind farm (WF). The essence of tapping the active power regulation ability is to realise the coordination and complementarity of each wind turbine's (WT's) dynamic adjustment performance (DAP). To address this, a novel data mining method is developed to derive the internal relations between WTs’ output power and pitch angle, impeller speed and pitch angle during the power adjustment process, and a unified mechanism model is established to describe DAP of WTs. Based on the discovered relationship between WTs’ DAP and its operating states, an active power distribution algorithm and a dynamic interval control method are proposed. Then, an active power dynamic interval control strategy that has been implemented using Java script in MyEclipse for WFs is further developed. The control strategy has been tested and applied in a 50 MW WF in northwest China. The preliminary results showed that the control strategy has improved the rapidity and accuracy of AGC in the WF.
Highlights
According to the Global Wind Energy Council, the total global capacity of wind energy was over 651 GW in 2019, an increase of 10 percent compared with 2018, and the average growth rate of wind power capacity is expected to exceed 10% in the five years [1]
Compared with the fixed interval control method (FICM) and non-interval control method (N-ICM), the proposed method can improve the accuracy of the output power of a wind farm (WF) and reduce frequent adjustment of wind turbines (WTs)
For a WF responding to automatic generation control (AGC), firstly, the control sequence of the controlled WTs is determined by selecting WTs with excellent dynamic adjustment performance (DAP) to participate in this power adjustment; Secondly, an active power distribution algorithm is designed to distribute the power adjustment amount of a WF to each controlled WT in a different way, and form a power command to send to the controlled WT; an active power control strategy for a WF is designed, determining in real time whether the output power of the WF has been adjusted into the dynamic control interval and updating the output power adjustment amount of the WF in real time
Summary
According to the Global Wind Energy Council, the total global capacity of wind energy was over 651 GW in 2019, an increase of 10 percent compared with 2018, and the average growth rate of wind power capacity is expected to exceed 10% in the five years [1]. The above control strategies have a few drawbacks They do not have conducted a comprehensive system research on the law of the WTs’ DAP changing with operating states, which causes WTs’ power command mismatching its own adjustment performance and a long response time for WF to respond to AGC command. Compared with the fixed interval control method (FICM) and non-interval control method (N-ICM), the proposed method can improve the accuracy of the output power of a WF and reduce frequent adjustment of WTs. The rest of this paper is organized as follows: Section 2 introduces a WT’s DAP research method, and introduces how to mine the dynamic characteristics of WTs’ DAP from actual operating data.
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