现有风电机群一次调频控制算法存在风速突变时能量过支撑导致风电机组功率跌落甚至脱网、抗扰动性能差、控制误差大等问题,难以满足电网超快速强补惯量支撑的高标准要求。为针对性解决上述问题,在对大量风电场历史数据进行分析基础上,提出一种防能量过支撑高精度高可靠优化控制算法。首先,提出一种尖峰识别算法,提前识别与预防能量过支撑问题;其次,给出一种渐进变长步进算法,以提升抗扰动性;然后,采用一种自适应动态补偿算法,提高系统的控制精度;最后,将本文算法应用于湖南某代表性山地风电机群进行控制。现场实际应用效果表明,使用该文算法后,系统未出现功率大范围跌落与脱网问题,抗扰动性能明显得到改善,控制精度在0.5%以内,远高于测试标准要求。该文提出的风电机群一次调频优化控制算法显著提高了风电机群的并网稳定性、安全性、抗扰动性。
Abstract
When the primary frequency control modulation applies the traditional control algorithm to control the existing wind groups, there are problems such as over-supporting of energy during sudden changes in wind speed leading to wind turbines power drop or even off-grid, poor anti-disturbance performance, and large control errors, making it difficult to meet the grid ultra-fast and strong complementary inertia support of the high standard requirements. In order to solve the above problems, based on the analysis of a large number of wind groups of historical data, this article proposes an anti-energy over-support high-precision and high-reliability optimization control algorithm. Firstly, a spike identification algorithm is proposed to identify and prevent the energy over-support problem in advance. Secondly, an asymptotic variable-length stepping algorithm is given to improve the perturbation resistance. Then an adaptive dynamic compensation algorithm is adopted to improve the control accuracy of the system. Finally, the algorithm is applied to control a representative wind groups in a mountainous area of Hunan province. The actual application results show that after using the algorithm in this article, the system does not appear power fall and off-grid problems, the anti-disturbance performance has been significantly improved, and the control accuracy is within 0.5%, which is much higher than the test standard requirements. The optimized control algorithm of wind groups electric primary frequency regulation proposed in this article significantly improves the grid stability, safety and disturbance rejection of wind groups.
关键词
一次调频 /
风电机群 /
控制算法 /
防能量过支撑 /
控制精度
Key words
primary frequency modulation /
wind groups /
control algorithms /
anti-energy over-support /
control accuracy
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基金
国家重点研发计划（2022YFF0608703）; 石家庄市科技支撑计划（2410604501）
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