基于果蝇-BP的风水协同发电控制
发布时间:2019-02-17 20:44
【摘要】:风电与水电在资源的季节分布上具有很强的互补性,利用水电良好的调峰调频特性,可以克服风电供应的间歇性和不稳定性,使风电与水电出力之和基本保持在一定范围之内,最终形成一个相对稳定的出力。根据风电、水电协同发电的基本原理以及研究现状,研究了风电、水电协同运行的控制方法及其局限性;为了提高协同效果,提出了将果蝇算法和BP神经网络相结合对风电、水电协同系统进行控制的方法。
[Abstract]:Wind power and hydropower are highly complementary in the seasonal distribution of resources. The intermittent and unstable supply of wind power can be overcome by using the good peak and frequency modulation characteristics of hydropower, so that the sum of wind power and hydropower output is basically kept within a certain range. Finally, a relatively stable force is formed. According to the basic principle and research status of wind power and hydropower cooperative power generation, the control method and its limitation of wind power and hydropower cooperative operation are studied. In order to improve the synergistic effect, a method of combining Drosophila algorithm and BP neural network to control wind power and hydropower cooperative system is proposed.
【作者单位】: 北京信息科技大学自动化学院电气工程系;
【基金】:北京市属高等学校高层次人才引进与培养计划项目(CIT&TCD201404126)
【分类号】:TM61
本文编号:2425572
[Abstract]:Wind power and hydropower are highly complementary in the seasonal distribution of resources. The intermittent and unstable supply of wind power can be overcome by using the good peak and frequency modulation characteristics of hydropower, so that the sum of wind power and hydropower output is basically kept within a certain range. Finally, a relatively stable force is formed. According to the basic principle and research status of wind power and hydropower cooperative power generation, the control method and its limitation of wind power and hydropower cooperative operation are studied. In order to improve the synergistic effect, a method of combining Drosophila algorithm and BP neural network to control wind power and hydropower cooperative system is proposed.
【作者单位】: 北京信息科技大学自动化学院电气工程系;
【基金】:北京市属高等学校高层次人才引进与培养计划项目(CIT&TCD201404126)
【分类号】:TM61
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