基于快速核学习的新能源高渗透电网频率风险评估
TM712; 新能源高渗透电网在功率扰动后,频率响应轨迹更容易呈现出频率偏差大和变化速率高的特性,导致频率保护动作受到明显影响.为准确预测强随机运行方式下的系统频率响应特性,利用基于核矩阵广义逆运算的快速核学习算法,结合共模频率解析所得关键特征量,提出一种新能源高渗透电网的频率风险评估方法.该方法通过一组相互独立的采样数据,运用核矩阵广义逆运算构造出正则项函数,避免了一般机器学习算法迭代求解所带来的收敛性问题,并且不降低学习结果的泛化能力.在IEEE 39节点测试系统中进行的算例分析验证了所提方法的有效性....
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Published in | 浙江电力 Vol. 41; no. 4; pp. 1 - 6 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | Chinese |
Published |
国网浙江省电力有限公司电力科学研究院,杭州 310014%浙江大学 电气工程学院,杭州 310027
2022
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Subjects | |
Online Access | Get full text |
ISSN | 1007-1881 |
DOI | 10.19585/j.zjdl.202204001 |
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Abstract | TM712; 新能源高渗透电网在功率扰动后,频率响应轨迹更容易呈现出频率偏差大和变化速率高的特性,导致频率保护动作受到明显影响.为准确预测强随机运行方式下的系统频率响应特性,利用基于核矩阵广义逆运算的快速核学习算法,结合共模频率解析所得关键特征量,提出一种新能源高渗透电网的频率风险评估方法.该方法通过一组相互独立的采样数据,运用核矩阵广义逆运算构造出正则项函数,避免了一般机器学习算法迭代求解所带来的收敛性问题,并且不降低学习结果的泛化能力.在IEEE 39节点测试系统中进行的算例分析验证了所提方法的有效性. |
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AbstractList | TM712; 新能源高渗透电网在功率扰动后,频率响应轨迹更容易呈现出频率偏差大和变化速率高的特性,导致频率保护动作受到明显影响.为准确预测强随机运行方式下的系统频率响应特性,利用基于核矩阵广义逆运算的快速核学习算法,结合共模频率解析所得关键特征量,提出一种新能源高渗透电网的频率风险评估方法.该方法通过一组相互独立的采样数据,运用核矩阵广义逆运算构造出正则项函数,避免了一般机器学习算法迭代求解所带来的收敛性问题,并且不降低学习结果的泛化能力.在IEEE 39节点测试系统中进行的算例分析验证了所提方法的有效性. |
Author | 董炜 华文 王冠中 王博文 王龙飞 叶承晋 |
AuthorAffiliation | 国网浙江省电力有限公司电力科学研究院,杭州 310014%浙江大学 电气工程学院,杭州 310027 |
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Author_FL | YE Chengjin DONG Wei WANG Longfei WANG Bowen HUA Wen WANG Guanzhong |
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Title | 基于快速核学习的新能源高渗透电网频率风险评估 |
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