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大型风电基地连锁故障在线预警系统研究与开发
引用本文:吕颖,孙树明,汪宁渤,訾鹏,陈得治,周强,高凯,何晓阳,张艳军.大型风电基地连锁故障在线预警系统研究与开发[J].继电器,2014,42(11):142-147.
作者姓名:吕颖  孙树明  汪宁渤  訾鹏  陈得治  周强  高凯  何晓阳  张艳军
作者单位:中国电力科学研究院,北京 100192;中国电力科学研究院,北京 100192;甘肃省电力公司风电技术中心,甘肃 兰州 730050;中国电力科学研究院,北京 100192;中国电力科学研究院,北京 100192;甘肃省电力公司风电技术中心,甘肃 兰州 730050;国网辽宁电力有限公司,辽宁 沈阳 110006;国网辽宁电力有限公司,辽宁 沈阳 110006;国网辽宁电力有限公司,辽宁 沈阳 110006
基金项目:国家电网公司重大科技项目
摘    要:针对大规模风电连锁脱网事故频发,研究并开发了大型风电基地连锁故障在线预警系统。首先分析风电连锁故障的事故特征,确定建立风电连锁故障在线预警系统的关键环节,完善风机模型、建立风机保护模型和无功补偿模型。然后基于在线动态安全评估技术,提出了适合于大型风电基地的连锁故障在线安全预警的方案和基本结构,包括在线数据整合与预想故障集,风电场连锁脱网事故搜索方法,连锁故障严重性评估方法和连锁故障在线预警并行计算方案。研发的系统在电网中进行了实际应用,验证了所提方法的合理性和有效性。

关 键 词:风电基地  连锁故障  在线预警
收稿时间:2013/8/30 0:00:00
修稿时间:2013/10/29 0:00:00

Study and development of on-line cascading fault early-warning system for large-scale wind power base
Affiliation:China Electric Power Research Institute, Beijing 100192, China;China Electric Power Research Institute, Beijing 100192, China;Wind Power Center of Gansu Electric Power Corporation, Lanzhou 730050, China;China Electric Power Research Institute, Beijing 100192, China;China Electric Power Research Institute, Beijing 100192, China;Wind Power Center of Gansu Electric Power Corporation, Lanzhou 730050, China;Liaoning Electric Power Company Limited, Shenyang 110006, China;Liaoning Electric Power Company Limited, Shenyang 110006, China;Liaoning Electric Power Company Limited, Shenyang 110006, China
Abstract:With consideration of large-scale cascading trip-off fault of wind generating, an on-line cascading fault early-warning system for large-scale wind power base is developed. Through the research of fault characteristics for wind generating cascading trip-off, the key links for building up cascading fault on-line early-warning system for wind power base are determined, including improving wind generator model and modeling wind generating protection and reactive compensation device. Based on on-line dynamic security analysis system, the scheme and basic structure of cascading fault on-line early-warning system for wind power base are proposed, including on-line data integration and contingency set, searching strategy for cascading trip-off fault, severity evaluation method for cascading fault, and parallel computing method. The system has been put into practice, which proves the rationality and effectiveness of the proposed method.
Keywords:wind power base  cascading fault  on-line early-warning
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