首页> 外文期刊>Computers & mathematics with applications >Reliability modelling of medium voltage distribution systems of nuclear power plants using generalized stochastic Petri nets
【24h】

Reliability modelling of medium voltage distribution systems of nuclear power plants using generalized stochastic Petri nets

机译:基于广义随机Petri网的核电站中压配电系统可靠性建模

获取原文
获取原文并翻译 | 示例

摘要

The purpose of this study was to obtain a performable tool based on generalized stochastic Petri nets (GSPN), able to join precise results and fast approach. In practice, it is well known that a dependability analysis in the power systems field is often more difficult to perform due to the multiple dependencies on the specific maintenance policies, on the great number of operation conditions, and the possibility to consider overall distributions (nonexponential) of the operation periods of time and the maintenance activities duration. Under these circumstances, the usage of conventional methods of analysis is limited in what the most precise modelling of all the system characteristics are concerned. This study managed by SNN (National Company-"NuclearElectrica" S.A.) in cooperation with the "POLITEHNICA" of Bucharest analyzes and compares different configurations for the medium voltage (10.5 and 6.3 kV) distribution systems (MVDS). It has a practical connotation (SNN application for Cernavoda NNP) and compares four proposed MVDS configurations for the main auxiliary services. After description and implementation through GSPN, each configuration has been evaluated, in order to choose the most appropriate structure. (c) 2006 Elsevier Ltd. All rights reserved.
机译:这项研究的目的是获得一种基于广义随机Petri网(GSPN)的可执行工具,该工具能够结合精确结果和快速方法。在实践中,众所周知,由于对特定维护策略,大量运行条件以及考虑整体分布的可能性(非指数性)存在多重依赖性,因此在电力系统领域中进行可靠性分析通常会更加困难。 )的运行时间和维护活动的持续时间。在这种情况下,传统的分析方法的使用受到局限,因为要考虑所有系统特性的最精确建模。由SNN(国家公司-“ NuclearElectrica” S.A。)与布加勒斯特的“ POLITEHNICA”合作管理的这项研究分析并比较了中压(10.5和6.3 kV)配电系统(MVDS)的不同配置。它具有实用的含义(用于Cernavoda NNP的SNN应用程序),并比较了针对主要辅助服务提出的四种MVDS配置。经过GSPN的描述和实施后,已对每种配置进行了评估,以选择最合适的结构。 (c)2006 Elsevier Ltd.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号