考虑输电设备可靠性的电网风险分析研究
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摘要
电力系统的风险评估是近年来研究的热点问题之一。而目前国内外对于电网风险分析中大多是以统计数据为基础来确定风险指标的,对于不同设备所处的各不相同的健康状况、运行工况、外部环境等特有的因素缺乏针对性考虑。在电网实际运行中,电网设备的故障概率各有不同而且会随着电网设备的运行方式、历史运行工况和外部因素而变化。因此,将设备自身健康状况评估与系统风险相结合,在设备、系统、外部环境等多种因素之间建立相互关系,研究量化设备健康状态和电网风险评估的方法,对于促进智能电网的调度决策、设备检修等向智能化、全面化发展具有深刻的重要意义。在此前提下,本文主要作出了如下的工作和创新：
(1)利用证据理论融合对变压器的健康状态进行评估。在现有的变压器层次分析评估体系下,本文采用证据理论方法对指标信息进行了融合,给出了变压器的在线综合状态评估结果。并在此基础上,将评估结果等效为电网风险评估所需的元件故障率等可靠性数据,为考虑电网设备的风险评估提供了支持。
(2)基于实时监测信息对断路器健康状态进行评估。在计算断路器累计剩余电寿命的基础上,综合机械状态等信息,提出了针对高压断路器的在线综合健康状态评估方法,并将评估结果转化为电网风险评估中所需的可靠性数据。研制了针对高压断路器的实时监测装置,该装置通过实时监测数据,对断路器的剩余电寿命进行计算和评估,同时也辅以机械状态等方面的监测数据,为断路器的综合评估提供了切实可行的方案。
(3)基于支持向量描述方法的电网设备状态分类和故障诊断。利用支持向量描述方法,提出基于样本数据训练的电网设备状态分类方法；该方法解决了训练样本缺乏或不够所带来的问题,并且具有较强的扩展性,能较为便捷的对各类电网设备进行状态分类和诊断等分类工作,同时通过仿真实例也证实了该方法具有较好的准确率。
(4)综合考虑了电网设备在线健康状态的输电网风险评估体系。与以往基于历史统计数据的电网风险评估不同,由于考虑了设备在线健康状态对电网风险的影响,使得电网风险指标更能体现真实的电网状况,也能反映出不同设备在不同运行方式下对电网的影响程度,指出电网的薄弱环节；另一方面,也可以验证由于良好的设备状态检修,对提高电网可靠性所产生的影响。基于本文提出的风险评估体系,即可以用于电网的规划和设计,也能为电网的运行、检修等提供良好的决策支持。
(5)提出了一种基于三维信息的电网设备监测方案并进行了开发实践。针对电网设备状态信息的监测,提出了一种基于面向对象的三维信息模型；为更全面、详实和直观的对电网设备进行监测提供了一种全新的思路,并在此基础上以变压器的三维信息建模为例,进行了开发实践。
Nowadays, risk assessment for electric power system becomes an important issue. However, most risk analysis methods for electric power grid are based on historical statistics, and those methods are lack of considerating equipments'health status, operation situation and environment. In an operating power system, different equipment has its own failure probability and the probability changes with the equipment status. Therefore, finding the relationship between system risk and equipments'reliability, and then building a new power system risk assessment framework based on equipments'condition are very important for condition maintenance(CM), dispatching decision-making and etc. Achieving those targets, some works and innovations have been made as follows:
(1) Transformer health status is evaluated based on evidential reasoning (ER) approach. An evidential reasoning (ER) approach to the transformer condition assessment is presented. And Analytic Hierarchy Process (AHP) is also used to analyse the transformer's attributes. Then, the transformer assessment results are converted to reliability data for power system risk assessment. Thus, the system risk can be better evaluated with the consideration of transformers'on-line condition.
(2) High Voltage Breaker health status is evaluated based on real-time monitoring information. Electrical endurance of high voltage circuit breaker is calculated in this paper. Considering the machinery status, an on-line health condition evaluation approach to high voltage circuit breaker is presented. The evaluation results are converted to reliability date, and used to support the power system risk assessment. A real-time monitoring system for High Voltage Breaker is proposed in this paper. This monitoring system can be used to evaluate the high voltage circuit breaker's electrical endurance, and machinery conditions are also monitored. With these monitoring data, high voltage circuit breaker health status evaluation can be achieved in practice.
(3) Support vector data description is used for equipments'status classification and fault giagnosis. A new machine learning approach called'Support Vector Data Description (SVDD)' which is based on sample data training is employed for electric equipment classification. The SVDD approach can classify equipment status easily with strong extendibility, high accuracy rate and less training sample data. Several simulation processes are presented to confirm the advantages of the SVDD.
(4) A new framework for power transmission risk assessment is proposed, which considers not only historical failure statistics of transmission systems but also operation failure risks of system components. Different from traditional risk assessment, under the new framework, both up-to-date component failure risks and traditional system risk indices can be processed with the proposed outage model. Thus, the system risk can reflect the real situation better than the traditional way. The influence degrees to system risk, which made by different equipments and different system operation modes, can be indicated in this new framework. Thus, the weak links of power system can be pointed out. Meanwhile, the advantages for developing the power system reliability, which caused by equipment condition maintenance can be embodied. This new risk assessment framework can be used in power grid planning, and also can provide good supports for operation and maintenance.
(5) A three dimension information monitoring scheme for electric equipments is proposed and practised. A3D information model based on object-oriented technique is designed for the equipment monitoring. With this model, electric power equipment monitoring can be achieved in a new way, which is much comprehensive, real and direct than the traditional way. Based on the proposed method,3D information transformer model is built.
(1)利用证据理论融合对变压器的健康状态进行评估。在现有的变压器层次分析评估体系下,本文采用证据理论方法对指标信息进行了融合,给出了变压器的在线综合状态评估结果。并在此基础上,将评估结果等效为电网风险评估所需的元件故障率等可靠性数据,为考虑电网设备的风险评估提供了支持。
(2)基于实时监测信息对断路器健康状态进行评估。在计算断路器累计剩余电寿命的基础上,综合机械状态等信息,提出了针对高压断路器的在线综合健康状态评估方法,并将评估结果转化为电网风险评估中所需的可靠性数据。研制了针对高压断路器的实时监测装置,该装置通过实时监测数据,对断路器的剩余电寿命进行计算和评估,同时也辅以机械状态等方面的监测数据,为断路器的综合评估提供了切实可行的方案。
(3)基于支持向量描述方法的电网设备状态分类和故障诊断。利用支持向量描述方法,提出基于样本数据训练的电网设备状态分类方法；该方法解决了训练样本缺乏或不够所带来的问题,并且具有较强的扩展性,能较为便捷的对各类电网设备进行状态分类和诊断等分类工作,同时通过仿真实例也证实了该方法具有较好的准确率。
(4)综合考虑了电网设备在线健康状态的输电网风险评估体系。与以往基于历史统计数据的电网风险评估不同,由于考虑了设备在线健康状态对电网风险的影响,使得电网风险指标更能体现真实的电网状况,也能反映出不同设备在不同运行方式下对电网的影响程度,指出电网的薄弱环节；另一方面,也可以验证由于良好的设备状态检修,对提高电网可靠性所产生的影响。基于本文提出的风险评估体系,即可以用于电网的规划和设计,也能为电网的运行、检修等提供良好的决策支持。
(5)提出了一种基于三维信息的电网设备监测方案并进行了开发实践。针对电网设备状态信息的监测,提出了一种基于面向对象的三维信息模型；为更全面、详实和直观的对电网设备进行监测提供了一种全新的思路,并在此基础上以变压器的三维信息建模为例,进行了开发实践。
Nowadays, risk assessment for electric power system becomes an important issue. However, most risk analysis methods for electric power grid are based on historical statistics, and those methods are lack of considerating equipments'health status, operation situation and environment. In an operating power system, different equipment has its own failure probability and the probability changes with the equipment status. Therefore, finding the relationship between system risk and equipments'reliability, and then building a new power system risk assessment framework based on equipments'condition are very important for condition maintenance(CM), dispatching decision-making and etc. Achieving those targets, some works and innovations have been made as follows:
(1) Transformer health status is evaluated based on evidential reasoning (ER) approach. An evidential reasoning (ER) approach to the transformer condition assessment is presented. And Analytic Hierarchy Process (AHP) is also used to analyse the transformer's attributes. Then, the transformer assessment results are converted to reliability data for power system risk assessment. Thus, the system risk can be better evaluated with the consideration of transformers'on-line condition.
(2) High Voltage Breaker health status is evaluated based on real-time monitoring information. Electrical endurance of high voltage circuit breaker is calculated in this paper. Considering the machinery status, an on-line health condition evaluation approach to high voltage circuit breaker is presented. The evaluation results are converted to reliability date, and used to support the power system risk assessment. A real-time monitoring system for High Voltage Breaker is proposed in this paper. This monitoring system can be used to evaluate the high voltage circuit breaker's electrical endurance, and machinery conditions are also monitored. With these monitoring data, high voltage circuit breaker health status evaluation can be achieved in practice.
(3) Support vector data description is used for equipments'status classification and fault giagnosis. A new machine learning approach called'Support Vector Data Description (SVDD)' which is based on sample data training is employed for electric equipment classification. The SVDD approach can classify equipment status easily with strong extendibility, high accuracy rate and less training sample data. Several simulation processes are presented to confirm the advantages of the SVDD.
(4) A new framework for power transmission risk assessment is proposed, which considers not only historical failure statistics of transmission systems but also operation failure risks of system components. Different from traditional risk assessment, under the new framework, both up-to-date component failure risks and traditional system risk indices can be processed with the proposed outage model. Thus, the system risk can reflect the real situation better than the traditional way. The influence degrees to system risk, which made by different equipments and different system operation modes, can be indicated in this new framework. Thus, the weak links of power system can be pointed out. Meanwhile, the advantages for developing the power system reliability, which caused by equipment condition maintenance can be embodied. This new risk assessment framework can be used in power grid planning, and also can provide good supports for operation and maintenance.
(5) A three dimension information monitoring scheme for electric equipments is proposed and practised. A3D information model based on object-oriented technique is designed for the equipment monitoring. With this model, electric power equipment monitoring can be achieved in a new way, which is much comprehensive, real and direct than the traditional way. Based on the proposed method,3D information transformer model is built.
引文
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