针对极端外部环境易引发的巨型停电灾难的问题,提出输电线路的综合风险评估方法.首先采用多维云模型理论,建立极端外部环境下输电线路的综合故障率预测模型;其次,根据预测的故障率,从输电线路自身损失、人身环境损失、社会损失和系统安全损失这4个方面建立一种输电线路的综合风险评估体系;最后,根据电力事故事件调查规程对所建立的综合风险评估体系进行量化评分,并利用贵州电网实例进行验证.算例仿真表明:所建立的输电线路的综合风险评估体系具有良好的实用性、可操作性,而且便于评估.

准确预测继电保护装置使用寿命,有利于消除安全隐患 、保证电力系统正常稳定运行.该文分析影响继电保护装置使用寿命的主要因素,并结合层次分析法对各因素进行赋权分析.以平均故障率为衡量指标,建立基于灰色马尔科夫链的继电保护装置寿命预测模型,并且将各因素权重加入预测模型,结合算例分析进行仿真计算.最后通过精度检验,验证模型的有效性和精确性.

具备负荷特征识别功能的监控系统对实现电力需求侧的自主式、智能化管理至关重要.为解决非侵入式检测技术仅局限于既定设备的问题,促进各类用电设备的主动识别,以支撑自动需求侧管理体系下用电行为分析、用电优化控制功能.文中定义了基于家用电器运行特性的"负荷指纹"及其构成,并以信息物理融合系统为基础,提出负荷指纹管理的层次化技术架构,包括本地及云端两层用电负荷指纹管理平台.最后研制插座式智能采集终端、具备多通信技术的智能交互集中器,可为该技术架构的实现提供坚实的硬件支撑.

能够接纳分布式电源的柔性配电网是将来智能配电网的主要特点.首先,建立了含柔性开关(SOP)的配电系统基本架构,依据各分布式电源的特点,把光伏、风机和储能装置接进配电网的交流或直流区域;然后,分析了SOP的数学模型及其主要运行控制策略;最后,通过变流器的控制模式和运行策略的灵活切换,基于柔性配电网做了如下仿真实验:馈线的出力优化均衡、不间断转供电及能量调度.仿真验证了含SOP的交直流柔性配电网系统架构具有能够接纳分布式电源和控制灵活等方面的优越性.

电力变压器内部结构复杂且运行状态受多种因素影响,为了对其状态做出快速准确地评价,提出一种基于TOPSIS和灰色关联分析的状态评价方法.该方法建立了变压器状态评价的层次结构模型,并运用层次分析法确定了指标的权重大小;引入健康度的概念表征各个指标的优劣情况,对选取的指标分别进行量化和规范化的处理;运用TOPSIS法和灰色关联分析分别计算待评价变压器状态与正、负理想状态之间的欧氏距离和灰色关联度,并将两者结合得到待评价变压器的状态.实际算例分析表明,所提出的状态评价方法能准确地评价变压器的运行状态,同时还能对不同的待评价变压器运行状态进行排序,为检修决策提出合理的依据.

In order to facilitate the active identification capability of various types of electrical equipment, so as to enhance the functions such as the behavioural analysis and optimization control of electricity utilization in an automatic demand side management (DSM) system. A definition is given on load fingerprint based on operating characteristics of household appliances, as well as its architecture. In addition, based on the cyber-physical systems (CPS) technology, a hierarchical technical framework for load fingerprint management is proposed. This framework is a two-layer electricity utilization load fingerprint management platform, including local management and cloud-based management. Finally, two hardware prototypes are developed, including a socket-type smart collection terminal and an intelligent interactive concentrator with multiple communication technologies, which can provide strong hardware support for the realization of the hierarchical technical framework proposed in this paper.

合理的设计冰厚可在保障电网抵御覆冰灾害能力的同时大大降低电网工程的整体造价,因此输电线路冰厚线径订正系数的正确计算具有重要的工程应用价值.本文基于量纲分析提出了一个导线覆冰碰撞率的简化计算公式,并结合雨雾凇导线覆冰理论模型导出了冰厚线径订正系数的理论计算方法,其结果与有关实验研究结果相符并优于最新行业标准(DL/T 5158-2012)推荐的方法.进一步利用该方法从理论上计算分析了不同覆冰类型冰厚线径订正系数及其差异,结果表明:雾凇覆冰情况下冰厚线径订正系数随导线直径增大而减小,雨凇覆冰情况下冰厚线径订正系数随导线直径增大而增大,而模拟雨雾凇混合覆冰情况下的线径订正系数介于前两者之间.由于具有较完整的理论基础并能够考虑不同的覆冰类型和气象条件,该方法具有较好的理论普适性,对电力线路防冰设计具有较大的应用参考价值.

The construction of intelligent substation provides conditions for the acquisition of real-time information of the secondary equipment.Accurate understanding of the state of relay protection system plays an important role in improving the reliability of power supply.According to the information flow and equipment functions of intelligent substation,the state evaluation information model based on real-time self-checking information and key historical information is established.Taking the hysteresis quality of traditional state evaluation method on the system's state into account,the correction strategy based on information trend prediction is proposed.Mountain shaped fuzzy subordinate function is selected for fuzzy processing according to trend prediction results.The weights are set by combination weighting method combining with the analytic hierarchy process method and anti-entropy weighting method,which overcomes the too-high sensitivity of traditional entropy weighting method.Compared with the traditional method,simulative results show that the proposed method can improve the accuracy and timeliness of state evaluation results effectively.

The prediction of dissolved gas content in transformer oil is helpful for early detection of latent faults in transformer, and it has important guiding significance for better condition based maintenance. In view of the abundant data of transformer DGA, and that the trend of the change of dissolved gas content in oil under normal running condition is not obvious, a prediction method based on fuzzy time series model is proposed. Consider that the change in dissolved gas content in oil is interaction and influenced, in this paper, the classical fuzzy time series model is improved from the view of domain division, and propose a multi factor fuzzy time series model based on spatial FCM domain partition. The example analysis shows that the method can well fit the changing trend of DGA data, and compared with the classic fuzzy time series model and the one-dimensional FCM fuzzy time series model, the superiority of the improved model in prediction is verified.

The black box arc model is widely used to describe the dynamic change of the arc in quenching process during interruption of circuit breaker. However, most of the black box models are not capable of realizing the analysis of the repeated breakdown of the circuit breaker. In this paper, an extended KEMA's equation based arc model is proposed in this paper to address this issue. To obtain the parameters of KEMA model, the voltage and current data of the arc during the interrupting process of the circuit breaker are obtained, the parameters are calculated by particle swarm optimization then. The comparison of calculated and measured voltage traces showed the accuracy and correctness of the obtained parameters. As this model is developed based on EMTP-ATP, it can be directly applied in electromagnetic transient studies.

In this paper, a model used for predicting icing thickness of power transmission lines is proposed. An algorithm derived from parallel coordinates is applied to convert the high-dimensional source data, which includes relevant factors about the icing thickness of power transmission lines, to two dimensional images. Then the images are used for training convolutional neural networks (CNNs). Finally, the icing thickness is predicted by the trained CNNs. In this way, our system combines the advantages of information visualization and CNNs. It provides an universal method to process multi-dimensional numerical data with CNNs algorithmically and in a real sense.

The overvoltage is the main cause of insulation damage in power grid. It is of great practical significance to study the feature extraction and classification of the measured overvoltage in the distribution network. This paper constructed the band of time-frequency distribution of overvoltage in Lo Shu Square based on Frequency Slice Wavelet Transform and completed the overall and detail information of overvoltage extraction. The measured overvoltage feature automatically extraction and classification is achieved based on modified Stacked Sparse Autoencoders. The influence of key parameters, namely, the size of convolutional patches, the number of convolutional maps and sparsity parameter in modified SSAEs are analyzed respectively, and the best optimization parameters are determined. The results show that this structure can extract and classify the measured overvoltage waveforms automatically.

The state maintenance of relay protection equipments requires scientific evaluation of the condition of equipments;and the objective selection of indices weights is the basis for scientific and reasonable evaluation of relay protection equipments.According to the principle of state evaluation index system,the main state parameters of relay protection equipment are selected;and a state parameter evaluation model of relay protection equipments is constructed.Based on the analytic hierarchy process (AHP) and expert method to determine the relay protection equipment status indices weights,this paper uses the prior probabilities of Bayesian theory to apply the empirical conclusions of predecessors to the evaluation.And it further combines the actual situation data of relay protection equipments,the posterior distribution of weights is obtained,so as to make the status of weights more reasonable and updating.It is proved that the weight updating based on Bayesian theory can more scientifically evaluate the state of relay protection equipments.

Power system risk includes two aspects:the probability of the accident and the severity of the consequences.In terms of consequence severity,the AC optimal load shedding model is established based on the interior point method;the amount of load loss severity index is defined and consequence severity is ranked according to membership function.In the aspect of failure rate,fuzzy C means clustering is used to realize fuzzy partitioning;and the fuzzy evaluation vector is constructed based on fuzzy comprehensive evaluation method.Finally,according to the maximum membership principle,power system risk level is output.Taking the IEEE-RTS79 reliability test system as an example,the results show that the proposed method can evaluate the power grid risk level accurately and effectively under different faults,identify key link of the system and provide a theoretical basis for the differentiation operation and maintenance.

According to the characteristics of the correlation of multiple wind farm output, this paper put forwards a modeling method based on fuzzy c-means clustering and the copula function, and correlation wind farms are inserted into IEEE-RTS79 reliability system for risk assessment.By the probabilistic load flow calculated by Monte Carlo simulation method, the probability of the accident is derived, and bus voltage and branch power flow overload risk index are defined in this paper.The results show that this method can realize the modeling of the correlation of wind power output, and the risk index can identify the weakness of the system, which can provide reference for the operation and maintenance personnel.

Due to the uncertainty of the grid accident and the serious consequences of accident, it is necessary to establish the risk model and the index system to realize the grid risk evaluation and the line importance identification. The grid risk evaluation model was built in this paper, and the risk index evaluation system was established based on the following aspects, including voltage limitation, branch power flow and load shedding. Based on the fuzzy reasoning method, the static security analysis and risk theory, the risk index was obtained by combining the line breaking accident case comprehensive risk value and sort classification. Taking IEEE-RTS79 system as an example, the simulation results showed that the proposed method could realize the quantification and classification of the comprehensive risk assessment, and identify the line importance, which could provide theoretical basis for security pre-warning and the operation maintenance strategy.

Secondary equipment of real-time information on its status evaluation plays a very important role. And the development of secondary equipment intellectualization and change the way of communication, the equipment real-time state information in an intelligent substation secondary can through the device self-checking information data to realize the online monitoring and network analyzer. Comprehensive evaluation model of secondary equipment health status based on real-time monitoring of environmental information is established. The analytic hierarchy process (AHP) and the subjective and objective combination method of the entropy weight method is used to reduce the weight deviation. Considering the serious information easy to be submerged risks in the process of traditional weighted, a mechanism of that serious information trigger weight fusing and redistribution weight correction is put forward, to ensure the accuracy of the evaluation results. The state evaluation results of fuzzy membership degree is transferred into the evaluation scores and the corresponding state level is determined. The rationality of the comprehensive status evaluation model proposed in the paper is verified by the example analysis.

It is significant important to quantify the impact of icing disaster on transmission lines and to construct the model of icing failure rate for the safety operation of transmission line under icing disaster.In allusion to the characteristics and limitations of online monitoring data by icing monitoring terminal,a maximum stress calculation method of transmission line based on the axial stress of the icing conductor is proposed and a corresponding calculation model of icing failure probability is established.Combined with the operating data by icing online monitoring terminal at a transmission tower of a certain company,the failure rate calculated by the proposed model is compared with the micro-meteorological and icing ratio recorded by the monitoring terminal.The coincidence degree of the change trend is high,so as to verify the effectiveness and accuracy of the proposed model.

Real-time stress over the limit is the icing fault reason in transmission line. An icing failure rate model of transmission line based on real-time stress was put forward in this paper. On the basis of the existing mechanical analysis process, the real-time stress calculation was introduced, and the real-time stress mathematical models with suspension point equal or un-equal height were established. Based on the variation conditions of temperature, wind speed and icing thickness, icing failure rate based on real-time stress was calculated. The example analysis results showed that the calculation results of the proposed model is more accurate than the traditional model.

Relay protection is important for power system's stable operation. However, logic state of traditional Bayesian network is simplex. To adapt to the relay protection system operation environment with increasing complexity in current years, a risk assessment model of relay protection system based on multiple-state Bayesian networks is established with dynamic and static indexes. Taking advantages of figurative expression of Bayesian network, the model can express multiple states of system and probability clearly, and also can calculate the risk grade by using qualitative and quantitative analysis of multi-state Bayesian networks.