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In order to solve the problem of short-circuit current exceeding the standard in the development of 500kV power grid, a new current limiting device based on high coupled split reactor and parallel circuit breaker is adopted, which can realize the function of equalizing the current of circuit breaker in steady-state operation and limiting current of circuit breaker in transient fault. Due to the introduction of an additional circuit breaker and a high coupling reactor in the current limiting device, there is a large transient voltage in the break of the circuit breaker and in the coupling coil when the fault occurs. In this paper, the overvoltage distribution in the new current limiting device is studied. Firstly, the basic structure of HCSR and the topological structure of main circuit are introduced, and the calculation formulas of coupling reactor and distributed capacitance are deduced. Then, the steady-state current sharing and transient current limiting processes of the parallel circuit breakers are described, and the technical effects of the current sharing process are analyzed and deduced. Last, this paper focuses on the analysis of the operation circuit in the current limiting process, and makes a theoretical analysis and a brief derivation of the current and overvoltage in the breaking process of two circuit breakers with different actions.

At present, with the comprehensive promotion of distribution network construction, the demand of reliability for electricity is getting higher and higher. Therefore, the investment planning model for distribution network, which focuses on the overall load growth within the region, is not applicable. In this paper, a distribution network planning model that considering different customers’ reliability requirements is proposed. Firstly, the fuzzy binary contrast strategy is adopted to quantify the reliability requirements of different customers in the region. The neural network is used to mine the correlation model between reliability indices of the different power supply requirements and corresponding reconstruction measures. Then, the optimal model of distribution network planning with the target of reliability indices and the constraint of investment cost is established. As a result, the proposed model fully meets the reliability requirements of customers and forms the optimal investment planning scheme of the distribution network. Finally, the results of the IEEE 33 test system verify the rationality and feasibility of the proposed model.

In recent years, with the development of distributed energy and the increased flexibility of active distribution networks (ADN), the interactive operation of ADNs has been widely concerned. Moreover, in some economically developed regions, the demand for customer diversification and personalized power consumption is increasing, which puts new requirements on the operation of active power distribution networks. In this paper, based on the coordinated multi-agents of active distribution network, fuzzy decision theory is adapted to implement the coordinated optimization operation of ADNs, and achieves the cascade utilization of adjustable resources by considering distinct power supply requirements of customers. The ADN agent will interact with actively assigned network participants based on the system's real-time unbalanced power to reduce power imbalances in ADN operations. The simulation results show that the proposed method can effectively realize the optimal operation of ADN under the premise of satisfying the power supply requirements of customers.

Nowadays, the detection of acoustical emission is widely used for fault diagnosis of gas insulated substations (GIS) in normal operation and factory tests, which is called 'non-conventional' method recommended in the standard IEC TS 62478-2016 and GIGRE D1.33 444. In this paper, to develop a data analyzer for acoustic detection (AD) system to make an assistant diagnosis for technical personnel or equipment operation and maintenance personnel, based on the previous research on the experimental research, pattern identification with phase compensation and the software development, the algorithm model design and its application is given in detail. For the acoustical emission signals (n, ti, qi), the BP artificial neural network optimized by genetic algorithm (GA-BP) is used as a classifier based on the fingerprint consisting of several statistic operators, which are derivate form typical 2D histograms of PRPD with identification with phase compensation (IPC). Experimental results show that the comprehensive algorithm model designed for identification is practical and effective.

At present, the acoustic emission (AE) method has the advantages of live measurement and easy fault location, so it is very suitable for insulation defect detection of power equipments such as GIS, etc. While the conventional AE detection system or instruments always can't give a right discrimination result, because them always work based on the reference voltage or phase information from an auxiliary 220V voltage signal source rather than the operation high voltage (HV) with the real phase information corresponding to the detected AE pulsed signals. So there is a random phase difference between the reference phase and operation phase. The discharge fingerprint formed by the detected AE pulsed signals with reference phase using the same processing process is compared to the discharge fingerprint database formed in the HV laboratory with the real phase information, therefore, the system may not be able to discriminate the discharge mode of the field measured data from GIS in substation operation. In this paper, in order to design and develop a general fast analysis algorithm model for PD acoustic detection system to make an assistant diagnosis, the pattern identification with phase compensation was designed and applied. The results show that the method is effective and useful to deatl with AE signals meased in operation situation.

Nowadays, the acoustic detection (AD) of partial discharge (PD) is widely used for defect diagnosis of gas insulated substations (GIS) in normal operation and factory tests, including the live detection, on-line monitoring, and offline tests etc. In this paper, in order to design and develop a general fast analysis algorithm model for PD acoustic detection (AD) system to make an assistant diagnosis, the characteristic of acoustic emission (AE) signals generated by different artificial defects such as protrusions (corona discharge), floating shield (floating discharge), void in spacer (inner discharge) and bouncing particles are investigated in the HV laboratory. Some meaningful parameters behind the detected AE signals are extracted and discussed with showing the discharge pattern of (Δ t i , qi) and (t i , q i ) respectively, which are used to distinguish the background noise, PD phenomena or bouncing particles. The results show that the data generated from the discharge tests of the defect models can be used as a sample library for artificial intelligence learning, which can be processed to form a general intelligent analysis model algorithm for GIS PD acoustic detection.

The nondestructive evaluation and fault diagnosis methods (NEFDM) for power substation grounding grids are reviewed, including standard grounding impendence detection (SGID), equivalent network resistances measurement (ENRM), magnetic induction intensity recording (MIIR), ultrasonic guided-wave detection (UGVD) and electrochemical analysis of grounding corrosion (EAGC), all of which belong to the popularly methods investigated and used in China nowadays. Those NEFDM for the power substation grounding grids are compared, and their application situations are also briefly introduced. At last, based on the above works, it is pointed out that the state response analysis method (SRAM) based on the input current and output voltage signals of the power substation grounding grids is a research topic worthy of future development

With plenty of energy accessing to the distribution networks, traditional single direction power transmission of “source-grid-load” mode is changing. The wide-area measurement system light (WAMS Light) extends dynamic condition monitoring to the low-voltage grid. With the increasing scale of WAMS Light, the volume of high-precision, high-density data provided by phasor measurement unit (PMU Light) is increasing. Straight listing extensive synchronous data is difficult for dispatchers to extract useful information and learn the system status. This paper presents a compositive visualization method based on geographic information system (GIS) for real-time monitoring of synchronized data in distribution networks. In this paper, the primitive is designed to adequately consider the data characteristics of synchronous data applied in the distribution network. The frequency contour layer, the voltage phasor layer, and the non-electricity information layer are displayed and superimposed on GIS. The trend sparklines are presented according to the zoom level of the GIS, helping dispatchers effectively monitor the actual state and variation trend of each measurement just by one glace.

Electronic current transformer (ECT) is a new type of high-voltage instrument transformer. It constitutes more components than that of the traditional one. To locate the fault accurately and rapidly during its performance tests, this paper proposed a fault tracing method based on the failure modes and effects analysis (FMEA). From the measuring results of the ECT under test, together with its failure patterns and the test types, we can easily locate its fault in the FMEA tables, and repair them quickly. The presented method is verified to be useful in the results of the analysis on two practical examples.

Commutation failure is common in HVDC transmission system. The fault recording in one converter station when commutation failure caused by disturbance of AC system was collected in this paper, and the landing amplitude, zero crossing offset and commutation area of the AC bus voltage was calculated and statistical analyzed. The results suggested that, when commutation failure: 1) The average landing amplitude of effective value of the AC bus phase voltage and line voltage was 5.13% and 4.6%, and the peak of zero sequence voltage was basically less than 50kV; 2)The average of zero crossing offset of the AC bus line voltage was −4.24 degree. But there were few cases that the zero crossing was lagging, but commutation failure occurs. 3) The average reduction of the commutation area was 22.02%, and the reduction was less than 30% in most cases. The results will provides basic data for analyzing the main influencing factors of commutation failure and setting up countermeasures for HVDC system.

The theme of this dissertation is to investigate how financial risks can be allocated in a multi-agent and multi-period setting under the economic principle of “Pareto efficiency and financial fairness” (PEFF). The dissertation is a combination of theory and practice and consists of three papers. In the first paper, the existence and uniqueness of the PEFF solution, which combines risk preferences with risk-neutral valuation, is established theoretically. This PEFF approach is adapted into a moving-horizon approach in the second paper, and is then applied to calculate how investment risks can be allocated between current and future benefit payments for a collective pension fund within a realistic ALM framework. The last paper of the trilogy extends the results further by incorporating risk preferences on an individual level.

We work with a multi-period system where a finite number of agents need to share multiple monetary risks. We look for the solutions that are both Pareto efficient utility-wise and financially fair value-wise. A buffer enables the inter-temporal capital transfer. Expected utility is used to evaluate the utility, and a risk-neutral measure is essential for determining the risk sharing rules. It can be shown that in the model setting there always exists a unique risk sharing rule that is both Pareto efficient and financially fair. An iterative algorithm is introduced to calculate this rule numerically.

Simulation technology provides a powerful tool for the IGBT module design. The IGBT chip model and the interconnect parasitics are the most important factors for the package design of IGBT module. By the aid of the simulation software, the IGBT chip model is fulfilled and the package parasitics is extracted. So the whole simulation deign platform of IGBT package achieves.

Aiming at the limitation that the interruption event recordings are simply used to calculate the reliability indexes in the reliability management of distribution network at present, this paper proposes a practical method of reliability weak links mining for distribution network based on multidimensional analysis. Firstly, a complete multidimensional cube model of interruption recording is built according to the normalized format of interruption recording. Secondly, the complete cube model is reconstructed considering the actual situation and application requirements. Lastly, slicing analyses on single dimension and dicing analyses on multiple dimensions are carried out on the reconstructed cube model, with the results shown in the form of chart, and then targeted recommendations for the operation and maintenance works are proposed. Practical application is found to be much effective in excavating the weak links of distribution network reliability, and providing valuable recommendations and decision basis for both the primary operation and maintenance department, and the management hierarchies.

This paper addresses how to inform nano science and technology management by mining a particularly rich information resource - the publicly accessible databases on nano fields. Empirical bibliometrics, technology forecast, technology assessment and competitive technical intelligence are not well utilized in technology management. Three factors could enhance managerial utilization: capability to exploit huge volumes of available information, ways to do so very quickly, and informative representations that help manage emerging technologies. In this paper, a framework based on text mining techniques is proposed to discover useful intelligence from the large body of nano's electronic text sources. This intelligence is a prime requirement for successful S&T management. After that the proposed method is applied to nano technology to give an empirical study.