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Power-grid faults pose a great threat to the economy and to social stability. In this paper, the detrended fluctuation analysis method is used to investigate the scaling properties of power grid faults and the correlation between faults and meteorological factors that are closely related to power grid faults. Multifractal detrended fluctuation analysis showed that the fault time series were multifractal. Further investigations revealed the origins of multifractality in power-grid fault time series, and the results showed that the temporal correlations in the data represent the distribution of the returns, which are a significant source of multifractal scaling. Then, cross correlations between the fault and the four meteorological factors were investigated using the detrended cross-correlation analysis method. The results showed that maximum wind speed has a considerable impact on the number of transmission system line faults per day, whereas daily precipitation, daily mean air temperature, and maximum wind speed have a considerable impact on the number of distribution system line faults per day.

Ice storms have seriously threatened power network security over the last decades. In 1998, an ice storm that struck North America damaged more than 1,000 transmission towers. In 2008, a severe ice storm struck South China, destroying thousands of transmission lines and towers, resulting in more than USd50 billion in economic loss. During this storm, the Chenzhou power network in the Hunan province suffered an outage, and the city experienced a weeklong power blackout. Figures 1 and 2 depict samples of damaged transmission lines and towers brought down by unbalanced tensions caused by ice-covered lines. Table 1 summarizes the corresponding damages to the transmission infrastructure, showing that more than 800 towers and 400 lines (i.e., in excess of 220 kV) were impaired. Moreover, the extent of ice storm damage in the distribution network included more than 60,000 towers and 47,000 lines.

Conductor galloping is a common phenomenon during the operation of the transmission line, which can easily result in electrical and mechanical accidents such as tower collapses and interphase flashover. And aerodynamic parameters are key factors to study galloping. In this paper, the aerodynamic parameters of crescent-shaped and D-shaped conductors, which are two typical iced conductors, are studied by wind tunnel test. The instability analysis is carried out according to Den Hartog instability mechanism and the linear galloping model. The results indicate that wind velocity, ice thickness, conductor type, bundle spacing and splitting number all have a great influence on aerodynamic parameters and conductor galloping. Then the galloping situation of a 500 kV quad bundle conductor are simulated according to the parameters obtained from wind tunnel test. The calculating results correspond with the actual situation. The results obtained in this paper are important to predict the galloping amplitudes under different weather conditions and investigate anti-galloping technology of iced quad bundle conductor.

Under the circumstances of global climate change, the El Nino event affects power grid icing by influencing the winter climate characteristics. The response characteristics of the massive power grid icing to El Nino should be of concern. Based on analysis and comparison, this study found that the overall level of response of Hunan power grid icing to El Nino was weak in 2015 winter. Areas with severe power grid icing of Hunan at 2015 El Nino period are mainly distributed at the midwest and southeastern mountainous and surrounding areas, but the maximum ice thickness extremum area range is shrinking. The maximum ice thickness at the El Nino winter enhancing (weakening) follows the trend of El Nino increasing (decreasing). Overall, the maximum ice thickness response characteristics of Hunan power grid at the El Nino period can be divided into four types. This analysis of power grid icing characteristics during El Nino period summarizes the response characteristics of icing and can guide the research of power grid icing and ant-icing countermeasures.

With the development of society, electricity has become an indispensable material, and the reliability of power grid has become more and more important. The ice-covered power grid will lead to accidents such as broken poles and other accidents, which seriously threaten the reliability of the power grid and safe operation. Therefore, a simple and efficient detection method of ice-covered power grid is urgently needed. To solve this problem, based on the good performance of convolution neural network, this paper applies it to the detection of power network icing. A classification method of power network icing detection image based on convolution neural network is proposed, which can effectively classify and recognize power network icing image. In addition, in view of the shortcomings of convolution neural network algorithm, this paper proposes a hybrid classification model combining convolution neural network and support vector machine. Firstly, the convolution neural network is used to extract features, and then the support vector machine is used to replace the softmax layer of the convolution neural network to realize the classification of ice-covered detection images. The simulation results show that it is feasible to use convolution neural network to classify the detection images of ice-covered power grid. Compared with convolution neural network, the hybrid classification model of convolution neural network and support vector machine proposed in this paper has better image classification effect, and further improves the classification performance of detection image of ice-covered power grid, and ensures the reliability and safe operation of power grid.

Based on ERA-Interim data, gauge observations, transmission line icing observational data, and hindcasted predictors from a numerical forecast system of transmission line icing, a new transmission line icing thickness (TLIT) dataset was constructed to solve the problem of limited historical data. The reliability of the dataset was analyzed using case studies and climate data. The results showed that the descriptions of three icing events in southern China by the TLIT were consistent with the actual observational data, and the icing thickness differences were less than 2 mm. The spatial distribution of annual icing days and icing thickness calculated using meteorological observation station icing data (OIT) and the TLIT data had a similar pattern, with small differences in the numerical values. A rotated empirical orthogonal function (REOF) decomposition was conducted for 67 transmission line icing events. It was found that the spatial distributions of the first three characteristic vectors of the TLIT and OIT data were similar, and the correlation coefficients for the time coefficients of the first three characteristic vectors were 0.801, −0.443, and 0.576, respectively. Three key areas were identified based on the first three patterns of REOF, and the average icing thickness of 67 events in southern China and the three key areas was calculated. The correlation coefficients of icing thickness calculated by the TLIT and OIT data for these areas were 0.648, 0.384, 0.565, and 0.599, respectively. The results illustrate that the TLIT data can reflect the temporal and spatial variations of ice thickness in southern China.

The thermal management of insulated-gate bipolar transistor (IGBT) modules is a critical issue in the field of power electronics. According to the minimum thermal resistance principle, this study proposed a rectangular heat pipe radiator with parallel heat flow structure that can be used for cooling two 1700 V/1000 A IGBT modules. The prototypes of typical and novel heat pipe radiators were produced to validate the heat transfer enhancement of the novel structure. Performance evaluation and analysis were numerically and experimentally carried out, and the numerical results agreed well with the experimental data. Parametric studies were performed to analyze the effects of inlet air temperature, air volume, and heat load on the heat dissipation capability. The study found that the novel heat pipe radiator has a good start-up characteristic due to the parallel heat flow structure. Moreover, the performance enhancement of the novel heat pipe radiator is obvious at large heat loads. Experiment results show that the two IGBT modules with 3500 W could be cooled down to 67.8 °C when the air volume is 450 m3 h−1, which is 8.9% lower than that of a typical heat pipe radiator. The proposed novel structure improves thermal performance of the novel heat pipe radiator by significantly decreasing its thermal resistance by 22% in comparison with that of a typical heat pipe radiator.

DC ice melting is an effective technical method against ice disaster on transmission lines. To satisfy the demand for simultaneous de-icing and reactive power compensation for substations, this paper proposed a large-capacity low-cost DC deicer with reactive power compensation, which is mainly composed of rectifier transformer, Static Var Generator (SVG) and diode rectifier. In the proposed topology, SVG and diode rectifier share the rectifier transformer, but rectifier transformer capacity is not increased compared with a single deicer. This paper firstly presents the proposed topology and analyzes its advantages. Then, the rectifier transformer design is introduced, and the SVG control strategy is presented. Simulation results for the proposed device are presented, and an engineering devices with a capacity of 21.8 MVA developed for the 220 kV Fuchong substation is described. The simulation and application results indicate that the proposed devices work well.

Ice disaster is a common form of natural disaster that threatens the safe operation of power grids. Long-term forecasting of power grid icing can provide valuable time for early deployment of power grid anti-icing measures, significantly reducing losses from power grid ice disasters. By analyzing the physical and quantitative relationships between power grid icing and multiple factors such as sunspots, atmospheric circulation, air temperature, and precipitation, the authors have proposed a novel analytic method based on key factors for long-term icing forecasting for power grids. In addition, a fuzzy membership-based forecasting model has been constructed to forecast the long-term icing degree of power grids. Example calculation results using the proposed models show that these models provides accurate forecasts of long-term grid icing degree, which demonstrates the effectiveness and practical usefulness of the proposed models.

Wildfires are a major natural disaster that can threaten the safe and stable operation of overhead transmission lines. Compared with large-area forest fires, transmission-line wildfires usually cover a small area and spread rapidly, making monitoring accuracy and real-time requirements of high priority. Wildfire monitoring based on satellite remote sensing has advantages in terms of monitoring-range width and the capacity for real-time monitoring; however, the detection threshold changes dynamically due to the influences of climate, geography, weather, and other factors that affect monitoring accuracy. To focus on small-area wildfires near overhead transmission lines, we developed a partition dynamic threshold calculation method based on time-series prediction. Basic thresholds are obtained based on a large number of historical values, followed by partitioning one of these values according to digital elevation model data and subsequent correction. Compared with conventional constant-threshold monitoring methods, our proposed method significantly reduced missed and false detection rates. Additionally, to improve fire-spot localization to the overhead transmission-line towers, we developed a tower-location algorithm based on block searching. Compared with the traditional traversal algorithm, our algorithm enabled a 15,000-fold increase in operation speed. These improvements will significantly enhance the monitoring of transmission-line wildfires, which are highly reliant upon alarm speed.

Widespread fire disasters always occur in several concentrated short periods. A large range of fire disasters can cause the tripping of dozens of transmission lines simultaneously, posing a serious threat to safe operation of the power grid. The degree of risk cannot be efficiently calculated, making it difficult to guide the optimization of the allocation of fire extinguishing equipment. This paper describes the development of a large wildfire disaster power grid fault fire extinguishing equipment optimal allocation method and a proposed fast calculation method of transmission line risk. The risk index is calculated for different regional power grids according to subareas. According to the grid risk, fire extinguishing equipment will be deployed in advance to address high-risk areas of the grid fire, fully exploiting the limited equipment fire extinguishing effectiveness. The proposed method is verified in the Hunan provincial power grid as a case study. The results show that the number of calculations can be reduced to 1.2 × 103 for the case in which 20 transmission lines are threatened by fire disasters; using computer resources with 30 trillion operations per second, the calculation time is less than 5 min. This capability can provide scientific and efficient guidance for disaster treatment of the electric power grid.