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Benefiting from high flexibility and weavability, the wire-shaped supercapacitors (SCs) arouse tremendous interests for the applications in wearable/portable electronics. Graphene fiber (GF) is considered as a promising linear electrode for wire-shaped SCs. However, the bottleneck is how to develop the GF-based linear electrode with facile fabrication process while well-maintaining satisfactory electrochemical performance. Herein, a novel Fe3O4@GF composite linear electrode is proposed via a chemical reduction-induced assembly approach, in which the GO and Fe3O4 nanoparticles (NPs) realize the efficient self-assembly owing to the electrostatic and van der Waals interactions, as well as the sufficient reduction of GO during the preparation process. The resultant fiber-shaped architecture shows boosted charge-transfer kinetics, high flexibility and structural integrity. Such Fe3O4@GF linear electrode exhibits excellent electrochemical behaviors including a large volumetric specific capacitance (∼250.75 F cm−3), remarkable rate capability and favorable electrochemical kinetics in aqueous electrolyte, superior than previously reported GF-based linear electrodes. For real application, a high-performance wire-shaped SC with excellent flexibility and weavability is fabricated based on such Fe3O4@GF linear electrode and gel electrolyte, demonstrating ultrahigh volumetric energy density (18.8 mWh cm−3), power density (4000 mW cm−3) and strong durability (∼93.5% retention after 10000 cycles). Prospectively, the fabricated wire-shaped SC can maintain reliable electrochemical behaviors in various deformation states, showing its potentials in future portable and wearable devices.

Summary Li-ion battery safety issues related to fires and explosions are frequently triggered by Li dendrite growth, which is a predominant reason for separator piercing and cell shorts and is very difficult to detect in the early state. Here, we developed a sensitive detection method based on H2 gas capture that could detect trace amounts of Li dendrite formation. H2 gas was generated due to reaction of metallic Li with polymer binders. Even micron-scale Li dendrite (∼2.8 × 10−4 mg and 50 μm) growth can trigger H2 capture. Overcharge experiment with a LiFePO4-graphite battery pack (8.8 kWh) shows that H2 was captured first among H2, CO, CO2, HCL, HF, and SO2, and the capture time was 639 s earlier than smoke and 769 s earlier than fire. The Li dendrite growth can be completely prevented once H2 is captured, with neither smoke nor fire observed, which provides an effective method for early safety warning.

Aiming at the problem of fault prognostics for the energy storage power station, this paper proposes a novel data-driven method named multiple elastic networks with time delays (MEN-TD). The proposed method can learn the status of the energy storage power station in advance and provide early detection of the fault. First, through the correlation analysis and the mechanism knowledge, the energy storage power station key parameter and corresponding key factors affecting the parameter are determined. Secondly, in order to predict the trend of the key parameter over a period of time and improve the prediction accuracy, the MEN-TD model is constructed. Then, based on the predicted values of the key parameter, compared with the control limit in the healthy status, the fault can be pre-warned in advance. Finally, through testing on the practical energy storage power station in Zhenjiang of China, the effectiveness and superiority of the proposed MEN-TD method are demonstrated.

Dissolved gas analysis (DGA) is an important method of predicting transformer faults, and the accuracy of DGA measurements is of great significance to the evaluation of the transformer state in grid edge systems. In actual situations, it is difficult to regularly calibrate online DGA monitoring devices in a uniform way. Therefore, this paper proposes a method based on B-EMD and DBN to evaluate the validity of online DGA monitoring data and optimize the corresponding calibration plan. An analysis of actual DGA signals shows that the method proposed in this paper can effectively diagnose faults and improve the reliability of DGA online monitoring devices.

The effects of furfural generation and partitioning on the aging assessment of oil-paper insulation of power equipment were investigated. Oil-paper samples with various furfural contents were prepared using an accelerated thermal aging experiment. The mass of the furfural generated during the aging of insulation paper was calculated and used to establish the quantitative equation between the accumulated furfural and the degree of polymerization (DP) of the insulation paper. Results showed that the reciprocal of the DP value was linearly related to the amount of furfural generated by the insulation paper. Effects of temperature, moisture, and temperature on the furfural partitioning ratio between oil and paper were analyzed using a furfural partitioning experiment, and a furfural partitioning model was established. Results showed that the furfural partitioning ratio in oil was positively correlated with temperature and moisture but negatively correlated with the DP of the insulation paper. A method for assessing the age of an insulation paper by integrating the furfural generation and partitioning models was proposed and applied on a 500-kV reactor that was returned for factory maintenance. The application result indicated that the method could accurately assess the overall aging condition of the oil-paper insulation of the power equipment.

The furfural concentration in oil is a well-accepted chemical marker indicating the aging condition of power transformers. However, recent researches suggest that the furfural concentration in oil ...

A color and fluorescence turn-on H2S probe is synthesized, achieving real-time detection of H2S in pure water solution with high selectivity. Importantly, the probe is able to sense H2S gas in air via the probe-deposited test paper, which has been successfully used for food spoilage identification.

Compared with the less thunderstorm region and middle thunderstorm region, the lightning protection safety of UHV AC substation located in more thunderstorm region and thunderstorm activity special strong region should be paid more attention to. The lightning invasion wave over-voltage protection must be strengthened. Lightning arrester is the main measure to limit the lightning inrush wave over-voltage in UHV AC substation, which directly determines the lightning impulse insulation level of substation equipment and the lightning protection safety of equipment. In this paper, the lightning arrester configuration of UHV AC substation which has been completed and put into operation so far was comprehensively investigated. On the premise that the main transformer side and line side must be equipped with lightning arrester, the configuration of bus arrester was focused on. Then, taking Changtai substation as example, which are located in the thunderstorm day as high as 65 days, a special study was carried out on the configuration mode and quantity of lightning arresters in substation, and the lightning protection safety evaluation method was given. Based on the basic conditions of Changtai station, the lightning protection safety calculation and evaluation of substation were carried out by using simulation calculation method. Finally, the configuration and quantity of lightning arresters in UHV AC substation located in more thunderstorm region and thunderstorm activity special strong region were put forward.

The power IoT (Internet of things) realizes the holographic perception of power grid state, and drives the data sharing and application through the Internet of things platform, data center and business center, providing a more comprehensive data base for the construction of equipment state maintenance. Edge computing provides a real-time processing method with low delay for equipment condition monitoring, it also provides a more comprehensive data basis for equipment condition maintenance. The paper proposed a framework design of equipment condition based maintenance knowledge base using machine learning. The combination of production rules and Petri net model are used to realize knowledge compilation and reasoning, and complete the intelligent decision of equipment fault repair.

With the widespread popularity of power Internet of Things (PIoT), the data collected from smart meters are growing explosively, which makes the calculation task of power data more and more complex. In order to improve computing power and maximize resource utilization, an offloading decision algorithm based on weighted K-nearest neighbor (WKNN) is proposed. It first collects the training set required by the WKNN-based algorithm, including the Received Signal Strength (RSS) required for offloading, the transmission rate, and the load balance of the Access Point (AP), and then the Euclidean distance between the training set and the sample is weighted by Gaussian function. Finally, the result with the largest K similarities in the training set is the offloading result. The simulation results show that the proposed algorithm reduces the offloading delay of the computing tasks and improves the resource utilization rate effectively when the number of meters increases in the network, which ensures that the resources of the mobile edge computing (MEC) servers in the system can be effectively and evenly utilized.

Lithium iron phosphate batteries have become the main choice for energy storage units in electrochemical energy storage due to their high safety, excellent electrochemical performance, long cycle life, and environmental friendliness. However, lithium-ion batteries inherently have safety risks. The thermal runaway of a single battery in a closed space may cause a chain reaction of surrounding batteries, and may ignite the generated combustible gas, causing serious explosion accidents. In this paper, the explosion characteristics under different initiation points of pressure relief plates are studied. The results show that the peak overpressure variation range of different detonation points in the prefabricated chamber is 1∼1.6 times the hatch opening pressure, where the peak overpressure of the detonation at the near end of the hatch is lower than that of the detonation at the distal end, reflecting the role of the detonation when the explosion energy is released to the outside of the chamber earlier. The above study can provide a reference basis for the safe operation of prefabricated cabin type energy storage power plant and the promotion of its application.

The microwave-based liquid sensors are indispensable techniques which can provide many advantages such as low cost, real time and label free for biological or chemical measurements. Metamaterials are well suitable for sensing applications due to the narrow spectral feature. A flexible plasmonic microfluidic sensor has been proposed to obtain a non-invasive measurement of different liquid solutions. The resonance frequency changes from 5.133 GHz to 5.006 GHz, with a frequency shift of 127 MHz, when the microfluidic channel is filled with deionized (DI) water.

In this letter, a dual-band bandpass filter using sixteenth-mode substrate integrated waveguide (SMSIW) cavity and a novel ultra-wideband (UWB) bandpass filter (BPF) using eighth-mode SIW (EMSIW) cavity are presented. The TE 101 , TE 102 and TE 201 resonant modes of the SIW a circular resonator are used to design the proposed filters. The complementary split-ring resonators (CSRRs) are employed in the middle of the circular SIW cavity to produce one transmission zero (TZ), so the dual-band BPF and UWB BPF with high selectivity are realized. The proposed filters possess compact size, because of the EMSIW and SMSIW cavity. The dualband filter is fabricated in SMSIW cavity and the center frequencies are 8.49 GHz and 12.8 GHz with 3-dB FBWs 30% and 31.25%, respectively. The UWB filter is simulated in EMSIW cavity and its center frequencies are 9GHz, 11.65 GHz and 14.9 GHz with FBW of 78%. The minimum insertion losses are expected to be 0.53/0.76 dB and 1.25 dB.

In recent years, more and more people choose to travel by high-speed rail. As a result, the 2G/3G/4G/5G network under high-speed rail scenario needs to have good coverage band and high gain. In this paper, an ultra-wideband low-frequency high-gain monopole antenna is proposed. By using the meander technology and introducing the tapered structure, the proposed antenna operates over a bandwidth of 645–752 MHz and 1010–6000 MHz (VSWR < 1.8). The dimensions of the proposed antenna are 200 mm × 200 mm × 84.8mm. The antenna can be used in ultra-wideband applications.

At present, infrared detection technology is widely used to diagnose the thermal fault of substation equipment, and it is needed to use computers to intelligently handle the progressively increasing infrared images. A model based on improved Bayesian optimization to diagnose thermal fault is proposed in this paper. Firstly, in order to utilize the effective network structure of image classification, ResNet10 and ResNet14 with much smaller parameter size are created based on CNN and residual block. Secondly, Bayesian optimization based on Gauss process and expected improvement is adopted to select hyperparameter, and the constrains of validation accuracy and parameter size are set to improve the performance of the algorithm. Experiment result shows that the improved Bayesian optimization can converge faster and obtain a smaller converge value. Compared with Alexnet, VGG-16, ResNet18, the proposed model has a highest accuracy and smallest parameter size, which can diagnose the thermal fault more effectively.

The battery energy storage system (BESS) is widely used in the power grid and renewable energy generation. With respect to a lithium-ion battery module of a practical BESS with the air-cooling thermal management system, a thermofluidic model is developed to investigate its thermal behavior. The thermal model for a single battery is established and experimentally validated first, and then the thermofluidic model for this battery module is developed based on the single battery thermal model and validated by experimental data also. Simulations are performed considering the practical frequency regulation condition and some hypothetical situations with unexpectedly high heat generation rates. Thermal behaviors of the battery module under different conditions are carefully analyzed. Results show that the fans-on forced air convection cooling reduces the maximum temperature by 0.4 K and makes the maximum temperature appear in a different battery of the BESS module compared with the natural air convection cooling. Especially, the temperature monitoring strategy is studied. Due to technical and cost constraints, only a limited number of temperature monitoring points can be set and the temperature that can be monitored is the battery surface temperature or some connecting bars’ surface temperature. The rationality of the locations of different temperature monitoring points is analyzed. The obtained results clearly indicate that enough caution must be paid when setting the temperature monitoring points in practical BESSs. The bad temperature-monitoring strategy may largely underestimate the maximum temperature (by as much as 3 K under the normal frequency regulation condition, and probably much larger under harsh working conditions) in the BESS and fails at reflecting the thermal status of the BESS.

In this paper, tree diagrams and symbols in visualization technology are selected to display the security status of sensor networks, and fully mine the micro-details of the network through multi-dimensional display of monitoring target status. Time series maps are used to predict the operation trend of sensor networks in eight dimensions, and analyze network attack modes combined with image characteristics to evaluate the security situation of the Internet of Things. On this basis, a centralized wireless routing method is adopted to find the optimal path from all the sensing nodes to sink, which ensures that the sum of links’ average transmission times of the optimal path and the minimum energy consumption of data transmission are the minimum. The results show that this method can identify the state of sensor network and discriminate attack modes, and has less data transmission times and low energy consumption.

This paper proposes a model predictive control (MPC) method to tackle the power flow control of the modular multilevel converter based unified power flow controller (MMC-UPFC) under unbalanced grid conditions. The predictive models corresponding to the discrete-time models of MMC-UPFC are derived. For the shunt MMC, the d-axis and q-axis current references for the MPC are deduced to maintain the dc-link voltage constant according to the energy balance on the dc-link side. The series MMC utilizes a cost function with the voltage constraints to suppress the faulted current and make the power flow controllable, and thus avoid the spread of the fault. Moreover, it makes full use of the capacity of MMC by operating it on the voltage boundary defined by the maximum output voltage of the converter. The model is established using the parameters from a 500 kV MMC-UPFC practical project in Jiangsu, China. Simulation results demonstrate a favorable response of the MMC-UPFC based on the proposed MPC strategy under different unbalanced grid conditions.

Metallized film capacitors have the advantages of high energy density and high reliability. However, there is no research on the characteristics of metallized film capacitors in UPFC modular multilevel converter. Therefore, this paper takes UPFC sub module capacitor as an example. First, the operation of UPFC submodule capacitor is studied. Operation characteristics are extracted. Then the breakdown characteristic and temperature rise characteristic test platform is designed, and the breakdown characteristic and temperature rise characteristic test under different power supply characteristics are carried out. Finally, the results are summarized. The results show that the DC voltage amplitude, AC voltage amplitude and frequency have little influence on the average breakdown voltage of metallized film capacitor and has a rapid thermal balance without external heat dissipation.

This paper studies the insulation coordination technology of UPFC system based on the 500 kV Suzhou UPFC. Firstly, the insulation coordination characteristics, methods and principles suitable for UPFC are proposed. Then the layout scheme of 500kV UPFC arresters is designed. Thirdly, to verify the insulation coordination design, the lightning overvoltage model and internal overvoltage model of UPFC are established. The transient overvoltage and lightning overvoltage is calculated, which proves the proposed insulation design. The insulation coordination method in this paper can provide an important reference for UPFC system.

Lithium batteries have been rapidly popularized in energy storage for their high energy density and high output power. However, due to the thermal instability of lithium batteries, the probability of fire and explosion under extreme conditions is high. This paper reviews the causes of fire and explosion of lithium-ion batteries from the perspective of physical and chemical mechanism.

When models are built for transformers, it has to estimate accurately the running state of iron core in various applications. However, the classical Jiles-Atherton(JA) model is only fit for the description of isotropic steel and the given circumstances that the value of the maximum magnetic induction density is closed to the value of the saturation magnetic induction density and the electrical sources is non-harmonic. If the running state of iron core changes, for example, the maximum magnetic induction density is low, or electrical sources for the transformer is non-sinusoidal, or the model is built for anisotropy materials, there is a large error when models are built with the classical Jiles-Atherton model. For this reason, a novel method is presented to address the issue of modeling minor loops which means the value of the maximum magnetic induction density is smaller, non-centered local hysteresis loops which is non-centered and the effect of anisotropy with the original JA model. The minor loops and non-centered local hysteresis loops are evaluated via an expression in which the parameters of model above are related with value of the major loop model. The four parameters of JA model are applied in the minor hysteresis loops and the local loops which is non-centered. The effect of anisotropy on JA model is considered with an additional parameter quantum number.

In recent years, high voltage overhead transmission line wind partial flashover accidents occur frequently, it seriously affected the power system safe and stable operation. The reason may lie in the fact that the calculation accuracy of the wind deflection angle and the minimum air clearance is not enough, it will lead to the tower design considerations are not sufficient, so now the transmission line will be real-time monitoring in order to get more realistic data. In this paper, the calculation of the minimum air clearance under the traditional wind angle and two-dimensional model is described first. Then, a real-time three-dimensional model of the minimum air clearance is proposed for the real-time monitoring system. And the model is compared with the two-dimensional model to verify its accuracy.

The oil-paper insulation of converter transformer withstands a long time electrical aging by combined AC-DC voltage and thermal aging during operation. The aging failure mode of converter transformers insulation exhibits a great difference with that of AC transformers. In this paper, a set of accelerated thermal aging experiments at 130 °C were designed, oil-paper specimens were aged for 5, 10, 20 and 35 days, respectively. The unaged oil-paper specimens were also prepared for comparison. The breakdown voltage and failure time of oilpaper specimens of different aging times at AC and combined AC-DC voltage were measured, respectively. The relationship between the failure time and aging time is obtained by using Weibull analysis method. The experiment results show that the breakdown voltage of oil-paper specimens all decrease not much with the increase of thermal aging time. The oil-paper specimens have a longer failure time at combined AC-DC voltage compared with that at AC voltage.

The triggering discharge behavior of the rail gap influences the jitter of discharge delay and inductance of the spark switch due to the formation of multiple spark channels in the rail-gap switch, which is related with the development of avalanche in the discharge process under the nanosecond triggering pulses. In this paper, the PIC/MCC method is used to investigate the avalanche development under a triggering pulse. A model of intershielding is proposed in the PIC/MCC method considering the effect of the space charges. From the simulation and experimental results, it has been clarified that the avalanche process can be controlled by the statistical delay time of the effective primary electrons. The intershielding model can also explain the effect of the rise time of a triggering pulse on the avalanche development.

The nanosecond single pulse was employed here to generate a large volume glow discharge between the wire-plane electrodes in air. In order to find requirements on pulse waveform for generation of a large volume discharge at atmospheric pressure, the effect of pulse risetime, pulse width, and amplitude on glow discharge has been widely investigated in this paper. Results reveal that a large volume glow discharge can be generated in an inhomogeneous electric field under the single pulse with the faster risetime, the lower peak amplitude. The pulse width has almost no influence on the density of glow discharge, but which has a great influence on the transition from glow discharge to streamer discharge. A model of inter-shielding-effect has been proposed to explain the influence of waveform parameters on pulsed glow discharge.

Circuit breaker is a very important control and protective equipment in the field of grid system. When the electric equipment or circuit are in accident, the relay protection and circuit breaker will cut the fault section from grid rapidly and guarantee the grid running safely. However, there are a mount of high voltage circuit breakers. According to the traditional planned overhaul model to inspect circuit breaker, there will be some phenomenons such as large workload, high expense and so on. At the same time, different circuit breakers need different signal sources. During maintenance, this character will lead to the waste of human resource and cause artificial errors. Therefore, the paper presents a new standard signal source of circuit breaker. It realized the integrated, informational and intelligent reform for the various kinds of signal sources. Utilize standard signal source to realize the calibration for common equipment can reduce the maintenance workload and improve the pertinence of maintenance. It is very helpful for improving the running reliability and economy of electric equipment.

Transformation equipment on-line monitoring device aims at monitoring substation equipment operation parameters. Through internal network, the data will be transported to the on-line monitoring platform of electric power internal network to provide maintenance basis for maintenance department. While the existing calibration method needs professional personnel carrying relevant calibrators and conducting contrast calibration on site. In order to make up for deficiency of existing substation on-line monitoring device calibration, such as instruments isolated with each other, instrument control and data management low automation, data contrast, retrieval and archiving is inconvenient, personnel requirement large and so on. This paper presents a new method for intelligent check of transformation equipment condition monitoring device based on wireless communication technology and computer control technology. It can promote the accuracy of calibration greatly and provide a powerful guarantee to grid reliable operation.

The calibration of SF6 gas density on-line monitoring device needs to simulate different pressure environment to calibrate the data accuracy of the on-line monitoring device. At present, the simulation of different pressure environment is conducted by artificial cranking bar to change the stroke of cylinder piston to realize the aim of change the gas pressure. Generally, technical personnel take calibration device to the field, select a suitable pressure, connect the checked device to test button and conduct the contrast calibration. Based on above operation, multi-group data of the checked on-line monitoring device can be obtained. While this method depends on artificial manual operation, squander time and vigour and can not set pressure value exactly. In order to make up for deficiency of existing problems, the paper presents a calibration device on SF_6 gas density monitoring equipment. The calibration device can make the calibration procession conducted automatically through controlling the pressure and its lasting time automatically. The use of the device can effectively complete calibration and improve the quality of work.Facts show that it can provide a powerful guarantee to grid equipment reliable operation.

Pure SnO2and NiO doped SnO2nanostructures were successfully synthesized via a simple and environment-friendly hydrothermal method. X-ray powder diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), and X-ray photoelectron spectra (XPS) were used to investigate the crystalline structures, surface morphologies and microstructures, and element components and their valences of the as-synthesized samples. Furthermore, planar chemical gas sensors based on the synthesized pure SnO2and NiO/SnO2composites were fabricated and their sensing performances to hydrogen, an important fault characteristic gas dissolved in power transformer oil, were investigated in detail. Gas sensing experiments indicate that the NiO/SnO2composites showed much higher gas response and lower working temperature than those of pure SnO2, which could be ascribed to the formation of p-n heterojunctions between p-type NiO and n-type SnO2. These results demonstrate that the as-synthesized NiO/SnO2composites a promising hydrogen sensing material.

Aiming at the existing problems such as heavy workload and low efficiency of intelligent substation state monitoring device calibration, combined with the current information technology and intelligent technology, his paper presents a vehicle-borne intelligent verification system. The system adopts vehicle as the platform and transport data through GPRS/3G and MIWAVE wireless network. From the point of function optimization, information interaction and intelligent monitoring, the system realizes the integrated, information and intelligent transformation of kinds of standard signal source device and monitoring equipment for calibration. The use of the system can effectively complete calibration and improve the quality of work. The system has completed the calibration of many 500kV, 220kV substations monitoring devices successfully. Facts show that it can provide a powerful guarantee to grid equipment reliable operation.

In the study of electrical life of the vacuum circuit breaker (VCB) condition assessment, the traditional fuzzy comprehensive evaluation model only considers fuzziness and ignored randomness of uncertainty, while the cloud model considers fuzziness and randomness of uncertainty at the same time; we establish a new condition comprehensive model based on cloud model. Dig the new index parameter, get the actual evaluation vectors using cloud formula, and the entropy method is applied to get the objective weight of each indicator relating to the actual data's change rate at the same time. Finally, the cloud model instead of the traditional range is used to dividing the insulating electrical life state level of circuit breaker. The value of each characteristic element is regarded as a cloud droplet which is used to calculate the membership degree of each grade cloud. Through case analysis we find that the result based on the new model is closer to the actual state.