To monitor the dynamic characteristics of the receiving AC system and assess the risk of wideband oscillation in LCC-HVDC without additional equipment, this paper presents a non-invasive impedance wideband measurement method for LCC-HVDC systems. Unlike existing invasive methods, such as single voltage/current or wideband harmonic disturbance injections, the proposed method does not inject harmonic disturbances into LCC-HVDC, thereby avoiding the potential resonance risk. Furthermore, the proposed method introduces curve similarity and a dynamically adjusted time-step sampling scheme. First, this paper discusses the interaction principles between the LCC system and the receiving AC system. Secondly, this paper establishes the harmonic state space (HSS) impedance model for LCC-HVDC, based on HSS theory, focusing on the unipolar earth loop topology. Subsequently, a non-invasive impedance wideband measurement method is proposed to observe the operating state of the system, judge the risk of wideband oscillation, and analyze the interaction and wideband oscillation characteristics between the LCC system and the receiver network through impedance analysis. Finally, an example of CIGRE standard model is used to verify the correctness and practicality of the proposed method.

Based on the HSS theory and the concept of digital modulus, this paper introduces a non-invasive impedance wideband measurement method. Firstly, the system topology and the interaction principles of the LCC-HVDC unipolar earth loop subsystems are detailed. Then, the impedance modeling of the LCC-HVDC system is elaborated, and the HSS impedance mathematical model for wideband measurement is derived based on the system's topology. Finally, the system model is constructed in MATLAB/Simulink using parameters from the CIGRE standard model, and the impedance calculation model is applied to measure the impedance of the LCC system. Combined with the measured wideband impedance curve, the interaction between the LCC system and the receiving network, as well as the wideband oscillation characteristics, were analyzed using the generalized Nyquist criterion for stability. At the same time, the Pearson correlation coefficient was introduced to capture the similarity of impedance curves with high granularity, thereby exploring the adaptability of impedance models of different orders and the factors influencing the oscillation risk. It offers theoretical support for the measurement methods used in the engineering application of impedance measurement, and appropriately expanding the permissible error range in the amplitude-frequency intersection can enhance the universality of impedance analysis methods.

The main contributions and conclusions of this paper are summarized as follows: (1) A non-invasive LCC-HVDC impedance model and impedance wideband measurement method are designed, which does not require injecting harmonic disturbances into the system. The Pearson correlation coefficient between the measured impedance curve of the 13th-order model and the fitted curve from active measurements is 0.998 3, which is very close to 1. This high value indicates that the accuracy of the measurement model is high, suggesting a close match with the actual impedance characteristics. (2) By analyzing the similarity matrix of measurement curves from models of varying orders, it is observed that the Pearson correlation coefficients for the phase measurement curves are closely matched for orders h=3, h=7, and h=11, with the highest deviation being within 0.2%. Consequently, the acceptable error margin for amplitude-frequency intersection points may be suitably broadened. Considering computational efficiency, a lower-order measurement model within the range of 3 to 13 can be selected. (3) The characteristics of the measured wideband impedance curve of the system can be observed under two conditions: adaptive adjustment of the sampling time step and variation in transmission power. Adaptive adjustment of the time step is not only conducive to accurately identifying the crossover points of the amplitude-frequency response but also reduces the computational load and minimizes storage requirements. Conversely, an increase in transmission power raises the risk of system instability.

Hydrogen energy system, with its inter temporal and spatial transfer characteristics, shows great potential for enhancing the resilience of distribution grids. However, few literatures have considered the inter temporal and spatial flexibility of hydrogen energy system and the inter-regional support capability of mobile emergency resources, and the post-disaster collaborative recovery mechanism of multi-region electric-hydrogen integrated energy system (MR-EH-IES) is still unclear, which makes it difficult to exploit the inter-regional support potential of mobile resilience resources. Aiming at the above problems, this paper proposes a post-disaster recovery strategy for MR-EH-IES with cross-regional resource sharing.

This paper firstly proposes a two-layer MR-EH-IES disaster recovery framework based on the idea of “intra-regional autonomy, resource integration, inter-regional sharing”. In the lower layer, the electric-hydrogen integrated energy system (EH-IES) carries out intra-zone autonomy. The potential of synergistic cooperation between mobile electric energy storage, hydrogen fuel power generation vehicles, maintenance personnel and hydrogen energy system in disaster recovery is fully considered, and the EH-IES disaster recovery model considering the synergistic scheduling of distributed power sources and maintenance personnel is established. At the upper level, the joint disaster resilience center carries out the coordinated allocation of mobile resilience resource (MRR). Starting from the disaster recovery mechanism of different types of MRR, the key factors affecting its allocation are analyzed, the MRR disaster recovery mechanism considering cross-region support is proposed, and the MRR disaster allocation model considering cross-region resource sharing is established. Then, based on the above framework and strategy, the MR-EH-IES two-layer disaster recovery model considering cross-region resource sharing is proposed.

The simulation analysis shows that the total cut-load loss of MR-EH-IES decreases by 22.4% after considering cross-region resource sharing, in which the cut-load loss of region 1 and region 3 increases slightly by ¥1.3×10³ and ¥7.3×10³, respectively, while the cut-load loss of region 2 and region 4 decreases by ¥157.8×10³ and ¥62.5×10³, respectively. Specifically, in the early stage of disaster recovery, when the mobile power supply left from region 1 and region 3 to support region 2 and region 4, the weighted load recovery rate of region 1 and region 3 showed a short drop, with the maximum drop of 0.5% and 1.1%, respectively, but both of them were higher than the weighted proportion of important loads. Meanwhile, the load-weighted recovery rates of region 2 and region 4 increased significantly, with maximum enhancements of 11.0% and 4.2%, respectively. In addition, when region 1 and region 3 were restored, idle mobile power supplies and maintenance personnel were the first to support other regions.

The following conclusions can be drawn from the simulation analysis: (1) The post-disaster recovery strategy proposed in this paper is able to rapidly restore the supply of important loads and reduce the system damage in the early stage of disaster recovery through the reasonable allocation of mobile emergency resources, and improve the utilization rate of mobile emergency resources in the later stage of disaster recovery. (2) The inter temporal and spatial flexibility of the hydrogen system and the long tube trailer can increase the energy transfer channels of MR-EH-IES in time and space scales, giving full play to the ability of hydrogen energy system to support the power grid in disaster recovery.

When multiple EMUs are simultaneously in a light-load starting condition within the traction network, it can lead to low-frequency oscillations in the traction network voltage. In severe cases, this may trigger traction locking, which poses a risk to the operational safety of high-speed trains. To address the issue of low-frequency oscillation, this study proposes a method based on virtual impedance for its suppression.

First, the impedance model of the EMUs-traction network coupling system is derived, and its stability is analyzed using the impedance ratio stability criterion and the Bode diagram. Second, based on the stability criterion, virtual impedance is incorporated into the EMU control strategy to correct the impedance characteristics of the load subsystem, thereby proposing a low-frequency oscillation suppression method. Third, an adaptive control method for virtual impedance is designed to handle the complex and dynamic working conditions, enabling the system to adjust the virtual impedance parameters and enhance the effectiveness of the suppression method. Finally, the proposed control strategy is compared with the traditional approach through a low-power experimental platform, validating the effectiveness of the suppression method.

The results of the system stability analysis indicate that the logarithmic amplitude-frequency characteristic curve of the system impedance ratio is significantly lower than 0 dB when only one unit (m=1) is connected to the traction network, and the absolute value of the system impedance ratio |T_sn(s)| is much less than 1, suggesting system stability. As the value of m increases, the amplitude-frequency characteristic curve approaches 0 dB, resulting in a decline in system stability. When m=6, the amplitude-frequency characteristic curve crosses 0 dB at 7.032 Hz, and the phase angle at the crossover frequency (f_c) is 182°. The absolute value of the phase angle exceeds 180°, and the system impedance ratio |T_sn(s)| does not meet the condition of being significantly less than 1, indicating an unstable state. Simulation results with the virtual impedance control strategy indicate that when six EMUs are connected to the traction network at the same time, when the virtual impedance R_p values are 10 Ω, 5 Ω, 2 Ω and 1 Ω respectively, the system voltage and current reach a steady state at 1.6 s, 1 s, 0.3 s, and 0.2 s, respectively. The suppression effect improves as the virtual impedance decreases. The simulation results with the adaptive virtual impedance control strategy show that when six EMUs are connected to the traction network, the system reaches a steady state in approximately 0.5 s. The voltage regulation time for the DC side of the EMUs is 0.46 s, with an overshoot of 37.71% and a post-stabilization voltage fluctuation of 58 V. Subsequently, one EMU with adaptive virtual impedance control is added every 2 seconds, resulting in a total of 11 EMUs. The system remains stable, and the virtual impedance value is reduced to 4.61. The comparative experimental results indicate that, after transitioning from the traditional control strategy to the adaptive virtual impedance control strategy, the system can rapidly recover from a low-frequency oscillation at approximately 7 Hz. Furthermore, the AC-side voltage stabilizes at 20 V, while the DC-side voltage remains stable at 40 V.

Based on the analysis, the following conclusions can be drawn: (1) A higher impedance ratio between the two sides of the EMUs-traction network coupling system results in decreased system stability. When the impedance ratio does not meet the stability criterion, system instability is induced, leading to low-frequency oscillations. (2) The incorporation of parallel virtual impedance in the control strategy for the EMU's four-quadrant converter can correct the impedance characteristics of the load subsystem, enhance system stability, and suppress low-frequency oscillation. (3) The adaptive virtual impedance control method can autonomously adjust the virtual impedance value based on the intensity of voltage oscillations on the network side of the EMU, thereby suppressing low-frequency oscillations under varying load conditions, improving the adaptability of the control strategy, and ensuring the stable operation of the EMUs-traction network coupling system across different operating conditions.

Gas insulated switchgear (GIS) faults occur frequently after live operation, and according to statistics, the faults after live operation account for 60% of the total. The strong shock vibration generated by GIS live operation not only produces metal contaminants, but also activates latent particles, which seriously affects the insulation safety of GIS. The physical effects generated by GIS live operation are complicated, mainly including shock vibration, overvoltage, residual voltage and other physical effects. The mechanism by which the particles inside the GIS are affected by switching operation is unknown and is extremely dangerous. The mechanism of switching operation on particles in GIS is unknown and extremely dangerous.

In order to solve the problem that particles are prone to discharge after live operation, and to clarify the motion mechanism of spherical metal particles in GIS after impact vibration, this paper carries out the following work: firstly, we study the propagation process of vibration inside the cavity, and then we carry out the forced correction on the basis of the flexible boundary three-dimensional cylindrical vibration model, which improves the equivalence with the actual working conditions. The propagation form and the "ripple" propagation behavior of shock vibration in GIS are revealed, and it is clarified that the vibration wave is divided into P-wave and S-wave during the propagation process, the P-wave propagates faster than the S-wave, and the S-wave plays a major role in the jumping of the particles. And then the energy transfer process of the cavity and particles after being vibrated is analyzed, and the excitation effect of the shock vibration on the system is analyzed in the form of energy as a link. The energy transformation of the system after the vibration work is clarified, the cavity-particle kinetic energy transfer conservation model is constructed, and the activation conditions of the particles are defined with the help of the jumping field strength, and the activation criterion of the particles subjected to vibration is proposed. On the basis of the aforementioned research, the whole process model of particle motion under typical vibration excitation of live operation is established by considering the particle charge motion characteristics and collision random characteristics, and verified by experiments. On the basis of the validation, the correction considering the microscopic force is carried out, and the error is analyzed from the microscopic point of view.

The model fully considers the influence of different particle sizes and materials on the particle dynamics, and is more equivalent to the actual working conditions than the method defined by the recovery coefficient. Finally, it is clarified that the vibration excitation can activate the motion of the particles, and the influencing factors of the motion behavior of the particles are explored. Combined with the propagation and attenuation characteristics of vibration, the criterion of critical activation distance of particles under charged working conditions is proposed, and the changes of critical activation distance of particles under different factors are calculated. The study shows that the critical activation distance increases logarithmically with the increase of voltage amplitude and vibration intensity. This study provides support for solving the problem that particles are very likely to cause discharge faults after GIS live operation.

With the development of the national unified electricity market, the market scale has gradually increased. Take inter-provincial medium- and long-term power transaction as an example, the number of market participants is over a thousand. The similarity of the bid prices of numerous market participants is likely to lead to multiple purchasing and selling pairs having the same social welfare. As a result, the market clearing problem that maximizes social welfare may have multiple optimal solutions. To ensure the effectiveness and fairness of market clearing, the multi-level objective sequential optimization should be implemented under multiple-solution scenarios. However, the existing methods based on multi-objective optimization cannot balance effectiveness and efficiency. To address this issue, take inter-provincial medium- and long-term power transaction that may have multiple solutions as a research objective, an efficient multi-level objective sequential optimization method is proposed in this paper. The main contributions are illustrated as follows:

First, the market clearing model with multi-level objective sequential optimization is established. Four objective functions are considered according to the industrial practices, including maximizing social welfare, maximizing transaction volume of renewable energy, maximizing total transaction volume, and equally distributing tradable power among purchasing and selling pairs with the same social welfare. Market clearing models considering the aforementioned four objective functions are separately established. The optimal objective functions of the preorder model are used as the operating constraints of the subsequent model to ensure the optimality of the objective functions with high priorities. By sequential solving these four market clearing models, the market clearing effectiveness and fairness can be guaranteed even under multiple-solution scenarios.

Second, the multiple-solution judgment auxiliary optimization model for the market clearing problem is established based on the bound constraints of the optimal solution, according to which the multiple-solution characteristics of market clearing problems can be recognized. The recognized multiple-solution characteristics can provide support for market operators to design the measure for handling multiple-solution scenarios. For instance, more objective functions can be introduced if multiple-solution scenarios cannot be effectively avoided after the sequential optimization of four objective functions. Besides, regarding the computational burden caused by the solution to four market clearing models, the multiple-solution judgment auxiliary optimization model is embedded into the sequential optimization process to simplify the clearing process by avoiding unnecessary optimization.

Third, to meet the calculation efficiency demand, the lossless acceleration method for market clearing based on solution information of the preorder model is proposed. For the market clearing models with multi-level objective functions, the optimal solution of the preorder model is used as the high-quality initial feasible solution of the subsequent model, which can guide the warm-start accelerating process of the subsequent model without the loss of accuracy. For the multiple-solution judgment auxiliary optimization model, the optimal solution of the preorder model is used as the initial feasible solution. Based on this, the termination criterion for the calculation process is established according to the comparison between the initial objective function and the current objective function. In this way, the judgment process can be accelerated without affecting judgment accuracy.

Finally, case studies based on practical inter-provincial medium- and long-term transaction data in China demonstrate that the proposed method can greatly improve the market clearing effect for the subordinate objectives while ensuring the optimality of the primary objective. In addition, benefiting from the proposed model solution acceleration strategy and the sequential optimization process simplification strategy, the market clearing efficiency can be improved by 37 times without the loss of accuracy under the typical scenario.

Electric car-sharing (ECS), as a component of the sharing economy, is of great significance in alleviating urban traffic congestion and reducing carbon emissions. Electric car-sharing system (ECSS) involves multiple entities such as users, operators and power grids. At present, one-way network operation mode is mostly adopted. Users can pick up and return vehicles at any network specified by the operator, and the operator arranges for vehicles in the network to connect to the power grid for charging. The optimal scheduling of urban electric car-sharing system is needed to solve the increasingly prominent problems such as imbalance between user demand and station cars supply, and mismatch between cars charging and grid operation status. Current strategies for vehicle scheduling are high-cost and coercive, while charging scheduling only ensures vehicle availability, lacking consideration of the impact of vehicle charging on the grid. Addressing these issues, the application of low-cost, non-coercive nudging methods from behavioral economics in the field of ECSS was explored and a coordinated user nudging and charging optimization scheduling method for urban shared electric vehicles was proposed.

Firstly, at the level of vehicle scheduling with supply and demand balance, nudging was used to guide user dispatch. Based on actual surveys, the main factors influencing users' choice of return points were identified, and nudging schemes for strong and weak scenarios were designed based on a framework of motivational and cognitive nudges. The revealed fuzzy comprehensive evaluation method (r-FCEM) was used to evaluate the user responsiveness to the nudging schemes, determining the probability of users participating in vehicle dispatch, thereby relocating vehicles from surplus supply points to stations with high demand, and improving operators' rental service income. And then we tested the feasibility of the nudging scheme and found that the design of the nudging scheme for users' choice of return stations can effectively improve user responsiveness and has a certain degree of feasibility.

Secondly, for the charging scheduling problem, nudge guided users to return vehicles to low-cost, low-carbon stations, and charging optimization model considering economic and low-carbon factors was designed. Based on deep Q network (DQN), an ECSS operating environment was constructed to simulate the interactions among users, operators, and the grid. After training process, coordinated solutions for nudging and charging optimization were obtained. This resulted in a dispatch plan for vehicle scheduling and a charging schedule for charging optimization.

The research first examined the number of vehicles and the travel and arrival volumes at typical stations under nudged and non-nudged scenarios, demonstrating the impact of nudging on supply-demand imbalance and charging optimization issues. It was found that user nudging can alleviate phenomena of under-supply and surplus, guiding vehicles to low-cost, low-carbon stations. Then, four scenarios were set up, revealing that single vehicle scheduling and charging scheduling alone offer limited improvement to the economic benefits of ECSS. It is necessary to solve nudging and charging scheduling in a coordinated manner to enhance user responsiveness through non-coercive strategies, reduce grid load fluctuations, and comprehensively improve the economic efficiency of operators while addressing vehicle scheduling and charging optimization problems.

Future work on nudging will expand the scope and number of questionnaire surveys to further validate the feasibility and effectiveness of practical applications. Algorithmically, future research will focus on refined modeling for large-scale ECSS operations and seek better algorithms to adapt to large-scale scenarios.

The increasing deployment of wind turbines in challenging environments has led to the prevalent issue of converter faults, which significantly affect the reliability and efficiency of wind power systems. Given the critical role that the converter plays in optimizing the wind power conversion process, detecting and identifying open-circuit fault in wind converter is essential for maintaining operational integrity and maximizing energy output. Current fault identification methods often suffer from limitations related to robustness and computational complexity, necessitating improved solutions. To address these shortcomings, this paper introduces an innovative fault identification method that integrates analysis of the direct current (DC) bus voltage and rotor current characteristics. It can accurately recognize the single and double tube faults of converter power tubes.

Firstly，Fault detection is facilitated by the fact that the DC bus voltage signal is easily accessible, independent of the load and control strategy. Extraction of DC bus voltage edge gradients using mathematical morphology as a feature to detect the occurrence of faults. Secondly, the Pearson correlation coefficients of the rotor side currents are calculated to analyze waveform characteristics. The coupling relationship between the three-phase currents is theoretically deduced, and it is proved that the Pearson correlation coefficients between the two-phase currents are significantly different under different fault conditions, enabling precise identification of the fault phase. Moreover, the location of the fault bridge arm is determined using the average value of the current, enhancing the accuracy of fault identification. Finally, the decision function is used to locate the faulty power tube and realize the fault classification.

Simulation results of the open-circuit fault model of doubly-fed wind power converter show that the proposed method in this paper can accurately determine the occurrence of faults and locate the position of power tubes. By comparing under large data sets, it is found that the proposed method improves the accuracy while maintaining a shorter detection time compared to other methods, which is more practical and reliable. The simulation results show that the wind speed fluctuation has a negligible effect on the DC bus voltage and rotor current, and no fault occurrence is detected, while the current characteristics are stabilized in the range of the fault-free case, which indicates that the proposed method can overcome the interference of wind speed fluctuation. By simulating voltage dips to model the load fluctuations, it is found that the fault detection module misjudges the occurrence of faults, and the current characteristics is small affected but similar in size. It is judged that no faults have occurred, so the fault identification module can be used as a verification of fault detection. A Gaussian white noise with a signal-to-noise ratio of 20 dB is also added to the acquired voltage and current data, and the results show that the proposed method is not disturbed by noise.

The following conclusions can be drawn from the simulation analysis: (1) Compared with existing methods, the method is not only simple and effective in calculation, but also has a higher accuracy rate. (2) The fault detection method based on mathematical morphology utilizes the DC bus voltage, which is easy to obtain data and rapid to detect, and is not affected by noise. (3) The Pearson correlation coefficient-based fault classification method classifies the rotor three-phase currents according to their waveform correlation, and the consistency of theoretical and simulation results shows that the method is effective and of practical significance, and the method has strong robustness.

As the penetration rate of renewable energy sources increases, the stability mechanisms of the power system are constantly changing. The double-fed induction generator (DFIG), as a mainstream renewable energy equipment, its stability is of great significance to the safe operation of the power system. The phase-locked loop (PLL) plays an important role in synchronization, but there has been less research on simultaneously considering the dynamics of the phase-locked loop and the power balance loop. Moreover, the small-signal synchronization mechanism of DFIG within rotor speed timescale needs to be further analyzed.

Firstly, the transient model of single-DFIG infinite-bus system is constructed within the rotor speed scale. The simplified model is compared with the full-order model by Matlab/Simulink, and the results show that they match very well. Then, through bifurcation analysis, it is found that the system would experience small disturbance instability under weak grid condition. And it manifests itself in the form of low-frequency oscillatory instability. Furthermore, through the dominant modal analysis, it is found that the dominant unstable loop is the power balance loop.

In order to analyze the small-signal synchronous instability mechanism of the system, the model is linearized around the operating point. The linearized model and the full-order model are compared using Matlab under small disturbance, and the results validate the rationality of linearization. The power balance loop dominates the instability, making it considered as the core loop. Therefore, the Heffron-Philips model of the system is established for analyzing the small-signal synchronous stability mechanism. Based on the complex torque coefficient method, the terminal voltage control loop plays a dominant role by introducing negative damping. And by studying the transfer function of the PLL, it is found that the PLL with typical parameters has a negligible impact on the system in the rotor speed scale, and can be approximately regarded as a constant.

Finally, the parameters of the active outer loop and the reactive outer loop are analyzed. With the changing of the grid strength, the damping torque and synchronizing torque of each branch are quantitatively calculated. It is found that increasing the proportional coefficient of active outer loop and decreasing the integral coefficient will improve the stability of the system, and increasing the proportional/integral coefficient of the terminal voltage control loop will benefit the stability of the system. These analyses have been verified through simulations and experiments.

The conclusions of this paper are as follows: (1) In the rotor speed scale, the small-signal synchronous instability of the single-DFIG infinite-bus system is dominated by the power balance loop (active outer loop and rotor dynamic), rather than the PLL. (2) By constructing the Heffron-Philips model, it is found that the synchronous phase ∆θ_pllis approximately represented by an algebraic expression of the state variable ∆ω_r/∆θ_rof the rotor. The essence of synchronous instability lies in the instability caused by the state variable of the energy storage element.3) Using complex torque coefficient method, it is found that the terminal voltage control loop is the main factor that introduces negative damping. Through the analysis of the influence of parameters, it is found that increasing the proportional coefficient of the active power outer loop and decreasing the integral coefficient will improve system stability, and increasing the proportional/integral coefficient of the terminal voltage control loop will be beneficial to system stability.

ZnO-based functional ceramics are widely used in the fields of varistor, thermistor, and gas-sensing. However, the temperature required for the preparation of ZnO-based functional ceramic is still high (>1 000℃). As a result, the additives that lead to modulating the properties of ceramic materials are limited to inorganic fillers. Conventional sintering leads to excessive growth of ZnO grains, which makes it difficult to achieve the miniaturization requirements of ZnO-based functional ceramic devices. Cold sintering process (CSP) enables the densification of ceramic materials at temperatures of below 300°C, thus providing the possibility for grain boundary engineering using ceramic materials as the matrix with organic polymer fillers or organic/inorganic composite fillers.

In this paper, zinc oxide (ZnO)-polytetrafluoroethylene (PTFE)-based ceramic composites were prepared by CSP. Based on the above cold sintering conditions, high-density (>97%) ZnO-PTFE composite ceramics were prepared with ZnO as the matrix and polytetrafluoroethylene (PTFE) as the filler. The electrical properties of the ZnO-PTFE specimens showed better non-ohmic characteristics at the polymer content of 15%, the breakdown field and nonlinear coefficient of the composites can reach 933.68 V/mm and 5.74. The breakdown field is 6.92 times higher than the classical five-element formulation of ZnO varistor (135 V/mm), but the nonlinear coefficient is low. Microstructure observation and impedance performance testing showed that the PTFE phase limits the grain growth and increases the ceramic grain boundary impedance. PTFE at grain boundaries can induce the formation of varistor properties of ZnO-based composite ceramics, and improve the flexibility of ZnO ceramics.

Further, the effects of metal oxides and PTFE on the microstructures and electrical properties of ZnO-PTFE based composites were investigated. The results indicate that a high relative density of over 97% was achieved for ZnO-PTFE-based composites doped with PTFE or co-doped with PTFE and metal oxides (CoO, Mn₂O₃). It is found that the electrical properties of ZnO-PTFE-based composites were significantly enhanced with the co-doping of PTFE, CoO, and Mn₂O₃. Specifically, the breakdown field and nonlinear coefficient of the composites were improved to 3 555.56 V/mm and 13.55, respectively. The J-E results show that the electrical conduction of the ceramic composites were dominated by the thermionic field emission at grain boundary. Moreover, the elastic modulus of the ceramic composites decreases greatly with the addition of PTFE and then increases after doping metal oxides (CoO, Mn₂O₃).

This study demonstrates that CSP provides a new route to fabricate ceramic-polymer-based composites and modulate their properties.

During the long operational time, porcelain insulators are subjected to a synergistic effect of the electrical, thermal, mechanical stresses, and environmental factors, which causes insulation degradation and lead to low and zero resistance insulators. Compared to traditional methods, infrared imaging has been widely used in the detection of deteriorated insulators and surface contamination because of its advantages of non-stop operation, non-contact and anti-electromagnetic interference. However, there is limited research on the impact of contamination on the heating characteristics of degraded insulators. Moreover, there is a lack of research on the effects of different types of contamination (category A and category B) on the heating characteristics of the insulators and the infrared detection of degraded insulators. In response to the above issues, the effects of contamination level, deterioration resistance and the location of deteriorated unit on infrared detection of the insulators were investigated through field tests and simulation analysis, obtaining the heating patterns of deteriorated insulators under different pollution conditions.

Firstly, the relationship between temperature rise, deterioration and surface contamination was explored through a heating model of porcelain insulator. Secondly, a test platform was built to simulate the operating conditions of 110 kV insulators, and the infrared imaging patterns of insulator strings were analyzed by changing the level of contamination resistance of deteriorated insulator, and the position of degraded insulators in the string. Finally, a thermal-electric coupling model of the insulator was established using finite element method to analyze and calculate the temperature distribution of insulator strings under the combined effects of dielectric loss, conduction current and heat conduction. This model is then used to validate the experimental results.

The results show that the temperature rise of the insulator in the string initially increases and then decreases with the decrease in its resistance. The maximum temperature rise and temperature growth rate of degraded piece with the same resistance value located at the high-voltage end are higher than those of degraded piece located at the medium-voltage end and the ground end, with temperature change rates of 0.093, 0.04 and 0.06, respectively. The overall temperature of steel cap increases with the increase in category A contamination. When the surface wet contamination is relatively light, the temperature variation rate range of each piece in the string is 0.014~0.107, while under severe wet contamination, it ranges from 0.087 to 0.12. The conductivity of fog water (category B contamination) has a significant impact on the temperature rise of the insulator, which increases with the increment of fog water conductivity. Taking the temperature rise under no salt fog condition as the benchmark, the overall average temperature change rates under fog water conductivities of 0.6, 2.2 and 4.1 S/m are 54.9%, 101.2% and 153.9%, respectively.

The following conclusions can be drawn from the test results and simulation analysis: (1) The impact of dry contamination on the heating of deteriorated insulator is negligible. Under conditions of fixed category B contamination, the effect of category A wet contamination on heating is related to the position of deteriorated piece in the string. Furthermore, as the degree of wet contamination increases, the temperature of each piece tends to be consistent. (2) Fog water conductivity (category B contamination) has an additional effect on salt deposit density, which further affects the temperature rise of the insulator by increasing the number of conductive ions. There is a saturation phenomenon in insulator temperature rise in salt fog environments. (3) The excessive humidity can cause disordered temperature changes on the insulator surface, therefore, humidity greater than 90% is not considered during the detection. The leeward side, with small amount of contamination, is selected as the infrared observation position to more clearly diagnose deteriorated insulator in the string.