Abstract:A complex grid investment decision indexes system is established from the single component and multiple interactions of source?grid?load?storage. To take the interdependence and feedback relationships of the indexes on each side of the complex grid into account, the ANP?EWM combined weighting method is introduced into the investment decision, considering the preferences of decision makers and the information contained in the indicators. Firstly, the unilateral indices of source, grid, load and storage in complex grids and the interaction indices considering grid?source interaction, load?grid interaction, source?load interaction, source?storage interaction, load?storage interaction and grid?storage interaction are proposed to establish the investment decision index system. Then, the ANP?EWM combined weighting method is designed using game theory to assign weights to the indices. Finally, the overall utility value of the project is calculated using the distance vector merging algorithm. Taking the IEEE 39?node system as an example, the proposed method is compared with other weighting methods to verify its effectiveness.

Abstract:With the development of energy storage in the frequency regulation market, it is urgent to solve the impact of the decision?making behavior of alliance containing energy storage on the clearance result and the problem of the maximization of its own profit. First, the concept of degree of participation is proposed to explore the influence of the difference of declared power and price in the energy and frequency regulation markets, and then a bi?level optimization model is constructed to maximize the profits of the alliances and to minimize the cost of distribution system operator (DSO). The game equilibrium problem is solved by the path?following interior point algorithm and genetic algorithm, and the Nash equilibrium of the markets is achieved for obtaining the optimal bidding strategies of alliances in two markets. Finally, the proposed model and algorithm are validated on IEEE 33?bus system. The market clearing result and its own profit under the influence of different degree of participation are analyzed, and the results show that reasonable selection of degree of participation can obtain higher profits.

Abstract:With the continuous advancement of the "double carbon" work and the growing maturity of the electricity market, new energy grid integration has become an important development trend to build a new energy system in China. However, due to the significant differences in marginal power generation costs and output characteristics between new energy and traditional energy, the new energy grid connection has brought a huge impact on the operation of the power grid. In order to solve the series of problems, firstly the concept of equivalent load is introduced from the perspective of demand response. Based on the support vector regression?particle swarm optimization (SVR?PSO) algorithm, a demand response model that takes into account new energy consumption and power generation costs is constructed to optimize the time?of?use electricity price and reduce the power purchase cost on the demand side. Secondly, based on the time?of?use electricity price, a VPP double?layer optimization dispatch model considering new energy consumption is proposed and corresponding operation strategies are formulated to build a bridge of "source?load interaction" between the distribution network and the demand side. Finally, the impact of time?of?use electricity price before and after equivalent load optimization on the economics of virtual power plants is discussed, which provides a reference for the formulation of time?of?use electricity price.

Abstract:In order to realize the efficient utilization of energy, as well as reduce carbon emissions and source load uncertainty, this paper proposes a multi?time?scale low?carbon collaborative optimal scheduling strategy for integrated energy systems considering hydrogen energy coupling and stepped carbon trading mechanism. Firstly, in order to effectively reduce the carbon emission level of the system, a ladder carbon trading mechanism is introduced, and a low?carbon economic scheduling model is established. Secondly, to give full play to the efficient and clean characteristics of hydrogen energy, a hydrogen energy coupling equipment model based on electrolytic cell, hydrogen fuel cell and methane reactor is established, and a multi?source energy storage model of electricity, heat and hydrogen is developed. Finally, with a purpose to reduce the impact of source and load prediction errors on the optimal scheduling of the system, and taking into account the response differences of electricity, heat, gas under different time scales, the scheduling models for day?ahead and intra?day multi time scale are constructed, respectively. The example analysis shows that the introduction of hydrogen energy coupling system and stepped carbon trading mechanism can not only improve the operation economy, but also reduce the carbon emissions, and the proposed multi time scale scheduling strategy can effectively suppress the power fluctuation, and reduce the uncertainty of the system source load.Key words: hydrogen energy coupling; multi time scale; carbon trading mechanism; collaborative optimization; multi?source energy storage

Abstract:The development of new energy vehicles has driven the maturity of the lithium-ion battery industry, resulting in rapid growth in the mobile energy storage vehicle (MESV) industry. Considering the involvement of mobile energy storage vehicles in peak load shaving and auxiliary services for high-power end-users, research is being conducted on the optimization of MESV paths and charging/discharging strategies. Firstly, the operation mode of MESVs storage is analyzed to establish an optimal scheduling framework for MESVs considering peak load shaving and anxiliary services. Secondly, the billing method based on demand charge tariff (DCT) is included in the target model considering the path selection, charging/discharging power limitation and state of charge (SOC) constraints. Then, with the aim of maximizing the overall revenue of MESVs in peak load shaving and auxiliary services, a model is constructed for optimizing the selection of MESV paths and charging/discharging strategies. Furthermore, the impact of DCT billing on user load curve is analyzed. Finally, taking the actual road network of a city as an example, the feasibility and effectiveness of the proposed method are verified by comparative analysis of the example.

Abstract:Reasonable distributed energy storage configuration plays a crucial role in the energy consumption process of the park. How to consider the connection between multiple parks and the constraints between economic costs and energy consumption benefits is a difficult problem to solve when configuring energy storage batteries. In addition, modern distribution networks are mostly closed?loop and open?loop operation, and the dynamic connection between multiple parks is also an important technical means to promote energy consumption. This paper proposes a multi?park energy storage multi?objective optimal configuration model considering network reconfiguration. First of all, the model mathematically represents the constraint relationship between configuration economy and energy consumption benefit, considers various investment and operation constraints, and introduces virtual power to represent the connection state between various parks; The model improves the energy consumption level from the system level through the dynamic reconstruction of the network. Secondly, based on the second?order cone relaxation and polyhedral linearization method, the original mixed?integer nonlinear non?convex model, which is difficult to solve directly, is transformed into a mixed?integer linear programming model. Finally, the proposed method is applied to the improved IEEE 33 bus system to construct a multi?objective Pareto curve. The results show that the dynamic connection between multiple parks is helpful to improve each other's energy consumption level, and the proposed method can provide the optimal solution of multi?objective energy storage configuration for engineering practice.

Abstract:The central air conditioning system and other equipment in buildings consume a large amount of electrical energy, leading to the continuous increase in energy consumption in the construction sector in our country. To address the above?mentioned issue, firstly, a mathematical model is established for the energy consumption of each equipment in the central air conditioning system based on its working principle, and the decision variables are selected. Then, with the objective of minimizing the total energy consumption of the central air conditioning system, an energy?saving optimization model for the central air conditioning system is established, taking into account the constraints such as variable bounds, coupling relationships between equipment, and energy conservation principles. Next, the real?time indoor cooling load and the set temperature are taken as known values, while the decision variables are taken as input variables, and the total energy consumption of the central air conditioning system is taken as the output variable to reduce the complexity of the model. Subsequently, an improved particle swarm optimization (PSO) algorithm is proposed based on dynamic weight coefficients and acceleration factors. The method achieves collaborative optimal control of the decision variables to search for the optimal solution of the energy?saving optimization model for the central air conditioning system. Finally, the ISPO algorithm is compared with the standard particle swarm optimization algorithm through simulation analysis. The results show that IPSO achieves superior performance and better convergence. The optimized total energy consumption of the air conditioning system is significantly reduced compared to the pre?optimized state, thus validating the effectiveness of the proposed model and method.

Abstract:Under the background of "carbon neutralization" and "carbon peak", in order to alleviate the pressure of distribution network capacity expansion caused by large?scale electric vehicle access, a capacity evaluation method of distribution network receiving charging facilities is proposed considering instantaneous kurtosis. Firstly, the calculation models of regional existing load and charging load are established. Secondly, taking the full?time power flow calculation results as security constraints, an acceptance capacity evaluation method based on bisection cyclic approximation method is proposed. Finally the maximum acceptance capacity is calculated by the method. In the case study, the acceptance capacity of charging facilities under different distribution network scenarios is solved through evaluating the influence of different load interaction characteristics on the acceptance capacity by instantaneous kurtosis. The results show that the proposed method can improve the utilization of distribution network capacity resources and reduce unnecessary capacity expansion requirements.

Abstract:Traditional RNN and CNN models have the issue of the time?invariance problem when they are used to make short?term predictions of wind power on longer time scales. This paper proposed a short?term wind power uncertainty prediction method based on the time?variant deep feed?forward neural network architecture (ForecastNet) model. This method has a time?varying network structure to improve multi?step ahead prediction, and has an interlaced output capability to mitigate the gradient disappearance problem. The probability density distribution can be obtained by using mixture density network. This model not only avoids the cumulative error of recursive multi?step prediction in the traditional deep learning model, but also fully considers the correlation of wind power at adjacent moments. In the hidden layer of the model, the actual data of wind power from PJM network in the United States are used to test three kinds of neural network models, namely, fully connected network, convolutional network, convolutional network with attention mechanism. The wind power of the next 12 hours is predicted each time, and the range and probability density of wind power of the next 500 hours are obtained by rolling prediction. The results of the experimental simulations prove the effectiveness of the proposed prediction model.

Abstract:Static voltage stability margin (SVSM) is a commonly used voltage stability evaluation index in power system operation. The SVSM will change with the uncertain fluctuation of wind farm output, which may threaten the secure operation of a power system. Therefore, this paper proposes an optimal control model for the SVS of an AC/DC hybrid power grid considering the uncertainty of wind farm output. With the objective of minimizing the total control cost, it is required that the lower bound of the system SVSM fluctuation range meets the predefined safe operation requirements under a given fluctuation range of wind power output. In order to solve the three?layer optimization model, a parametric approximation method is introduced, and the inner and middle layer optimization models are parameterized layer by layer, which helps to obtain the approximate analytical expression of the relationship between the lower bound of the SVSM interval and each control variable. The optimization model is converted into a single?layer optimization model, and the SBB solver is used to obtain the optimal control scheme. Meanwhile, to improve the computational efficiency, a method of removing redundant cross terms in the approximate polynomials is proposed by using high?order mixed derivatives of SVSM with respect to control variables. Finally, a modified IEEE 39?bus AC?DC hybrid system is used as an example to verify the correctness and effectiveness of the proposed method.

Abstract:Due to the low voltage level in the medium and low voltage distribution network, the number of modular multilevel converter (MMC) sub?modules is also small. Therefore, the modulation strategy of MMC with few sub?modules MMC has an important impact on the performance of the MMC system. In order to improve the total harmonic distortion (THD) of output waveform under nearest?level modulation and reduce large switching loss under carrier phase?shift modulation of the few?sub?module MMC system, a quantization error setting method is proposed for the minority module MMC system under nearest level approximation modulation. The quantization error is a new MMC hybrid modulation strategy that mixes the nearest level approximation and the carrier phase shift method. When the quantization error is less than the quantization error given by the system, the nearest level approximation modulation method is used, otherwise, the carrier phase shift modulation method is used. At the same time, combined with circulating current control and sub?module voltage equalization control, to further ensure the normal operation of the minority sub?module MMC under the mixed modulation. Finally, the simulation model of the MMC hybrid modulation with 4 sub?modules is established, and the simulation study of the MMC hybrid modulation strategy of the few sub?modules is carried out. The modulation error is controlled within the quantization error range given by the system.Key words: DC distribution grid; modular multilevel converter; modulation strategy; harmonic analysis; voltage sharing control; circulation control

Abstract:The impedance interaction between the inverter and the grid cannot be avoided. When the distributed capacitance of the transmission cable is large and cannot be ignored, multiple resonance points will appear in the grid?connected system of the inverter, which is easy to cause high?frequency resonance. From the perspective of impedance interaction, this paper uses passivity theory to analyze the potential unstable region of grid?connected inverter system, and the influence of line length and grid side impedance on the resonant frequency of grid?connected inverter system. Aiming at the problem of high frequency resonance of the system, the active damping method of series second?order low?pass filter and phase compensator in the inverter control path is proposed to reshape the impedance of the inverter, so that the output impedance of the inverter can meet the passive condition in the whole frequency band, achieve the purpose of suppressing high frequency resonance and improve the stability of the system. Finally, the simulation model in Matlab/Simulink is established, verifying the effectiveness of the proposed scheme.

Abstract:In recent years, with the increasing electronization of the power grid, the overall inertia of the grid has decreased. As a result, the technology of virtual synchronous generator (VSG) has emerged and rapidly developed. The core idea is to mimic the electrical and mechanical characteristics of synchronous generators used in traditional power systems in order to enhance the rotational inertia of high?proportion distributed energy systems. However, the existing control strategies for VSG have fixed control parameters or simple continuous variations, which may lead to power oscillations in the system when subjected to small disturbances. In order to adjust the virtual inertia and damping coefficient more flexibly, a variable?parameter VSG adaptive control strategy based on piecewise exponential functions is proposed after a detailed analysis of VSG. The variation of virtual inertia and rotational damping with grid frequency follows an exponential function trajectory, aiming to reduce grid fluctuations. Additionally, when the disturbance rate is low, the parameter changes are small to avoid causing system oscillations. Finally, the parameters of the main circuit and the VSG control part are designed, and simulation results show that the strategy can effectively improve the stability of the inverter operation.

Abstract:The secondary circuit of the substation is the basis of the secondary advanced integrated business. The automatic feature recognition and information extraction of the secondary circuit by image recognition technology can realize the secondary circuit's intelligent operation and maintenance business. However, the images collected by the substation have messy backgrounds, low resolution, and distortion, making it very challenging to identify irregular text using image recognition technology. Therefore, a text detection and recognition method of a secondary loop terminal based on an attention mechanism is proposed. This method mainly includes preprocessing, text detection, and text recognition. In the text recognition part, a spatiotemporal embedding encoding method is proposed, which can better use the picture's location information. Compared with the unimproved method, only the sequence?level annotation information is needed in the training process, and no additional fine?grained character level box or segmentation mask is needed. Finally, it is proved that the proposed method is not only easy to use and has good performance but is also better than other methods in recognition accuracy.

Abstract:Aiming at the low accuracy problem of insulator fault detection caused by the fault position occupies a small proportion in the image and complex background environment in aerial images, an insulator fault detection method based on optimized Cascade R-CNN model is proposed in this paper. Based on the original Cascade R-CNN model, deformable convolution is inserted into the backbone network to learn geometric transformation capabilities, and balance loss function is introduced in the detector to balance difficult and easy samples. In the model training phase, the faulty insulator samples are enriched by using Copy-Paste and Mosica, and the positive and negative samples are balanced. The proposed model is tested for insulator fault detection. Compared with the traditional Cascade R-CNN model, the average recall of the optimized loss function model improves 0.38%. Comparing with the Faster R-CNN model, the average recall of the Cascade R-CNN model after introducing variable convolution improves from 89.78% to 93.49%. The results indicate that the proposed model can overcome the interference of samples shielding and sample imbalance effectively.

Abstract:With the expansion of the distribution network scale, the traditional centralized state estimation algorithms require increasingly complex model construction, leading to increased computational complexity during the solution process, reduced timeliness and accuracy of the state estimation. Aiming at this problem, a distribution network state estimation method based on node degree search partitioning is proposed. Firstly, a node degree search partitioning method based on balanced regions is proposed, and the measurement model and distributed state estimation model for the distribution network are designed. Secondly, the distributed state estimation model is solved in three stages. Finally, the IEEE 30 node distribution system is selected for simulation analysis. While ensuring the observability of the system after partitioning, a comparison is made among different partitioning methods in terms of the accuracy and duration of state estimation. The impact of measurement redundancy on state estimation accuracy is further analyzed. The simulation results demonstrate that the proposed distributed state estimation method has significant advantages in terms of state estimation speed and accuracy.

Abstract:In order to improve the power supply reliability and the source acceptance capacity of distribution networks, the active ring network has become one main development trend of the distribution network. However, the connection of numerous distributed power sources will impact the power flow and fault characteristics, and thus reduce the performance of the traditional three?stage current protection scheme. In this regard, an improved current differential protection scheme is proposed for annular active distribution networks in this paper. Firstly, the expressions for the relationship between the fault currents inside and outside the annular active distribution network are derived, and thus the vectorial relationship between the fault current components at both ends can be figured out. Then the main protection criterion is constructed by the fault current ratio of the two ends of protected area section., and the auxiliary protection criterion to avoid protection misoperation is also set for the annular structure distribution network. Finally, the PSCAD/EMTDC simulation platform is used to verify the effectiveness and interference resistance of the proposed protection scheme.

Abstract:Large?scale offshore wind farms are one key tendency of wind power generation development. Submarine cables, as an important link between offshore wind farms and grids, are with much higher distributed capacitance than overhead lines, and thus will generate a non?negligible capacitance current. In case of the long?distance high voltage transmission, this may lead to the refusal?operation of relays in the distance protection area. The reliability of distance protection operation criterion depends on the accuracy of measurement impedance. Therefore, in this paper, combined with the actual physical structure of cables, the calculation of relevant electrical parameters is studied, and the accuracy of the corresponding formulas are demonstrated. According to the consequent calculation results, a distributed parameter model is established for cable lines, and the influence of distributed capacitance on the measured impedance at the protection installation is analyzed. It is proved that the measured impedance of long distance cable lines is a function of hyperbolic tangent to the fault distance. On the basis of the traditional capacitive current semi?compensation scheme, an improved scheme is proposed. A cable model for fault simulation is carried out through PSCAD. The simulation results show that the improved scheme can effectively compensate the line capacitive current, reduce the portential refusal?operations in the distance protection area and the misoperation outside the area, with a better anti?transition resistance ability at the same time, which will assist in distance protection performance.

Abstract:The fracture failure of substation grounding grid buried underground endanger the safety of equipment and person. However, the current fault diagnosis for the grounding grid is still mainly based on regular excavation detection. This method has shortcomings such as blindness and low efficiency, so the nondestructive testing of grounding grids is of important application prospects. Aiming at the under-determined diagnosis equations defect of the electrical network diagnosis method, this paper proposes the method of applying magnetic field inversion to detect the grounding grid. Considering the electromagnetic interference problem of the grounding grid site, a corresponding hardware system device is designed. First, the grounding grid is analyzed, and the feasibility and specific operation of magnetic field inversion method are discussed. Secondly, according to the characteristics of electromagnetic interference in substation grounding network, a magnetic field detection hardware system with anti-electromagnetic interference ability is developed. Finally, the feasibility and accuracy of the method and system are verified through the experiment on the grounding grid model and the field application of the grounding grid in a substation.

Abstract:As a typical network model of artificial neural network, BP neural network has been widely used in fault diagnosis of distribution network. However, due to the randomness of initial weight and initial threshold, the diagnosis accuracy is not high in application. Aiming at this problem, a distribution network fault diagnosis method based on genetic algorithm optimization of BP neural network is proposed. The initial weight and threshold of BP neural network are optimized by genetic algorithm, and the fault diagnosis results are compared with those of traditional neural network in the calculation example. Finally, the simulation errors of the two are analyzed to verify the feasibility. The results show that the genetic algorithm provides relatively ideal initial weights and thresholds for the BP neural network, effectively reducing the error in the operational results and improving the accuracy of the diagnosis.

Abstract:The measurement accuracy of electronic voltage transformer (EVT) is closely related to the security and economy of the power grid. In order to accurately predict the error of EVT during the long?term operation, a combined error prediction method considering multiple features is proposed. This method selects parameters with strong correlation to EVT errors through correlation analysis as feature quantities. It utilizes a fused attention mechanism LSTM model and an SVR model to predict the errors of the transformer separately. The obtained prediction results are then combined to generate the final prediction result. The real?time operational data of a certain substation is simulated and analyzed. The results indicate that the proposed method can effectively predict the error variation information of the EVT over a certain period of time and has certain reference value for the timely prediction of EVT errors in substations and scheduling of measurement performance maintenance.

Abstract:Compared with electromagnetic voltage transformer, capacitor voltage transformer commonly used in power system has many advantages, such as high impulse withstand strength, low production cost and low maintenance workload. However, some common problems that large space occupation, high insulation design level required (contact with high voltage directly), and insulation failure in severe environment are still exist in capacitor voltage transformer. In order to solve these problems, a non?contact capacitor?coupling voltage transformer suitable for 10 kV and below voltage level is designed in this paper. Based on electromagnetic induction principle, the coupling capacitors formed between the measuring end of voltage transformer and the inner core of cable, the transmission line or the wire inside the insulating bushing are designed as the high?voltage terminal capacitance. The capacitor formed between the voltage transformer measuring end and the earth is acted as the low?voltage terminal capacitance. Then the influence of voltage transformer capacitance on frequency characteristics is analyzed theoretically. The electric field and capacitance between the measurement end of coupling voltage transformer and high voltage transmission line is calculated and optimized by finite element simulation. Finally, experimental test is carried out on a single?phase 10 kV power transmission cable. The results show that the designed voltage transformer is capable of measuring the voltage accurately in real time, which can provide references for the establishment of intelligent power system, real?time online monitoring of power grid and field operation of relay protection.

Abstract:Many existing studies on the magnetic flux leakage of broken strands in the steel core only consider geometric parameters such as length, width and depth of the broken strands, and the impact of the broken strand angle on the leakage field has rarely been discussed. Therefore, this paper establishes a 3D finite element model of a steel core magnetic flux leakage detection device to analyze the magnetic flux leakage vectors Bx, By and Bz under 12 different broken strand angle conditions. By comparing the three vectors, the vector direction which is most sensitive to detecting broken strand faults is obtained. The results show that vectors Bx and By exhibit multimodal distributions, and the distributions of positive and negative peaks are opposite with a 90° broken strand angle as the division point. Moreover, vector Bz exhibits multiple peaks at a 90° broken strand angle due to the influence of the broken strand width, while in other conditions Bz exhibits a single-peak distribution. The comparison of the vector peak values shows that the vectors Bx and By have similar positive and negative peak values under different operating conditions. The peak values of vector Bz significantly exceed that of Bx and By, with the largest difference observed at a 90° broken strand angle. The positive peak values of Bx and By are only 4.5% and 2.2% of the positive peak value of Bz, and the absolute values of the negative peaks are only 1.5% and 2.9% of the positive peak value of Bz. Vector Bz proves to be the most sensitive in detecting broken strands of the steel core. Consequently, Hall elements should be arranged perpendicular to the transmission line surface to detect vector Bz as the most effective signal detection scheme.

Abstract:Mechanical defects of gas insulated switchgear (GIS) may occur in the process of assembly and long?term operation. Detecting and diagnosing mechanical defects is of great significance to ensure the reliable operation of GIS. At present, scholars have carried out a large number of vibration signal detection. However, the result analysis is mostly time?frequency analysis based on FFT (fast Fourier transform), and the diagnostic methods for vibration?signal feature extraction under different typical mechanical defects is deficient. Therefore, based on the basic principle that frequency characteristics differences exists in the vibration signals of different typical mechanical defects, the method adopting EMD?FFT joint algorithm to extract the characteristics of GIS vibration signals is proposed in this paper. According to the vibration signals detection and analysis of typical mechanical defects in 550 kV entity GIS equipment, the characteristic maps of GIS mechanical vibration signals under different defects are summarized. Thus the effective diagnosis of mechanical defects of on?site GIS equipment can be realized. The results show that the proposed EMD?FFT algorithm can extract the main characteristic frequency points of vibration signals under different typical defects effectively. The constructed characteristic spectrum can reflect the variation of frequency information under different defects directly. Which leads to realize the diagnosis of typical mechanical defects. Based on the proposed diagnosis method, field test is conducted to detect the loosening defects of anchor bolts in a certain GIS equipment, which proves the effectiveness of the proposed method. The research results can provide methods and test results reference for on?site GIS mechanical defect diagnosis.

Abstract:To enhance the measurement accuracy of icing thickness on transmission lines, a novel method for measuring the thickness of uneven icing on transmission lines in complex background images was proposed. Firstly, a series of preprocessing steps, including image grizzling, median filter denoising, and maximum inter-class variance method, were applied to the transmission line icing images. Subsequently, by leveraging the connected domain characteristics of transmission line icing information and background noise, the contour of the icing transmission line was extracted from the complex background. Finally, to address the issue of local uneven icing thickness, a vertical approximation method was employed to obtain the pixel width of icing transmission lines. The experimental results demonstrate that the proposed transmission line target extraction method, based on the parameter features of connected domain, can accurately extract the icing transmission line contour from images with complex backgrounds and low contrast. Moreover, the vertical line approximation method is obviously superior to the traditional Hough transform method in areas with local uneven icing, significantly improving the measurement accuracy of icing thickness on transmission lines.

Abstract:Temperature rise is a major influence factor on the miniaturization and high?load design of DC electromagnetic relays. Thus, accurate temperature rise calculation is an important supplementary means in achieving the performance goals of the relay design. In this paper, a computational fluid dynamics heat dissipation simulation model using fluid?solid coupled heat transfer and discrete coordinate method radiation transfer equations is proposed to improve the accuracy of the original solid thermodynamic finite element heat dissipation simulation model in terms of convection and radiation calculations. The temperature field of a certain type of electromagnetic relay is simulated by adopting the proposed model. Then a temperature rise test is conducted to verify the accuracy of the simulation results. In addition, the temperature distribution simulation results of the relay by adopting the proposed model are closer to the actual situation than that using the solid thermodynamic finite element heat dissipation model. Therefore, the simulation model in this paper can provide a more effective thermal field design tool for the same type of relay products.

Abstract:The 35 kV overhead lines have significantly taller towers compared to the 10 kV lines. However, the lightning protection configuration of the 35 kV lines is relatively insufficient, leading to a higher rate of lightning?induced trip outs. This paper proposes the installation of parallel gaps on a single phase as a means to enhance the lightning withstand level of the lines. Specifically, the parallel gaps are installed on the fixed single phase of the same circuits. The tripping mechanism for the 35 kV overhead lines is inter?phase short?circuit faults. The parallel gaps, when installed on a single phase, utilize the coupling effects to reduce the overvoltages of the other two phases, thereby reducing the rate of inter?phase short?circuit faults and improving the lightning withstand level of the 35 kV overhead lines. By establishing an overvoltage simulation model of 35 kV overhead lines, considering the effects of overhead ground wires and grounding resistance, the impact of parallel gaps on the lightning withstand level of the lines under the single?phase installation mode is calculated. When a single phase is equipped with parallel gaps, the maximum increments in lightning withstand levels under counterattack are 81.9%, 21.2%, and 11.1% respectively, for scenarios with no overhead ground wire, a single overhead ground wire, and double overhead ground wires. Similarly, the maximum increments in lightning withstand levels under induction lightning are 68.2%, 50.2% and 38.4% respectively. Through experiments and calculations, the method to determine the discharge distance of the single?phase installed parallel gaps is proposed according to the probabilities of lightning strikes with different types. Single?phase parallel gaps, characterized by low cost and maintenance?free operation, can serve as important lightning protection measures for 35 kV overhead lines.

Abstract:Based on the perspective of data fusion, in response to the low level of automation in fault localization in a certain city's power distribution network and underutilization of data from various systems, a multidimensional information fusion?based power distribution network fault diagnosis system is developed. It is achieved by integrating system data from the distribution network dispatch management system, SCADA system, fusion terminals, and data acquisition systems via an internal private network. The system can be divided into two parts: the front?end user interface and the back?end server. The front?end user interface is developed using the Visual C++6.0 development environment and modularizes different functional components. The back?end server is implemented using a database system developed based on Java Web technology. The system is user?friendly, reliable in operation, highly adaptable, and exhibits good scalability. It enables fault localization, isolation, and reconstruction in power distribution networks. It is convenient for province?wide promotion and holds practical engineering significance for the development of power distribution automation. The system has been undergoing trial operation in a specific region, and the results have been positive.