Abstract:Aiming at the difficulty of detecting transient power quality disturbances in noisy environments,this paper proposes a detection method based on the combination of wavelet modulus maximum and hierarchical adaptive threshold function. Firstly,in order to effectively reduce the noise of the disturbance signal, in other words, to ensure the smoothness of the signal after noise reduction and retain the mutation point information, adaptively adjusted HATF is adopted. The function is derivable at the threshold and in the wavelet domain, avoiding the defect that traditional or improved threshold functions can not reduce noise or reduce noise excessively. Secondly,based on the WMM method,the transient power quality disturbance after noise reduction is located by the position of the modulus maximum point in the detail coefficient. Based on noisy single and composite disturbance signals, simulation and comparative analysis show that HATF has obvious advantages in noise reduction and WMM+HATF has good versatility and high positioning accuracy.

Abstract:In order to reduce the adverse impact of location and capacity of charging station in distribution network, this paper considers the load fluctuation and voltage offset of the distribution network to build a optimal planning model for the location and size of electric vehicle (EV) charging stations. First of all, the cost of investment operator and the cost of user are comprehensively considered to construct the optimization model that minimizes the sum of investment and construction costs, operation and maintenance costs, and user costs of charging stations. Then, under the distribution network constraints, the evaluation model is built for the distribution network with the smallest loss, the smallest load fluctuation rate, and the smallest voltage offset indicator. Genetic algorithm is combined with Voronoi diagram to obtain the site and capacity of the charging station and select the comprehensive optimal scheme with the least impact on the distribution network and the total cost. Finally, the transportation network and power grid information are combined in the planned area. The simulation results verify the rationality and effectiveness of the model.

Abstract:The accuracy of wind power prediction can improve the security environment of largescale wind power integration. Under the background, a combined approach considering wind speed fluctuation characteristics for shortterm wind power forecasting is proposed in this paper. Firstly, five types of wind speed fluctuations are defined, and the fluctuation type of historical wind speed series in numerical weather prediction is divided to get the time period of different wind speed fluctuation types. Secondly, the historical wind power series corresponding to these time periods are classified, and the variational mode decomposition algorithm is used to deal with various types of wind power series for obtaining multiple submodalities with different characteristics and frequency bands. Thirdly, a prediction model based on the gated recurrent unit neural network is constructed for each submode, and the prediction results of each submode are added to obtain the predicted value of the wind power. Finally, the wind speed series of the forecasted day is identified from the types of fluctuation, and the matching power prediction model is selected to calculate the final prediction value. The wind speed data in the numerical weather prediction and power data of an actual wind farm are used for simulation analysis to verify the effectiveness of the proposed combined forecasting method.

Abstract:With the new round of power market reform and the development of the ubiquitous power internet of things, power sales companies have gradually developed into integrated energy service providers based on the different resources they have. Aiming at the problem of power capacity allocation on the power generation side under the background of new electricity reform, the paper establishes a twolayer model of power capacity allocation considering the operating status of electricity sales companies. The lower optimization object is an integrated energy service provider including wind turbines, photovoltaic cells, microturbines and controllable loads. The upper layer takes the lowest power investment cost of the power generator as the optimization goal. The bilevel programming model is solved by using the nonlinear programming tool. The results of numerical examples verify the effectiveness of the method. In the example, the electricity sales company impact the power supply capacity planning of the power generator from the two aspects of new energy consumption growth and demandside response reduction in peak load.

Abstract:Although the intelligence level of the power system is constantly improving, the operation, maintenance and repair work still require the direct participation of electricity workers, so it is of great significance to study the effective quantification of personal risks to ensure the safety of workers.Based on profoundly discussing the quantification model of personal risks of the workers in power systems, this paper proposes a quantification method of personal risks in a substation based on behavioral tendency, considering the influence of the insufficient method of determining the risk hazard value and the phenomenon of artificial selection tendency on the quantification of personal risks. The hazard value was further subdivided, and the mean of hazard value was processed by the Bootstrap method to simulate statistical uncertainty. For the problem of artificial selection tendency in risk assessment, the prospect theory is used to multiply the value of risk by a coefficient of behavioral tendency ω, so as to reflect the response psychology of managers when facing events with different risk values.The results show that this method is more effective in quantifying personal risks, which can provide references for managers to carry out practical risk response strategies and resource allocation schemes, and further guarantee the safety of operation workers.

Abstract:Overhaul operation and maintenance costs of substations are affected by many complicated factors. Fuzzy and fluctuating data records of maintenance costs worsen the situation. In order to solve the unclearness of the overhaul cost record, this paper firstly divides the substation maintenance items and uses data analysis method of horizontal and vertical direction to process the items. Then BP neural network is used to predict the maintenance cost. In order to improve the accuracy of BP neural network prediction,Kfold crossvalidation is used to accurately adjust the original data training model. The genetic algorithm is used to adjust and improve the initial value and threshold of the BP neural network. Therefore an improved BP neural network maintenance and operation cost prediction method is established based on the genetic algorithm. Taking a substation in a certain city as an example to predict the operation and maintenance cost of substation maintenance, comparative analysis shows that the proposed method can effectively improve the accuracy of model prediction, thereby providing reference value for the power grid to allocate maintenance costs to substations.

Abstract:As the new environmentally friendlyand energysaving vehicle, the application scale of electric vehicles is increasing rapidly.Bringing electric vehicles into microgrid is also thedevelopment trend of the power grid. The electric vehicle,having properties of flexible power demandandbidirectional energy fluidity, has become a significant part of balancing loads in the microgrid. In this paper, an economic dispatch model of microgrid with electric vehicles is established, and the Lingo software is utilized to solve the optimization problem. The power supply of various kinds of energy is adjusted through the improved model. The optimal combination of electric vehicles in the microgrid is obtained by considering the cost of environmental governance in the optimization goal, which reduces energy loss and improves the utilization of resources.

Abstract:According to the actual distribution of solar energy in China, largescale photovoltaic power plants frequently connect to weak delivery AC systems, which have a low shortcircuit capacity but a high background harmonic content. The large capacity of photovoltaics connecting to the grid has already made a significant impact on the end grid’s damping characteristics, meanwhile providing a new method to suppress low frequency oscillation. Under the background, on the basis of the fourmachine twoarea system, an electromagnetic transient simulation model including largecapacity photovoltaic plantsis set up. And the low frequency oscillation characteristics of the system areanalyzed by the total least squaresestimation of signal parameters via the rotational invariance technique(TLSESPRIT). Aiming at coordinatelysuppressing low frequency oscillation in intraarea and interarea, the additional damping controller designed by linear quadratic regulator(LQR) control method with an observer isrespectively set in the different control loop of photovoltaic inverter and SVG. Simulation results show that the proposed method can effectively suppress the low frequency oscillation and increase the system's capability ofsending power in a certain extent.

Abstract:According to the theory of lightning leader, the influence of tower topography on the lightning risk of distribution lineis analyzed in this paper. Firstly, the tower elevation, ground inclination, soil resistivity and other parameters are applied to characterize the tower topography, and then the quantitative value assignment rules of provided parameters are established. Secondly, the BP artificial neural network classifier is constructed to classify the topography of distribution line towers in mountainous areas, which can meet the practical requirements of lightning risk identification of distribution line towers. The case application results are consistent with the actual situation. The proposed method provides a new idea for differential lightning protection of distribution lines in mountainous areas.

Abstract:The rush repair work of the distribution network is mainly aimed at the faultsof residential users below 10 kV. The rush repair is heavy workload and the requirement of the arrival time is short. The existing rush repair has the following problems: the differences and uncertainties of different regions are not fully considered for layout; the location selection model ofrepairing resources is simple. Considering the influence of different objectives on resources allocation, a multiobjective optimization location model for repair resources in distribution network is built. The distance and cost objective functions are constructed according to the failure schedule, weather and road conditions, and the constraints of the coverage area and arrival distance are set at the same time. A multiobjective particle swarm optimization (PSO) algorithm based on Pareto dominance is used to solve the optimization problem. The final optimization scheme is obtained by the ordinal number preference method based on information entropy. Finally, an case study is performed to illustrate the feasibility of the proposed model.

Abstract:The fault tree of the relay protection system is an important tool for risk identification and evaluation of the system. To solve the difficulty in precisely obtaining the toplevel event rate of fault tree, and the inability of reverse reasoning of fault trees, a fault risk assessment method for relay protection which is based on the fault tree and the Bayesian network is proposed. In the positive direction, the fault state of the root nodes in the Bayesian network (corresponding to the basic event of the fault tree) can be confirmed according to the realtime operational data of relay protection. Combined with by the Bayesian network reasoning, the fault probability of the leaf node of Bayesian network (corresponding to the top event of the fault tree) can then be generated, thus to realize the risk prediction of the protection system. In the reserve direction, the leaf nodes of Bayesian network are combined with the Bayesian conditional probability formula, to calculate the failure probability of the root nodes of the Bayesian network, therefore the positioning and tracing of the fault cause can be achieved. The proposed method can provide bases for the reliability improvement and the fault diagnosis of the protection system.

Abstract:Network reconfiguration is one of the most important measures to improve the economical operation, security and reliability of distribution networks. A fast service restoration method for distribution network is proposed in this paper by combining the heuristic rules with network reconfiguration theory. Breadth first traversal is utilized to find the outofservice area first. Subsequently, heuristic rules are employed to determine the service restoration strategy, whose aims at connecting the outofservice area to the energized area. For the network without the intending islanding part, a network reconfiguration model, whose objective is minimization of the network loss and constraints are the safety operation of the distribution network, is constructed for the rest network, and the improved harmony search algorithm is used to solve the model. The simulation results of 69 bus system show that the proposed method is superior to other methods, and the effectiveness of the proposed network reconfiguration model is verified.

Abstract:This paper takes the park microgrid as the research object,and the electric vehicles in the charging station are divided into two main types: private electric vehicles and electric buses. Firstly, the travel time characteristics of different types of electric vehicles are analysed in this paper. The power interaction strategy between the combined energy storage equipment of electric vehicle charging station and the microgrid power system, the interactive power calculation model are constructed. Then, grading the microgrid feeder area with the switch as the boundary, the isolation operation methods for different faults are proposed. Based on the traditional evaluation indicators, the evaluation indexes of average charging depth, average discharge depth and average load reduction depth of electric vehicle charging stations are proposed. Finally, Sequential Monte Carlo intelligent algorithm is adopted for simulation. The power distribution network modified based on the F4 feeder area of the reliability evaluation test system of IEEE distribution system RTBS Bus 6 is used as an example to carry out simulation calculation. The calculation results show that after the electric vehicle charging station responding to the V2G technology is connected to the microgrid, a reasonable power interaction strategy can effectively improve the reliability of the microgrid under island operation.

Abstract:Considering the emergence of new market entities in the electricity market environment, this paper firstly introduces a distribution company participation matrix to simulate market bilateral trading behaviors. On this basis of traditional load frequency control model, the new load frequency control model based on the distribution company participation matrix is built. Then the distributed model predictive control method is adopted to control the load frequency control model according to the distributed characteristics of the model in the region. At last, a load frequency control model of twoarea ACDC interconnected power grid is taken as an example for Simulink simulation. The results show the established model can effectively simulate the market bilateral transaction process. Compared with CMPC control and traditional PI control, the distributed model predictive control method has better control performance.

Abstract:Power grid operation section is an important measure in power system operation control. Faced with the numerous intelligent generation methods of grid operation sections at present, how to make a reasonable choice has become an important content of the research in the field of online generation algorithms for grid operation sections. To solve this problem, a dynamic detection method for power grid operation section based on Qlearning algorithm is proposed. The main feature of this method is that the Qlearning agent is trained, and the grid operation section generation method is dynamically selected according to the grid operation characteristics, so as to make full use of the algorithm advantages of different generation methods in different scenarios. Finally, a case study based on the actual data in a certain provincial power grid shows that the dynamic detection method can improve the accuracy of the generated results by optimizing the selection of the detection algorithms in different scenarios. For the applied sample set, the method could improve the accuracy by nearly 5.2%.

Abstract:Travel temperature directly affects the specific energy consumption of electric vehicle through various interferences, resulting in the difference in charging power demand at different temperatures. According to the statistical principle, under the support of a large number of samples, the least squares method to obtain the specific relationship between the electric power consumption per km of electric vehicles and the travel temperatures in this paper. Then a power calculation model for electric vehicles considering the influence of travel temperature is proposed. The distribution network of a certain residential district in Beijing is taken as an example. Monte Carlo method is used to simulate the specific difference of electric vehicle charging load under different seasons (temperatures). The different impacts of EV load on the regional power grid in different seasons are analyzed to provide a new seasonal scheduling idea for the orderly control of EV charging behavior in the future.

Abstract:Power system has nonstationary and nonlinear characteristics of the subsynchronous oscillation (SSO), it is difficult for existing detection methods to capture the oscillation characteristics and the changing trend. In this paper, an oscillation detection approach, which combines Kmeans clustering and synchrosqueezed wavelet transform (SWT), is proposed to achieve the harmonic detection and analysis of subsynchronous oscillation. The antimodal aliasing ability and antinoise ability of the SWT are utilized to clearly and intuitively show the oscillation modes of the signals with noise. The frequency domain slicing is employed in the SWT to extract multiple oscillation modes for the reconstruction and the parameter identification. Considering that the SWT will squeeze the wavelet coefficients to the central frequency, the Kmeans clustering method is applied to calculate the central frequency of the oscillating signal. At the same time, the frequency interval of the signal can be automatically selected for reconstruction. Finally, the simulations are conducted to examine the effectiveness of the proposed method.

Abstract:In recent years,the ACDCAC transmission methods have been deployed ubiquitously in the highspeed trains, the grid voltage fluctuation and even instability becomes more frequently which willaffect the safe operations of these equipment. The previous study found that the stability of the power grid will be sufficiently impacted when highspeed trains are in the regenerative braking mode.In order to realize the regenerative braking energy recovery of the traction converter, and to ensure the stable operation of the cascade system between the power grid and the traction converter.In the nonideal power grids, the cause of the stability problem is derived based on the impedance analysis in this paper. The joint simulation verification is conducted among the Simperer, Maxwell, RMxprt, Matlab/Simulink platforms. The results show that improved parameters can overtly reduce the oscillation in the cascade system, and hence enhance the train operation reliability.

Abstract:In order to research the magnetic field interference on cables nearby 3phase air core reactor and the shielding effect of different materials, this paper analyses the influence of high conductivity materials and high permeability materials on spatial magnetic field on the basis of 3D electromagnetic field simulation model. Then the influence mechanisms are expounded. Furthermore, the induced voltages in different shielding measures are calculated and discussed basing on magnetic vector potential obtained from the finite element simulation results. The results show that, for the shielding of high permeability materials, good shielding effect can be achieved only by connecting 3 phases shield together. Moreover, a large number of magnetic leakages on the edge of shield may aggravate the magnetic field interference in surrounding areas. Therefore, the distribution of onsite cables in substation needs to be considered when applying high permeability 3phase connection shielding.

Abstract:Gas insulated switchgear (GIS) partial discharge fault type identification is an important basis for fault warning and maintenance planning, and is of great significance for maintaining the safe and stable operation of power equipment. This paper firstly analyzes several common types of GIS faults. Then, in the processing and classification of the spectral envelop signal collected by the UHF sensor, the composite neural network model formed by the fusion of the convolutional neural network (CNN) and the deep belief network (DBN) can quickly realize the extraction of effective feature signals and accurate classification of fault types. Therefore this paper integrates CNN and DBN, establishes the main structure of the composite neural network, and uses this network to identify GIS partial discharge fault types. Finally, the method is verified in simulation experiments. Results show that the accuracy of the composite neural network model to identify faults can reach up to 99%.

Abstract:By establishing the simulation model of 35 kV lines, the difference of lightning withstand level and the variation of shunt coefficient of towers are studied under three lightning protection cases of applying a shielding wire without lightning arresters, applying lightning arresters without shielding wires, and applying lightning arresters and a shielding wire. The simulation results show that the shunt coefficient of the tower with a shielding wire without lightning arresters is at least 20% larger than that with both lightning arresters and a shielding wire under the same grounding resistance. In addition, when the grounding resistance is less than 20 Ω, the lightning withstand level of the line having a shielding wire without lightning arresters is 1.8 to 2.0 times higher than that of the line having lightning arresters without shielding wires. The lightning withstand level of the line having lightning arresters and a shielding wire is 1.9 to 2.3 times higher than that of the line having a shielding wire without lightning arresters. When the grounding resistance is 20, 15, 10 and 5 Ω respectively, the improvement effect of lightning withstand level of the line in the condition of having shielding wire without lightning arrester is less than 60% of the other two conditions. The research results have certain guidance and reference value for the lightning protection of 35 kV transmission line.

Abstract:The paper performs the risk analysis of potential cybersecurity problems in residential consumer unmanned aerial vehicles (UAVs) adopted by power utilities for the transmission line inspection. Considering the realtime requirement, unstable communication links, easytotamper GPS navigation signal, and flight path confidentiality, the paper shows the cybersecurity matters in applying professional UAVs for the transmission line inspection. After that, the paper proposes the evaluation and screening method in UAVs and ground control systems for falsified GPS signals, which is based on the symmetric encryption control signal, encrypted communication and storage of aerial data, key distribution mechanism, and inertial guidance system in UAVs. Moreover, the cloud security malwaredetectionbased reinforcement measure is also proposed. The proposed method and measure ensure the cybersecurity of professional patrol UAVs.

Abstract:To match to the development of the concurrency and expansibility requirements of multiuser static security analysisin power dispatching systems, this paper analyzes the characteristics of static security analysis and calculation, and combines it with docker technology.Based on Docker technology, astatic security analysis cloud computing application method is proposed for designing the operation architecture of the application. In this method, Docker container images are generated corresponding to different power flow algorithms, and the data exchangebetween users and containers are realized by using Protobuf. New containers are dynamically created and idle containers is allocated according to the calculation request. Containerswill be released once the calculation is finished. This method uses Docker technology to improve the utilization of cloud platform computing resources, and meet the concurrent requirements of static security analysis calculation function. The case studiesshow that the proposed method can effectively utilize the computing resources and extend the concurrency and extensibility of static security analysis.

Abstract:Most of arresters are external gap arresters for limiting the lightning overvoltage on overhead transmission lines. Arresters for limiting operating overvoltage are not applied on power transmission lines. After the first installation of gapless arresters for limiting operating overvoltage on ±1 100 kV ChangjiGuquan UHV DC transmission line, the operating overvoltage for the whole line can be limited below 1.5 p.u., thus the clearance value is reduced, tower size and crossover distance are reduced, engineering investment is significantly saved. The installation schemes of arrester for line tangent and tension tower are proposed in this paper. Through comparative analysis, the hanging mounting scheme on the outer pick bracket is selected as the best scheme. The static and dynamic loads of arresters, innovative tower head layout design, drainage line selection and connection hardware design are analyzed on the basis of the best scheme. Through Installation and operation on real lines, the feasibility of installing gapless arresters on UHV DC lines is verified for the first time, and provides an example for the installation of gapless arresters.

Abstract:This article presents a novel multicast retransmission scheme for wireless communication network in the ubiquitous electric internet of things. Firstly, the advantages and disadvantages of two retransmission schema, the centralized and distributed, are analyzed. Then, a new method is consequently proposed based on retransmission mode preselection. Instead of the approach of the UEs in the centralized scheme, the proposed method's signaling cost is significantly reduced through reporting ACK/NACK and link quality by the cluster head UE. The proposed method can avoid resource waste of the base station to reserve wireless resource for retransmission. In addition, the cluster head can exploit the multicast gain and multichannel diversity gain jointly. Finally, the computer simulations verify the effectiveness of both the cost and the efficiency of the proposed method.