Abstract:With the development of high voltage direct current transmission system, the new large-capacity synchronous condenser has become the best choice to meet the dynamic reactive power demand of the system. Therefore, it has gradually become one of the research hot topics. Based on this, this paper systematically summarizes the research status of the new type of the condenser. Firstly, the operation principle of the condenser is introduced from three aspects: its mathematical model, operation state and control strategy. Secondly, by comparing it with power electronic reactive power compensation equipment, the superior dynamic reactive power output characteristics of the new condenser are expounded, and their influence factors are analyzed. Finally, the latest development of the state monitoring technology of the condenser is summarized from both the existing fault diagnosis technology and parameter identification technology of the condenser. In this paper, the mathematical model, control strategy and operation state monitoring of the new synchronous condenser are summarized, which can provide reference for the further research of the new synchronous condenser.

Abstract:Reactive voltage regulation is an important control measure to ensure voltage stability in the power grid area. The existing single agent design method based on reinforcement learning has many problems, such as high coupling between state and action, various combinations of reactive power compensation devices, and unreasonable reward design based on target deviation model. Aiming at these problems, a method for describing the integrated operation state of the grid considering the node voltage amplitude and capacitor switching condition is proposed. The reinforcement learning agent group architecture for grid reactive voltage regulation is designed. The group determines the members of the agent according to the current comprehensive operating state of the grid, and gives corresponding reactive power regulation actions. Each agent member uses the improvement degree of the grid state in the adjacent time period as a reward mechanism. The example shows that the method can be applied to the grid reactive voltage regulation environment. Compared with the single agent design method, the number of action sets can be effectively reduced, and various reactive voltage regulation conditions can be better dealt with.

Abstract:Aiming at the problem of poor grid connection condition and low success rate of large synchronous condenser, the traditional phase angle difference time function is improved. The improved curve can reflect the change rule of phase angle difference between 0 and 2 π, and directly show whether there are synchronization points and their number in a certain slip speed range and the corresponding closing time range in a certain phase angle difference range. It is very convenient to predict the time when the closing pulse is sent out. When the initial moment of inert deceleration is 0 and the acceleration starts to decelerate with -0.167 r/s² as the starting point of inert deceleration, the number of simultaneous points within the maximum allowable slip range and the closing time range allowed by the synchronous condensers are analyzed through examples, and the correctness of the example analysis results is verified by Matlab/Simulink simulation software. At the same time, taking the impulse current of the phase modulator as the setting basis of the maximum allowable phase angle difference can effectively reduce the impact on the synchronous condenser when connected to the grid, and improve the success rate of connected to the grid.

Abstract:Regarding at the problem of inadequate adaptive regulation ability of traditional control strategy of SVG, the traditional control strategy is improved. On the basis of inner loop decoupling control, fuzzy control is introduced to adjust PI parameters adaptively to improve the compensation accuracy of SVG. The traditional fuzzy PI control takes the initial PI parameters as the center and adjusts up and down, and the adjusting range is limited. Aiming at this problem, the method of accumulating PI parameters is proposed to increase the adjusting range. According to the changing system, not only the initial values but also the last moment values is not as the referring values during adjusting the parameters. And the PI parameters are adjusted adaptively according to the change of error signal. The simulation results show that compared with the existing control strategies, the compensation accuracy is further improved and the dynamic performance of the system is enhanced.

Abstract:Under the premise of satisfying steady operation of distribution network, fully utilizing the rated capacity of the grid-connected inverter, and excavating the reactive power support of photovoltaic power station, which can promote economic operation of distribution network. Thus, it is of great practical significance to research the evaluation method of reactive power support for photovoltaic power station. Firstly, the evaluation method based on dynamic time warping(DTW) algorithm and the evaluation index system is proposed,so as to realize reactive power support evaluation in the real time. Then the prediction method of photovoltaic output based on deep belief network(DBN) and the predictive index system is proposed, combined with predicted data to realize reactive power support evaluation in the future state. Numerical examples show that the predicted evaluation result is highly consistent with the actual evaluation result,which verifies the effectiveness of the established evaluation and prediction method.

Abstract:The reactive power and voltage compensation principles of static synchronous compensator (STATCOM) are introduced. In order to easily increase the output voltage levels, a STATCOM based on modular multilevel converter (MMC) is proposed as well. Since the conventional control strategy is mostly focused on the system performance with balanced load and its control performance is usually unsatisfying under unbalanced conditions. In this paper, the STATCOM is analyzed using positive, negative sequence model and based on that, the sequence control method is applied and elaborated. The voltages at point of common coupling (PCC) are locked by applying the decoupled double synchronous reference frame-phase locked loop (DDSRF-PLL). The sub-module (SM) capacitor voltages of MMC are balanced by a distributed control strategy which avoids large amount of information exchange between central controller and local controllers. The simulation model of a five-level MMC based STATCOM is built in PSCAD/EMTDC. Simulation results validate the correctness of the proposed controllers.

Abstract:There may be serious static security problem after UHVDC related single or multiple DC locking faults, on-line analysis is necessary. At present, on-line simulation computational speed of the security&stability control is difficult to meet analysis requirements and the results of DC reactive power control strategies are not accurate. An On-line static security analysis method of UHVDC faults is proposed, considering the security&stability control strategies and primary frequency regulation characteristics. A quasi-static simulation method is used to estimate the change of active injection of each node under the faults, according to time sequence of security&stability control first action and primary frequency regulation second action. In the simulation, the DC reactive power control function model is established by the bus type conversion of the converter station,thus the accuracy and convergence of the calculation is improved. The effectiveness of proposed method is verified by actual cases.

Abstract:With the change of energy consumption, the consumption proportion of renewable energy power generation rises gradually. Photovoltaic power is chosen as the research object to study the characteristics of power curve under different weather conditions and to analyze the correlation of the efforts of various meteorological factors and photovoltaic power generation. Then by combining Empirical Mode Decomposition (EMD) and Long-short Term Memory (LSTM), a load forecasting model suitable for photovoltaic power generation is proposed. Firstly, the historical sequence of preprocessed photovoltaic power generation is reconstructed. Then, the reconstructed historical time series is decomposed in EMD model, and the decomposed sub-sequences are respectively predicted in the LSTM network. Finally, the results of each sub-sequence are superimposed to obtain the predicted result of photovoltaic power generation. The actual output data of photovoltaic power generation in a certain region in China is used to test the model. Compared with the ARIMA model, SVM model, LSTM model and EMD-SVM model, the model proposed in this paper has lower prediction error and can effectively improve the prediction accuracy of photovoltaic power generation.

Abstract:As the last line of defense of the micro-grid system, emergency control can maintain the frequency stability after the system is greatly disturbed, which is of great significance to the stable operation of the micro-grid. This paper analyzes the problem that frequency emergency control strategy and round load shedding strategy are difficult to set and cannot accurately load down in micro-grid, and an independent micro-grid emergency control strategy based on the PCS output power limit criterion is proposed. When the external disturbance causes the PCS output power to exceed the limit, the PCS's over-limit power is calculated by taking into account the SOC equalization control strategy, the load is accurately cut off by the load accurate load shedding scheme, and adopting GOOSE communication technology for engineering implementation, proposing small step trend variation sampling algorithm and anti-point large number strategy to improve the response speed of control system, improving the stability of large-capacity independent micro-grid operation. The feasibility and effectiveness of this scheme are verified by an independent micro-grid project in Xinjiang.

Abstract:The energy crisis is getting more and more serious around the world. In recent years, renewable energy has developed rapidly as one of the ways to relieve the energy crisis. However, renewable energy has the characteristics of uncertainty. Therefore, high renewable energy penetrated power system will bring new challenge to the optimal dispatching for the power system. In the case of rapid development of renewable energy power generation and nuclear power station, the peak and valley difference of the power system becomes larger, which increase the pressure on the power system peak regulation. In order to increase the peak regulation capacity, a model for flexible participation in peak regulation is proposed in this paper. Meanwhile, a two-stage stochastic optimization for power system nuclear power plants participating in peak regulation with the consideration of the stochastic renewable energy output is given. The first stage of optimization determines the status of the power plants. In the second stage of optimization minimize the expected operation cost of power system based on the decision made in first stage. The model is tested by IEEE 24 bus system and a real power system. The results verify the feasibility and economy of the nuclear plants participating in peak regulation.

Abstract:There are thousands of transient stability faults in large scale power system. Transient stability analysis cannot be finished in given time required by online assessment. To meet the requirement of calculation time of on-line transient security and stabiliby assessment, an transient power angle security and stability contingency screening method base on clustering analysis of power grid operation history data.Extracting key feature quantities based on power grid operation mode and transient power angle stability assessment results in historical data.Determine the number of clusters and the initial clustering center by vector quantization method that takes into account the stable mode.Optimization of clustering center points using K-Medoids algorithm. The transient power angle margin is quickly estimated for the faults of the transient power angle stability after classification. Finally, a severe contingency set consisting of the faults of the transient power angle instability and the estimated margin below the threshold is obtained. According to the clustering analysis of actual history data, the validity and practicability fo the proposed method can be verified.

Abstract:Improving the accuracy of photovoltaic power generation prediction has important significance for ensuring the security and stability of power system and improving the development and utilization of solar energy resources. A short-term power forecasting model for photovoltaic power generation is proposed in this paper. This model is based on weather similiarty degree and improved cuckoo search algorithm(ICS),which is used to optimize Elman neural network. Firstly,in order to select the similar days with higher similarity,a similarity calculation method based on distance and angle trend is proposed. Secondly,the improved cuckoo algorithm is used to optimize the weight and threshold of Elman neural network,and a short-term power prediction model for photovoltaic power generation is established. Finally,the prediction results of the proposed model is compared with the results of traditional model. The results show that the prediction accuracy of this method is higher.

Abstract:Commutation failure is one of the most common faults in HVDC system, and the predictive control of commutation failure is an important means to prevent commutation failure. In this paper, the disturbance mechanism caused by the AC filter to the predictive control of commutation failure is analyzed in detail from the aspects of discrete action characteristics and control principle of circuit breaker. And at the same time, the feasibility of control strategy improvement is also analyzed from the detection. In order to thoroughly solve the influence of slight AC system disturbance on commutation failure predictive control and HVDC transmission system, such as the input of AC filter, the characteristics of DC current variation during AC system disturbance and failure are analyzed, and the new electrical parameters are introduced as auxiliary criteria to improve the commutation failure predictive control principle. The simulation results show that, the optimized commutation failure predictive control has stronger ability to resist the disturbance of AC system, higher applicability to HVDC project, and is more conducive to the stable operation of HVDC system.

Abstract:In view of the existing signal processing methods can not effectively solve the nonlinear and aliasing problems of low-frequency oscillation signals in power system, an improved variational mode decomposition (VMD) method is introduced into the pattern recognition of low frequency oscillation in this paper. Moreover, sample entropy and fast Fourier transform (FFT) are used to solve the problem of insufficient adaptive ability of VMD. The original signal is decomposed into several mode components by IVMD method. Then, Teager-Kaiser energy operator(TKEO) is applied on the fitting of each component to get the amplitude, frequency and damping of it. By the constructed test signal, the method of this paper is compared with VMD, empirical mode decomposition (EMD), total least squares-estimation of signal parameters via rotational invariance techniques (TLS-ESPRIT), and Prony on the performance of mode parameter identification. Results show that the IVMD method effectively overcomes the shortcomings of EMD, TLS-ESPRIT and Prony in dealing with mode mixing, noise sequence and non-stationary signals. Finally, the feasibility of the method of this paper in extracting the low frequency oscillation mode parameters of power system is verified by the simulation signal identification of the IEEE two-area four-generator power system and the New England 39-bus system.

Abstract:With the larger and larger amounts of distributed generation, the safe and stable operation of microgrid is being greatly tested, the importance of precise load-shedding control strategy is becoming more and more prominent. In order to minimize the overcutting value, and to improve the economy of load control, the control strategy of precise load-shedding in microgrid needs to be improved. At first, the principle of smart load is introduced and the dynamic change of power of intelligent load is realized by adjusting the voltage of electric spring (ES). Then, the traditional precise load-shedding control strategy of applying weight method and round method is analyzed, and a precise load-shedding control strategy based on smart loads is proposed to minimize the overcutting value through the dynamic response of the load, and apply it to the weight method and the round method. At last, the cases analysis indicate that, the proposed strategy can reduce the system overcutting value effectively, and enhance the economy of load control.

Abstract:In order to improve the forecasting accuracy of photovoltaic (PV) output power, a forecasting method is proposed based on k-means, KPCA and PSO-BP. Firstly, wavelet threshold de-noising algorithm is used to pretreat PV output data. Then, the k-means clustering algorithm is applied to divide the forecasting model into four sub models under different modes. The kernel principal component analysis (KPCA) method is used to reduce the dimensionality of the input space. Neural network algorithm is optimized based on particle swarm optimization (PSO). Finally, the PV output power forecasting model based on k-means /KPCA/PSO-BP is established. The example data is used to verify the forecasting model, the results show that it can forecast the PV output power accurately in different modes and have good forecasting performance.

Abstract:The uncertainty of hydro, wind resources and load will affect the economics and robustness of microgrid configuration, this paper proposes a bi-level optimal planning and design model for grid-connected hydro-wind-diesel microgrid, considering uncertainty of renewable energy and load. The up-level optimization is a microgrid configuration model. The low-level optimization is a microgrid economic dispatch model considering the uncertainty of hydro-wind power and load. Based on the robust linear optimization theory proposed by Seng-Cheol Kang(SCK-type robust linear optimization), the uncertainty model is transformed into a deterministic model. Then, combined with the fast non-dominated sorting genetic algorithm with elite strategy(NSGA-II) and mixed integer linear programming (MILP), the multi-objective optimal configuration problem of microgrid is solved. Finally, a distribution system in Shaoguan city is taken as a simulation example. The results show that the model not only improves the robustness of the microgrid, but also ensures the economics and reliability of the configuration.

Abstract:In order to effectively improve the operation safety perception ability of distribution network in the process of ubiquitous power Internet of Things construction, a real-time situation prediction method of distribution network based on multi-time scale state estimation is proposed, which can realize fast and accurate prediction of distribution network security situation. First of all, the multi-timescale recursive dynamic state estimation is realized based on hybrid measurement including distribution PMU through recursive transformation between state projection and pseudo measurement, which realizes the fast equivalent transformation of measurement and shorten the state update period. A correction module is added in the recursive transformation algorithm to eliminate pseudo-measurement fluctuation error, improving the stability and calculation speed of the state estimation algorithm. Then, the real-time safety situation projection of distribution network is realized through partitioned multivariate time series analysis based on historic estimated states, which establishes a real-time state prediction model. Finally, practical examples are simulated and analyzed on MATLAB simulation platform. The simulation results validate the accuracy and effectiveness of the proposed real-time situation prediction method for distribution network.

Abstract:HVDC cable is the key equipment of HVDC flexible transmission technology, and the insulation thickness design of HVDC cable is based on the safety margin of lightning impulse voltage. In order to obtain the safety margin, test method of safety margin under lightning impulse voltage is proposed in this paper, and impulse waveform is calculated, simulated and verified. Impulse voltage waveforms with wavefront time (1~5) μs and half peak time (40~60) μs is obtained. An analysis method of lightning impulse voltage safety margin of dc cable is presented, and the electric field distribution of cable insulation is calculated. The research shows that the safety margin of HVDC cable can be obtained by using the test method proposed in this paper, the research results provide a basis for the design of HVDC cable structure.

Abstract:The key gas method and IEC method for dissolved gases analysis only focus several gas index that may be affected by random error and relative percentages, and maybe it is not perfect to be used to conduct preventive maintenance and inspection of transformers. To solve the problem, key gases are mapped into 62 features including traditional combinations of key gases and other new features. The features highly correlated to transformer status are selected by maximum information coefficient, to escape random error of gas concentration. To avoid redundancy between selected features, Pearson coefficient is used to filter features to reduce the redundancy of the selected features. The result showed that correlation coefficient between the selected features and the transformer fault is relatively high. And the result of distance correlation coefficient also shows that the feature set formed by the selected features is more closely related to the transformer overheat fault state than that of the traditional fault characteristic gas.

Abstract:Dielectric materials are widely used in modern power grids. However, cracking phenomena easily occurs in the using process, and it may lead to partial discharge, electrical treeing, and even system failure. Micro-cracks are difficult to detect, and the replacement of dielectric materials requires a lot of manpower, material resources, and financial resources. Therefore, self-healing materials come into being. The self-healing of dielectric materials can be realized by doping with self-healing microcapsules of which dicyclopentadiene as core material and poly (urea-formaldehyde) (PUF) as wall material. However, PUF microcapsules have insufficient hardness and mechanical properties need to be enhanced. Three sets of models are established by molecular simulation. Each group included a pure PUF model and a PUF model doped with nano-SiO₂. The density, fractional free volume and mechanical properties are analyzed after molecular dynamics calculation. Results show that doping nano-SiO₂ is beneficial to increase the density of PUF materials, reduce the fractional free volume and enhance the mechanical properties. It is found that there are hydrogen bonds interactions between the polar atoms of PUF chain and hydroxyl, as well as O atoms on the surface of nano-SiO₂ by analyzing the interaction mechanism of PUF/SiO₂ interface.

Abstract:In order to solve the problem of qualitative analysis and low real-time performance of collusion identification methods in power market, this paper proposes an intelligent identification method of collusion behavior based on AdaBoost-DT algorithm, which uses AdaBoost-DT integrated classification algorithm to identify collusion behavior, and solves the problem that collusion behavior is difficult to identify quantitatively. Firstly, based on the mechanism of collusion, a set of collusion identification index system is designed. In the face of the problem of data imbalance, the oversampling method is used to expand the training data set, and the AdaBoost-DT classification algorithm is used to train the collusion behavior intelligent identification model. Finally, based on the monthly transaction data, an example is analyzed, and the receiver operating characteristic curve (ROC curve) and the area under the receiver operating characteristic curve (AUC value) are used to evaluate the recognition effect of the model. The experimental results show that the proposed method has good accuracy and real-time performance, which fully verifies the effectiveness of the algorithm.

Abstract:In view of the frequent occurrence of electricity arrears, how to use scientific methods and technical means to predict the arrears risk of power customers and reduce business risk is an urgent problem for the Power Grid Corp. Taking high-voltage customers from a certain areaas an example, this paper analyzes the factors affecting the recovery of electricity tariff, and extracts therisk features from multiple scales such as arrears frequency and duration, and then establishes a model based on logistic regression algorithm to predict the risk of user arrears. The model′s evaluation results show that the indicators such as the prediction accuracy, precision and recall rate are still relatively accurate when user information is not comprehensive enough. The model issensitive to the identification of risk users, and can be used to guide the power grid corp to formulate arrears risk management policiesand improving their management capabilities.

Abstract:On the basis of the research results of domestic and foreign threat tracing methods, in order to solve the problem of network security threat defense in power monitoring system. This paper combines with the requirements of power monitoring system security protection and the characteristics of power secondary system security protection by establishing the source of event location chain attack. The method firstly models the alarm log tree, constructs an event generation tree, and then aggregates the occurrence tree to obtain an initial event generation chain set. Finally, after the chain breaking process, the final event generation chain set is obtained. The method can automatically analyze the alarm data of the power monitoring system, extract the attack event, and process the original alarm into an attack map that can be visually displayed, thereby effectively capturing the associated host, and helping the network manager to monitor network security status in real time. So that timely safety measures are taken to ensure the safety of the network, data and equipment.

Abstract:In smart substation, the stability control device as a cross-interval device needs to receive and process a plurality of spaced sampling quantities simultaneously. Aiming at the problem of multi-interval sampling synchronization in "direct sampling ", a synchronization and resampling interpolation combining processing method based on local time scale is proposed. The message time stamp is used as the stability control device in the "direct sampling " for multi-interval sampling synchronization and resampling reference. With the auxiliary clock, the sampling data is synchronized, resampling by linearly interpolated and analyzed the interpolation error. Finally, the digital sampling of the stability control device is realized by FPGA+DSP hardware platform, and the experimental system is built. The timeliness of the local time-scale based synchronization interpolation algorithm proposed in this paper is analyzed from the aspects of sampling accuracy and synchronization effectiveness. The feasibility is verified. The test results verify that the synchronous linear resampling based on local time scale can meet the real-time and accuracy requirements of the actual engineering of the stability control device.

Abstract:Power converters are important components of power conversion transmission in wind power generation systems, and open circuit failures can cause unplanned downtime of wind power generation systems,so it is especially important to diagnose the open fault of the power converter. In this paper, the influence of space vector pulse width modulation (SVPWM) on the sector affected by the open circuit fault of the power switch and the change of the basic voltage space vector are analyzed. In this paper, according to the comparison of the sector numbers of SVPWM modulation before and after the failure of the power switch, a method for judging and locating the open circuit fault of the power switch is proposed. Compared with the existing diagnostic methods, the method can realize single-switch and double-switch open-circuit fault diagnosis, and only needs to collect a single variable of the sector number in SVPWM modulation, without adding additional hardware equipment, low data storage requirements, simple calculation and easy to implement. Finally, the effectiveness and feasibility of the proposed open circuit fault diagnosis method are verified by simulation and experiment.

Abstract:Conventional single-phase reclosing mode cannot identify instantaneous fault and permanent fault, when reclosing permanent fault, will increase an impact related to system or equipment, and is likely to lead to DC commutation failure. An adaptive reclosure criterion of double-circuit line is proposed, which only require single line information and have engineering practicability. The criterion uses the voltage of fault point, calculates the action threshold in real time through the capacitance parameters and the relationship between capacitance coupled voltages under various fault types to eliminate the fuzzy zone caused by the line capacitance parameter and fault type, introduces an auxiliary criterion and sets the reset time reasonably to eliminate the fuzzy zone caused by the cross-line non-earth fault. The simulation results show that the adaptive reclosing criterion is applicable to various types of failures that may occur on double-circuit line.

Abstract:In view of the unreasonable design of the dust filter mesh affecting the cooling effect of the transformer, a method for designing dust filter mesh width of transformer is proposed, which aims to reduce wind speed decay rate and dust filter weight, then establishes an optimal model on the basis of ensuring cooling effect of transformer, therefore the optimal value of mesh width for dust filter can be obtained. Based on the study of the structure of dust filter, the specific steps of the above method are displayed, and the optimal value of mesh width for dust filter is calculated for taking the cooler of 1 000 kV UHV transformer as an example. Finally, the wind speed decay rate test and field test verification have been done, which show that dust filter mesh width of transformer designed by this method can reduce the weight of dust filter, and be economical and practical on the basis of ensuring cooling effect of transformer, it verifies its validity and feasibility.