Single-phase-to-ground fault caused by insulation deterioration is one of the main fault forms of medium-voltage distribution network, which seriously affects the reliability of power supply. Rapid and accurate identification of insulation deterioration types can improve the efficiency of fault inspection, and is of great significance to prevent further expansion of faults. In this paper, nine waveform features are extracted from the time domain and frequency domain of the single-phase grounding fault waveform data. MANOVA and Pearson correlation coefficients were used to analyze their effectiveness in identifying insulation deterioration types. Furthermore, based on extreme learning machine and support vector machine, the identification models of single-phase grounding fault caused by insulation deterioration are established respectively. On this basis, based on Dempster-Shafer evidence theory, the results of the two recognition models were fused and the comprehensive recognition model was established. Using the obtained field data for verification, it is proved that the integrated model has a good recognition effect.
In the operation of urban rail transit, the stray current of the subway is generated and flows into the earth, resulting in different ground potentials of each substation, which causes the DC magnetic bias of the transformer. Firstly, this paper establishes the stray current distribution model of dual-terminal power supply mode of subway, and simulates the dynamic change of stray current by adjusting the change of subway position. Then, the COMSOL software is used to build the coupling model between the subway operation line and the urban AC grid, and the ground potential distribution characteristics during the subway operation are simulated and studied. Finally, based on the neutral grounding voltage obtained by simulation and the topology of urban power grid, the variation law of DC magnetic bias single current in each substation is analyzed. The research shows that when the local railway locomotive runs in the middle of the line, the leakage of the stray current of the subway is the most serious, which will produce greater induction potential, and the influence on the substations in different locations is intensified, which makes the magnetic bias current of each substation increase.
SF6 has strong greenhouse effect and many countries have enacted laws restricting the use of the gas. There have been several feasible alternatives to SF6. As an environmental friendly gas with excellent insulation characteristics, CF3I has the hope of replacing SF6 in medium and low voltage electrical equipment. In this paper, the influence of pressure and gap distance on the insulation strength of CF3I-N2 mixed gas was studied, and the results show that the insulation strength of CF3I-N2 mixture increases with the increase of CF3I mixture ratio. In slightly inhomogeneous electric field, the breakdown voltage of CF3I-N2 increases linearly with the increase of discharge gap, and the increase rate is proportional to the pressure. The breakdown voltage of CF3I-N2 gas mixture shows a trend of saturation with the gap in the extremely non-uniform electric field.
Because a large number of distributed energy sources are connected to the grid, the system becomes a high-order LC network. When a certain disturbance frequency is close to the system resonance point, the system resonance phenomenon will occur. Therefore, it is necessary to study the resonance detection method of clustered grid-connected photovoltaic power generation. In this paper, the resonance principle of the clustered grid-connected photovoltaic system is firstly analyzed based on the resonance model of the clustered grid-connected photovoltaic system. Then an LWT-based resonance detection technique is proposed. Through this algorithm, the start-stop time and frequency range of the clustered grid-connected photovoltaic system can be obtained. Finally, the simulation results demonstrate the effectiveness of the LWT-based resonance detection method for clustered grid-connected photovoltaic systems.
The alarm management system often has the problem of "flood" alarm for a period of time. A large number of flooding alarm will cause a crisis of trust between human and machine and reduce the availability of the system. The article first investigates the problem of unbalanced alarm distribution in the actual application of the alarm system. In order to adjust the probability density of different alarms, it is necessary to introduce the concept of alarm chatter rate that characterizes the arrival density of alarms. Then, the description principles and methods of the characteristics of alarm redundancy chatter are given. An alarm chatter rate characterization algorithm combining attenuation factor and natural alarm arrival rate is proposed. Finally, the concrete realization of the compression strategy based on this feature processing is given. Comparing and analyzing in actual test, this method can effectively reduce the number of redundant alarms and improve the efficiency of human-machine information interaction expression.
In the 1970s, German-style and American transmission and distribution cabinets (boxes) took the lead in research and application, and subsequent applications were popularized in countries around the world [ 1 ]. Transmission and distribution box, ring network cabinet, distribution cabinet, cable T connection cabinet, box change and other distribution facilities, equipment in the long-term operation will be affected by various factors such as the external environment, cabinet (box) many accessories, so that the internal and external gas is difficult to circulate convection ventilation, there is a non-convection "temperature difference effect", especially in the winter humidity sharp increase to form "condensation ice", the current industry a number of colleges and universities have carried out transmission and distribution cabinet (box) anti-condensation research and application, is still in the preliminary stage." This paper studies and designs the condenser [2], chip MCU dual-frequency control, NTC negative temperature coefficient thermal resistance, temperature and humidity, intelligent adjustment of temperature and humidity, fixed-point condensation water exclusion, which can effectively prevent the occurrence of "wet flash" failure [3] .
AC-DC hybrid microgrid has advantages of both AC/DC power supply and consumption system, and can meet the access of a variety of distributed power sources, energy storage units and loads. This study focuses on the application mode of ac-DC hybrid microgrid based on energy router.In terms of application mode research of hybrid microgrid with multi-port energy router, topology and coordination control of hybrid microgrid are studied and simulated in detail for typical application scenarios of large industrial enterprise parks.For large industrial enterprise parks, the hybrid microgrid topology of optical storage industrial enterprise parks is constructed to realize the common DC access of distributed power supply, electric vehicles and energy storage.The coordinated control strategy of energy router to controllable resources in the park under multi-mode grid connection is developed.Through the simulation experiment built in DIgSILENT/PowerFactory software, it is verified that the proposed scheme can significantly reduce the loss of industrial enterprise park and reduce the impact on distribution network.
Analyzing the influencing factors and degree of competitiveness of green power market is very important to establish its market mechanism. Based on the Porter's five forces model, this study uses Delphi method to identify five primary indicators and nineteen secondary indicators which affecting the competitiveness of green power market, then carry out expert scoring which based on Likert’s Nine Standard method and uses Analytic Hierarchy Process to construct judgment matrix and calculate weight. The results show that the suppliers, the buyers and the substitutes have great impact on the competitiveness of green power market. Based on this, two strategies to improve the competitiveness of green power market are proposed: one is to develop the energy storage technology, and the other is to improve the accuracy of electricity demand forecast.
multi-source data fusion is the background of the data processing in the future, for multi-source data analysis and processing, the current lack of quantifiable than consistency check method, need through the compare of multi-source data analysis, the correctness of the data to cany out the lean check, to the running state of field sampling equipment for evaluation of different dimensions.This paper proposes a consistency index analysis of multi-measurement data, which provides a new method for multi-source data comparison. The main idea is to obtain the total data consistency index through index and weighting based on the two-part analysis of the deviation index of comprehensive measurement data and the similarity index of comprehensive measurement data change trend. This method quantifies the consistency of multi-source data and provides a new evaluation method for the real-time running status of equipment through multi-source data verification, which improves the reliability of power grid operation.
In the future, the new power system dominated by high proportion of new energy will pose a new flexibility challenge to China's traditional reserve ancillary services market. In addition to power generation resources, user-side demand response resources can also provide reserve services. In the market environment, with the development of new market subject load aggregators, more small and medium-sized users' demand response resources can participate in system operation more effectively through the agent of load aggregators, especially in the spinning reserve market, and give full play to the value of demand response resources to improve system flexibility and economy. Based on the new model of small and medium users' demand response resource load aggregators participating in the spinning reserve market, and the generator set outage failure and the uncertainty when demand response resource provides reserve, This paper introduced the expected energy not supplied (EENS) reliability index ,and established the optimization model of multiple rotating reserve resources. On the premise of satisfying certain reliability, the model can minimize the reserve ancillary services market purchase cost and expected loss of low power. The example of IEEE30 node system shows that the model effectively coordinates the economy and reliability of the system.
As an important part of the construction of smart grids, distribution network fault location technology has received widespread attention to improve the level of grid automation. However, the complex structure and poor measurement conditions of distribution network have seriously restricted its application. By applying the synchronous vector information of Phasor Measurement Unit (PMU), this article proposes an optimization-based method to determine the fault location for distribution networks and realizes the fault location of various types. In this method, the voltage and current synchronous vector information provided by the PMU constitutes the optimization objective functions based on the voltage-current relationship. By solving these functions, the fault section and the accurate fault location can be obtained. In addition, the effectiveness of the proposed method when PMU information is missing is also discussed. The simulation results of PSCAD software show that the method is effective for various fault types in distribution network with distributed generation, and is still possible to provide effective fault section and accurate fault location in case of information loss.
Carbon peak and carbon neutrality goals will further accelerate the energy system revolution, promote economic comprehensive green and low-carbon transformation, and promote the diversification of energy utilization structure. A dynamic economic dispatching strategy of island operation multi-energy complementary multi-energy system for park is presented in this paper. Firstly, on the basis of collecting energy supply and demand data from park, the multi-type energy conversion equipment model and energy storage model are established respectively according to the geographical resource endowment. Then, the dynamic economic dispatching model is established by taking the operation cost of multi-energy system as the objective function and considering the multi-type safe operation constraints. Finally, an example is given to verify the rationality and validity of the proposed model and method for dynamic economic dispatching. The proposed model and method can realize optimal operation management of energy in park and provide reference for economic dispatching of multi-energy system in engineering applications.
In networked microgrids, each microgrid is usually managed by an independent operator, and it is difficult to adapt to the actual situation of data privacy protection and distributed management among microgrids by using the global power flow method, so distributed power flow should be used for analysis. Existing distributed power flow algorithms rarely solve the problem of non-smooth limits of distributed photovoltaic, and the non-smooth constraints such as limits will cause the microgrid power flow to not converge. This paper proposes a distributed power flow calculation method considering limiting constraints of photovoltaic inverters. Firstly, the non-smooth limits models for DG are established based on complementary constraints, and smoothed by Fischer-Burmeister (FB) function; then, according to the requirements of distributed management, the networked microgrids is partialized, and the boundary coordination equation of coordination side is established in the form of implicit function, which is solved by the Jacobian-Free Newton-GMRES (JFNG) algorithm, avoiding the explicit Jacobian matrix. Finally, an example is used to verify the accuracy of the proposed distributed algorithm and the effectiveness of the non-smooth characteristic processing method.
The traditional series active power filter based on magnetic flux compensation (MFC) can be divided into current type and voltage type according to the control method. The former can realize accurate compensation, but has the disadvantages of complex controller design and slow dynamic response. Although the latter responds quickly, its strong nonlinearity of impedance regulation and the characteristics of open-loop control lead to low impedance control accuracy. Considering the characteristics of the two control types, this paper presents a new voltage current hybrid control method for harmonic control of wind turbine, in which the current loop is designed to control the fundamental current, which can simplify the current loop and realize accurate control of the fundamental impedance, while the voltage feedforward is used to controlled the harmonic impedance, which has fast response and can make the adjustable impedance present a large impedance to dynamically suppress the harmonic current in transmission lines. A simulation model has been built in Matlab/Simulink and the simulation results verify the effectiveness of the proposed control method.
The scale of modern power grids is huge and the structure is complex, and most of the power equipment is directly exposed to the external environment. In recent years, the problems of global warming and environmental damage have become increasingly prominent. The impact of disasters on the safe and stable operation of power grids has become increasingly prominent. In order to deal with the impact of meteorological disasters on the power grid and reduce the losses caused by meteorological disasters to the power system, it is necessary to build a micrometeorological monitoring station for the power grid, and use the meteorological monitoring data for disaster early warning analysis. However, existing meteorological monitoring stations have a series of data quality problems due to the particularity of their own spatial locations, and there are a lot of dirty data in the original data, which seriously affects the accuracy of subsequent data analysis. To this end, this paper proposes a power meteorological data cleaning method based on spatiotemporal inverse distance weight interpolation. Experiments show that this method can remove most of the dirty data in the original power meteorological data, thereby effectively improving the prediction accuracy of power grid meteorological disasters. Safe and stable operation is of great significance
There are more than 70,000 wildfires in China every year. Wildfires cause air insulation to drop, causing trips and blackouts on important transmission lines such as UHV. The UHV Changnan Line was tripped three times due to wildfires, and the blackouts lasted for up to 72 hours. The wildfires have seriously threatened the safe and stable operation of the power grid. Remote sensing monitoring technology can detect wildfires early, effectively reducing the number of wildfire trips. In view of the difficulty of early detection of small-area wildfires, this paper uses the deep convolutional neural network (DCNN) to monitor the wildfire area of Landsat-8 OLI images with a spatial resolution of 30 meters. We propose powerful network architecture, named multi-scale U2-Net, for transmission line wildfire detection (WFD). The multi-scale U2-Net is a two-level nested U-structure and allows the network to go deeper. It adopts the multi-scale image pyramid (MIP) and ReSidual U-blocks (RSUs), which achieved higher overall accuracy for WFD than traditional algorithms. And it also allows the network to be trained from scratch and achieve competitive results. Experimental results on Landsat-8 images show that the network is competitive both quantitatively and qualitatively, preserving the edge structures of wildfire regions. Compared with existing state-of-the-art networks, our proposed algorithm achieves better final results.
With the development of flexible DC transmission systems, DC distribution systems applying modular multi-level converter (MMC) are gradually becoming a new trend in the development of future distribution networks. But the fault problem of this system is also more serious. Firstly, the transient characteristics of a bipolar short-circuit fault occurring in the DC line of a double-ended flexible DC distribution system are analyzed, followed by a new distribution structure that can effectively suppress the overcurrent, which can effectively suppress the current growth rate of the MMC bridge arm and facilitate the DC circuit breaker to cut off the fault current, and finally, based on the double-ended flexible DC distribution system built in PSCAD/EMTDC, the proposed structure is verified to be validity.
As new energy accelerates to replace traditional fossil energy, large-scale new energy stations are under construction and operation in full swing. Potential fault detection of collector line can effectively avoid equipment damage and improve operation reliability. Based on the high-frequency traveling wave, the potential fault detection technology is proposed in this paper. Firstly, the structure of new energy station is analyzed, the definition of potential fault is explored, and the principle and technology of potential fault detection based on traveling wave are mainly introduced. Finally, this paper presents the potential fault identification system and its field application.
In the line loss management of low voltage distribution table area, it is difficult for power company to manage line loss because of the abnormal behavior of users and the behavior of stealing power. In this paper, the contribution of user loss is calculated by transfer entropy algorithm for users in high-loss area. Copula entropy is used for nonparametric estimation to improve computational performance. After ranking the loss contribution degree of users, targeted measures should be taken to rectify the loss contribution degree of users of different degrees. This method can effectively improve the efficiency of line loss management and reduce the overall line loss rate of the distribution area.
The existing protection of the PV power plant collection line is staged overcurrent protection at the line exit. A fault at any point on the line causes the entire line to be completely removed, bringing unnecessary power loss. This paper addresses the problem that the existing protection is not selective and proposes a new collection line protection scheme based on the Distribution line Non-Communication Protection(DNCP). After a fault occurs, the Protection Terminal Unit(PTU) on the grid-connected side of the fault point system detects an evident overcurrent corresponding to the power side of the DNCP. The PTU on the PV generation unit side of the fault point detects a voltage dip corresponding to the load side of the DNCP. After the PTU at one end operates first, the PTU at the other end accelerates the action at this end based on the detected secondary disturbance information to achieve fault zone isolation and minimal cut-off. Through the analysis of calculation cases, it is verified that the new protection scheme can realize refined operation control and protection and improve operation efficiency compared with the original protection scheme.
