WO2019128335A1 - 配电网拓扑错误辨识方法 - Google Patents
配电网拓扑错误辨识方法 Download PDFInfo
- Publication number
- WO2019128335A1 WO2019128335A1 PCT/CN2018/107061 CN2018107061W WO2019128335A1 WO 2019128335 A1 WO2019128335 A1 WO 2019128335A1 CN 2018107061 W CN2018107061 W CN 2018107061W WO 2019128335 A1 WO2019128335 A1 WO 2019128335A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- load
- voltage
- distribution network
- current
- sample space
- Prior art date
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
- H04L67/1004—Server selection for load balancing
- H04L67/1008—Server selection for load balancing based on parameters of servers, e.g. available memory or workload
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R19/00—Arrangements for measuring currents or voltages or for indicating presence or sign thereof
- G01R19/25—Arrangements for measuring currents or voltages or for indicating presence or sign thereof using digital measurement techniques
- G01R19/2513—Arrangements for monitoring electric power systems, e.g. power lines or loads; Logging
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/12—Discovery or management of network topologies
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/02—Topology update or discovery
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
- H04L67/1004—Server selection for load balancing
- H04L67/101—Server selection for load balancing based on network conditions
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
- H04L67/1004—Server selection for load balancing
- H04L67/1012—Server selection for load balancing based on compliance of requirements or conditions with available server resources
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/30—State monitoring, e.g. fault, temperature monitoring, insulator monitoring, corona discharge
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S40/00—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
- Y04S40/18—Network protocols supporting networked applications, e.g. including control of end-device applications over a network
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S40/00—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
- Y04S40/20—Information technology specific aspects, e.g. CAD, simulation, modelling, system security
Definitions
- the present application belongs to the technical field of power system parameter identification, for example, to a topology error identification method for a distribution network.
- Power system topology analysis data is mainly composed of switching quantities.
- bad data will inevitably occur, resulting in network topology information errors.
- the correct network topology is the basis for other analyses such as power flow calculation, state estimation, fault location, isolation and power restoration, network reconstruction, and reliability analysis.
- the topology error identification function is one of the important foundations to ensure the effective operation of many functions.
- the transfer flow method has a good ability to identify single topology errors and multiple related telemetry errors. However, this method must obtain a well-tuned cross-section state as the ground state. If the selected ground state is significantly different from the current topology, Its topology error recognition effect will be greatly reduced.
- the new interest graph method has a good identification effect for dealing with multiple topological errors and multiple related telemetry errors, but this method has the problem of sudden load change, which has a great influence on the identification effect.
- Residual method, set theory method and minimum information loss method are based on augmented state variables, establish a unified estimation model of remote signal and telemetry, and then transform topological error identification into large-scale mixed integer programming problem, but the convergence of these methods is calculated. And the stability is less effective than simple state estimation, and it is not suitable for online applications. These traditional methods rely on a single source of data and a complex calculation process.
- the application provides a topology error identification method for distribution network, which has reasonable design, fast identification speed and reliable identification result.
- the present application provides a distribution network topology error identification method, including:
- the verification and correction of the distribution network topology is completed according to the voltage correlation coefficient and the current correlation coefficient.
- calculating a coupling node voltage U pc to which each load in the distribution network topology belongs, and obtaining a coupling node voltage sample space to which all loads of the distribution network belong include:
- the coupling node voltage U pc of the feeder to which each load belongs is calculated to obtain the power distribution.
- the coupling node voltage sample space to which all loads in the network belong.
- the calculation calculates the coupling node voltage U pc of the feeder to which each load belongs to obtain the coupling node voltage sample space to which all loads in the distribution network belong:
- j is the number of the measuring instrument
- U j is the measured value of the load voltage obtained by the measuring instrument j
- I j is the measured value of the current obtained by the measuring instrument j
- Z sj is expressed as the measuring instrument j Measuring the impedance value of the point to the coupling point PCj, where N is a positive integer greater than or equal to 2;
- T is a positive integer greater than or equal to 2
- the sample space of the voltage at ..., N) is expressed as
- the method further includes:
- the measuring instrument j does not detect the current value of the I j current measurement, in accordance with the collected load active AMI M j, the reactive power and the voltage amplitude coupling node measurement information obtained current measurement values the I j, calculated
- the formula is as follows,
- P represents the load active power measurement M j of j
- Q j M j representative of the load reactive power measured values.
- the branch current I L to which each load in the distribution network topology belongs is calculated, and the branch current sample space to which all loads of the distribution network belong is obtained:
- the branch current I L of the branch to which each load belongs is calculated, and the branch current sample space to which all loads of the distribution network belong is obtained:
- the verifying and correcting the distribution network topology according to the voltage correlation coefficient and the current correlation coefficient comprises:
- the present application provides a distribution network topology error identification apparatus, including: a memory and a processor; wherein the memory stores an executable program, and when the processor executes the program, the following steps are performed:
- the verification and correction of the distribution network topology is completed according to the voltage correlation coefficient and the current correlation coefficient.
- the calculating the coupling node voltage U pc to which each load in the distribution network topology belongs, and obtaining the coupling node voltage sample space to which all loads of the distribution network belong include:
- the coupling node voltage U pc of the feeder to which each load belongs is calculated to obtain the power distribution.
- the coupling node voltage sample space to which all loads in the network belong.
- the calculation calculates the coupling node voltage U pc of the feeder to which each load belongs to obtain the coupling node voltage sample space to which all loads in the distribution network belong:
- j is the number of the measuring instrument
- U j is the measured value of the load voltage obtained by the measuring instrument j
- I j is the measured value of the current obtained by the measuring instrument j
- Z sj is expressed as the measuring instrument j Measuring the impedance value of the point to the coupling point PCj, where N is a positive integer greater than or equal to 2;
- T is a positive integer greater than or equal to 2
- the sample space of the voltage at ..., N) is expressed as
- the processor further performs the following steps when executing the program:
- the measuring instrument j does not detect the current value of the I j current measurement, in accordance with the collected load active AMI M j, the reactive power and the voltage amplitude coupling node measurement information obtained current measurement values the I j, calculated
- the formula is as follows,
- P represents the load active power measurement M j of j
- Q j M j representative of the load reactive power measured values.
- the branch current I L to which each load in the distribution network topology belongs is calculated, and the branch current sample space to which all loads of the distribution network belong is obtained:
- the branch current I L of the branch to which each load belongs is calculated, and the branch current sample space to which all loads of the distribution network belong is obtained:
- the verifying and correcting the distribution network topology according to the voltage correlation coefficient and the current correlation coefficient comprises:
- the application also provides a computer readable storage medium storing computer executable instructions for performing any of the methods described above.
- the application also provides a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions, when the program instructions are executed by a computer, Having the computer perform any of the methods described above.
- the principle of topology error identification is constructed. Then, with the measurement information and network data provided by the advanced measurement system AMI, the coupling voltage and the branch current of the load are obtained. Then, the correlation analysis of the coupling voltage and the branch current is carried out. Finally, the correctness of the topology is verified, and the detected topology error is corrected, and the identification and correction of the topology error is finally completed.
- the validity of the topology error identification algorithm proposed in this application is tested. The results show that the algorithm has good ability to identify and correct multiple complex cases with multiple topological errors. The example shows the feasibility and effectiveness of the algorithm.
- This application considers the voltage and current distribution characteristics of the distribution network at the same time, avoiding the shortage of considering only a single identification factor, ensuring the reliability of topology identification and improving the effectiveness of topology identification.
- 1 is a schematic view showing the structure of a distribution network in an embodiment.
- FIG. 2 is a schematic diagram of a simplified voltage distribution of a distribution network in an embodiment.
- Fig. 3 is a schematic view showing the current distribution of the branch circuit of the distribution network in an embodiment.
- FIG. 4 is a schematic diagram showing the hardware structure of a distribution network topology error identification device in an embodiment.
- the topology error identification method based on AMI measurement information used in the present application includes: based on the voltage distribution and current distribution characteristics of the distribution network, respectively calculating the load of each load in the entire time series based on the data collected by the AMI The voltage value of the coupling node and its branch current value are obtained, and the sample space of the coupling node voltage and its branch current of each load is obtained, and then the correlation between the coupled node voltage and its branch current sample space is obtained. Analysis; based on the results of the correlation analysis, verify the correctness of the distribution network topology and correct the wrong distribution network topology.
- the topology error identification method of the distribution network based on the AMI measurement information in the present application includes:
- Step 110 Calculate a coupling node voltage U pc to which each load belongs in the distribution network topology, and obtain a coupling node voltage sample space to which all loads of the distribution network belong.
- the step 110 includes: calculating, according to the measurement information of the active power, the reactive power, and the node voltage amplitude of each load collected by the AMI, in the entire time series based on the AMI data collection.
- the node voltage of the feeder to which the load belongs that is, the coupling node voltage U pc to which each load belongs, thereby obtaining the coupling node voltage sample space to which all loads of the distribution network belong.
- Step 120 Calculate the branch current I L to which each load belongs in the distribution network topology, and obtain the branch current sample space to which all loads of the distribution network belong.
- the step 120 includes: calculating, according to the measurement information of the active power, the reactive power, and the node voltage amplitude of each load collected by the AMI, in the entire time series of data collected by the AMI, The current value of the branch to which the load belongs, that is, the branch current I L to which each load belongs, thereby obtaining the branch current sample space to which all loads of the distribution network belong.
- Step 130 Calculate a voltage correlation coefficient and a current correlation coefficient between different loads according to the voltage sample space and the current sample space obtained in step 110 and step 120, respectively.
- Step 140 Perform verification and correction of the distribution network topology according to the voltage correlation coefficient and the current correlation coefficient.
- the step 140 includes: determining, according to the determination condition of the selected correlation analysis method, the feeder associated with the load based on the voltage correlation coefficient and the current correlation coefficient calculated in step 130, and then based on step 110 The voltage amplitude of the coupling node to which each load belongs, determines the upstream and downstream relationship of each load in the feeder, and completes the verification and correction of the topology of the distribution network.
- the embodiment of the present application only needs to calculate the coupling node voltage and the branch current to which the load belongs, thereby effectively reducing the running time required for identification, and ensuring the quickness of topology identification.
- the embodiment of the present application considers the voltage and current distribution characteristics of the distribution network at the same time, avoids the shortage of considering only a single identification factor, ensures the reliability of the topology identification, and improves the validity of the topology identification.
- a radial distribution network model is taken as an example to describe a topology error identification method based on AMI measurement information.
- PCj 1, 2, ..., N
- the node that represents the branch to which the load belongs and the feeder is recorded as a coupling node.
- Figure 1 shows the load topology relationship under the same distribution transformer.
- TX represents the distribution transformer
- Step 210 Calculate the coupling node voltage to which each load belongs.
- P j and Q j represent the active power measurement value and the reactive power measurement value of the load M j , respectively.
- FIG. 1 can be simplified to FIG. 2, that is, each load and its associated branch are Can be removed in Figure 1.
- Figure 2 shows the simplified power distribution system diagram obtained after calculating the voltage of the coupling node to which each load belongs. The simplified process is to remove each load and its associated branch from Figure 1.
- TX represents a distribution transformer
- the above analysis and derivation are performed on the distribution network at a certain time, that is, the time t is equal to a specific moment. Since the advanced measurement system provides long enough time series measurement data for calculation and analysis, the voltage sample space of the coupled node to which all loads of the distribution network belong can be obtained in the entire time series, namely:
- Step 220 Calculate the branch current to which each load belongs.
- P j, Q j M j representing the load measured value of active power and reactive power measurement value
- U j representative of the amount of the load voltage measured value M j.
- Figure 1 Based on the branch current distribution of each load, Figure 1 can be converted into Figure 3, that is, the branch current to which each load belongs can be identified in its branch.
- Figure 3 shows the distribution of the branch currents for each load after calculating the branch current for each load. That is, the branch current to which each load belongs can be clearly indicated in the branch road to which it belongs.
- TX represents the distribution transformer
- the above analysis and derivation are carried out on the distribution network at a certain time, that is, the time t is equal to a certain moment, because the advanced measurement system provides a sufficiently long time series measurement data for calculation and analysis, considering the entire time.
- the sequence T can obtain the branch current sample space belonging to all loads of the distribution network, namely:
- Step 230 Calculate voltage correlation coefficients and current correlation coefficients between different loads.
- Step 240 Verify and correct the distribution network topology.
- the feeders to which each load belongs are determined according to the discrimination conditions selected by the correlation analysis method, and then based on the voltage amplitude of the coupled node to which each load belongs in step 210, that is, the same
- the voltage amplitude of the coupling node in the feeder is degraded from upstream to downstream, and the upstream and downstream relationship of each load in the feeder is determined to complete the topology verification. If the wrong topology connection is identified, the error topology connection is corrected, that is, the load of the topology connection error is determined, and the voltage and current correlation coefficients of the load and other coupling nodes in the distribution network are calculated, and the correlation criterion is satisfied.
- the feeder to which the load belongs and the position of the coupled connection point in the feeder can be determined to complete the verification of the correctness of the topology of the distribution network and the correction of the wrong topology connection.
- the embodiment of the present application first constructs a topology error identification principle based on the voltage distribution characteristics of the distribution network and the load current distribution characteristics, and then obtains the coupling voltage and the branch current of the load by using the measurement information provided by the advanced measurement system AMI. The correlation analysis of the coupling voltage and the branch current is carried out. Finally, the correctness of the topology is verified, and the detected topological errors are corrected, and the identification and correction of the topology errors are finally completed.
- the validity of the topology error identification algorithm proposed in this application is tested. The results show that the algorithm has good ability to identify and correct multiple complex cases with multiple topological errors. The example shows the feasibility and effectiveness of the algorithm.
- An embodiment provides a distribution network topology error identification device, including: a memory and a processor; wherein
- the memory stores an executable program, and when the processor executes the program, the following steps are performed:
- the verification and correction of the distribution network topology is completed according to the voltage correlation coefficient and the current correlation coefficient.
- the calculating the coupling node voltage U pc to which each load in the distribution network topology belongs, and obtaining the coupling node voltage sample space to which all loads of the distribution network belong include:
- the coupling node voltage U pc of the feeder to which each load belongs is calculated to obtain the power distribution.
- the coupling node voltage sample space to which all loads in the network belong.
- the calculation calculates the coupling node voltage U pc of the feeder to which each load belongs to obtain the coupling node voltage sample space to which all loads in the distribution network belong:
- j is the number of the measuring instrument
- U j is the measured value of the load voltage obtained by the measuring instrument j
- I j is the measured value of the current obtained by the measuring instrument j
- Z sj is expressed as the measuring instrument j Measuring the impedance value of the point to the coupling point PCj, where N is a positive integer greater than or equal to 2;
- T is a positive integer greater than or equal to 2
- the sample space of the voltage at ..., N) is expressed as
- the processor further performs the following steps when executing the program:
- the measuring instrument j does not detect the current value of the I j current measurement, in accordance with the collected load active AMI M j, the reactive power and the voltage amplitude coupling node measurement information obtained current measurement values the I j, calculated
- the formula is as follows,
- P represents the load active power measurement M j of j
- Q j M j representative of the load reactive power measured values.
- the branch current I L to which each load in the distribution network topology belongs is calculated, and the branch current sample space to which all loads of the distribution network belong is obtained:
- the branch current I L of the branch to which each load belongs is calculated, and the branch current sample space to which all loads of the distribution network belong is obtained:
- the verifying and correcting the distribution network topology according to the voltage correlation coefficient and the current correlation coefficient comprises:
- An embodiment further provides a computer readable storage medium storing computer executable instructions for performing any of the distribution network topology error identification methods described above.
- FIG. 4 is a schematic diagram of a hardware structure of a distribution network topology error identification apparatus according to an embodiment. As shown in FIG. 4, the identification apparatus includes: one or more processors 410 and a memory 420. One processor 410 is taken as an example in FIG.
- the identification device may further include: an input device 430 and an output device 440.
- the processor 410, the memory 420, the input device 430, and the output device 440 in the identification device may be connected by a bus or other means, and the bus connection is taken as an example in FIG.
- the input device 430 can receive input numeric or character information
- the output device 440 can include a display device such as a display screen.
- the memory 420 is a computer readable storage medium that can be used to store software programs, computer executable programs, and modules.
- the processor 410 executes a plurality of functional applications and data processing by executing software programs, instructions, and modules stored in the memory 420 to implement any of the distribution network topology error identification methods in the above embodiments.
- the memory 420 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application required for at least one function; the storage data area may store data created according to the use of the identification device, and the like.
- the memory may include volatile memory such as random access memory (RAM), and may also include non-volatile memory such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device.
- Memory 420 can be a non-transitory computer storage medium or a transitory computer storage medium.
- the non-transitory computer storage medium such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device.
- memory 420 can optionally include memory remotely located relative to processor 410, which can be connected to the identification device over a network. Examples of the above networks may include the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.
- the input device 430 can be configured to receive input digital or character information and to generate key signal inputs related to user settings and function control of the identification device.
- Output device 440 can include a display device such as a display screen.
- the identification device of this embodiment may also include a communication device 450 for transmitting and/or receiving information over a communication network.
- a person skilled in the art can understand that all or part of the process of implementing the above embodiment method can be completed by executing related hardware by a computer program, and the program can be stored in a non-transitory computer readable storage medium.
- the program when executed, may include the flow of an embodiment of the method as described above, wherein the non-transitory computer readable storage medium may be a magnetic disk, an optical disk, a read only memory (ROM), or a random access memory (RAM). Wait.
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Power Engineering (AREA)
- Computer Hardware Design (AREA)
- General Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Supply And Distribution Of Alternating Current (AREA)
- Remote Monitoring And Control Of Power-Distribution Networks (AREA)
Abstract
一种配电网拓扑错误辨识算法,包括:计算每个负荷所属的耦合节点电压,获得负荷所属的耦合节点电压样本空间;计算每个负荷所属的支路电流,获得负荷所属的支路电流样本空间;根据获得的电压样本空间和电流样本空间,分别计算不同负荷间的电压相关系数和电流相关系数;完成配电网拓扑的校验与修正。
Description
本申请要求在2017年12月29日提交中国专利局、申请号为201711476473.9的中国专利申请的优先权,该申请的全部内容通过引用结合在本申请中。
本申请属于电力系统参数辨识技术领域,例如涉及一种配电网拓扑错误辨识方法。
电力系统拓扑分析数据主要由开关量组成,然而在开关量采集过程中,由于系统设备、网络等原因,将不可避免地产生不良数据,导致网络拓扑信息出现错误。然而,正确的网络拓扑是进行潮流计算、状态估计、故障定位、隔离与供电恢复、网络重构、可靠性分析等其他分析的基础。随着智能电网建设的不断发展,不同层级的配电自动化系统陆续投入使用,而拓扑错误辨识功能是保障其诸多功能有效运行的重要基础之一。
国内外学者针对电网拓扑错误辨识进行了大量的研究,并提出了诸多辨识方法,主要包括转移潮流法、新息图法、残差法、集合论法以及最小信息损失法等方法。
转移潮流法对于存在单一拓扑错误与多个相关遥测错误情况具有较好的辨识能力,但该方法必须预先得到一个调试很好的断面状态作为基态,如果所选基态与当前拓扑存在较大差别,其拓扑错误辨识效果将大大降低。新息图法对于处理多重拓扑错误以及多个相关遥测错误具有良好的辨识效果,但该方法存在负荷突变的问题,其对辨识效果存在很大影响。残差法、集合论法以及最小信息损失法基于增广状态变量,建立遥信、遥测相统一的估计模型,进而把拓扑错误辨识转化为大规模混合整数规划问题,但这些方法计算的收敛性以及稳定性相比于单纯的状态估计,辨识效果较差,且尚不能适应于在线应用。这些传统方法所依赖数据源较为单一,并且计算过程复杂。
随着智能电网建设的不断推进以及智能传感器设备的大量投入运行,以及高级量测体系(advanced meter infrastructure,AMI)在配电网中的应用,这为电力系统拓扑错误辨识提供了大量的数据来源以及新的技术手段。但目前基于 AMI量测数据对配电网拓扑错误进行辨识的研究尚处于起步阶段,因此,本申请提出了一种基于AMI量测信息的配电网拓扑错误辨识算法。
发明内容
本申请提供了配电网拓扑错误辨识方法,设计合理、辨识速度快且辨识结果可靠。
本申请提供一种配电网拓扑错误辨识方法,包括:
计算所述配电网拓扑中每个负荷所属的耦合节点电压U
pc,获得所述配电网所有负荷所属的耦合节点电压样本空间;
计算所述配电网拓扑中每个负荷所属的支路电流I
L,获得所述配电网所有负荷所属的支路电流样本空间;
根据获得的所述电压样本空间和所述电流样本空间,分别计算不同负荷间的电压相关系数和电流相关系数;以及
根据所述电压相关系数和所述电流相关系数完成所述配电网拓扑的校验与修正。
在一实施例中,计算所述配电网拓扑中每个负荷所属的耦合节点电压U
pc,获得所述配电网所有负荷所属的耦合节点电压样本空间包括:
在基于高级测量体系AMI采集数据的整个时间序列内,根据AMI采集的每个负荷的耦合节点电压幅值的量测信息,计算得到每个负荷所属馈线的耦合节点电压U
pc,以获得配电网中所有负荷所属的耦合节点电压样本空间。
在一实施例中,所述计算得到每个负荷所属馈线的耦合节点电压U
pc,以获得配电网中所有负荷所属的耦合节点电压样本空间包括:
根据欧姆定律,耦合节点PCj(j=1,2,…,N)处的电压幅值表示为,
U
pcj=U
j+Z
sj×I
j
式中,j表示为量测仪表的编号;U
j是量测仪表j获取的负荷电压量测值,I
j是量测仪表j获取的电流量测值;Z
sj表示为量测仪表j的量测点到耦合点PCj的阻抗值,N为大于等于2的正整数;
在所述整个时间序列内,配电网中所有负荷所属耦合节点电压样本空间为,
其中,对于某一特定时刻t
i(i=1,2,...,T),T为大于等于2的正整数,配电网中所有负荷对应的耦合节点PCj(j=1,2,…,N)处电压的样本空间表示为,
在所述整个时间序列内,负荷M
j所属耦合节点PCj(j=1,2,…,N)处的电压样本空间表示为,
在一实施例中,所述方法还包括:
若量测仪表j未检测到当前的电流量测值I
j,根据AMI采集的负荷M
j的有功功率、无功功率和耦合节点电压幅值的量测信息得到电流量测值I
j,计算公式如下所示,
式中,P
j代表负荷M
j的有功功率量测值,Q
j代表负荷M
j的无功功率量测值。
在一实施例中,所述计算所述配电网拓扑中每个负荷所属的支路电流I
L,获得所述配电网所有负荷所属的支路电流样本空间包括:
在整个时间序列内,根据AMI采集的每个负荷的有功功率、无功功率和耦合节点电压幅值的量测信息,计算得到每个负荷所属支路的支路电流I
L,进而获得所述配电网所有负荷所属的支路电流样本空间。
在一实施例中,所述计算得到每个负荷所属支路的支路电流I
L,进而获得所述配电网所有负荷所属的支路电流样本空间包括:
基于欧姆定律,每个负荷所属支路电流I
Lj(j=1,2,...,N)幅值表示为,
式中,P
j代表负荷M
j的有功功率量测值,Q
j代表负荷M
j的无功功率量测值;U
j代表该负荷M
j的量测电压幅值,N为大于等于2的正整数;
在整个时间序列内,所述配电网所有负荷所属支路电流样本空间为,
在一实施例中,所述根据所述电压相关系数和所述电流相关系数完成所述配电网拓扑的校验与修正包括:
基于所述电压相关系数和所述电流相关系数,依据所选用相关性分析法的判别条件,判断每个负荷所属的馈线,然后基于每个负荷所属耦合节点电压幅值,确定每个负荷在所属馈线中的上下游关系是否满足同一馈线中耦合节点的电压幅值由上游至下游递减,不满足电压幅值由上游至下游递减的负荷为拓扑连接错误的负荷;若辨识出拓扑连接错误的负荷,则计算该负荷与配电网网络中其他耦合节点的电压相关性系数和电流相关性系数,当所述电压相关性系数和所述电流相关性系数满足相关性判别准则时,确定该负荷所属馈线以及在馈线中的耦合连接点,以完成对配电网拓扑正确性的校验以及对错误拓扑连接的修正。
本申请提供一种配电网拓扑错误辨识装置,包括:存储器和处理器;其中,所述存储器存储有可执行程序,所述处理器执行所述程序时执行以下步骤:
计算所述配电网拓扑中每个负荷所属的耦合节点电压U
pc,获得所述配电网所有负荷所属的耦合节点电压样本空间;
计算所述配电网拓扑中每个负荷所属的支路电流I
L,获得所述配电网所有负荷所属的支路电流样本空间;
根据获得的所述电压样本空间和所述电流样本空间,分别计算不同负荷间的电压相关系数和电流相关系数;以及
根据所述电压相关系数和所述电流相关系数完成所述配电网拓扑的校验与修正。
在一实施例中,所述计算所述配电网拓扑中每个负荷所属的耦合节点电压U
pc,获得所述配电网所有负荷所属的耦合节点电压样本空间包括:
在基于高级测量体系AMI采集数据的整个时间序列内,根据AMI采集的每个负荷的耦合节点电压幅值的量测信息,计算得到每个负荷所属馈线的耦合节点电压U
pc,以获得配电网中所有负荷所属的耦合节点电压样本空间。
在一实施例中,所述计算得到每个负荷所属馈线的耦合节点电压U
pc,以获 得配电网中所有负荷所属的耦合节点电压样本空间包括:
根据欧姆定律,耦合节点PCj(j=1,2,…,N)处的电压幅值表示为,
U
pcj=U
j+Z
sj×I
j
式中,j表示为量测仪表的编号;U
j是量测仪表j获取的负荷电压量测值,I
j是量测仪表j获取的电流量测值;Z
sj表示为量测仪表j的量测点到耦合点PCj的阻抗值,N为大于等于2的正整数;
在所述整个时间序列内,配电网中所有负荷所属耦合节点电压样本空间为,
其中,对于某一特定时刻t
i(i=1,2,...,T),T为大于等于2的正整数,配电网中所有负荷对应的耦合节点PCj(j=1,2,…,N)处电压的样本空间表示为,
在所述整个时间序列内,负荷M
j所属耦合节点PCj(j=1,2,…,N)处的电压样本空间表示为,
在一实施例中,所述处理器执行所述程序时还执行以下步骤:
若量测仪表j未检测到当前的电流量测值I
j,根据AMI采集的负荷M
j的有功功率、无功功率和耦合节点电压幅值的量测信息得到电流量测值I
j,计算公式如下所示,
式中,P
j代表负荷M
j的有功功率量测值,Q
j代表负荷M
j的无功功率量测值。
在一实施例中,所述计算所述配电网拓扑中每个负荷所属的支路电流I
L,获得所述配电网所有负荷所属的支路电流样本空间包括:
在整个时间序列内,根据AMI采集的每个负荷的有功功率、无功功率和耦合节点电压幅值的量测信息,计算得到每个负荷所属支路的支路电流I
L,进而获得所述配电网所有负荷所属的支路电流样本空间。
在一实施例中,所述计算得到每个负荷所属支路的支路电流I
L,进而获得 所述配电网所有负荷所属的支路电流样本空间包括:
基于欧姆定律,每个负荷所属支路电流I
Lj(j=1,2,...,N)幅值表示为,
式中,P
j代表负荷M
j的有功功率量测值,Q
j代表负荷M
j的无功功率量测值;U
j代表该负荷M
j的量测电压幅值,N为大于等于2的正整数;
在整个时间序列内,所述配电网所有负荷所属支路电流样本空间为,
在一实施例中,所述根据所述电压相关系数和所述电流相关系数完成所述配电网拓扑的校验与修正包括:
基于所述电压相关系数和所述电流相关系数,依据所选用相关性分析法的判别条件,判断每个负荷所属的馈线,然后基于每个负荷所属耦合节点电压幅值,确定每个负荷在所属馈线中的上下游关系是否满足同一馈线中耦合节点的电压幅值由上游至下游递减,不满足电压幅值由上游至下游递减的负荷为拓扑连接错误的负荷;若辨识出拓扑连接错误的负荷,则计算该负荷与配电网网络中其他耦合节点的电压相关性系数和电流相关性系数,当所述电压相关性系数和所述电流相关性系数满足相关性判别准则时,确定该负荷所属馈线以及在馈线中的耦合连接点,以完成对配电网拓扑正确性的校验以及对错误拓扑连接的修正。
本申请还提供一种计算机可读存储介质,存储有计算机可执行指令,所述计算机可执行指令用于执行上述任一种方法。
本申请还提供了一种计算机程序产品,所述计算机程序产品包括存储在非暂态计算机可读存储介质上的计算机程序,所述计算机程序包括程序指令,当所述程序指令被计算机执行时,使所述计算机执行上述任意一种方法。
本申请首先基于配电网电压分布特性以及负荷电流分布特性,构建拓扑错误辨识原则,然后借助高级量测体系AMI提供的量测信息以及网络数据,得出负荷所属耦合电压以及所属支路电流,之后对耦合电压、支路电流进行相关性分析,最后对拓扑的正确性进行校验,并对检验出的拓扑错误进行修正,最终 完成对拓扑错误的辨识与修正。并对本申请提出的拓扑错误辨识算法的有效性进行检验,结果证明该算法对同时存在多个拓扑错误的复杂情况具有良好的辨识与修正能力,算例表明了该算法的可行性与有效性。
本申请仅需计算负荷所属的耦合节点电压与支路电流,有效减少辨识所需运行时间,保证了拓扑辨识的速动性。
本申请同时考虑配电网电压、电流分布特性,避免了仅考虑单一辨识因素的不足,保证了拓扑辨识的可靠性,提高了拓扑辨识的有效性。
图1是一实施例中的配电网结构示意图。
图2是一实施例中的简化配电网电压分布示意图。
图3是一实施例中的配电网支路电流分布示意图。
图4为一实施例中的一种配电网拓扑错误辨装置的硬件结构示意图。
以下结合附图对本申请实施例进行详述:
本申请所采用的基于AMI量测信息的配电网拓扑错误辨识方法包括:基于配电网的电压分布和电流分布特性,在基于AMI采集数据的整个时间序列中,分别计算出每个负荷所属耦合节点电压值及其所属支路电流值,得到每个负荷所属耦合节点电压及其支路电流的样本空间,然后分别对求出的负荷所属耦合节点电压及其支路电流样本空间进行相关性分析;基于相关性分析的结果,对配电网拓扑的正确性进行校验,并对错误的配电网拓扑进行修正。
本申请中基于AMI量测信息的配电网拓扑错误辨识方法,包括:
步骤110、计算配电网拓扑中每个负荷所属的耦合节点电压U
pc,获得配电网所有负荷所属的耦合节点电压样本空间。
在一实施例中,所述步骤110包括:在基于AMI采集数据的整个时间序列内,根据AMI采集的每个负荷的有功功率、无功功率和节点电压幅值的量测信息,计算每个负荷所属馈线的节点电压,即每个负荷所属的耦合节点电压U
pc,进而获得配电网所有负荷所属的耦合节点电压样本空间。
步骤120、计算配电网拓扑中每个负荷所属的支路电流I
L,获得配电网所有 负荷所属的支路电流样本空间。
在一实施例中,所述步骤120包括:在AMI采集数据的整个时间序列内,根据AMI采集的每个负荷的有功功率、无功功率和节点电压幅值的量测信息,计算得到每个负荷所属支路的电流值,即每个负荷所属的支路电流I
L,进而获得配电网所有负荷所属的支路电流样本空间。
步骤130、根据步骤110和步骤120获得的电压样本空间和电流样本空间,分别计算不同负荷间的电压相关系数和电流相关系数。
步骤140、根据所述电压相关系数和所述电流相关系数完成所述配电网拓扑的校验与修正。
在一实施例中,所述步骤140包括:基于步骤130所计算出的电压相关系数和电流相关系数,依据所选用相关性分析法的判别条件,判断每个负荷所属的馈线,然后基于步骤110中每个负荷所属耦合节点电压幅值,确定每个负荷在所属馈线中的上下游关系,完成配电网拓扑的校验与修正。
本申请实施例仅需计算负荷所属的耦合节点电压与支路电流,有效减少辨识所需运行时间,保证了拓扑辨识的速动性。本申请实施例同时考虑配电网电压、电流分布特性,避免了仅考虑单一辨识因素的不足,保证了拓扑辨识的可靠性,提高了拓扑辨识的有效性。
本申请实施例以一个辐射状配电网模型为例,对基于AMI量测信息的配电网拓扑错误辨识方法进行说明。
配电网结构示意图如附图1所示,该配电网络包含一个配电变压器TX以及与该配电变压器TX相连接的两条馈线,其中,PCj(j=1,2,…,N)代表负荷所属支路与馈线相连接的节点,记为耦合节点。每条馈线连接有不同负荷M
j(j=1,2,…,N),每个负荷M
j均配置有智能电表,用于提供拓扑辨识所需的量测数据,N为大于等于2的正整数。
附图1表示为同一配电变压器下的负荷拓扑连接关系。其中,TX代表配电变压器,M
j(j=1,2,…,N)为安装有智能电表的负荷,PCj(j=1,2,…,N)为每个负荷在馈线中所属的耦合节点。
步骤210:计算每个负荷所属的耦合节点电压。
根据欧姆定律,耦合节点PCj(j=1,2,…,N)处的电压幅值可以表示为:
U
pcj=U
j+Z
sj×I
j (1)
式中,j表示为量测仪表的编号;U
j和I
j分别是量测仪表j获取的负荷电压量测值和电流量测值;Z
sj表示为量测仪表j的量测点到耦合点PCj的阻抗值。若当前的电流量测值I
j不能提供,则可以通过功率量测值与电压量测值获得,如式(2)所示:
式中,P
j、Q
j分别代表负荷M
j的有功功率量测值以及无功功率量测值。
由式(1)和(2)可以求得每个负荷对应的耦合节点处的电压值,根据耦合节点电压值的分布可将图1简化为图2,即将每个负荷及其所属支路从图1中去掉即可。
附图2表示为计算每个负荷所属耦合节点电压后,所得到的简化后的配电系统图,简化过程为,将每个负荷及其所属支路从图1中去掉即可。另外,TX代表配电变压器,PCj(j=1,2,…,N)为每个负荷在馈线中所属的耦合节点。
以上分析与推导均是对某一时刻配电网进行的,即时间t等于某一特定的时刻。由于高级量测体系提供了足够长的时间序列量测数据用于计算与分析,在整个时间序列内,可得到配电网所有负荷所属耦合节点电压样本空间,即:
其中,对于某一特定时刻t
i(i=1,2,...,T),配电网所有负荷对应的耦合节点PCj(j=1,2,…,N)处电压的样本空间表示为:
步骤220:计算每个负荷所属的支路电流。
基于欧姆定律,每个负荷所属支路电流I
Lj(j=1,2,...,N)幅值可以表示为:
式中,P
j、Q
j分别代表负荷M
j的有功功率量测值以及无功功率量测值;U
j代表该负荷M
j的电压量测值。
基于每个负荷所属支路电流分布,可将图1转化为图3,即将每个负荷所属支路电流在其所属支路标明即可。
附图3表示为计算每个负荷所属支路电流后,每个负荷所属支路电流的分布图。即将每个负荷所属支路电流在其所属支路标明即可。其中,TX代表配电变压器,M
j(j=1,2,…,N)为安装有智能电表的负荷,PCj(j=1,2,…,N)为每个负荷在馈线中所属的耦合节点。I
Lj(j=1,2,...,N)表示每个负荷所属的支路电流。
以上分析与推导均是对某一时刻配电网进行的,即时间t等于某一特定的时刻,由于高级量测体系提供了足够长的时间序列量测数据用于计算与分析,考虑整个时间序列T,可得到配电网所有负荷所属支路电流样本空间,即:
步骤230:计算不同负荷间的电压相关系数和电流相关系数。
可以选择常见的相关性分析法进行计算。
步骤240:对配电网拓扑进行校验与修正。
基于步骤230所计算出的电压相关系数和电流相关系数,依据所选用相关性分析法的判别条件,判断每个负荷所属馈线,然后基于步骤210中每个负荷所属耦合节点电压幅值,即同一馈线中耦合节点的电压幅值由上游至下游呈递减趋势,确定每个负荷在所属馈线中的上下游关系,完成拓扑的校验。若辨识 出错误的拓扑连接,则对错误拓扑连接进行修正,即确定拓扑连接错误的负荷,计算该负荷与配电网网络中其他耦合节点的电压、电流相关性系数,当满足相关性判别准则时,即可确定该负荷所属馈线以及在馈线中的耦合连接点位置,以完成对配电网拓扑正确性的校验以及对错误拓扑连接的修正。
本申请实施例首先基于配电网电压分布特性以及负荷电流分布特性,构建拓扑错误辨识原则,然后借助高级量测体系AMI提供的量测信息,得出负荷所属耦合电压以及所属支路电流,之后对耦合电压、支路电流进行相关性分析,最后对拓扑的正确性进行校验,并对检验出的拓扑错误进行修正,最终完成对拓扑错误的辨识与修正。并对本申请提出的拓扑错误辨识算法的有效性进行检验,结果证明该算法对同时存在多个拓扑错误的复杂情况具有良好的辨识与修正能力,算例表明了该算法的可行性与有效性。
一实施例提供一种配电网拓扑错误辨识装置,包括:存储器和处理器;其中,
所述存储器存储有可执行程序,所述处理器执行所述程序时执行以下步骤:
计算所述配电网拓扑中每个负荷所属的耦合节点电压U
pc,获得所述配电网所有负荷所属的耦合节点电压样本空间;
计算所述配电网拓扑中每个负荷所属的支路电流I
L,获得所述配电网所有负荷所属的支路电流样本空间;
根据获得的所述电压样本空间和所述电流样本空间,分别计算不同负荷间的电压相关系数和电流相关系数;以及
根据所述电压相关系数和所述电流相关系数完成所述配电网拓扑的校验与修正。
在一实施例中,所述计算所述配电网拓扑中每个负荷所属的耦合节点电压U
pc,获得所述配电网所有负荷所属的耦合节点电压样本空间包括:
在基于高级测量体系AMI采集数据的整个时间序列内,根据AMI采集的每个负荷的耦合节点电压幅值的量测信息,计算得到每个负荷所属馈线的耦合节点电压U
pc,以获得配电网中所有负荷所属的耦合节点电压样本空间。
在一实施例中,所述计算得到每个负荷所属馈线的耦合节点电压U
pc,以获 得配电网中所有负荷所属的耦合节点电压样本空间包括:
根据欧姆定律,耦合节点PCj(j=1,2,…,N)处的电压幅值表示为,
U
pcj=U
j+Z
sj×I
j
式中,j表示为量测仪表的编号;U
j是量测仪表j获取的负荷电压量测值,I
j是量测仪表j获取的电流量测值;Z
sj表示为量测仪表j的量测点到耦合点PCj的阻抗值,N为大于等于2的正整数;
在所述整个时间序列内,配电网中所有负荷所属耦合节点电压样本空间为,
其中,对于某一特定时刻t
i(i=1,2,...,T),T为大于等于2的正整数,配电网中所有负荷对应的耦合节点PCj(j=1,2,…,N)处电压的样本空间表示为,
在所述整个时间序列内,负荷M
j所属耦合节点PCj(j=1,2,…,N)处的电压样本空间表示为,
在一实施例中,所述处理器执行所述程序时还执行以下步骤:
若量测仪表j未检测到当前的电流量测值I
j,根据AMI采集的负荷M
j的有功功率、无功功率和耦合节点电压幅值的量测信息得到电流量测值I
j,计算公式如下所示,
式中,P
j代表负荷M
j的有功功率量测值,Q
j代表负荷M
j的无功功率量测值。
在一实施例中,所述计算所述配电网拓扑中每个负荷所属的支路电流I
L,获得所述配电网所有负荷所属的支路电流样本空间包括:
在整个时间序列内,根据AMI采集的每个负荷的有功功率、无功功率和耦合节点电压幅值的量测信息,计算得到每个负荷所属支路的支路电流I
L,进而获得所述配电网所有负荷所属的支路电流样本空间。
在一实施例中,所述计算得到每个负荷所属支路的支路电流I
L,进而获得所述配电网所有负荷所属的支路电流样本空间包括:
基于欧姆定律,每个负荷所属支路电流I
Lj(j=1,2,...,N)幅值表示为,
式中,P
j代表负荷M
j的有功功率量测值,Q
j代表负荷M
j的无功功率量测值;U
j代表该负荷M
j的量测电压幅值;
在整个时间序列内,所述配电网所有负荷所属支路电流样本空间为,
在一实施例中,所述根据所述电压相关系数和所述电流相关系数完成所述配电网拓扑的校验与修正包括:
基于所述电压相关系数和所述电流相关系数,依据所选用相关性分析法的判别条件,判断每个负荷所属的馈线,然后基于每个负荷所属耦合节点电压幅值,确定每个负荷在所属馈线中的上下游关系是否满足同一馈线中耦合节点的电压幅值由上游至下游递减,不满足电压幅值由上游至下游递减的负荷为拓扑连接错误的负荷;若辨识出拓扑连接错误的负荷,则计算该负荷与配电网网络中其他耦合节点的电压相关性系数和电流相关性系数,当所述电压相关性系数和所述电流相关性系数满足相关性判别准则时,确定该负荷所属馈线以及在馈线中的耦合连接点,以完成对配电网拓扑正确性的校验以及对错误拓扑连接的修正。
一实施例还提供一种计算机可读存储介质,存储有计算机可执行指令,所 述计算机可执行指令用于执行上述任一配电网拓扑错误辨识方法。
图4是一实施例提供的一种配电网拓扑错误辨识装置的硬件结构示意图,如图4所示,该辨识装置包括:一个或多个处理器410和存储器420。图4中以一个处理器410为例。
所述辨识装置还可以包括:输入装置430和输出装置440。
所述辨识装置中的处理器410、存储器420、输入装置430和输出装置440可以通过总线或者其他方式连接,图4中以通过总线连接为例。
输入装置430可以接收输入的数字或字符信息,输出装置440可以包括显示屏等显示设备。
存储器420作为一种计算机可读存储介质,可用于存储软件程序、计算机可执行程序以及模块。处理器410通过运行存储在存储器420中的软件程序、指令以及模块,从而执行多种功能应用以及数据处理,以实现上述实施例中的任意一种配电网拓扑错误辨识方法。
存储器420可以包括存储程序区和存储数据区,其中,存储程序区可存储操作系统、至少一个功能所需要的应用程序;存储数据区可存储根据辨识装置的使用所创建的数据等。此外,存储器可以包括随机存取存储器(Random Access Memory,RAM)等易失性存储器,还可以包括非易失性存储器,例如至少一个磁盘存储器件、闪存器件或者其他非暂态固态存储器件。
存储器420可以是非暂态计算机存储介质或暂态计算机存储介质。该非暂态计算机存储介质,例如至少一个磁盘存储器件、闪存器件、或其他非易失性固态存储器件。在一些实施例中,存储器420可选包括相对于处理器410远程设置的存储器,这些远程存储器可以通过网络连接至辨识装置。上述网络的实例可以包括互联网、企业内部网、局域网、移动通信网及其组合。
输入装置430可用于接收输入的数字或字符信息,以及产生与辨识装置的用户设置以及功能控制有关的键信号输入。输出装置440可包括显示屏等显示设备。
本实施例的辨识装置还可以包括通信装置450,通过通信网络传输和/或接收信息。
本领域普通技术人员可理解实现上述实施例方法中的全部或部分流程,是可以通过计算机程序来执行相关的硬件来完成的,该程序可存储于一个非暂态计算机可读存储介质中,该程序在执行时,可包括如上述方法的实施例的流程,其中,该非暂态计算机可读存储介质可以为磁碟、光盘、只读存储记忆体(ROM)或随机存储记忆体(RAM)等。
Claims (15)
- 一种配电网拓扑错误辨识方法,包括:计算所述配电网拓扑中每个负荷所属的耦合节点电压U pc,获得所述配电网所有负荷所属的耦合节点电压样本空间;计算所述配电网拓扑中每个负荷所属的支路电流I L,获得所述配电网所有负荷所属的支路电流样本空间;根据获得的所述电压样本空间和所述电流样本空间,分别计算不同负荷间的电压相关系数和电流相关系数;以及根据所述电压相关系数和所述电流相关系数完成所述配电网拓扑的校验与修正。
- 根据权利要求1所述的辨识方法,其中,所述计算所述配电网拓扑中每个负荷所属的耦合节点电压U pc,获得所述配电网所有负荷所属的耦合节点电压样本空间包括:在基于高级测量体系AMI采集数据的整个时间序列内,根据AMI采集的每个负荷的耦合节点电压幅值的量测信息,计算得到每个负荷所属馈线的耦合节点电压U pc,以获得配电网中所有负荷所属的耦合节点电压样本空间。
- 根据权利要求2所述的辨识方法,其中,所述计算得到每个负荷所属馈线的耦合节点电压U pc,以获得配电网中所有负荷所属的耦合节点电压样本空间包括:根据欧姆定律,耦合节点PCj(j=1,2,…,N)处的电压幅值表示为,U pcj=U j+Z sj×I j式中,j表示为量测仪表的编号;U j是量测仪表j获取的负荷电压量测值,I j是量测仪表j获取的电流量测值;Z sj表示为量测仪表j的量测点到耦合点PCj的阻抗值,N为大于等于2的正整数;在所述整个时间序列内,配电网中所有负荷所属耦合节点电压样本空间为,其中,对于某一特定时刻t i(i=1,2,...,T),T为大于等于2的正整数,配电网中所有负荷对应的耦合节点PCj(j=1,2,…,N)处电压的样本空间表示为,在所述整个时间序列内,负荷M j所属耦合节点PCj(j=1,2,…,N)处的电压样本空间表示为,
- 根据权利要求1至4中任一所述的辨识方法,其中,所述计算所述配电网拓扑中每个负荷所属的支路电流I L,获得所述配电网所有负荷所属的支路电流样本空间包括:在整个时间序列内,根据AMI采集的每个负荷的有功功率、无功功率和耦合节点电压幅值的量测信息,计算得到每个负荷所属支路的支路电流I L,进而获得所述配电网所有负荷所属的支路电流样本空间。
- 根据权利要求1至6中任一所述的辨识方法,其中,所述根据所述电压相关系数和所述电流相关系数完成所述配电网拓扑的校验与修正包括:基于所述电压相关系数和所述电流相关系数,依据所选用相关性分析法的 判别条件,判断每个负荷所属的馈线,然后基于每个负荷所属耦合节点电压幅值,确定每个负荷在所属馈线中的上下游关系是否满足同一馈线中耦合节点的电压幅值由上游至下游递减,不满足电压幅值由上游至下游递减的负荷为拓扑连接错误的负荷;若辨识出拓扑连接错误的负荷,则计算该负荷与配电网网络中其他耦合节点的电压相关性系数和电流相关性系数,当所述电压相关性系数和所述电流相关性系数满足相关性判别准则时,确定该负荷所属馈线以及在馈线中的耦合连接点,以完成对配电网拓扑正确性的校验以及对错误拓扑连接的修正。
- 一种配电网拓扑错误辨识装置,包括:存储器和处理器;其中,所述存储器存储有可执行程序,所述处理器执行所述程序时执行以下步骤:计算所述配电网拓扑中每个负荷所属的耦合节点电压U pc,获得所述配电网所有负荷所属的耦合节点电压样本空间;计算所述配电网拓扑中每个负荷所属的支路电流I L,获得所述配电网所有负荷所属的支路电流样本空间;根据获得的所述电压样本空间和所述电流样本空间,分别计算不同负荷间的电压相关系数和电流相关系数;以及根据所述电压相关系数和所述电流相关系数完成所述配电网拓扑的校验与修正。
- 根据权利要求8所述的辨识装置,其中,所述计算所述配电网拓扑中每个负荷所属的耦合节点电压U pc,获得所述配电网所有负荷所属的耦合节点电压样本空间包括:在基于高级测量体系AMI采集数据的整个时间序列内,根据AMI采集的每个负荷的耦合节点电压幅值的量测信息,计算得到每个负荷所属馈线的耦合节点电压U pc,以获得配电网中所有负荷所属的耦合节点电压样本空间。
- 根据权利要求9所述的辨识装置,其中,所述计算得到每个负荷所属馈线的耦合节点电压U pc,以获得配电网中所有负荷所属的耦合节点电压样本空间包括:根据欧姆定律,耦合节点PCj(j=1,2,…,N)处的电压幅值表示为,U pcj=U j+Z sj×I j式中,j表示为量测仪表的编号;U j是量测仪表j获取的负荷电压量测值,I j是量测仪表j获取的电流量测值;Z sj表示为量测仪表j的量测点到耦合点PCj 的阻抗值,N为大于等于2的正整数;在所述整个时间序列内,配电网中所有负荷所属耦合节点电压样本空间为,其中,对于某一特定时刻t i(i=1,2,..,T),T为大于等于2的正整数,配电网中所有负荷对应的耦合节点PCj(j=1,2,…,N)处电压的样本空间表示为,在所述整个时间序列内,负荷M j所属耦合节点PCj(j=1,2,…,N)处的电压样本空间表示为,
- 根据权利要求8至11中任一所述的辨识装置,其中,所述计算所述配电网拓扑中每个负荷所属的支路电流I L,获得所述配电网所有负荷所属的支路电流样本空间包括:在整个时间序列内,根据AMI采集的每个负荷的有功功率、无功功率和耦合节点电压幅值的量测信息,计算得到每个负荷所属支路的支路电流I L,进而获得所述配电网所有负荷所属的支路电流样本空间。
- 根据权利要求8至13中任一所述的辨识装置,其中,所述根据所述电压相关系数和所述电流相关系数完成所述配电网拓扑的校验与修正包括:基于所述电压相关系数和所述电流相关系数,依据所选用相关性分析法的判别条件,判断每个负荷所属的馈线,然后基于每个负荷所属耦合节点电压幅值,确定每个负荷在所属馈线中的上下游关系是否满足同一馈线中耦合节点的电压幅值由上游至下游递减,不满足电压幅值由上游至下游递减的负荷为拓扑连接错误的负荷;若辨识出拓扑连接错误的负荷,则计算该负荷与配电网网络中其他耦合节点的电压相关性系数和电流相关性系数,当所述电压相关性系数和所述电流相关性系数满足相关性判别准则时,确定该负荷所属馈线以及在馈线中的耦合连接点,以完成对配电网拓扑正确性的校验以及对错误拓扑连接的修正。
- 一种计算机可读存储介质,存储有计算机可执行指令,所述计算机可执行指令用于执行权利要求1-7任一项的方法。
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US16/301,555 US11297129B2 (en) | 2017-12-29 | 2018-09-21 | Method and device for identifying distribution network topology error |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201711476473.9A CN108173263B (zh) | 2017-12-29 | 2017-12-29 | 一种基于ami量测信息的配电网拓扑错误辨识算法 |
CN201711476473.9 | 2017-12-29 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2019128335A1 true WO2019128335A1 (zh) | 2019-07-04 |
Family
ID=62520011
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/CN2018/107061 WO2019128335A1 (zh) | 2017-12-29 | 2018-09-21 | 配电网拓扑错误辨识方法 |
Country Status (3)
Country | Link |
---|---|
US (1) | US11297129B2 (zh) |
CN (1) | CN108173263B (zh) |
WO (1) | WO2019128335A1 (zh) |
Cited By (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110718908A (zh) * | 2019-09-29 | 2020-01-21 | 肖家锴 | 基于层次聚类法的配电网拓扑结构识别方法及系统 |
CN111210149A (zh) * | 2020-01-06 | 2020-05-29 | 河南康派智能技术有限公司 | 一种配电网拓扑识别方法及装置 |
CN112086965A (zh) * | 2020-09-08 | 2020-12-15 | 国网江苏省电力有限公司电力科学研究院 | 一种低压配电网拓扑识别方法及装置 |
CN112581306A (zh) * | 2019-09-30 | 2021-03-30 | 广东电网有限责任公司佛山供电局 | 一种基于穷举的区域网络拓扑关系确认方法、装置和系统 |
CN112688310A (zh) * | 2020-12-14 | 2021-04-20 | 国网河北省电力有限公司电力科学研究院 | 一种应用于配电网的线损分析方法及装置 |
CN113824210A (zh) * | 2021-08-25 | 2021-12-21 | 浙江万胜智能科技股份有限公司 | 一种利用智能电表、智能终端进行台区拓扑识别的方法 |
EP4050748A1 (en) * | 2021-02-27 | 2022-08-31 | Hitachi Energy Switzerland AG | Power grid topology determination |
Families Citing this family (23)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108173263B (zh) * | 2017-12-29 | 2022-02-22 | 国网天津市电力公司电力科学研究院 | 一种基于ami量测信息的配电网拓扑错误辨识算法 |
CN109034666B (zh) * | 2018-09-04 | 2021-06-22 | 国家电网有限公司 | 一种基于负荷突变的低压电网拓扑大数据辨识系统及方法 |
CN109274095B (zh) * | 2018-10-30 | 2020-07-14 | 东北大学秦皇岛分校 | 基于互信息的低压配电网用户拓扑估计方法及系统 |
CN109873420A (zh) * | 2018-11-15 | 2019-06-11 | 国网安徽省电力公司 | 基于ami数据的城市低压配电网拓扑校验方法、装置及系统 |
CN109753762B (zh) * | 2019-03-05 | 2022-08-19 | 国网江苏省电力有限公司电力科学研究院 | 基于类别修正的配电网两阶段网络拓扑识别方法及装置 |
CN110289613B (zh) * | 2019-06-17 | 2022-12-02 | 湖南大学 | 基于灵敏度矩阵的配电网拓扑识别与线路参数辨识方法 |
CN110190600B (zh) * | 2019-06-21 | 2022-09-30 | 国网天津市电力公司 | 一种基于ami量测近邻回归的三相配电网拓扑辨识方法 |
CN110601173B (zh) * | 2019-06-24 | 2021-07-16 | 国网甘肃省电力公司电力科学研究院 | 基于边缘计算的配网拓扑识别方法及装置 |
CN111064180B (zh) * | 2019-10-23 | 2024-01-26 | 国网天津市电力公司电力科学研究院 | 基于ami潮流匹配的中压配电网拓扑检测与辨识方法 |
CN111313405B (zh) * | 2020-02-29 | 2022-04-01 | 上海电力大学 | 一种基于多量测断面的中压配电网拓扑辨识方法 |
CN111880121B (zh) * | 2020-07-02 | 2024-06-21 | 国网天津市电力公司 | 一种基于运行扰动数据分析的低压台区拓扑系统及拓扑识别方法 |
CN113054740B (zh) * | 2021-01-21 | 2024-10-15 | 中电装备山东电子有限公司 | 一种畸变电流发生装置及采用其的拓扑识别系统 |
CN113300371B (zh) * | 2021-05-31 | 2022-07-12 | 广东电网有限责任公司 | 一种配电房实时电压的确定方法及装置 |
CN114090961A (zh) * | 2021-11-26 | 2022-02-25 | 广东电网有限责任公司汕尾供电局 | 一种低压配电网拓扑结构校验方法和系统 |
CN114819484A (zh) * | 2022-03-14 | 2022-07-29 | 国网江苏省电力有限公司宿迁供电分公司 | 一种基于数据驱动的电网自动拓扑数据管理方法 |
CN114881164B (zh) * | 2022-05-24 | 2024-05-31 | 国网江苏省电力有限公司电力科学研究院 | 一种基于图数据库的配电网拓扑自动校核方法及装置 |
CN115051912B (zh) * | 2022-06-20 | 2023-11-03 | 广东电网有限责任公司 | 一种停电用户定位方法、装置、设备、介质 |
CN115130327A (zh) * | 2022-08-10 | 2022-09-30 | 东南大学 | 一种考虑区域相似性的中压配电网拓扑识别方法 |
CN115144679B (zh) * | 2022-08-31 | 2022-11-29 | 武汉格蓝若智能技术有限公司 | 一种采集电压实时拓扑关系在线辨识方法及系统 |
CN116436152B (zh) * | 2022-12-13 | 2023-11-10 | 国网湖北省电力有限公司电力科学研究院 | 一种基于特征信息相关性的智能低压配电台区拓扑识别方法 |
CN115994136B (zh) * | 2023-01-10 | 2023-09-05 | 广东电网有限责任公司 | 一种基于能源网络拓扑关系的能源数据清洗方法及系统 |
CN116881955B (zh) * | 2023-09-08 | 2023-11-21 | 北京龙德缘电力科技发展有限公司 | 电力系统用户侧配电开关类设备统一编码方法 |
CN118536050A (zh) * | 2024-07-29 | 2024-08-23 | 国网江西省电力有限公司南昌供电分公司 | 基于gis和电压数据融合的配电网线变关系识别方法 |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102005757A (zh) * | 2010-10-29 | 2011-04-06 | 江西电力调度中心 | 一种基于量测生成树的电网拓扑错误的辨识方法 |
CN104679968A (zh) * | 2013-11-27 | 2015-06-03 | 哈尔滨恒誉名翔科技有限公司 | 一种含分布式电源的配电网潮流计算器 |
CN107453357A (zh) * | 2017-08-24 | 2017-12-08 | 天津大学 | 一种基于分层求解的配电网状态估计方法 |
CN108173263A (zh) * | 2017-12-29 | 2018-06-15 | 国网天津市电力公司电力科学研究院 | 一种基于ami量测信息的配电网拓扑错误辨识算法 |
Family Cites Families (14)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8810251B2 (en) * | 2011-08-31 | 2014-08-19 | General Electric Company | Systems, methods, and apparatus for locating faults on an electrical distribution network |
US9140576B2 (en) * | 2012-01-23 | 2015-09-22 | General Electric Company | Demand response without Time-of-Use metering |
US9678520B2 (en) * | 2013-03-15 | 2017-06-13 | Dominion Resources, Inc. | Electric power system control with planning of energy demand and energy efficiency using AMI-based data analysis |
CA2869372C (en) * | 2013-10-31 | 2023-04-04 | Ilya Roytelman | Determining distribution system voltages from remote voltage alarm signals |
US10571493B2 (en) * | 2014-02-25 | 2020-02-25 | Itron, Inc. | Smart grid topology estimator |
US11757304B2 (en) * | 2014-06-23 | 2023-09-12 | Gridbridge, Inc. | Versatile site energy router |
US9835662B2 (en) * | 2014-12-02 | 2017-12-05 | Itron, Inc. | Electrical network topology determination |
CN106300331B (zh) * | 2015-06-04 | 2019-02-22 | 中国电力科学研究院 | 一种精确计算配电网支路阻抗的方法 |
US10337885B2 (en) * | 2015-10-14 | 2019-07-02 | Inventus Holdings, Llc | Voltage pattern analysis system and method |
CA2915674A1 (fr) * | 2015-12-17 | 2017-06-17 | Francois Leonard | Mise a jour d'une topologie d'un reseau de distribution par reattribution successive des compteurs |
CN105514994B (zh) * | 2015-12-23 | 2018-11-27 | 国网福建省电力有限公司 | 一种基于拓扑树的配电网络数据辨识与修正的方法 |
CN106599318B (zh) * | 2016-12-30 | 2020-03-20 | 山东鲁能软件技术有限公司 | 一种配电网模型数据校验方法 |
CN107370147A (zh) * | 2017-07-18 | 2017-11-21 | 国网天津市电力公司 | 一种基于ami数据分析的配电网拓扑修正方法 |
WO2019053588A1 (en) * | 2017-09-12 | 2019-03-21 | Depsys Sa | METHOD OF ESTIMATING THE TOPOLOGY OF AN ELECTRICAL NETWORK USING MEASUREMENT DATA |
-
2017
- 2017-12-29 CN CN201711476473.9A patent/CN108173263B/zh active Active
-
2018
- 2018-09-21 WO PCT/CN2018/107061 patent/WO2019128335A1/zh active Application Filing
- 2018-09-21 US US16/301,555 patent/US11297129B2/en active Active
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102005757A (zh) * | 2010-10-29 | 2011-04-06 | 江西电力调度中心 | 一种基于量测生成树的电网拓扑错误的辨识方法 |
CN104679968A (zh) * | 2013-11-27 | 2015-06-03 | 哈尔滨恒誉名翔科技有限公司 | 一种含分布式电源的配电网潮流计算器 |
CN107453357A (zh) * | 2017-08-24 | 2017-12-08 | 天津大学 | 一种基于分层求解的配电网状态估计方法 |
CN108173263A (zh) * | 2017-12-29 | 2018-06-15 | 国网天津市电力公司电力科学研究院 | 一种基于ami量测信息的配电网拓扑错误辨识算法 |
Cited By (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110718908A (zh) * | 2019-09-29 | 2020-01-21 | 肖家锴 | 基于层次聚类法的配电网拓扑结构识别方法及系统 |
CN110718908B (zh) * | 2019-09-29 | 2024-05-03 | 中科合创科技实业(深圳)有限公司 | 基于层次聚类法的配电网拓扑结构识别方法及系统 |
CN112581306A (zh) * | 2019-09-30 | 2021-03-30 | 广东电网有限责任公司佛山供电局 | 一种基于穷举的区域网络拓扑关系确认方法、装置和系统 |
CN111210149A (zh) * | 2020-01-06 | 2020-05-29 | 河南康派智能技术有限公司 | 一种配电网拓扑识别方法及装置 |
CN111210149B (zh) * | 2020-01-06 | 2023-11-07 | 河南康派智能技术有限公司 | 一种配电网拓扑识别方法及装置 |
CN112086965A (zh) * | 2020-09-08 | 2020-12-15 | 国网江苏省电力有限公司电力科学研究院 | 一种低压配电网拓扑识别方法及装置 |
CN112086965B (zh) * | 2020-09-08 | 2022-02-15 | 国网江苏省电力有限公司电力科学研究院 | 一种低压配电网拓扑识别方法及装置 |
CN112688310A (zh) * | 2020-12-14 | 2021-04-20 | 国网河北省电力有限公司电力科学研究院 | 一种应用于配电网的线损分析方法及装置 |
CN112688310B (zh) * | 2020-12-14 | 2024-01-09 | 国网河北省电力有限公司电力科学研究院 | 一种应用于配电网的线损分析方法及装置 |
EP4050748A1 (en) * | 2021-02-27 | 2022-08-31 | Hitachi Energy Switzerland AG | Power grid topology determination |
WO2022180255A1 (en) * | 2021-02-27 | 2022-09-01 | Hitachi Energy Switzerland Ag | Power grid topology determination |
CN113824210A (zh) * | 2021-08-25 | 2021-12-21 | 浙江万胜智能科技股份有限公司 | 一种利用智能电表、智能终端进行台区拓扑识别的方法 |
Also Published As
Publication number | Publication date |
---|---|
CN108173263A (zh) | 2018-06-15 |
US11297129B2 (en) | 2022-04-05 |
CN108173263B (zh) | 2022-02-22 |
US20210234922A1 (en) | 2021-07-29 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
WO2019128335A1 (zh) | 配电网拓扑错误辨识方法 | |
Peppanen et al. | Distribution system low-voltage circuit topology estimation using smart metering data | |
CN107016489A (zh) | 一种电力系统抗差状态估计方法和装置 | |
CN112510707A (zh) | 一种配电台区电力阻抗拓扑图生成方法及系统 | |
CN111505433A (zh) | 一种低压台区户变关系纠错及相位识别方法 | |
CN113078630B (zh) | 一种基于实时量测数据的低压配电网拓扑辨识方法 | |
CN112930504B (zh) | 用于联网微电网的安全分布式状态估计 | |
CN109193635B (zh) | 一种基于自适应稀疏回归方法的配电网拓扑结构重建方法 | |
TWI759027B (zh) | 電池性能評鑑方法及電池性能評鑑裝置 | |
CN111008641B (zh) | 一种基于卷积神经网络的输电线路杆塔外力破坏检测方法 | |
CN109753762A (zh) | 基于类别修正的配电网两阶段网络拓扑识别方法及装置 | |
CN115508770B (zh) | 一种基于kl-nb算法的电能表运行状态在线评估方法 | |
CN116520095B (zh) | 故障测距方法、系统以及计算机可读存储介质 | |
CN115685046A (zh) | 互感器计量异常识别方法、装置、设备及存储介质 | |
Xing et al. | Exact solutions for average trapping time of random walks on weighted scale-free networks | |
CN115392141A (zh) | 一种自适应的电流互感器误差评估方法 | |
CN115201563A (zh) | 一种基于联合熵的多谐波源定位方法及系统 | |
CN117498379A (zh) | 新能源场站宽频带频率耦合阻抗在线辨识建模方法及系统 | |
CN104283942A (zh) | 遥测数据收集与分发系统 | |
CN117421622A (zh) | 基于聚类算法的低压台区线损计算方法及系统 | |
CN112698150B (zh) | 基于配电变压器监测终端的配电网行波故障定位方法 | |
CN109193639A (zh) | 一种电力系统抗差估计方法 | |
Ananthan et al. | Novel system model‐based fault location approach using dynamic search technique | |
KR20210037202A (ko) | 다양한 기종의 pmu로부터 동기페이저 데이터를 수집하는 장치 및 방법 | |
CN112581306A (zh) | 一种基于穷举的区域网络拓扑关系确认方法、装置和系统 |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 18897490 Country of ref document: EP Kind code of ref document: A1 |
|
NENP | Non-entry into the national phase |
Ref country code: DE |
|
122 | Ep: pct application non-entry in european phase |
Ref document number: 18897490 Country of ref document: EP Kind code of ref document: A1 |