CN106022590B - Voltage quality evaluation method and device for active power distribution network - Google Patents
Voltage quality evaluation method and device for active power distribution network Download PDFInfo
- Publication number
- CN106022590B CN106022590B CN201610320183.4A CN201610320183A CN106022590B CN 106022590 B CN106022590 B CN 106022590B CN 201610320183 A CN201610320183 A CN 201610320183A CN 106022590 B CN106022590 B CN 106022590B
- Authority
- CN
- China
- Prior art keywords
- power distribution
- active power
- distribution network
- load
- network
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 64
- 238000013441 quality evaluation Methods 0.000 title claims abstract description 47
- 238000004088 simulation Methods 0.000 claims abstract description 65
- 238000012545 processing Methods 0.000 claims abstract description 24
- 230000008569 process Effects 0.000 claims abstract description 21
- 239000011159 matrix material Substances 0.000 claims description 28
- 238000005070 sampling Methods 0.000 claims description 20
- 238000004364 calculation method Methods 0.000 claims description 12
- 230000002776 aggregation Effects 0.000 claims description 11
- 238000004220 aggregation Methods 0.000 claims description 11
- 238000004146 energy storage Methods 0.000 claims description 8
- 238000006467 substitution reaction Methods 0.000 claims description 8
- 238000010845 search algorithm Methods 0.000 claims description 6
- 230000000694 effects Effects 0.000 abstract description 4
- 238000011156 evaluation Methods 0.000 description 6
- 238000004422 calculation algorithm Methods 0.000 description 4
- 238000011161 development Methods 0.000 description 4
- 230000001133 acceleration Effects 0.000 description 3
- 230000004931 aggregating effect Effects 0.000 description 3
- 238000012216 screening Methods 0.000 description 3
- 238000005094 computer simulation Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000009472 formulation Methods 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000001303 quality assessment method Methods 0.000 description 2
- 238000011158 quantitative evaluation Methods 0.000 description 2
- 230000008439 repair process Effects 0.000 description 2
- 238000000342 Monte Carlo simulation Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000001052 transient effect Effects 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06395—Quality analysis or management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
-
- 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
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Theoretical Computer Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Educational Administration (AREA)
- Marketing (AREA)
- Development Economics (AREA)
- Health & Medical Sciences (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Public Health (AREA)
- Primary Health Care (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses a voltage quality evaluation method and device for an active power distribution network. The voltage quality evaluation method of the active power distribution network comprises the following steps: performing statistical simulation on the current state of the element of the active power distribution network and the duration of the element of the active power distribution network in the current state to obtain a simulation result; classifying the load nodes of the active power distribution network according to the simulation result to obtain a classification result; determining the topological structure of the classification result to obtain a determination result; establishing a preset model of the active power distribution network according to the classification result and the determination result; processing the preset model to obtain voltage distribution information of the load node; and performing statistics on the voltage distribution information to obtain a voltage quality evaluation result of the active power distribution network. According to the invention, the effect of reducing the difficulty of accurately evaluating the voltage quality in the active power distribution network planning process is achieved.
Description
Technical Field
the invention relates to the field of power systems, in particular to a voltage quality evaluation method and device for an active power distribution network.
background
at present, distributed new energy is an important feature of a new generation of power system, and supporting rapid development of new energy has become an important core of a future energy plan. With the standardized development of distributed power sources and electric vehicles, the transition from passive control to active control of a power distribution network is one of the future development modes and directions, and an active power distribution network becomes the core of the development of an intelligent power distribution network.
With the increasing variety and number of distributed power sources, the power distribution network has power quality problems caused by the uncertainty of the distributed power sources. In addition, due to the special network properties and the operation characteristics of the active power distribution network, and the numerous energy storage devices, the detection control devices and the multiple nonlinear loads contained in the active power distribution network, the generation reasons and the propagation range of the power quality problems of the power distribution network have many new characteristics, for example, the power generated by the distributed power supply is not matched with the loads in time and space, the most main problem caused is the possible power transmission, and the voltage deviation is possibly caused to a certain extent; when the distributed power supply and the multi-element nonlinear load are accessed through the power electronic device, harmonic current is injected into a distribution network to cause voltage distortion and the like.
Different from the purpose of power quality evaluation in the operation stage, the power quality evaluation in the planning stage mainly aims at formulation and selection of a planning scheme and focuses on the estimation of power quality problems. In the planning process, actual operation data cannot be acquired, special conditions in the direct-current microgrid planning stage and the particularity of the power quality problem must be considered, and a qualitative and quantitative combined method, such as an analytic hierarchy process, a fuzzy evaluation method and the like, can be generally adopted, or system modeling simulation is performed based on planning parameters, and quantitative evaluation is performed depending on simulation results.
It has become a trend to consider power quality indicators during the power grid planning process. In the active power distribution network planning process, actual operation data or detailed simulation parameters cannot be acquired, and accurate pre-evaluation of voltage quality is difficult.
Aiming at the problem that the voltage quality in an active power distribution network is not easy to be accurately evaluated in the active power distribution network planning process in the related technology, an effective solution is not provided at present.
Disclosure of Invention
The invention mainly aims to provide a voltage quality evaluation method and a voltage quality evaluation device for an active power distribution network, so as to at least solve the problem that the voltage quality in the active power distribution network is not easy to be accurately evaluated in the planning process of the active power distribution network in the related technology.
in order to achieve the above object, according to one aspect of the present invention, there is provided a voltage quality evaluation method of an active power distribution network. The voltage quality evaluation method of the active power distribution network comprises the following steps: performing statistical simulation on the current state of the element of the active power distribution network and the duration of the element of the active power distribution network in the current state to obtain a simulation result; classifying the load nodes of the active power distribution network according to the simulation result to obtain a classification result; determining the topological structure of the classification result to obtain a determination result; establishing a preset model of the active power distribution network according to the classification result and the determination result; processing the preset model to obtain voltage distribution information of the load node; and performing statistics on the voltage distribution information to obtain a voltage quality evaluation result of the active power distribution network.
Further, performing statistical simulation on the current state of the element of the active power distribution network and the duration of the current state of the element of the active power distribution network, and obtaining a simulation result includes: sampling the current state of the element of the active power distribution network and the probability distribution of the duration time in the current state in the active power distribution network to obtain a state sequence of the element of the active power distribution network; and determining an operation state sequence of the system of the active power distribution network and a duration time sequence of the system of the active power distribution network according to the state sequence.
Further, classifying the load nodes of the active power distribution network according to the simulation result, and obtaining the classification result comprises: selecting the operation state of the system of the active power distribution network according to the operation state sequence of the system of the active power distribution network and the duration time sequence of the system of the active power distribution network; determining an adjacency matrix of a network line topology of the active power distribution network in an operating state; acquiring a source-load minimum path set according to the adjacency matrix, wherein the source-load minimum path set is a minimum path set between any load nodes; and classifying the load nodes according to the source-load minimum path set to obtain a network load node set, an island load node set and an interrupt load node set.
further, determining a topology of the classification result, and obtaining the determination result includes: when the classification result is a network load node set, determining a topological structure of a grid-connected part of the active power distribution network; and when the classification result is the island load node set, according to the adjacency matrix and the source-load minimum path set, performing aggregation on the load nodes according to the connected domain to obtain an island load node subset of the island load node set, and determining a distributed power supply, a load and an energy storage device which are included in the island load node subset.
Further, determining a topology of the classification result, and obtaining the determination result includes: and according to the breadth-first search algorithm, the adjacency matrix, the island load node set and the source-load minimum path set, carrying out aggregation on the load nodes according to the connected domain to obtain an island load node subset of the island load node set, and determining a grid-connected point set which has a connected path with the public power distribution network.
further, the step of establishing a preset model of the active power distribution network according to the classification result and the determination result comprises the following steps: selecting the operation condition of the active power distribution network in the operation process according to the classification result and the determination result; acquiring probability distribution information of an operation condition in an active power distribution network; acquiring access information of a distributed power supply and a load when the distributed power supply and the load are accessed through a power electronic device; and establishing a preset model comprising probability distribution information and access information.
Further, after the preset model of the active power distribution network is established according to the classification result and the determination result, the voltage quality evaluation method of the active power distribution network further comprises the following steps: acquiring parameters of a load and input and output information of the load; and determining a probability distribution model for representing the probability of the distribution of the distributed power sources and the loads in the active power distribution network according to the parameters of the distributed power sources and the loads and the input and output information of the loads.
In order to achieve the above object, according to another aspect of the present invention, there is provided a voltage quality evaluation apparatus of an active power distribution network. This voltage quality evaluation device of active power distribution network includes: the simulation unit is used for performing statistical simulation on the current state of the element of the active power distribution network and the duration of the element of the active power distribution network in the current state to obtain a simulation result; the classification unit is used for classifying the load nodes of the active power distribution network according to the simulation result to obtain a classification result; the determining unit is used for determining the topological structure of the classification result to obtain a determination result; the establishing unit is used for establishing a preset model of the active power distribution network according to the classification result and the determination result; the processing unit is used for executing processing on the preset model to obtain voltage distribution information of the load node; and the statistical unit is used for performing statistics on the voltage distribution information to obtain a voltage quality evaluation result of the active power distribution network.
further, the analog unit includes: the sampling module is used for sampling the current state of the element of the active power distribution network and the probability distribution of the duration time in the current state in the active power distribution network to obtain a state sequence of the element of the active power distribution network; the first determining module is used for determining the operation state sequence of the system of the active power distribution network and the duration time sequence of the system of the active power distribution network according to the state sequence.
Further, the classification unit includes: the selection module is used for selecting the operation state of the system of the active power distribution network according to the operation state sequence of the system of the active power distribution network and the duration time sequence of the system of the active power distribution network; the second determination module is used for determining an adjacency matrix of the network line topology of the active power distribution network in the running state; the acquisition module is used for acquiring a source-load minimum path set according to the adjacency matrix, wherein the source-load minimum path set is a minimum path set between any load nodes; and the classification module is used for classifying the load nodes according to the source-load minimum path set to obtain a network load node set, an island load node set and an interrupt load node set.
According to the method, the current state of the element of the active power distribution network and the duration time of the element of the active power distribution network in the current state are subjected to statistical simulation to obtain a simulation result; classifying the load nodes of the active power distribution network according to the simulation result to obtain a classification result; determining the topological structure of the classification result to obtain a determination result; establishing a preset model of the active power distribution network according to the classification result and the determination result; processing the preset model to obtain voltage distribution information of the load node; the voltage distribution information is counted to obtain the voltage quality evaluation result of the active power distribution network, and the effect of reducing the difficulty of accurately evaluating the voltage quality in the active power distribution network is achieved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
fig. 1 is a flowchart of a voltage quality evaluation method of an active power distribution network according to a first embodiment of the present invention;
fig. 2 is a flowchart of a voltage quality evaluation method of an active power distribution network according to a second embodiment of the present invention; and
Fig. 3 is a voltage quality evaluation apparatus of an active power distribution network according to an embodiment of the present invention.
Detailed Description
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings.
in order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
it should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the application described herein may be used. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The embodiment of the invention provides a voltage quality evaluation method for an active power distribution network.
Fig. 1 is a flowchart of a voltage quality evaluation method for an active power distribution network according to a first embodiment of the present invention. As shown in fig. 1, the voltage quality evaluation method for the active power distribution network includes the following steps:
Step S101, performing statistical simulation on the current state of the element of the active power distribution network and the duration of the element of the active power distribution network in the current state to obtain a simulation result.
And performing statistical simulation on the current state of the element of the active power distribution network and the duration of the element of the active power distribution network in the current state to obtain a simulation result. The multi-state simulation of the active power distribution network can adopt a Monte Carlo-state time sampling Method, a Monte Carlo Method (also called a statistical simulation Method), which is a very important numerical calculation Method guided by a probability statistical theory, and is a Method for solving many calculation problems by using random numbers (or more common pseudo-random numbers). Corresponding to it is a deterministic algorithm, when the problem to be solved is the probability of the occurrence of a certain random event or the expected value of a certain random variable, the probability of this random event is estimated by some experimental method with the frequency of the occurrence of this event or some digital characteristic of this random variable is obtained and taken as the solution of the problem.
the elements of the active power distribution network, that is, the network elements, are configured according to the active power distribution network line-device in the planning stage, generally, assuming that the elements of the active power distribution network are all in a running state at the initial time, sampling the duration of each element in the system of the active power distribution network staying in the current state, and obtaining the duration state sequence by backward simulation according to the probability distribution of element faults and repair time. And based on sampling the probability distribution of the element states and the duration of the active power distribution network, comprehensively giving out the state sequence of each element and giving out the operation state-duration sequence of the system of the active power distribution network in the total time period.
And S102, classifying the load nodes of the active power distribution network according to the simulation result to obtain a classification result.
And after the current state of the element of the active power distribution network and the duration of the element of the active power distribution network in the current state are subjected to statistical simulation to obtain a simulation result, classifying the load nodes of the active power distribution network according to the simulation result to obtain a classification result. The load nodes, also known as PQ nodes, inject active power and inject reactive power for a given node, while the node voltage phasors are pending. Such nodes correspond to pure load nodes (including with load on the node), generator nodes with both active and reactive outputs given (including with load on the node), and tie nodes (with both injected active and reactive equal to zero) in the actual system. The system operation state of the active power distribution network can be selected according to the operation state-duration time sequence, and the load nodes are classified to obtain a classification result.
According to the state sequence of each element, the operation state of the system on the active power distribution network and the system operation state of the system on the active power distribution network are selected according to the duration sequence in the total time period, a source-load minimum path set can be obtained by utilizing a network line topological adjacent array, load nodes are classified, and a classification result is obtained, wherein the classification result can be a grid-connected load node set, an island load node set and an interrupted load node set.
And step S103, determining the topological structure of the classification result to obtain a determination result.
And after the load nodes of the active power distribution network are classified according to the simulation result to obtain a classification result, determining the topological structure of the classification result to obtain a determination result. The topological structure is in a form that all stations in the network are mutually connected, the topological structure comprises bus topology, star topology, ring topology, tree topology and mixed topology of the bus topology, the star topology, the ring topology and the tree topology, the topological structure identification is operated on the classification result, and the topology and the configuration of a grid-connected part are determined for a grid-connected load node set; and for the island load node set, aggregating all nodes of the network according to the adjacent array and the connected domain, thereby screening out an island node subset and determining the distributed power supply, the load and the energy storage device contained in the island node subset.
and step S104, establishing a preset model of the active power distribution network according to the classification result and the determination result.
after the topological structure of the classification result is determined and the determination result is obtained, a preset model of the active power distribution network is established according to the classification result and the determination result, a network-element space sub-model can be established, namely, the network-element space sub-model containing distributed power supply and load access information and operation condition probability distribution information is established, and the probability distribution model of the distributed power supply and the load is estimated according to the distributed power supply, load basic parameters and input and output characteristics in the active power distribution network planning stage.
and step S105, executing processing on the preset model to obtain the voltage distribution information of the load node.
and after a preset model of the active power distribution network is established according to the classification result and the determination result, executing processing on the preset model to obtain the voltage distribution information of the load nodes. And grouping and parallel processing and accelerated processing are carried out on the multi-working-condition information of the active power distribution network in the operation process according to the topological similarity. Selecting one of the similar network samples in the group as a network base, and performing three-phase forward-backward substitution probability load flow calculation and probability harmonic load flow calculation to obtain the distribution characteristics of each phase voltage of the node; and (3) respectively carrying out three-phase forward-backward substitution probability tide and probability harmonic tide acceleration on the difference of the network samples in the group by adopting a compensation method, thereby obtaining the distribution characteristics of each phase voltage of the node under the corresponding working condition of other network samples and obtaining the actual operation data and detailed simulation parameters of the active power distribution network.
And S106, performing statistics on the voltage distribution information to obtain a voltage quality evaluation result of the active power distribution network.
After the preset model is processed to obtain the voltage distribution information of the load nodes, the voltage distribution information is counted to obtain the voltage quality evaluation result of the active power distribution network, the node voltage distribution information of each operation condition of the active power distribution network can be counted according to the probability distribution information of the operation condition, and therefore the evaluation result of the active power distribution network for evaluating the voltage quality of the active power distribution network in the planning stage is obtained. The voltage quality is to reflect whether the power distributed to users by the power supply department is qualified or not through the deviation of the actual voltage and the ideal voltage, and the voltage quality comprises voltage deviation, voltage frequency deviation, voltage unbalance, voltage transient phenomenon, voltage fluctuation and flicker, voltage temporary and interruption, voltage harmonic wave, voltage trap, undervoltage, overvoltage and the like.
the electric energy quality evaluation is a process of evaluating each characteristic index of the electric energy quality and checking and deducing whether the characteristic index meets the standard requirement after obtaining basic data based on actual measurement of system electric operation parameters or through modeling simulation, and can provide an important reference basis for planning, construction and operation of the active power distribution network. Different from the purpose of power quality evaluation in the operation stage, the power quality evaluation in the planning stage mainly aims at formulation and selection of a planning scheme and focuses on the estimation of power quality problems. In the planning process, the actual operation data of the active power distribution network can be obtained, a qualitative and quantitative combined method can be adopted, for example, an analytic hierarchy process, a fuzzy evaluation method and the like, or system modeling simulation is carried out based on planning parameters, quantitative evaluation is carried out on the active power distribution network according to a simulation result, a method for considering special conditions in a planning stage and establishing comprehensive evaluation is realized, and the method is combined with the system operation state of the active power distribution network, so that corresponding feedback is provided for planning and design of the active power distribution network, the planning strategy is adjusted in time, readjustment after engineering is built is avoided, and economic benefits of the engineering are improved.
The embodiment performs statistical simulation on the current state of the element of the active power distribution network and the duration of the element of the active power distribution network in the current state to obtain a simulation result; classifying the load nodes of the active power distribution network according to the simulation result to obtain a classification result; determining the topological structure of the classification result to obtain a determination result; establishing a preset model of the active power distribution network according to the classification result and the determination result; processing the preset model to obtain voltage distribution information of the load node; the voltage distribution information is subjected to statistics to obtain a voltage quality evaluation result of the active power distribution network, and the effect of reducing the difficulty of accurately evaluating the voltage quality in the active power distribution network in the planning process of the active power distribution network is achieved.
As an alternative embodiment, performing a statistical simulation on the current state of the element of the active power distribution network and the duration of the current state of the element of the active power distribution network, and obtaining a simulation result includes: sampling the current state of the element of the active power distribution network and the probability distribution of the duration time in the current state in the active power distribution network to obtain a state sequence of the element of the active power distribution network; and determining an operation state sequence of the system of the active power distribution network and a duration time sequence of the system of the active power distribution network according to the state sequence.
Performing statistical simulation on the current state of the element of the active power distribution network and the duration of the current state of the element of the active power distribution network may perform multi-state simulation on the active power distribution network, which may employ a monte carlo-state time sampling method. The method comprises the steps of obtaining probability distribution of the current state and the duration of a network element of the active power distribution network, sampling the probability distribution of the current state and the duration of the network element of the active power distribution network to obtain a sampling sample, obtaining a state sequence of the element of the active power distribution network in the current state according to the sampling sample, and giving an operation state-duration sequence of a system in a total time period by integrating the state sequence of each element of the active power distribution network.
As an optional implementation manner, classifying the load nodes of the active power distribution network according to the simulation result, and obtaining the classification result includes: selecting the operation state of the system of the active power distribution network according to the operation state sequence of the system of the active power distribution network and the duration time sequence of the system of the active power distribution network; determining an adjacency matrix of a network line topology of the active power distribution network in an operating state; acquiring a source-load minimum path set according to the adjacency matrix, wherein the source-load minimum path set is a minimum path set between any load nodes; and classifying the load nodes according to the source-load minimum path set to obtain a network load node set, an island load node set and an interrupt load node set.
selecting the operation state of a system of the active power distribution network according to the operation state-duration sequence, obtaining a source-load minimum path set by utilizing an adjacent array of the active power distribution network, wherein the adjacent array is a matrix representing the adjacent relation between vertexes of the matrix, and obtaining the classification results of a grid-connected load node set, an island load node set and an interruption load node set by classifying load nodes of the active power distribution network.
alternatively, the source-to-load minimum set of paths may be obtained from a topological contiguous array of network lines. For the adjacency matrix C, if r ≧ n, C must be presentrWhere r adjoins the number of rows of the matrix C and n adjoins the number of columns of the matrix C. Therefore, the minimum path set between any load nodes obtained by the adjacency matrix is:
If it is assumed that of the n nodes of the network S of the active distribution network, n1～nRThe nodes are distributed power supplies and grid-connected common connection points, nN+1～nNEach node is a distribution network node, and the last nN+1～nLthe nodes are load nodes, and then are distributedthe minimum path set between the power supply and the grid-connected public connecting point and the load is C1，C2，…，Cn-1in n1～nRNode and nN+1～nLelements between nodes. In the above-mentioned C1，C2，…，Cn-1In the multiplication of (2): when i ≠ j,When the value of i is equal to j,And is arranged atIn a polynomial expression, a term is taken to be 0 if an arc in that term occurs more than once, ifAlready contained inin a certain item of (2), the item is taken as 0.
As an alternative embodiment, determining the topology of the classification result, and obtaining the determination result includes: when the classification result is a network load node set, determining a topological structure of a grid-connected part of the active power distribution network; and when the classification result is the island load node set, according to the adjacency matrix and the source-load minimum path set, performing aggregation on the load nodes according to the connected domain to obtain an island load node subset of the island load node set, and determining a distributed power supply, a load and an energy storage device which are included in the island load node subset.
For a grid-connected load node set, determining the topology and configuration of a grid-connected part; for an island load node set, according to an adjacent array and a source-load minimum path set, aggregating each node of the network according to a connected domain, thereby screening out an island node subset, and determining a distributed power supply, a load and an energy storage device which are contained;
As an alternative embodiment, determining the topology of the classification result, and obtaining the determination result includes: and according to the breadth-first search algorithm, the adjacency matrix, the island load node set and the source-load minimum path set, carrying out aggregation on the load nodes according to the connected domain to obtain an island load node subset of the island load node set, and determining a grid-connected point set which has a connected path with the public power distribution network.
The topology identification can be performed by using a Breadth First Search algorithm (BFS), which is also a Breadth First algorithm, or a horizontal First algorithm, which is a graph Search algorithm, starting from a root node, traversing nodes of the tree along the width of the tree, and if a target is found, terminating the algorithm. According to the embodiment, each node in the network is aggregated according to the adjacent matrix, the island load node set and the source-load minimum path set, so that an island node subset is screened out, and meanwhile, a grid-connected node set of a connected path existing in the public power distribution network can be determined.
As an optional implementation manner, the establishing a preset model of the active power distribution network according to the classification result and the determination result includes: selecting the operation condition of the active power distribution network in the operation process according to the classification result and the determination result; acquiring probability distribution information of an operation condition in an active power distribution network; acquiring access information of a distributed power supply and a load when the distributed power supply and the load are accessed through a power electronic device; and establishing a preset model comprising probability distribution information and access information.
According to the load node classification and operation topology identification results, selecting operation conditions of a main active power distribution network, acquiring probability distribution information of the operation conditions in the active power distribution network, acquiring access information of distributed power supplies and loads when the distributed power supplies and the loads are accessed through a power electronic device, and establishing a network-element space sub-model containing the distributed power supplies and load access information and the operation condition probability distribution information.
and grouping the network samples in the network-element space submodel according to the topological similarity for parallel processing. And selecting one of the similar network samples in the group as a network base, and performing three-phase forward-backward substitution probability load flow calculation and probability harmonic load flow calculation to obtain the distribution characteristics of each phase voltage of the node. And (3) respectively carrying out three-phase forward-backward substitution probability tide and probability harmonic tide acceleration on the difference of the network samples in the group by adopting a compensation method, thereby obtaining the distribution characteristics of each phase voltage of the nodes under the corresponding working conditions of other network samples. And counting the node voltage distribution of each operation condition according to the probability distribution information of the operation conditions, thereby obtaining the evaluation result of the voltage quality of the active power distribution network in the planning stage.
As an optional implementation manner, after the preset model of the active power distribution network is established according to the classification result and the determination result, the method for evaluating the voltage quality of the active power distribution network further includes: acquiring parameters of a load and input and output information of the load; and determining a probability distribution model for representing the probability of the distribution of the distributed power sources and the loads in the active power distribution network according to the parameters of the distributed power sources and the loads and the input and output information of the loads.
And acquiring basic parameters of the load and input and output information of the load, and estimating a probability distribution model of the distributed power supply and the load according to the distributed power supply, the basic parameters of the load and the input and output characteristics of the active power distribution network in a planning stage.
The embodiment provides a power quality assessment method in a planning stage of an active power distribution network aiming at the problem that the voltage quality assessment of the existing active power distribution network is difficult in the planning stage.
The technical solution of the present invention will be described below with reference to preferred embodiments.
fig. 2 is a flowchart of a voltage quality evaluation method for an active power distribution network according to a second embodiment of the present invention. As shown in fig. 2, the voltage quality evaluation method for the active power distribution network includes the following steps:
step S201, multi-state simulation of the active power distribution network.
The method comprises the steps of sampling the state and duration probability distribution of elements of the active power distribution network by adopting a Monte Carlo-state time sampling method, and comprehensively obtaining a state sequence of each element of the active power distribution network, so that an operation state-duration sequence of a system of the active power distribution network in a total time period is obtained.
According to the active power distribution network line and equipment configuration in the planning stage, assuming that elements of the active power distribution network are in a running state at the initial moment, sampling the duration of each element in the system of the active power distribution network staying in the current state, wherein the duration state sequence can be obtained by backward simulation of probability distribution of element faults and repair time.
and step S202, classifying the working conditions of the load nodes.
and selecting the running state of the system of the active power distribution network according to the running state-duration sequence, obtaining a source-load minimum path set through a network adjacent array of the active power distribution network, and classifying the load nodes to obtain classification results of a grid-connected load node set, an island load node set and an interrupted load node set.
And selecting the system running state according to the state sequence of each element, comprehensively giving the running state and the duration sequence of the system of the active power distribution network in the total time period, obtaining a source-load minimum path set by utilizing a network line topological adjacent array, and classifying the load nodes to obtain the classification results of a grid-connected load node set, an island load node set and an interrupt load node set.
Step S203, a topology identification is performed.
And after the working conditions of the load nodes are classified to obtain the classification results of the grid-connected load node set, the island load node set and the interrupted load node set, operating the topological structure identification. For a grid-connected load node set, determining the topology and configuration of a grid-connected part; and for the island load node set, according to the adjacent matrix and the source-load minimum path set in the step S202, aggregating all nodes of the network according to the connected domain, thereby screening out an island node subset and determining the included distributed power supply, load and energy storage device.
And step S204, constructing a network-element space submodel.
And according to the load node classification and operation topology identification results in the steps S202 and S203, selecting main operation conditions of the active power distribution network, and establishing a network-element space sub-model containing distributed power supply and load access information and operation condition probability distribution information.
In step S205, a load and a distributed power source are simulated.
and estimating a probability distribution model of the distributed power sources and the loads according to the distributed power sources, the load basic parameters and the input and output characteristics of the loads of the active power distribution network in a planning stage.
and step S206, grouping the multiple working conditions in parallel and accelerating the processing.
and grouping the network samples in the network-element space submodel according to the topological similarity for parallel processing. And selecting one of the similar network samples in the group as a network base of the active power distribution network, and performing three-phase forward-backward substitution probability load flow calculation and probability harmonic load flow calculation to obtain the distribution characteristics of each phase voltage of the node. And (3) for the differences of the network samples in the group, respectively carrying out three-phase forward-backward substitution probability tide and probability harmonic tide acceleration by adopting a compensation method, thereby obtaining the distribution characteristics of each phase voltage of the nodes under the corresponding working conditions of other network samples.
And step S207, counting the node voltage distribution of each operation condition according to the probability distribution information of the operation condition, and obtaining the voltage quality evaluation result of the active power distribution network in the planning stage.
After grouping, paralleling and accelerating the multiple working conditions, counting the node voltage distribution of each operating working condition according to the probability distribution information of the operating working conditions, thereby obtaining the voltage quality evaluation result of the active power distribution network in the planning stage.
according to the embodiment, through active power distribution network multi-state simulation, the working conditions of the load nodes are classified, the operation topological structure is identified, a network-element space sub-model is constructed, the load and the distributed power supply are simulated, the multiple working conditions are grouped and processed in parallel and in an accelerating mode, the node voltage distribution of each operation working condition is counted according to the probability distribution information of the operation working conditions, the voltage quality evaluation result of the active power distribution network in the planning stage is obtained, and the effect of reducing the difficulty of accurately evaluating the voltage quality in the active power distribution network planning process is achieved.
it should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.
The embodiment of the invention also provides a voltage quality evaluation device of the active power distribution network. It should be noted that the voltage quality evaluation device of the active power distribution network of this embodiment may be used to execute the voltage quality evaluation method of the active power distribution network of the embodiment of the present invention.
Fig. 3 is a voltage quality evaluation apparatus of an active power distribution network according to an embodiment of the present invention. As shown in fig. 3, the voltage quality evaluation apparatus for an active power distribution network includes: a simulation unit 10, a classification unit 20, a building unit 40, a processing unit 50 and a statistical unit 60.
And the simulation unit 10 is used for performing statistical simulation on the current state of the element of the active power distribution network and the duration of the element of the active power distribution network in the current state to obtain a simulation result.
The classification unit 20 is configured to classify the load nodes of the active power distribution network according to the simulation result to obtain a classification result;
A determining unit 30, configured to determine a topological structure of the classification result, and obtain a determination result;
The establishing unit 40 is used for establishing a preset model of the active power distribution network according to the classification result and the determination result;
The processing unit 50 is configured to execute processing on the preset model to obtain voltage distribution information of the load node;
And the statistical unit 60 is configured to perform statistics on the voltage distribution information to obtain a voltage quality evaluation result of the active power distribution network.
optionally, the simulation unit 10 comprises a sampling module and a first determination module. The sampling module is used for sampling the current state of the element of the active power distribution network and the probability distribution of the duration time of the current state in the active power distribution network to obtain a state sequence of the element of the active power distribution network; the first determining module is used for determining the operation state sequence of the system of the active power distribution network and the duration time sequence of the system of the active power distribution network according to the state sequence.
Optionally, the classification unit 20 includes a selection module, a second determination module, an acquisition module and a classification module. The selection module is used for selecting the operation state of the system of the active power distribution network according to the operation state sequence of the system of the active power distribution network and the duration time sequence of the system of the active power distribution network; the second determination module is used for determining an adjacency matrix of the network line topology of the active power distribution network in the running state; the acquisition module is used for acquiring a source-load minimum path set according to the adjacency matrix, wherein the source-load minimum path set is a minimum path set between any load nodes; and the classification module is used for classifying the load nodes according to the source-load minimum path set to obtain a network load node set, an island load node set and an interrupt load node set.
Optionally, the determination unit 30 comprises a third determination module and a first aggregation module. The third determining module is used for determining a topological structure of a grid-connected part of the active power distribution network when the classification result is the network load node set; and the first aggregation module is used for performing aggregation on the load nodes according to the connected domain according to the adjacency matrix and the source-load minimum path set when the classification result is the island load node set to obtain an island load node subset of the island load node set, and determining a distributed power supply, a load and an energy storage device which are included in the island load node subset.
Optionally, the determining unit 30 includes a second aggregation module, configured to perform aggregation on load nodes according to a breadth-first search algorithm, an adjacency matrix, an island load node set and a source-load minimum path set and a connected domain, to obtain an island load node subset of the island load node set, and determine a connected node point set where a connected path exists with a public power distribution network.
optionally, the establishing unit 40 is configured to select an operation condition of the active power distribution network in an operation process according to the classification result and the determination result; acquiring probability distribution information of an operation condition in an active power distribution network; acquiring access information of a distributed power supply and a load when the distributed power supply and the load are accessed through a power electronic device; and establishing a preset model comprising probability distribution information and access information.
Optionally, the voltage quality evaluation apparatus for an active power distribution network further includes: the obtaining unit is used for obtaining the parameters of the load and the input and output information of the load after a preset model of the active power distribution network is established according to the classification result and the determination result; the determining unit 30 is further configured to determine a probability distribution model for representing the probability that the distributed power sources and the loads are distributed in the active power distribution network according to the distributed power sources, the parameters of the loads, and the input and output information of the loads.
In the embodiment, the simulation unit 10 performs statistical simulation on the current state of the element of the active power distribution network and the duration of the current state of the element of the active power distribution network to obtain a simulation result; classifying the load nodes of the active power distribution network through a classification unit 20 according to the simulation result to obtain a classification result; determining the topological structure of the classification result by the determining unit 30 to obtain a determination result; establishing a preset model of the active power distribution network according to the classification result and the determination result through the establishing unit 40; the preset model is processed through the processing unit 50 to obtain voltage distribution information of the load nodes; the voltage distribution information is subjected to statistics by the statistics unit 60, and a voltage quality evaluation result of the active power distribution network is obtained.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and they may alternatively be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, or fabricated separately as individual integrated circuit modules, or fabricated as a single integrated circuit module from multiple modules or steps. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. a voltage quality evaluation method of an active power distribution network is characterized by comprising the following steps:
Performing statistical simulation on the current state of an element of an active power distribution network and the duration of the element of the active power distribution network in the current state to obtain a simulation result;
Classifying the load nodes of the active power distribution network according to the simulation result to obtain a classification result;
Determining the topological structure of the classification result to obtain a determination result;
Establishing a preset model of the active power distribution network according to the classification result and the determination result;
processing the preset model to obtain voltage distribution information of the load node; and
Performing statistics on the voltage distribution information to obtain a voltage quality evaluation result of the active power distribution network;
Grouping and parallel processing and accelerated processing are carried out on the multi-working-condition information of the active power distribution network in the operation process according to topological similarity; and selecting one of the similar network samples in the group as a network base, and performing three-phase forward-backward substitution probability load flow calculation and probability harmonic load flow calculation on the network base to obtain the distribution characteristics of each phase voltage of the load node.
2. the method of claim 1, wherein performing statistical simulations of a current state of an element of the active power distribution network and a duration of time that the element of the active power distribution network is in the current state comprises:
Sampling the current state of the element of the active power distribution network and the probability distribution of the duration time in the current state in the active power distribution network to obtain a state sequence of the element of the active power distribution network; and
And determining an operation state sequence of the system of the active power distribution network and a duration time sequence of the system of the active power distribution network according to the state sequence.
3. The method of claim 2, wherein classifying the load nodes of the active power distribution network according to the simulation result, and obtaining the classification result comprises:
selecting the operation state of the system of the active power distribution network according to the operation state sequence of the system of the active power distribution network and the duration time sequence of the system of the active power distribution network;
Determining an adjacency matrix of a network line topology of the active power distribution network in the operating state;
Acquiring a source-load minimum path set according to the adjacency matrix, wherein the source-load minimum path set is a minimum path set between any load nodes; and
And classifying the load nodes according to the source-load minimum path set to obtain a network load node set, an island load node set and an interrupt load node set.
4. The method of claim 3, wherein determining the topology of the classification result comprises:
when the classification result is the network load node set, determining a topological structure of a grid-connected part of the active power distribution network; and
and when the classification result is the island load node set, according to the adjacency matrix and the source-load minimum path set, performing aggregation on the load nodes according to a connected domain to obtain an island load node subset of the island load node set, and determining a distributed power supply, a load and an energy storage device which are included in the island load node subset.
5. The method of claim 3, wherein determining the topology of the classification result comprises: and according to the breadth-first search algorithm, the adjacency matrix, the island load node set and the source-load minimum path set, carrying out aggregation on the load nodes according to a connected domain to obtain an island load node subset of the island load node set, and determining a grid-connected point set which has a connected path with a public power distribution network.
6. the method of claim 4, wherein establishing the preset model of the active power distribution network according to the classification result and the determination result comprises:
selecting the operation condition of the active power distribution network in the operation process according to the classification result and the determination result;
Acquiring probability distribution information of the operating conditions in the active power distribution network;
Acquiring access information of the distributed power supply and the load when the distributed power supply and the load are accessed through a power electronic device; and
And establishing a preset model comprising the probability distribution information and the access information.
7. The method of claim 6, wherein after establishing the preset model of the active power distribution network according to the classification result and the determination result, the method further comprises:
Acquiring parameters of the load and input and output information of the load; and
And determining a probability distribution model for representing the probability of the distributed power sources and the loads distributed in the active power distribution network according to the distributed power sources, the parameters of the loads and the input and output information of the loads.
8. A voltage quality evaluation device of an active power distribution network is characterized by comprising:
The simulation unit is used for carrying out statistical simulation on the current state of the element of the active power distribution network and the duration of the element of the active power distribution network in the current state to obtain a simulation result;
The classification unit is used for classifying the load nodes of the active power distribution network according to the simulation result to obtain a classification result;
The determining unit is used for determining the topological structure of the classification result to obtain a determination result;
The establishing unit is used for establishing a preset model of the active power distribution network according to the classification result and the determination result;
the processing unit is used for executing processing on the preset model to obtain voltage distribution information of the load node; and
The statistical unit is used for performing statistics on the voltage distribution information to obtain a voltage quality evaluation result of the active power distribution network;
The device is also used for carrying out grouping parallel processing and accelerated processing on the multi-working-condition information of the active power distribution network in the operation process according to topological similarity; and selecting one of the similar network samples in the group as a network base, and performing three-phase forward-backward substitution probability load flow calculation and probability harmonic load flow calculation on the network base to obtain the distribution characteristics of each phase voltage of the load node.
9. The apparatus of claim 8, wherein the analog unit comprises:
the sampling module is used for sampling the current state of the element of the active power distribution network and the probability distribution of the duration time in the current state in the active power distribution network to obtain a state sequence of the element of the active power distribution network; and
The first determination module is used for determining the operation state sequence of the system of the active power distribution network and the duration time sequence of the system of the active power distribution network according to the state sequence.
10. The apparatus of claim 9, wherein the classification unit comprises:
The selection module is used for selecting the operation state of the system of the active power distribution network according to the operation state sequence of the system of the active power distribution network and the duration time sequence of the system of the active power distribution network;
A second determination module, configured to determine, in the operating state, an adjacency matrix of a network line topology of the active power distribution network;
An obtaining module, configured to obtain a source-load minimum path set according to the adjacency matrix, where the source-load minimum path set is a minimum path set between any load nodes; and
and the classification module is used for classifying the load nodes according to the source-load minimum path set to obtain a network load node set, an island load node set and an interrupt load node set.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610320183.4A CN106022590B (en) | 2016-05-13 | 2016-05-13 | Voltage quality evaluation method and device for active power distribution network |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610320183.4A CN106022590B (en) | 2016-05-13 | 2016-05-13 | Voltage quality evaluation method and device for active power distribution network |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106022590A CN106022590A (en) | 2016-10-12 |
| CN106022590B true CN106022590B (en) | 2019-12-10 |
Family
ID=57096904
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610320183.4A Active CN106022590B (en) | 2016-05-13 | 2016-05-13 | Voltage quality evaluation method and device for active power distribution network |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106022590B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111666697B (en) * | 2020-06-19 | 2022-07-05 | 国网福建省电力有限公司电力科学研究院 | Active power distribution network reliability evaluation method and system based on sequential Monte Carlo method |
| CN113094899A (en) * | 2021-04-07 | 2021-07-09 | 全球能源互联网研究院有限公司 | Random power flow calculation method and device, electronic equipment and storage medium |
| CN113295963B (en) * | 2021-05-12 | 2022-08-23 | 西北工业大学 | Cross-domain cascading failure source node judgment method for CPS system of active power distribution network |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101179195A (en) * | 2007-11-15 | 2008-05-14 | 上海交通大学 | Power distribution network planning scheme assistant decision system |
| CN104504246A (en) * | 2014-12-05 | 2015-04-08 | 清华大学 | Quick reliability estimation algorithm based on ring-radiation network decoupling |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9634866B2 (en) * | 2013-09-06 | 2017-04-25 | Intel Corporation | Architecture and method for hybrid circuit-switched and packet-switched router |
-
2016
- 2016-05-13 CN CN201610320183.4A patent/CN106022590B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101179195A (en) * | 2007-11-15 | 2008-05-14 | 上海交通大学 | Power distribution network planning scheme assistant decision system |
| CN104504246A (en) * | 2014-12-05 | 2015-04-08 | 清华大学 | Quick reliability estimation algorithm based on ring-radiation network decoupling |
Non-Patent Citations (2)
| Title |
|---|
| V2G模式下城市电网电压质量概率评估方法;郭小敏 等;《电网技术》;20151031;第39卷(第10期);正文第3.2节 * |
| 基于蒙特卡罗模拟的含微网配电网可靠性评估;梁惠施 等;《电网技术》;20111031;第35卷(第10期);正文第2,3节，图3 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106022590A (en) | 2016-10-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Mulenga et al. | A review of hosting capacity quantification methods for photovoltaics in low-voltage distribution grids | |
| Da Silva et al. | Risk assessment in probabilistic load flow via Monte Carlo simulation and cross-entropy method | |
| Oliveira et al. | Power system security assessment for multiple contingencies using multiway decision tree | |
| Rezaei et al. | Estimating cascading failure risk with random chemistry | |
| Noebels et al. | AC cascading failure model for resilience analysis in power networks | |
| Gruosso et al. | Uncertainty-aware computational tools for power distribution networks including electrical vehicle charging and load profiles | |
| CN106022590B (en) | Voltage quality evaluation method and device for active power distribution network | |
| Guo et al. | Failure localization in power systems via tree partitions | |
| Xu et al. | Risk‐averse multi‐objective generation dispatch considering transient stability under load model uncertainty | |
| Cavraro et al. | Bus clustering for distribution grid topology identification | |
| Hua et al. | Eliminating redundant line flow constraints in composite system reliability evaluation | |
| Akrami et al. | Sparse distribution system state estimation: An approximate solution against low observability | |
| da Silva et al. | Constructive metaheuristics applied to transmission expansion planning with security constraints | |
| CN114065634A (en) | Data-driven power quality monitoring and stationing optimization method and device | |
| Guo et al. | On-line prediction of transient stability using decision tree method—Sensitivity of accuracy of prediction to different uncertainties | |
| Guillen et al. | Data‐driven short‐circuit detection and location in microgrids using micro‐synchrophasors | |
| de Oliveira et al. | Voltage sags: Validating short-term monitoring by using long-term stochastic simulation | |
| Ma et al. | An evaluation method for bus and grid structure based on voltage sags/swells using voltage ellipse parameters | |
| Aguas et al. | EDPD’S experience with data analytics and stochastic simulation methods for risk-controlled network planning | |
| CN111884254B (en) | Distributed photovoltaic absorption access method and device based on double random simulation | |
| Gorjani et al. | Application of optimized deterministic methods in long-term power quality | |
| Fan et al. | Integrated approach for online dynamic security assessment with credibility and visualization based on exploring connotative associations in massive data | |
| Pierre et al. | A framework to model and analyze electric grid cascading failures to identify critical nodes | |
| Liu et al. | A novel acceleration strategy for nl contingency screening in distribution system | |
| Chen et al. | Dynamic optimal power flow model incorporating interval uncertainty applied to distribution network |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |