CN116187870A - Method, device, equipment and storage medium for tracing carbon track of electric power system - Google Patents
Method, device, equipment and storage medium for tracing carbon track of electric power system Download PDFInfo
- Publication number
- CN116187870A CN116187870A CN202310261216.2A CN202310261216A CN116187870A CN 116187870 A CN116187870 A CN 116187870A CN 202310261216 A CN202310261216 A CN 202310261216A CN 116187870 A CN116187870 A CN 116187870A
- Authority
- CN
- China
- Prior art keywords
- data
- power
- carbon
- node
- power system
- 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.)
- Pending
Links
Images
Classifications
-
- 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
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/80—Management or planning
- Y02P90/84—Greenhouse gas [GHG] management systems
Landscapes
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The application relates to the technical field of power systems and carbon emission, in particular to a method, a device, equipment and a storage medium for tracing carbon tracks of a power system. Comprising the following steps: acquiring related data of a power system; carrying out power grid topology decomposition by utilizing the related data of the power grid structure to obtain a node topology model of the power system; the method comprises the steps of obtaining power generation carbon emission intensity data and injection node data of a generator set through power flow analysis by using injection nodes; obtaining the carbon intensity of the network node by using the power grid tide data and the power generation carbon emission intensity data of the generator set; and tracing the carbon track of the power system by utilizing the carbon intensity of the network node and the output node to obtain the carbon emission data of each power load. The method and the device are beneficial to solving the problem that the real-time data reference cannot be provided for the establishment of policies such as energy conservation, carbon reduction and the like due to the fact that the data collection difficulty is high and hysteresis is caused in carbon emission.
Description
Technical Field
The application relates to the technical field of power systems and carbon emission, in particular to a method, a device, equipment and a storage medium for tracing carbon tracks of a power system.
Background
In the prior art, when the carbon emission intensity and the carbon emission quantity related to the electricity consumption behavior of a user are analyzed through tracking the carbon emission trend in an electric power network, regional carbon emission calculation is performed according to the energy consumption quantity, electric quantity and other data of each region, the carbon emission calculation period can only be based on months or years, the data collection difficulty is high, the carbon emission result has hysteresis, and real-time data reference cannot be provided for the establishment of policies such as energy conservation, carbon reduction and the like.
In the prior art, the carbon emission cannot provide real-time data reference for the establishment of policies such as energy conservation, carbon reduction and the like due to the fact that the data collection difficulty is high and the hysteresis is caused.
Disclosure of Invention
In order to at least overcome the problem that the real-time data reference cannot be provided for the establishment of policies such as energy conservation, carbon reduction and the like due to the fact that the carbon emission is large in data collection difficulty and hysteresis in the related technology to a certain extent, the application provides a method, a device, equipment and a storage medium for tracing the carbon track of a power system.
The scheme of the application is as follows:
in a first aspect, the present application provides a method for tracing a carbon track of an electrical power system, the method comprising:
acquiring power system related data, the power system related data including: grid structure related data and grid power flow data;
and carrying out power grid topology decomposition by utilizing the related data of the power grid structure to obtain a power system node topology model, wherein nodes of the power system node topology model comprise: injection nodes and output nodes;
wherein the injection node comprises: the generator set and the swing node;
obtaining the generated carbon emission intensity data and the injection node data of the generator set through power flow analysis by utilizing the injection nodes;
obtaining the carbon intensity of a network node by using the power grid tide data, the power generation carbon emission intensity data of the generator set and the injection node data;
and carrying out carbon track tracing on the electric power system by utilizing the carbon intensity of the network node and the output node to obtain carbon emission data of each electric load.
Further, the performing power grid topology decomposition by using the related data of the power grid structure to obtain a node topology model of the power system includes:
describing the connection relation of the power system by using the related data of the power grid structure and adopting a node model;
and generating a bus model and topology island information by using the related data of the power grid structure and the connection relation of the power system through a search algorithm to obtain a node topology model of the power system.
Further, obtaining the carbon intensity of the network node by using the power grid tide data, the power generation carbon emission intensity data of the generator set and the injection node data, including:
and calculating carbon track distribution data of all lines of the whole network by using the power flow data of the power grid and the power generation carbon emission intensity data of the generator set through a flow sharing principle and a complex power tracing method to obtain the carbon intensity of nodes of the whole network.
In a second aspect, the present application provides an apparatus for tracing a carbon trajectory of an electrical power system, the apparatus comprising:
the acquisition module is used for acquiring power system related data, and the power system related data comprises: grid structure related data and grid power flow data;
the network topology analysis module is used for carrying out power grid topology decomposition by utilizing the related data of the power grid structure to obtain a power system node topology model, and the nodes of the power system node topology model comprise: injection nodes and output nodes;
wherein the injection node comprises: the generator set and the swing node;
the power flow analysis module is used for obtaining the power generation carbon emission intensity data and the injection node data of the generator set through power flow analysis by utilizing the injection nodes;
the tide tracing decomposition module is used for obtaining the carbon intensity of the network node by utilizing the power grid tide data, the power generation carbon emission intensity data of the generator set and the injection node data;
and the carbon emission tracing module is used for tracing the carbon track of the power system by utilizing the carbon intensity of the network node and the output node to obtain the carbon emission data of each power load.
In a third aspect, the present application provides an apparatus for tracing a carbon trajectory of an electrical power system, the apparatus comprising: a memory having an executable program stored thereon;
a processor for executing the executable program in the memory to implement the steps of any of the methods described above.
In a fourth aspect, the present application provides a computer readable storage medium, wherein the computer readable storage medium stores computer instructions for causing a computer to perform the steps of any one of the methods described above.
The technical scheme that this application provided can include following beneficial effect:
the method comprises the steps of obtaining relevant data of a power system; carrying out power grid topology decomposition by utilizing the related data of the power grid structure to obtain a node topology model of the power system; the method comprises the steps of obtaining power generation carbon emission intensity data and injection node data of a generator set through power flow analysis by using injection nodes; obtaining the carbon intensity of the network node by using the power grid tide data and the power generation carbon emission intensity data of the generator set; and tracing the carbon track of the power system by utilizing the carbon intensity of the network node and the output node to obtain the carbon emission data of each power load. The method and the device are beneficial to solving the problem that the real-time data reference cannot be provided for the establishment of policies such as energy conservation, carbon reduction and the like due to the fact that the data collection difficulty is high and hysteresis is caused in carbon emission.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.
FIG. 1 is a schematic flow chart of a method for tracing a carbon track of an electric power system according to an embodiment of the present application;
fig. 2 is a schematic diagram of an apparatus for tracing a carbon track of an electric power system according to another embodiment of the present disclosure;
fig. 3 is a schematic diagram of an apparatus set for tracking carbon trajectories of an electric power system according to another embodiment of the present application.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present application as detailed in the accompanying claims.
Example 1
Referring to fig. 1, fig. 1 is a flowchart of a method for tracing a carbon track of an electric power system according to an embodiment of the present application, where the method includes:
s1, acquiring power system related data, wherein the power system related data comprises: grid structure related data and grid power flow data;
s2, carrying out power grid topology decomposition by utilizing the related data of the power grid structure to obtain a power system node topology model, wherein nodes of the power system node topology model comprise: injection nodes and output nodes;
wherein the injection node comprises: the generator set and the swing node;
s3, utilizing the injection node to obtain power generation carbon emission intensity data and injection node data of the generator set through power flow analysis;
s4, obtaining the carbon intensity of the network node by using the power grid tide data, the power generation carbon emission intensity data of the generator set and the injection node data;
s5, carrying out carbon track tracing on the electric power system by utilizing the carbon intensity of the network node and the output node to obtain carbon emission data of each electric load
In one embodiment, as described in step S2, performing power grid topology decomposition by using power grid structure related data to obtain a power system node topology model, including:
describing the connection relation of the power system by using the related data of the power grid structure and adopting a node model;
generating a bus model and topology island information by using the related data of the power grid structure and the connection relation of the power system through a search algorithm to obtain a node topology model of the power system.
In one embodiment, as described in step S3, the generating carbon emission intensity data and the injection node data of the generator set are obtained through power flow analysis by using the injection node, including:
preparing the power grid structure related data and the equipment parameter related data;
acquiring voltage, power, line loss and other power grid operation parameters by using the power grid structure related data and the equipment parameter related data;
and carrying out power flow analysis on the power grid operation parameters by utilizing the injection nodes to obtain the power generation carbon emission intensity data and the injection node data of the generator set.
In one embodiment, as described in step S4, the obtaining the carbon intensity of the network node by using the power grid trend data and the power generation carbon emission intensity data of the generator set includes:
and calculating carbon track distribution data of all lines of the whole network by using the power flow data of the power grid and the power generation carbon emission intensity data of the generator set and by using a flow sharing principle and a complex power tracing method to obtain the carbon intensity of nodes of the whole network.
In specific implementation, a carbon tide intensity calculation model is constructed through a tide sharing principle and a complex power tracing method, and carbon track distribution data of all lines of the whole network are calculated through solving the model, so that the carbon intensity of nodes of the whole network is obtained.
It should be noted that, the specific carbon tide intensity calculation model is as follows:
the specific carbon tide intensity calculation model is as follows:
1) Carbon strength GCI (generation carbon intensity) for all individual genset generation (gCO 2 /kWh or tCO 2 MWh) is determined by its own carbon dioxide emission factor and its fuel consumption (or other official standards), GCI describes the relationship of electricity production to injected carbon flow. For a power plant containing multiple generator sets, the carbon strength is as shown in equation 1:
wherein K is p Is the number of generator sets in the power plant, P Gi And e Gi The active output and the carbon strength of the unit i are respectively.
2) And calculating the carbon flow of the injection node.
Definition of carbon flow Rate
R represents the carbon trend in unit time, and F represents the carbon trend.
Definition of node carbon Strength
Wherein G and P are electric quantity and active power respectively.
And calculating a carbon flow rate matrix as shown in formula 2:
R G ＝P G ·e g (2)
wherein R is G And e g The carbon flow rate vector and the carbon intensity matrix of the injection node are respectively, P G Is a power distribution matrix. P (P) G Is an n x k matrix, contains topological position information and power information of a generator set, and P Gnk Representing the power injected by the kth unit at the nth node, R G As N-dimensional vector, E G And the K-dimensional vector represents the carbon flow rate and the carbon strength of the generator set.
3) The calculation node outputs the carbon intensity as shown in equation 3.
The carbon strength of the ith node in the system is:
wherein I is + Representing the line injecting power into node i ρ s The carbon intensity of the line s is rewritten into a matrix form as shown in formula 4:
P′ B is an N-order matrix representing linesA road tide distribution matrix; e (E) N The N-dimensional row vector represents the output carbon intensity of the node;
is the N-dimensional row vector of the i-th node; p (P) N And (5) flowing out an active power matrix for the node.
Is arranged as shown in a formula (5)
On the basis, the carbon emission data of all nodes can be calculated by combining the power generation data (electric power and electric quantity data).
In the embodiments of the present application, the electrical energy in the power system is transmitted in the network in the form of a power flow, and the corresponding carbon emissions of the electrical energy also flow in the network with the power flow. By tracking the carbon emission trend in the power network, the carbon emission intensity and the carbon emission amount associated with the user electricity behavior are analyzed.
It should be noted that, considering the different carbon intensities of different output nodes, in the tracking process, according to the distribution of the power flow in the power grid, the power source proportion of each branch and each node is tracked, and the carbon intensities of each node and each branch are accurately formed by combining the corresponding carbon intensities, so as to complete the tracking of the carbon track of the whole network.
Example two
Referring to fig. 2, fig. 2 is a schematic diagram illustrating an apparatus for tracing a carbon track of an electric power system according to another embodiment of the present application, where the apparatus includes:
an acquiring module 101, configured to acquire power system related data, where the power system related data includes: grid structure related data and grid power flow data;
the network topology analysis module 102 is configured to perform power grid topology decomposition by using the power grid structure related data to obtain a power system node topology model, where a node of the power system node topology model includes: injection nodes and output nodes;
wherein the injection node comprises: the generator set and the swing node;
the power flow analysis module 103 is configured to obtain, by using the injection node, power generation carbon emission intensity data and injection node data of the generator set through power flow analysis;
the tide traceability decomposition module 104 is configured to obtain the carbon intensity of a network node by using the power grid tide data, the power generation carbon emission intensity data of the generator set and the injection node data;
and the carbon emission tracing module 105 is configured to trace the carbon track of the power system by using the carbon intensity of the network node and the output node, so as to obtain carbon emission data of each power load. Example III
Referring to fig. 3, fig. 3 is a schematic diagram of an apparatus set for tracing a carbon track of an electric power system according to another embodiment of the present application, where the apparatus includes:
a memory 31 on which an executable program is stored;
a processor 32 for executing the executable program in the memory 31 to implement the steps of the method as described in any one of the above.
Furthermore, the present application provides a computer readable storage medium storing computer instructions for causing a computer to perform the steps of any one of the methods described above. Wherein the storage medium may be a magnetic Disk, an optical Disk, a Read-only Memory (ROM), a random access Memory (Random Access Memory, RAM), a Flash Memory (Flash Memory), a Hard Disk (HDD), a Solid State Drive (SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.
It is to be understood that the same or similar parts in the above embodiments may be referred to each other, and that in some embodiments, the same or similar parts in other embodiments may be referred to.
It should be noted that in the description of the present application, the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Furthermore, in the description of the present application, unless otherwise indicated, the meaning of "plurality" means at least two.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and further implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present application.
It is to be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
Those of ordinary skill in the art will appreciate that all or part of the steps carried out in the method of the above-described embodiments may be implemented by a program to instruct related hardware, and the program may be stored in a computer readable storage medium, where the program when executed includes one or a combination of the steps of the method embodiments.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing module, or each unit may exist alone physically, or two or more units may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules. The integrated modules may also be stored in a computer readable storage medium if implemented as software functional modules and sold or used as a stand-alone product.
The above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, or the like.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Although embodiments of the present application have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the application, and that variations, modifications, alternatives, and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the application.
Claims (6)
1. The method for tracing the carbon track of the electric power system is characterized by comprising the following steps:
acquiring power system related data, the power system related data including: grid structure related data and grid power flow data;
and carrying out power grid topology decomposition by utilizing the related data of the power grid structure to obtain a power system node topology model, wherein nodes of the power system node topology model comprise: injection nodes and output nodes;
wherein the injection node comprises: the generator set and the swing node;
obtaining the generated carbon emission intensity data and the injection node data of the generator set through power flow analysis by utilizing the injection nodes;
obtaining the carbon intensity of a network node by using the power grid tide data, the power generation carbon emission intensity data of the generator set and the injection node data;
and carrying out carbon track tracing on the electric power system by utilizing the carbon intensity of the network node and the output node to obtain carbon emission data of each electric load.
2. The method according to claim 1, wherein said performing a power grid topology decomposition using said power grid structure related data to obtain a power system node topology model comprises:
describing the connection relation of the power system by using the related data of the power grid structure and adopting a node model;
and generating a bus model and topology island information by using the related data of the power grid structure and the connection relation of the power system through a search algorithm to obtain a node topology model of the power system.
3. The method of claim 1, wherein using the grid power flow data and the power generation carbon emission intensity data and injection node data of the generator set to obtain the carbon intensity of the network node comprises:
and calculating carbon track distribution data of all lines of the whole network by using the power flow data of the power grid and the power generation carbon emission intensity data of the generator set through a flow sharing principle and a complex power tracing method to obtain the carbon intensity of nodes of the whole network.
4. Device for tracking carbon track of electric power system, characterized in that, the device includes:
the acquisition module is used for acquiring power system related data, and the power system related data comprises: grid structure related data and grid power flow data;
the network topology analysis module is used for carrying out power grid topology decomposition by utilizing the related data of the power grid structure to obtain a power system node topology model, and the nodes of the power system node topology model comprise: injection nodes and output nodes;
wherein the injection node comprises: the generator set and the swing node;
the power flow analysis module is used for obtaining the power generation carbon emission intensity data and the injection node data of the generator set through power flow analysis by utilizing the injection nodes;
the tide tracing decomposition module is used for obtaining the carbon intensity of the network node by utilizing the power grid tide data, the power generation carbon emission intensity data of the generator set and the injection node data;
and the carbon emission tracing module is used for tracing the carbon track of the power system by utilizing the carbon intensity of the network node and the output node to obtain the carbon emission data of each power load.
5. An apparatus for tracking carbon trajectories in an electrical power system, the apparatus comprising:
a memory having an executable program stored thereon;
a processor for executing the executable program in the memory to implement the steps of the method of any one of claims 1-3.
6. A computer readable storage medium having stored thereon computer instructions for causing a computer to perform the steps of the method according to any of claims 1-3.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310261216.2A CN116187870A (en) | 2023-03-15 | 2023-03-15 | Method, device, equipment and storage medium for tracing carbon track of electric power system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310261216.2A CN116187870A (en) | 2023-03-15 | 2023-03-15 | Method, device, equipment and storage medium for tracing carbon track of electric power system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116187870A true CN116187870A (en) | 2023-05-30 |
Family
ID=86434586
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310261216.2A Pending CN116187870A (en) | 2023-03-15 | 2023-03-15 | Method, device, equipment and storage medium for tracing carbon track of electric power system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116187870A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116562512A (en) * | 2023-07-11 | 2023-08-08 | 国网浙江省电力有限公司宁波供电公司 | Carbon diagnosis method, device, equipment and storage medium for electric power system |
| CN116823296A (en) * | 2023-08-31 | 2023-09-29 | 国网山东省电力公司营销服务中心(计量中心) | Method, system, equipment and medium for determining carbon emission of electricity utilization side |
| CN117194458A (en) * | 2023-09-22 | 2023-12-08 | 国家电网有限公司大数据中心 | Updating method, device and equipment of electric power carbon intensity and storage medium |
-
2023
- 2023-03-15 CN CN202310261216.2A patent/CN116187870A/en active Pending
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116562512A (en) * | 2023-07-11 | 2023-08-08 | 国网浙江省电力有限公司宁波供电公司 | Carbon diagnosis method, device, equipment and storage medium for electric power system |
| CN116562512B (en) * | 2023-07-11 | 2023-11-03 | 国网浙江省电力有限公司宁波供电公司 | Carbon diagnosis method, device, equipment and storage medium for electric power system |
| CN116823296A (en) * | 2023-08-31 | 2023-09-29 | 国网山东省电力公司营销服务中心(计量中心) | Method, system, equipment and medium for determining carbon emission of electricity utilization side |
| CN116823296B (en) * | 2023-08-31 | 2024-02-02 | 国网山东省电力公司营销服务中心(计量中心) | Method, system, equipment and medium for determining carbon emission of electricity utilization side |
| CN117194458A (en) * | 2023-09-22 | 2023-12-08 | 国家电网有限公司大数据中心 | Updating method, device and equipment of electric power carbon intensity and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN116187870A (en) | Method, device, equipment and storage medium for tracing carbon track of electric power system | |
| CN110943453A (en) | Power system fault sample generation and model construction method facing transfer learning | |
| CN107730111A (en) | A kind of distribution voltage risk evaluation model for considering customer charge and new energy access | |
| CN103248049B (en) | Containing the acquisition methods in DFIG wind energy turbine set voltage stability domain of electric power system section | |
| CN108695862A (en) | A kind of power grid inertia feature online evaluation method based on PMU measured datas | |
| CN113659635A (en) | Method and device for identifying key unit with electric carbon emission | |
| Hu et al. | Optimal operation of power systems with energy storage under uncertainty: A scenario-based method with strategic sampling | |
| Aghili et al. | Uncertainty analysis using fuzzy transformation method: an application in power-flow studies | |
| CN110457295A (en) | Time series data completion system based on social relationships perception | |
| CN107276093B (en) | Power system probability load flow calculation method based on scene reduction | |
| CN117273386A (en) | Virtual power plant system scheduling method, device and terminal based on deep reinforcement learning | |
| CN116579902B (en) | Digital park electric carbon data mapping method, system, equipment and storage medium | |
| CN117113239A (en) | Ship gas turbine fault detection method and equipment based on federal learning | |
| Al-Haija et al. | Time-series model for forecasting short-term future additions of renewable energy to worldwide capacity | |
| CN114744631A (en) | Data driving voltage estimation method based on non-PMU power distribution network | |
| CN112446171B (en) | Power system transient stability monitoring method and device, terminal equipment and storage medium | |
| Liu et al. | Static grid equivalent models based on artificial neural networks | |
| Angel et al. | Hardware in the loop experimental validation of PID controllers tuned by genetic algorithms | |
| CN114004081A (en) | Affine algorithm-based power distribution network load supply capacity calculation method | |
| CN103972886B (en) | A kind of active distribution network harmonic trend analytical method | |
| Wang et al. | Reliability evaluation of power-generating systems including time-dependent sources based on binary particle swarm optimization | |
| Xu et al. | A new approach for fast reliability evaluation of composite power system considering wind farm | |
| Göncü et al. | A new cellular automata model with memory and its fpga implementation | |
| Almutairi et al. | Inclusion of wind generation modeling into the conventional generation adequacy evaluation | |
| Jiang et al. | The spatial statistics of self-organized in power system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |