CN110991740B - Power grid planning method and system based on operation simulation and intelligent agent technology - Google Patents
Power grid planning method and system based on operation simulation and intelligent agent technology Download PDFInfo
- Publication number
- CN110991740B CN110991740B CN201911221284.6A CN201911221284A CN110991740B CN 110991740 B CN110991740 B CN 110991740B CN 201911221284 A CN201911221284 A CN 201911221284A CN 110991740 B CN110991740 B CN 110991740B
- Authority
- CN
- China
- Prior art keywords
- agent
- planning
- substation
- site selection
- selection
- 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
- 238000004088 simulation Methods 0.000 title claims abstract description 59
- 238000000034 method Methods 0.000 title claims abstract description 33
- 238000005516 engineering process Methods 0.000 title claims abstract description 23
- 238000011156 evaluation Methods 0.000 claims abstract description 21
- 238000012216 screening Methods 0.000 claims abstract description 21
- 238000010276 construction Methods 0.000 claims abstract description 7
- 238000010586 diagram Methods 0.000 claims description 13
- 238000012545 processing Methods 0.000 claims description 12
- 238000004364 calculation method Methods 0.000 claims description 3
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 238000004891 communication Methods 0.000 description 2
- 230000005611 electricity Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000013210 evaluation model Methods 0.000 description 1
- 238000000556 factor analysis Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification 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
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G06Q10/043—Optimisation of two dimensional placement, e.g. cutting of clothes or wood
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
-
- 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
Abstract
The invention provides a power grid planning method and system based on operation simulation and intelligent Agent technology, comprising the steps of calculating the number N of substation site selection agents based on planning area load prediction Agent Initializing each substation site selection Agent; analyzing according to the regional prediction load density distribution and geographic factors, and establishing an Agent information base to form basic information content of transformer substation site selection; according to the basic information content of the site selection of the transformer substation, each site selection Agent of the transformer substation is respectively embedded into the existing network frame to perform operation simulation, and simulation system information is output; and (3) carrying out reliability evaluation on the simulation system, and screening the substation site selection Agent according to an evaluation result. The invention can perfect the layout of the transformer substation, realize the reliable construction of the power grid and improve the efficiency and the scientificity of the planning work of the power grid.
Description
Technical Field
The invention relates to the technical field of power grid planning, in particular to a power grid planning method and system based on operation simulation and intelligent agent technology.
Background
The transformer substation site selection and grid planning are important links of intelligent power grid planning, have great influence on power grid structure, power supply reliability and operation economy, and the scientific and reasonable transformer substation site selection and grid planning not only can reduce electric energy loss, but also can save construction investment cost. Because many factors involved in site selection and grid planning of the transformer substation are complex and huge, the method belongs to a complex system problem, and in the prior art, the traditional method is difficult to analyze and solve factors, has low efficiency and is unfavorable for the development of power grid planning work.
Disclosure of Invention
The invention aims to provide a power grid planning method based on operation simulation and intelligent agent technology, which at least solves the problem that in the prior art, factor analysis and solution are difficult when a traditional method is used for substation site selection and grid planning.
The first aspect of the invention provides a power grid planning method based on operation simulation and agent technology, which comprises the following steps:
calculating the number of substation site selection agents based on the planning area load prediction, and initializing each substation site selection Agent;
analyzing according to the regional prediction load density distribution and geographic factors, and establishing an Agent information base to form basic information content of transformer substation site selection;
according to the basic information content of the site selection of the transformer substation, each site selection Agent of the transformer substation is respectively embedded into the existing network frame to perform operation simulation, and simulation system information is output;
and (3) carrying out reliability evaluation on the simulation system, and screening the substation site selection Agent according to an evaluation result.
Further, the number N of the substation site selection agents Agent Obtained by calculation of the formula (1),
in the formula (1), load is a regional Load predicted value, beta is a capacity ratio, S is the total capacity of the planned single-seat substation, and up () represents an upward rounding.
Further, initializing the location Agent of each substation further includes: after the number of substation site-selection agents is determined, planning parameters including transformer capacity and average power supply radius are set for each substation site-selection Agent.
Further, the analyzing according to the area forecast load density distribution and the geographic factors, and establishing an Agent information base specifically includes:
analyzing and processing according to the regional prediction load density distribution, geographical factors and planning parameters of each substation site selection Agent to form a plurality of primary site selection schemes, wherein each primary site selection scheme corresponds to one substation site selection Agent;
and collecting point distribution planning information from primary point distribution schemes corresponding to the substation site selection agents respectively, and constructing an Agent information base, wherein the point distribution planning information comprises electrical information and geographic information.
Further, the analyzing and processing are performed according to the predicted load density distribution, the geographical factors and the planning parameters of the site selection Agent of each transformer substation to form a plurality of initially selected distribution point schemes, which specifically comprises:
generating a predicted load density distribution diagram according to a planning scheme, and determining a load center;
performing site primary selection according to the site selection Agent planning parameters of the transformer substation and the positions of each load center;
and further screening the primary station addresses according to geographic factors to obtain a plurality of substation planning distribution points to form a primary station distribution point scheme.
A second aspect of the present invention provides a power grid planning system based on operational simulation and agent technology, comprising:
the Agent initializing module is used for calculating the number of the substation site selection agents based on the planning area load prediction;
the Agent information base module is used for analyzing according to the regional prediction load density distribution and the geographic factors, establishing an Agent information base and forming basic information content of transformer substation site selection;
the planning simulation module is used for embedding each substation site selection Agent into the existing network frame respectively to perform operation simulation according to the basic information content of the substation site selection, and outputting simulation system information;
and the evaluation screening module is used for evaluating the reliability of the simulation system and screening the substation site selection Agent according to the evaluation result.
Further, the Agent initializing module calculates the number of the substation site selection agents specifically by the formula (1),
in the formula (1), load is a regional Load predicted value, beta is a capacity ratio, S is the total capacity of the planned single-seat substation, and up () represents an upward rounding.
Further, the Agent initializing module further comprises a parameter setting sub-module, wherein the parameter setting sub-module is used for setting planning parameters for each substation site-selection Agent after the number of the substation site-selection agents is determined, and the planning parameters comprise transformer capacity and average power supply radius.
Further, the Agent information base module includes:
the distribution point primary selection sub-module is used for analyzing and processing according to the regional prediction load density distribution, the geographic factors and the planning parameters of each substation site selection Agent to form a plurality of primary selection distribution point schemes, and each primary selection distribution point scheme corresponds to one substation site selection Agent;
the construction sub-module is used for respectively collecting point distribution planning information from primary point distribution schemes corresponding to the substation site selection agents and constructing an Agent information base, and the point distribution planning information comprises electric information and geographic information.
Further, the point setting initial selection sub-module includes:
the load center determining module is used for generating a predicted load density distribution schematic diagram according to the planning scheme and determining a load center;
the station address primary selection module is used for conducting station address primary selection according to the substation site selection Agent planning parameters and the positions of the load centers;
and the station address screening module is used for further screening the primary selected station addresses according to geographic factors to obtain a plurality of transformer substation planning distribution points so as to form a primary selected distribution point scheme.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a power grid planning method and a system based on operation simulation and intelligent Agent technology, which are characterized in that the final state of each Agent is determined according to the operation simulation result through initialization of a substation site selection Agent, construction of an Agent information base and multi-Agent operation simulation, and the reliability evaluation and screening are carried out according to the operation simulation result, so that a final substation site selection and grid planning scheme is obtained.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only preferred embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic overall flow diagram of a power grid planning method based on operation simulation and agent technology according to an embodiment of the present invention.
Fig. 2 is a schematic overall flow chart of a power grid planning method based on operation simulation and agent technology according to another embodiment of the present invention.
Fig. 3 is a schematic diagram of the overall structure of a power grid planning system based on operation simulation and intelligent agent technology according to another embodiment of the present invention.
Detailed Description
The principles and features of the present invention are described below with reference to the drawings, the illustrated embodiments are provided for the purpose of illustrating the invention and are not to be construed as limiting the scope of the invention.
Fig. 1 is a schematic overall flow diagram of a power grid planning method based on operation simulation and intelligent agent technology according to an embodiment of the present invention.
As shown in fig. 1, the present embodiment provides a power grid planning method based on operation simulation and intelligent agent technology, which includes the following steps:
s11, calculating the number N of substation site selection agents based on planning area load prediction Agent And initializing the site selection agents of each transformer substation.
The planning area is a target area for substation site selection and grid planning, and the planning area load prediction is to predict future loads of the planning area. On the basis of predicting the load of the planning area, the number N of substation location agents Agent Obtained by calculation of the formula (1),
in the formula (1), load represents a regional Load prediction value, which may be obtained by a spatial power Load prediction method, or may be obtained by other known Load prediction methods known to those skilled in the art; beta represents the capacity-to-load ratio; s is the total capacity of a planned single substation, and the total capacity is the design capacity of the substation; up () represents rounding up.
In addition, after the number of the substation site selection agents is determined, planning parameters are set for each substation site selection Agent, and initialization of the substation site selection agents is completed. The planning parameters are used to define relevant parameters of the substation plan, which in some embodiments include, but are not limited to, transformer capacity and average power supply radius.
And S12, analyzing according to the regional forecast load density distribution and the geographic factors, and establishing an Agent information base to form basic information content of transformer substation site selection.
Analyzing according to the area forecast load density distribution and geographic factors, and establishing an Agent information base, wherein the method specifically comprises the following steps:
analyzing and processing according to the regional prediction load density distribution, geographical factors and planning parameters of each substation site selection Agent to form a plurality of primary site selection schemes, wherein each primary site selection scheme corresponds to one substation site selection Agent;
collecting point distribution planning information from primary point distribution schemes corresponding to each substation site selection Agent respectively, and constructing an Agent information base, wherein the point distribution planning information comprises electrical information and geographic information, and the electrical information comprises but is not limited to information such as a line in and out of a substation, substation capacity and the like; the geographic information includes, but is not limited to, information of electricity load conditions, geological factors and the like.
S13, according to the basic information content of the substation site selection, each substation site selection Agent is respectively embedded into the existing network frame to perform operation simulation, and simulation system information is output.
After the basic information content of the site selection of the transformer substation is formed through the steps, based on the corresponding basic information content of the site selection of the transformer substation, each site selection Agent of the transformer substation is respectively embedded into the existing grid to perform operation simulation, and simulation system information is output, wherein the simulation system information comprises, but is not limited to, information of electric power and electricity balance, reliability, electric power reserve rate and the like of a corresponding simulation system.
S14, reliability evaluation is conducted on the simulation system, and substation site selection agents are screened according to evaluation results.
The reliability evaluation of the simulated system may be performed by using a time sequence reliability evaluation model, or may be performed by using other methods. In some embodiments, the reliability evaluation may be to calculate the loss of power failure of the LOLP/LOLE and EENS of the simulated system, analyze whether the analog quantity meets the balance of electric power and electric quantity according to the result of the operation simulation, and analyze whether the LOLP/LOLE and EENS are in a reasonable range, and evaluate the rationality and reliability of the site selection scheme corresponding to each substation site selection Agent by analyzing the above. And after the reliability evaluation of the substation site selection agents is finished, the substation site selection Agent with the highest reliability is screened out according to the evaluation result.
According to the power grid planning method based on the operation simulation and the intelligent Agent technology, the final state of each substation site selection Agent is determined according to the operation simulation result by initializing the substation site selection Agent, constructing an Agent information base and performing operation simulation on multiple substation site selection agents, and the final substation site selection and grid planning scheme is obtained by performing reliability evaluation and screening on the operation simulation result.
Fig. 2 is a schematic overall flow chart of a power grid planning method based on operation simulation and agent technology according to another embodiment of the present invention.
On the basis of the foregoing embodiment, as shown in fig. 2, the analyzing and processing are performed according to the predicted load density distribution, the geographic factors and the planning parameters of the location agents of each substation, so as to form a plurality of initially selected distribution point schemes, which specifically includes:
s121, generating a predicted load density distribution diagram according to a planning scheme, and determining a load center.
The load density distribution diagram is a diagram for generating a load density distribution obtained through future load prediction on an administrative division diagram of a planning area, the load center is determined through the load density, for example, a region with large load density on the load density distribution diagram is searched through image recognition and the like, and a plurality of load centers can be used as the load center.
S122, station address primary selection is carried out according to the substation address Agent planning parameters and the load center positions.
Based on the substation site selection Agent planning parameters and the positions of the load centers determined in the previous step, the primary site selection is performed by judging whether the average power supply radius of the substation can meet the distance to the load centers when the substation is positioned at different positions of the planning area, and a plurality of primary site selection sites can be obtained in the final step.
And S123, further screening the primary selection sites according to geographic factors to obtain a plurality of substation planning distribution points to form a primary selection distribution point scheme.
The geographical factors include, but are not limited to, whether the geographical factors are natural disaster frequent zones, whether the geographical factors relate to large-area relocation, whether the cultivated land is occupied or not and the like, the primary selected station addresses are further screened according to the factors, and finally a plurality of transformer substation planning distribution points with proper distances from each load center and reasonable geographical positions are obtained to form a primary selected distribution point scheme.
Based on the same inventive concept, fig. 3 shows a power grid planning system based on operation simulation and intelligent agent technology according to another embodiment of the present invention.
As shown in fig. 3, the system comprises an Agent initializing module 1, an Agent information base module 2, a planning simulation module 3 and an evaluation screening module 4.
The Agent initializing module 1 is used for calculating the number of substation site selection agents based on planning area load prediction.
The Agent information base module 2 is used for analyzing according to the regional forecast load density distribution and the geographic factors, establishing an Agent information base and forming basic information content of transformer substation site selection;
the planning simulation module 3 is used for respectively embedding each substation site selection Agent into the existing network frame to perform operation simulation according to the basic information content of the substation site selection, and outputting simulation system information;
and the evaluation screening module 4 is used for evaluating the reliability of the simulation system and screening the substation site selection Agent according to the evaluation result.
Optionally, the Agent initializing module 1 calculates the number of substation site-selection agents according to the formula (1),
in the formula (1), load is a regional Load predicted value, beta is a capacity ratio, S is the total capacity of the planned single-seat substation, and up () represents an upward rounding.
Optionally, the Agent initializing module 1 further includes a parameter setting sub-module 11, where the parameter setting sub-module 11 is configured to set a planning parameter for each substation site-selection Agent after determining the number of substation site-selection agents, where the planning parameter includes a transformer capacity and an average power supply radius.
Optionally, the Agent information base module 2 further includes a point setting initial selection sub-module 21 and a construction sub-module 22,
the distribution point primary selection sub-module 21 is configured to perform analysis processing according to the area prediction load density distribution, the geographic factors and the planning parameters of each substation site selection Agent, so as to form a plurality of primary selection distribution point schemes, where each primary selection distribution point scheme corresponds to one substation site selection Agent;
the construction submodule 22 collects point distribution planning information from primary point distribution schemes corresponding to the substation site selection agents respectively, and constructs an Agent information base, wherein the point distribution planning information comprises electrical information and geographic information.
Optionally, the point placement reselection sub-module 21 further includes a load center determining module 211, a site reselection module 212, and a site screening module 213.
The load center determining module 211 is configured to generate a predicted load density distribution schematic diagram according to a planning scheme, and determine a load center.
The site primary selection module 212 is configured to perform site primary selection according to the substation site selection Agent planning parameters and each load center position.
The site screening module 213 is configured to further screen the primary selected sites according to geographic factors, obtain a plurality of substation planning distribution points, and form a primary selected distribution point scheme.
The system is used for executing the foregoing embodiments, and the implementation principle and technical effects may refer to the foregoing method embodiments, which are not described herein again.
The above modules may be one or more integrated circuits configured to implement the above methods, for example: one or more specific integrated circuits, or one or more microprocessors, or one or more field programmable gate arrays, etc. For another example, when a module above is implemented in the form of a processing element scheduler code, the processing element may be a general purpose processor, such as a central processing unit or other processor that may invoke the program code. For another example, the modules may be integrated together and implemented in a system-on-chip form.
In the several embodiments provided by the present invention, it should be understood that the disclosed systems and methods may be implemented in other ways. For example, the system embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical functional division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and scope of the invention are intended to be included within the scope of the invention.
Claims (6)
1. A power grid planning method based on operation simulation and agent technology, characterized in that the method comprises the following steps:
based on planning area load prediction, the number N of substation site selection agents is calculated Agent Initializing each substation site selection Agent;
analyzing according to the regional prediction load density distribution and geographic factors, and establishing an Agent information base to form basic information content of transformer substation site selection;
according to the basic information content of the site selection of the transformer substation, each site selection Agent of the transformer substation is respectively embedded into the existing network frame to perform operation simulation, and simulation system information is output;
performing reliability evaluation on the simulation system, and screening substation site selection agents according to evaluation results;
number N of substation site selection agents Agent Obtained by calculation of the formula (1),
in the formula (1), load is a regional Load predicted value, beta is a capacity ratio, S is the total capacity of a planned single-seat transformer substation, and up () represents rounding up;
initializing each substation site Agent further includes: after the number of the substation site-selection agents is determined, setting planning parameters for each substation site-selection Agent, wherein the planning parameters comprise transformer capacity and average power supply radius;
analyzing according to the area forecast load density distribution and geographic factors, and establishing an Agent information base, wherein the method specifically comprises the following steps:
analyzing and processing according to the regional prediction load density distribution, geographical factors and planning parameters of each substation site selection Agent to form a plurality of primary site selection schemes, wherein each primary site selection scheme corresponds to one substation site selection Agent;
collecting point distribution planning information from primary point distribution schemes corresponding to each substation site selection Agent respectively, and constructing an Agent information base, wherein the point distribution planning information comprises electrical information and geographic information;
analyzing and processing the load density distribution, the geographic factors and the planning parameters of each substation site selection Agent according to the regional prediction to form a plurality of primary site selection schemes, wherein the method specifically comprises the following steps:
generating a predicted load density distribution diagram according to a planning scheme, and determining a load center;
performing site primary selection according to the site selection Agent planning parameters of the transformer substation and the positions of each load center;
and further screening the primary station addresses according to geographic factors to obtain a plurality of substation planning distribution points to form a primary station distribution point scheme.
2. A method of operating simulation and smart technology based grid planning for implementing the method as claimed in claim 1, wherein the operating simulation and smart technology based grid planning system comprises:
the Agent initializing module is used for calculating the number of the substation site selection agents based on the planning area load prediction;
the Agent information base module is used for analyzing according to the regional prediction load density distribution and the geographic factors, establishing an Agent information base and forming basic information content of transformer substation site selection;
the planning simulation module is used for embedding each substation site selection Agent into the existing network frame respectively to perform operation simulation according to the basic information content of the substation site selection, and outputting simulation system information;
and the evaluation screening module is used for evaluating the reliability of the simulation system and screening the substation site selection Agent according to the evaluation result.
3. The power grid planning method based on operation simulation and Agent technology according to claim 2, wherein the Agent initialization module calculates the number of substation site-selection agents specifically by formula (1),
in the formula (1), load is a regional Load predicted value, beta is a capacity ratio, S is the total capacity of the planned single-seat substation, and up () represents an upward rounding.
4. The power grid planning method based on operation simulation and Agent technology according to claim 2, wherein the Agent initializing module further comprises a parameter setting sub-module, the parameter setting sub-module is used for setting planning parameters for each substation site Agent after determining the number of the substation site agents, and the planning parameters comprise transformer capacity and average power supply radius.
5. The power grid planning method based on operation simulation and Agent technology according to claim 4, wherein the Agent information base module comprises:
the distribution point primary selection sub-module is used for analyzing and processing according to the regional prediction load density distribution, the geographic factors and the planning parameters of each substation site selection Agent to form a plurality of primary selection distribution point schemes, and each primary selection distribution point scheme corresponds to one substation site selection Agent;
the construction sub-module is used for respectively collecting point distribution planning information from primary point distribution schemes corresponding to the substation site selection agents and constructing an Agent information base, and the point distribution planning information comprises electric information and geographic information.
6. A method of grid planning based on operational simulation and agent technology as defined in claim 5, wherein the setpoint-first-selection sub-module comprises:
the load center determining module is used for generating a predicted load density distribution schematic diagram according to the planning scheme and determining a load center;
the station address primary selection module is used for conducting station address primary selection according to the substation site selection Agent planning parameters and the positions of the load centers;
and the station address screening module is used for further screening the primary selected station addresses according to geographic factors to obtain a plurality of transformer substation planning distribution points so as to form a primary selected distribution point scheme.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201911221284.6A CN110991740B (en) | 2019-12-03 | 2019-12-03 | Power grid planning method and system based on operation simulation and intelligent agent technology |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201911221284.6A CN110991740B (en) | 2019-12-03 | 2019-12-03 | Power grid planning method and system based on operation simulation and intelligent agent technology |
Publications (2)
Publication Number | Publication Date |
---|---|
CN110991740A CN110991740A (en) | 2020-04-10 |
CN110991740B true CN110991740B (en) | 2023-12-15 |
Family
ID=70089739
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201911221284.6A Active CN110991740B (en) | 2019-12-03 | 2019-12-03 | Power grid planning method and system based on operation simulation and intelligent agent technology |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN110991740B (en) |
Families Citing this family (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114137331B (en) * | 2021-10-25 | 2023-09-08 | 四川蓉信开工程设计有限公司 | BIM-based power substation design method |
Citations (26)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2004059446A2 (en) * | 2002-12-20 | 2004-07-15 | Union Switch & Signal, Inc. | Dynamic optimizing traffic planning method and system |
JP2005011154A (en) * | 2003-06-20 | 2005-01-13 | Nec Informatec Systems Ltd | System and method for planning plan, and its program |
JP2007264849A (en) * | 2006-03-27 | 2007-10-11 | Meiji Univ | Distribution system extension plan selection method and distribution system extension plan selection program |
CN102508995A (en) * | 2011-09-26 | 2012-06-20 | 河南理工大学 | Coal mine accident simulating method and system based on multi-intelligent agent |
CN102521443A (en) * | 2011-12-06 | 2012-06-27 | 河海大学 | Logistics node facility layout optimization method based on computer vision |
CN102663512A (en) * | 2012-03-07 | 2012-09-12 | 同济大学 | Simulation prediction method for dynamic evolution simulation of urban greenbelt |
CN103049799A (en) * | 2012-12-10 | 2013-04-17 | 河海大学 | Multi-objective-optimization-based power grid planning and designing method |
CN103077483A (en) * | 2013-02-07 | 2013-05-01 | 重庆市电力公司綦南供电局 | Power grid planning method based on comprehensive boundary conditions |
CN103336876A (en) * | 2013-07-23 | 2013-10-02 | 国家电网公司 | Open loop distribution network power flow simulation method based on multi-agents |
CN103617570A (en) * | 2013-12-10 | 2014-03-05 | 国家电网公司 | Geographical factor-involved automatic site selection method for transformer substation |
CN104317637A (en) * | 2014-10-16 | 2015-01-28 | 安徽理工大学 | Multi-agent-based virtual miner safety behavior modeling and emergency simulation system |
CN104504183A (en) * | 2014-12-10 | 2015-04-08 | 广州供电局有限公司 | Power distribution network intelligent planning system based on automatic optimization |
CN104680340A (en) * | 2015-03-30 | 2015-06-03 | 国家电网公司 | Distribution network planning method and system |
CN104680427A (en) * | 2015-03-06 | 2015-06-03 | 国家电网公司 | Planning system for comprehensive optimization of regional power distribution network |
CN104934968A (en) * | 2015-06-04 | 2015-09-23 | 国家电网公司 | Multi-agent based distribution network disaster responding recovery coordinate control method and multi-agent based distribution network disaster responding recovery coordinate control device |
CN105046354A (en) * | 2015-07-09 | 2015-11-11 | 国网四川省电力公司经济技术研究院 | Multi-agent power distribution network planning scene simulation generation method and system |
CN105787959A (en) * | 2015-11-16 | 2016-07-20 | 浙江工业大学 | Method for multi-agent network object tracking based on improved adaptive particle filtering |
EP3312971A1 (en) * | 2013-02-19 | 2018-04-25 | Astrolink International LLC c/o Lockheed Martin Corporation | Methods for discovering, partitioning, organizing, and administering communication devices in a transformer area network |
CN108092267A (en) * | 2018-01-09 | 2018-05-29 | 国网河南省电力公司经济技术研究院 | A kind of power distribution network access planning system and method based on intelligent body |
CN108400593A (en) * | 2018-03-16 | 2018-08-14 | 国家电网公司 | Active distribution network electrical model method for building up based on layering multi-agent technology |
CN108549977A (en) * | 2018-03-29 | 2018-09-18 | 华南理工大学 | The flexible production dynamic scheduling system towards order based on multi-Agent |
CN108683187A (en) * | 2018-06-12 | 2018-10-19 | 国网河南省电力公司濮阳供电公司 | A kind of EMS grid monitoring systems based on big data |
CN108876103A (en) * | 2018-05-07 | 2018-11-23 | 国网天津市电力公司 | District power network planning scheme comparison method based on voltage class sequence measures of effectiveness |
CN109658510A (en) * | 2018-12-10 | 2019-04-19 | 中国电建集团江西省电力设计院有限公司 | The method, apparatus and server of substation site selection |
CN110210683A (en) * | 2019-06-12 | 2019-09-06 | 海南电网有限责任公司 | A kind of electric car electrically-charging equipment site selecting method |
CN110490787A (en) * | 2019-07-25 | 2019-11-22 | 沈振江 | A kind of method for building up of the multiple agent model of residential location choice |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20100138353A1 (en) * | 2008-08-27 | 2010-06-03 | Avinash Srivastava | Computer implemented system and method for providing an optimized sustainable land use plan |
-
2019
- 2019-12-03 CN CN201911221284.6A patent/CN110991740B/en active Active
Patent Citations (27)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2004059446A2 (en) * | 2002-12-20 | 2004-07-15 | Union Switch & Signal, Inc. | Dynamic optimizing traffic planning method and system |
EP1573578A2 (en) * | 2002-12-20 | 2005-09-14 | UNION SWITCH & SIGNAL Inc. | Dynamic optimizing traffic planning method and system |
JP2005011154A (en) * | 2003-06-20 | 2005-01-13 | Nec Informatec Systems Ltd | System and method for planning plan, and its program |
JP2007264849A (en) * | 2006-03-27 | 2007-10-11 | Meiji Univ | Distribution system extension plan selection method and distribution system extension plan selection program |
CN102508995A (en) * | 2011-09-26 | 2012-06-20 | 河南理工大学 | Coal mine accident simulating method and system based on multi-intelligent agent |
CN102521443A (en) * | 2011-12-06 | 2012-06-27 | 河海大学 | Logistics node facility layout optimization method based on computer vision |
CN102663512A (en) * | 2012-03-07 | 2012-09-12 | 同济大学 | Simulation prediction method for dynamic evolution simulation of urban greenbelt |
CN103049799A (en) * | 2012-12-10 | 2013-04-17 | 河海大学 | Multi-objective-optimization-based power grid planning and designing method |
CN103077483A (en) * | 2013-02-07 | 2013-05-01 | 重庆市电力公司綦南供电局 | Power grid planning method based on comprehensive boundary conditions |
EP3312971A1 (en) * | 2013-02-19 | 2018-04-25 | Astrolink International LLC c/o Lockheed Martin Corporation | Methods for discovering, partitioning, organizing, and administering communication devices in a transformer area network |
CN103336876A (en) * | 2013-07-23 | 2013-10-02 | 国家电网公司 | Open loop distribution network power flow simulation method based on multi-agents |
CN103617570A (en) * | 2013-12-10 | 2014-03-05 | 国家电网公司 | Geographical factor-involved automatic site selection method for transformer substation |
CN104317637A (en) * | 2014-10-16 | 2015-01-28 | 安徽理工大学 | Multi-agent-based virtual miner safety behavior modeling and emergency simulation system |
CN104504183A (en) * | 2014-12-10 | 2015-04-08 | 广州供电局有限公司 | Power distribution network intelligent planning system based on automatic optimization |
CN104680427A (en) * | 2015-03-06 | 2015-06-03 | 国家电网公司 | Planning system for comprehensive optimization of regional power distribution network |
CN104680340A (en) * | 2015-03-30 | 2015-06-03 | 国家电网公司 | Distribution network planning method and system |
CN104934968A (en) * | 2015-06-04 | 2015-09-23 | 国家电网公司 | Multi-agent based distribution network disaster responding recovery coordinate control method and multi-agent based distribution network disaster responding recovery coordinate control device |
CN105046354A (en) * | 2015-07-09 | 2015-11-11 | 国网四川省电力公司经济技术研究院 | Multi-agent power distribution network planning scene simulation generation method and system |
CN105787959A (en) * | 2015-11-16 | 2016-07-20 | 浙江工业大学 | Method for multi-agent network object tracking based on improved adaptive particle filtering |
CN108092267A (en) * | 2018-01-09 | 2018-05-29 | 国网河南省电力公司经济技术研究院 | A kind of power distribution network access planning system and method based on intelligent body |
CN108400593A (en) * | 2018-03-16 | 2018-08-14 | 国家电网公司 | Active distribution network electrical model method for building up based on layering multi-agent technology |
CN108549977A (en) * | 2018-03-29 | 2018-09-18 | 华南理工大学 | The flexible production dynamic scheduling system towards order based on multi-Agent |
CN108876103A (en) * | 2018-05-07 | 2018-11-23 | 国网天津市电力公司 | District power network planning scheme comparison method based on voltage class sequence measures of effectiveness |
CN108683187A (en) * | 2018-06-12 | 2018-10-19 | 国网河南省电力公司濮阳供电公司 | A kind of EMS grid monitoring systems based on big data |
CN109658510A (en) * | 2018-12-10 | 2019-04-19 | 中国电建集团江西省电力设计院有限公司 | The method, apparatus and server of substation site selection |
CN110210683A (en) * | 2019-06-12 | 2019-09-06 | 海南电网有限责任公司 | A kind of electric car electrically-charging equipment site selecting method |
CN110490787A (en) * | 2019-07-25 | 2019-11-22 | 沈振江 | A kind of method for building up of the multiple agent model of residential location choice |
Non-Patent Citations (4)
Title |
---|
刘声田 ; 翟玉庆 ; .一个多Agent结构的个性化信息搜索系统设计.山东广播电视大学学报.2009,(02),全文. * |
基于多Agent的能量管理系统支持平台;赵传霖;吴文传;张伯明;;电力系统自动化(13);全文 * |
基于改进多组织粒子群体优化算法的配电网络变电站选址定容;刘自发;张建华;;中国电机工程学报(01);全文 * |
董思远 ; 符茜茜 ; .园区电力专项规划思路及案例分析.科技与创新.2017,(13),全文. * |
Also Published As
Publication number | Publication date |
---|---|
CN110991740A (en) | 2020-04-10 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN102722764B (en) | Integration network optimization computer-aided decision support System | |
Billinton et al. | A novel method for incorporating weather effects in composite system adequacy evaluation | |
CN110298553A (en) | A kind of National land space planing method, system and equipment based on GIS | |
CN111143764B (en) | Distribution network reliability assessment method with complex structure based on diffusion theory | |
CN103996147A (en) | Comprehensive evaluation method for power distribution network | |
Ang et al. | Multi-objective optimization of hybrid renewable energy systems with urban building energy modeling for a prototypical coastal community | |
CN110119888A (en) | A kind of active gridding planing method based on distributed generation resource access | |
CN111859621A (en) | Monte Carlo method based grid structure reliability collaborative evaluation method for main network and distribution network | |
CN103150605B (en) | Power grid planning auxiliary system | |
CN111465025B (en) | Tourism city 5G network networking method based on novel capacity prediction model | |
CN110991740B (en) | Power grid planning method and system based on operation simulation and intelligent agent technology | |
Syranidou et al. | Development of an open framework for a qualitative and quantitative comparison of power system and electricity grid models for Europe | |
CN114184881A (en) | Fault event positioning method based on topological model tracking analysis | |
CN105225162A (en) | A kind of harmonizing ways method of distribution system operational efficiency | |
CN103020290B (en) | Electric network information method of calibration and system | |
CN103207953B (en) | A kind of determination method planning to build substation site selection line investment contour and application mode | |
KR20220083353A (en) | Power system stability analysis system and method considering renewable energy variablity | |
CN108416531A (en) | A kind of automatic evaluation method of distribution automation planning design effect | |
CN115879652B (en) | Hierarchical collaborative planning method and device for energy network, electronic equipment and storage medium | |
Zhang et al. | The application of hybrid genetic particle swarm optimization algorithm in the distribution network reconfigurations multi-objective optimization | |
CN104484546B (en) | A kind of automatic trend of Electric Power Network Planning project checks the generation method of file | |
Balijepalli et al. | A holistic approach for transmission system expansion planning studies: An Indian experience | |
CN110310048A (en) | A kind of distribution planning overall process appraisal procedure and device | |
CN116307110A (en) | Distributed roof photovoltaic power generation aggregation management method and system | |
CN115983478A (en) | Distributed photovoltaic power generation power prediction analysis method, system, terminal and medium |
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 | ||
GR01 | Patent grant | ||
GR01 | Patent grant |