CN116823044A - Construction decision method, device and equipment of transformer substation and storage medium - Google Patents
Construction decision method, device and equipment of transformer substation and storage medium Download PDFInfo
- Publication number
- CN116823044A CN116823044A CN202310760410.5A CN202310760410A CN116823044A CN 116823044 A CN116823044 A CN 116823044A CN 202310760410 A CN202310760410 A CN 202310760410A CN 116823044 A CN116823044 A CN 116823044A
- Authority
- CN
- China
- Prior art keywords
- construction
- transformer substation
- substation
- target
- determining
- 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
- 238000010276 construction Methods 0.000 title claims abstract description 174
- 238000000034 method Methods 0.000 title claims abstract description 64
- 238000003860 storage Methods 0.000 title claims abstract description 21
- 238000011156 evaluation Methods 0.000 claims abstract description 62
- 238000005457 optimization Methods 0.000 claims abstract description 52
- 230000006870 function Effects 0.000 claims description 88
- 238000004590 computer program Methods 0.000 claims description 15
- 230000009466 transformation Effects 0.000 claims description 10
- 239000002245 particle Substances 0.000 description 12
- 238000004891 communication Methods 0.000 description 8
- 238000012545 processing Methods 0.000 description 8
- 230000008901 benefit Effects 0.000 description 5
- 238000010586 diagram Methods 0.000 description 5
- 230000008569 process Effects 0.000 description 4
- 238000011161 development Methods 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 230000003044 adaptive effect Effects 0.000 description 2
- 230000000295 complement effect Effects 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000010606 normalization Methods 0.000 description 2
- 238000013439 planning Methods 0.000 description 2
- 230000004044 response Effects 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 230000002776 aggregation Effects 0.000 description 1
- 238000004220 aggregation Methods 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 238000013475 authorization Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 230000001149 cognitive effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 230000007717 exclusion Effects 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 238000013468 resource allocation Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 230000001953 sensory effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/007—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources
- H02J3/0075—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources for providing alternative feeding paths between load and source according to economic or energy efficiency considerations, e.g. economic dispatch
-
- 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
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- 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—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
-
- 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)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Health & Medical Sciences (AREA)
- Physics & Mathematics (AREA)
- Entrepreneurship & Innovation (AREA)
- Theoretical Computer Science (AREA)
- Development Economics (AREA)
- Marketing (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Educational Administration (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Game Theory and Decision Science (AREA)
- Power Engineering (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a construction decision method, a device, equipment and a storage medium of a transformer substation, wherein the method comprises the following steps: acquiring basic information of an item to be built; the basic information of the project to be built comprises: project requirement information and a plurality of transformer substation information to be built; constructing a construction decision optimization objective function of the transformer substation according to the basic information; determining a target constraint condition according to the basic information; optimizing and iterating a construction decision optimization objective function of the transformer substation based on the objective constraint condition to obtain construction schemes of a plurality of candidate transformer substations; the construction scheme of the transformer substation comprises at least one target transformer substation and a plurality of evaluation indexes; and determining the construction scheme of a target transformer substation from the construction schemes of the plurality of candidate transformer substations. By using the method, the construction scheme can be analyzed and evaluated from multiple angles of cost, reliability and social cost, and the optimal construction project of the transformer substation can be determined by adopting a scientific method.
Description
Technical Field
The embodiment of the invention relates to the technical field of power system planning, in particular to a construction decision method, a device, equipment and a storage medium of a transformer substation.
Background
The continuous increase of the power ratio in the terminal energy consumption makes the reasonable planning of the power grid construction continuously show the effect of optimizing the energy resource allocation. The power grid construction project has the characteristics of dense funds, long investment and gain period and more participation subjects, and the proportion of the power grid construction investment in the power construction investment is increased year by year, so that the power grid construction investment decision level plays a role in improving the production operation and economic benefit of power grid enterprises.
With the development of new power system construction and power transmission and distribution price reform, the power grid investment decision to meet accurate investment requirements becomes more and more important. The traditional investment decision method is difficult to meet the requirements of high-quality development and accurate investment of power grid enterprises, so that the method is capable of analyzing and evaluating the power grid enterprises from an economic perspective in the face of problems existing in the development of the power grid enterprises and huge investment construction required, and has important value in researching the optimization of the investment decision of the power grid suitable for the current environment by adopting a scientific method.
Disclosure of Invention
The embodiment of the invention provides a construction decision method, a device, equipment and a storage medium of a transformer substation, which can analyze and evaluate a construction scheme from multiple angles of cost, reliability and social cost, and adopts a scientific method to determine the optimal construction project of the transformer substation.
In a first aspect, an embodiment of the present invention provides a construction decision method for a substation, where the method includes:
acquiring basic information of an item to be built; the basic information of the project to be built comprises: project requirement information and a plurality of transformer substation information to be built;
constructing a construction decision optimization objective function of the transformer substation according to the basic information;
determining a target constraint condition according to the basic information;
optimizing and iterating a construction decision optimization objective function of the transformer substation based on the objective constraint condition to obtain construction schemes of a plurality of candidate transformer substations; the construction scheme of the transformer substation comprises at least one target transformer substation and a plurality of evaluation indexes;
and determining the construction scheme of a target transformer substation from the construction schemes of the plurality of candidate transformer substations.
In a second aspect, an embodiment of the present invention further provides a construction decision device of a substation, where the device includes:
the data acquisition module is used for acquiring basic information of the item to be built; the basic information of the project to be built comprises: project requirement information and a plurality of transformer substation information to be built;
the objective function construction module is used for constructing a construction decision optimization objective function of the transformer substation according to the basic information;
the constraint condition determining module is used for determining a target constraint condition according to the basic information;
the optimization iteration module is used for carrying out optimization iteration on the construction decision optimization objective function of the transformer substation based on the objective constraint condition to obtain construction schemes of a plurality of candidate transformer substations; the construction scheme of the transformer substation comprises at least one target transformer substation and a plurality of evaluation indexes;
and the construction scheme evaluation module is used for determining the construction scheme of a target transformer substation from the construction schemes of the plurality of candidate transformer substations.
In a third aspect, embodiments of the present disclosure further provide an electronic device, including:
one or more processors;
storage means for storing one or more programs,
and when the one or more programs are executed by the one or more processors, the one or more processors are enabled to realize the construction decision method of the transformer substation provided by the embodiment of the disclosure.
In a fourth aspect, the disclosed embodiments also provide a storage medium containing computer executable instructions, which when executed by a computer processor, are for performing a construction decision method implementing the substation provided by the disclosed embodiments.
The invention discloses a construction decision method, a device, equipment and a storage medium of a transformer substation, wherein the method comprises the following steps: acquiring basic information of an item to be built; the basic information of the project to be built comprises: project requirement information and a plurality of transformer substation information to be built; constructing a construction decision optimization objective function of the transformer substation according to the basic information; determining a target constraint condition according to the basic information; optimizing and iterating a construction decision optimization objective function of the transformer substation based on the objective constraint condition to obtain construction schemes of a plurality of candidate transformer substations; the construction scheme of the transformer substation comprises at least one target transformer substation and a plurality of evaluation indexes; and determining the construction scheme of a target transformer substation from the construction schemes of the plurality of candidate transformer substations. By using the method, the construction scheme can be analyzed and evaluated from multiple angles of cost, reliability and social cost, and the optimal construction project of the transformer substation can be determined by adopting a scientific method.
Drawings
The above and other features, advantages, and aspects of embodiments of the present disclosure will become more apparent by reference to the following detailed description when taken in conjunction with the accompanying drawings. The same or similar reference numbers will be used throughout the drawings to refer to the same or like elements. It should be understood that the figures are schematic and that elements and components are not necessarily drawn to scale.
Fig. 1 is a flowchart of a construction decision method of a substation according to an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of a construction decision device of a substation according to an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure have been shown in the accompanying drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are for illustration purposes only and are not intended to limit the scope of the present disclosure.
It should be understood that the various steps recited in the method embodiments of the present disclosure may be performed in a different order and/or performed in parallel. Furthermore, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present disclosure is not limited in this respect.
The term "including" and variations thereof as used herein are intended to be open-ended, i.e., including, but not limited to. The term "based on" is based at least in part on. The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments. Related definitions of other terms will be given in the description below.
It should be noted that the terms "first," "second," and the like in this disclosure are merely used to distinguish between different devices, modules, or units and are not used to define an order or interdependence of functions performed by the devices, modules, or units.
It should be noted that references to "one", "a plurality" and "a plurality" in this disclosure are intended to be illustrative rather than limiting, and those of ordinary skill in the art will appreciate that "one or more" is intended to be understood as "one or more" unless the context clearly indicates otherwise.
The names of messages or information interacted between the various devices in the embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.
It will be appreciated that prior to using the technical solutions disclosed in the embodiments of the present disclosure, the user should be informed and authorized of the type, usage range, usage scenario, etc. of the personal information related to the present disclosure in an appropriate manner according to the relevant legal regulations.
For example, in response to receiving an active request from a user, a prompt is sent to the user to explicitly prompt the user that the operation it is requesting to perform will require personal information to be obtained and used with the user. Thus, the user can autonomously select whether to provide personal information to software or hardware such as an electronic device, an application program, a server or a storage medium for executing the operation of the technical scheme of the present disclosure according to the prompt information.
As an alternative but non-limiting implementation, in response to receiving an active request from a user, the manner in which the prompt information is sent to the user may be, for example, a popup, in which the prompt information may be presented in a text manner. In addition, a selection control for the user to select to provide personal information to the electronic device in a 'consent' or 'disagreement' manner can be carried in the popup window.
It will be appreciated that the above-described notification and user authorization process is merely illustrative and not limiting of the implementations of the present disclosure, and that other ways of satisfying relevant legal regulations may be applied to the implementations of the present disclosure.
It will be appreciated that the data (including but not limited to the data itself, the acquisition or use of the data) involved in the present technical solution should comply with the corresponding legal regulations and the requirements of the relevant regulations.
Example 1
Fig. 1 is a flowchart of a construction decision of a substation provided by an embodiment of the present disclosure, where the embodiment of the present disclosure is applicable to a case of providing a construction decision of a user substation, the method may be performed by a construction decision device of the substation, and the device may be implemented in a form of software and/or hardware, optionally, by an electronic device, where the electronic device may be a mobile terminal, a PC side, a server, or the like.
As shown in fig. 1, the construction decision method of a substation provided by the embodiment of the present disclosure may specifically include the following steps:
s110, acquiring basic information of the item to be built.
In this embodiment, the project to be built may be a construction project of a substation. The basic information of the project to be built can comprise project requirement information and a plurality of transformer substation information to be built. The project requirement information is a requirement of the construction project. The project requirement information can comprise construction limit, capacity of a transformer substation to be constructed, capacity of an existing transformer substation, maximum load of a power grid and demand load of a user. The substation information to be built may be information of each substation. The method can comprise the cost, the power transformation capacity and the constraint conditions among the substations to be built.
By way of example, it is assumed that at least two 200kV substations will be built with a total investment of no more than 2 hundred million 5000 kiloyuan, and the total transformation capacity of the newly built substation is no less than 800MVA. The current transformer capacity 2300MVA of the 220kV transformer substation has a maximum load of 2000MW.
Specifically, basic information of an item to be built is acquired.
S120, constructing a construction decision optimization objective function of the transformer substation according to the basic information.
In this embodiment, the construction decision optimization objective function may be a construction decision optimization function constructed as needed.
Specifically, a cost function, a capacity evaluation information function, a social cost function and a penalty function can be constructed according to basic information, and the functions are linearly overlapped to obtain a construction decision optimization objective function of the transformer substation.
Illustratively, the construction decision optimization objective function of the substation may be:
minF(x)＝C(x)+R(x)-P(x)+n(x)
where F (x) is an objective function, C (x) is a cost function, R (x) is a capacity assessment information function, P (x) is a social cost function, and n (x) is a penalty function.
Optionally, the method for constructing the power grid construction decision optimization objective function according to the basic information may be: constructing a cost function according to the cost of the transformer substation to be constructed; constructing a capacity evaluation information function according to the power transformation capacity, the existing transformer substation capacity and the maximum load of the power grid; constructing a social cost function according to the transformation capacity and the existing transformer substation capacity; constructing a punishment function according to the cost and the construction limit of the transformer substation to be constructed; and linearly superposing the cost function, the capacity evaluation information function, the social cost function and the penalty function to obtain the power grid construction decision optimization objective function.
Specifically, a cost function is constructed according to the cost of the transformer substation to be constructed, and the cost function is as follows:
wherein I is i Is the cost of the transformer station i to be built, x i Is a construction variable, when x i When=1, it means that the transformer substation i to be built can be built, when x i When=0, it means that the substation i to be built cannot be built.
Constructing a capacity evaluation information function according to the power transformation capacity, the existing transformer substation capacity and the maximum load of the power grid, wherein the capacity evaluation information function is as follows:
wherein alpha is the influence coefficient of the redundant capacity of the power grid, beta is the influence coefficient of the insufficient capacity of the power grid, L is the maximum load of the power grid, and c i The new capacity of item i, c is the existing substation capacity of the power grid. The capacity assessment information function mainly considers the capacity ratio. Wherein, the capacity-to-load ratio can be used for measuring the reliability of the investment of the power grid. When the capacity is larger, more equipment is idle, and more funds are used for investment in advance, so that the investment efficiency is lower; when the capacity is small, it is stated that the invested equipment does not meet the current demand. The capacity-to-load ratio interval selected by the invention is 1.6 to 1.8.
And constructing a social cost function according to the transformation capacity and the existing transformer substation capacity, wherein the social cost function is as follows:
wherein c t Is the maximum power failure cost x i Is a construction variable, c i The new capacity of item i, c is the existing substation capacity of the power grid. For the electric power project, in addition to the cost of the project itself, social cost of the project needs to be considered. The grid needs to provide safe, reliable, stable power to the user, and once a power outage, a huge loss is incurred, wherein the social cost is proportional to the capacity.
The construction decision is limited by the construction capacity of the enterprise, and a punishment function is constructed according to the cost and the construction limit of the transformer substation to be constructed, wherein the punishment function is as follows:
wherein N represents an electrical construction limit.
S130, determining target constraint conditions according to the basic information.
In this embodiment, the target constraint condition is determined according to the user demand load and the construction limit in the basic information and according to the constraint condition between the substations to be constructed.
Optionally, the method for determining the target constraint condition according to the basic information may be: determining a first constraint condition according to the user demand load; determining a second constraint condition according to the construction limit; determining a third constraint condition according to constraint conditions among all substations to be built; the target constraint conditions comprise a first constraint condition, a second constraint condition and a third constraint condition.
Specifically, the construction capacity needs to meet the load demand of the user side, and the real-time balance of the power is ensured, so that the power supply quality is ensured. Therefore, a first constraint is determined according to the user demand load, the first constraint being as follows:
wherein D is the user demand load.
Meanwhile, the decision-making construction cost cannot exceed the construction limit. And determining a second constraint condition according to the construction limit, wherein the second constraint condition is as follows:
wherein N represents an electrical construction limit.
Determining a third constraint condition according to constraint conditions among all substations to be built, wherein the constraint conditions among all substations to be built comprise: mutually exclusive, mutually independent, interdependent, closely dependent, and complementarily related. Mutual exclusion means that two items cannot be invested simultaneously; independent means that the investment of two projects does not affect each other; interdependence means that the investment of one project is premised on the investment of the other project in two projects; close dependency means that two projects must be invested simultaneously or not at the same time; complementary association means that two items can be selected simultaneously as complementary items, but not individually. The above five relationships are extended to n items available:
x 1 +x 2 ++x n ≤1
x 1 +x 2 ++x n ≤n
x j -x i ≥0
x j -x i ＝0
x i +x j +x ij ≤1
the third constraint condition can be determined by selecting at least one constraint condition from among the constraint conditions among the substations to be built.
And S140, optimizing and iterating the construction decision optimization objective function of the transformer substation based on the objective constraint condition to obtain construction schemes of a plurality of candidate transformer substations.
The construction scheme of the transformer substation comprises at least one target transformer substation and a plurality of evaluation indexes.
In this embodiment, the evaluation index may include: total cost, capacity assessment information, and cost penalty.
Specifically, optimization iteration is carried out on a construction decision optimization objective function of the transformer substation based on the objective constraint condition according to a set optimization algorithm, so that construction schemes of a plurality of candidate transformer substations are obtained. The set optimization algorithm may be a non-dominant ordered particle swarm algorithm.
By way of example, the construction scheme of the candidate substation may be that the substation 1 and the substation 3 are constructed while determining the total cost, capacity assessment information and cost loss of the construction scheme. It can also be substation 1, substation 2 and substation 4. And obtaining the construction schemes of a plurality of candidate substations by optimizing and iterating the objective function under the constraint condition.
Optionally, the optimization iteration mode of the construction decision optimization objective function of the transformer substation based on the objective constraint condition may be: and carrying out optimization iteration on the construction decision optimization objective function of the transformer substation based on the constraint conditions and the set optimization algorithm.
In the embodiment of the invention, each potential solution is regarded as a particle in space by the particle swarm algorithm, each particle has a corresponding adaptive value, the adaptive value is determined by the value of the objective function, and each particle has a corresponding velocity vector which determines the flight distance and the flight direction of the particle in space. The particles update themselves by tracking individual extrema and global extrema for each iteration. The individual extremum refers to the optimum value searched by the particle itself, while the global extremum refers to the optimum value searched by the whole population. In this scheme the optimal value is the minimum of the objective function.
It is assumed that there is a D-dimensional space, wherein the dimensions are determined according to the number of substations to be built. There is a population of k particles. The position of the ith particle is represented as vector x i ＝(x i1 ,x i2 ,…x iD ) I=1, 2 … k, the speed of which is expressed as vector v i ＝(v i1 ,v i2 ,…v iD ) I=1, 2 … k. The optimal position found by the ith particle is denoted as Prest i ＝(pbest i1 ,pbest i2 ,…pbest iD ) I=1, 2 … k; the optimal position found by the population is named as Gbest i ＝(Gbest i1 ,Gbest i2 ,…Gbest iD ) I=1, 2 … k. Each iteration of the population of particles is shown below:
v i+1 ＝ωv i +c 1 rand(0,1)(Pbest i -x i )+c 2 rand(0,1)(Gbest i -x i )
x i+1 ＝x i +v i+1
wherein v is i ∈[-v max ,v max ]The method comprises the steps of carrying out a first treatment on the surface of the Omega is the inertial weight; c 1 、c 2 Is a cognitive constant; v i+1 V is i 、Pbest i -x i 、Gbest i -x i Vector sum of (d).
In each iteration process, all individuals before and after updating are mixed and layered, smaller individuals in the non-dominant layer are reserved, if the population scale of a certain dominant layer is overlarge, individual selection is carried out through the crowding degree, and individuals with larger crowding degree in the last layer are reserved. Until the population size remains unchanged.
If there is an individual a among the plurality of targets that is the subject of the individual B, the individual a is said to dominate the individual B. If there is an individual C that is not dominated by any of the remaining individuals, then individual C is referred to as the dominated individual. The non-dominant individuals in the population are taken as a first layer, then the first layer is removed, the non-dominant individuals in the rest individuals are taken as a second layer, and the process is repeated until the sorting is completed. The degree of aggregation of individual layers is referred to as the degree of congestion. Assuming that the individual congestion degree of both ends of each layer is infinity, the congestion degrees of the remaining individuals are as follows.
Wherein d m Means the degree of congestion of individual m;representing adjacent individuals to individual m, respectively.
Specifically, when the set maximum iteration number is reached, solving to obtain a plurality of pareto solutions, and obtaining a construction scheme of a plurality of candidate substations.
S150, determining a construction scheme of a target transformer substation from the construction schemes of the plurality of candidate transformer substations.
In this embodiment, first, for a construction scheme of each candidate substation, a first weight of each evaluation index is obtained. The method of determining the first weight may use an optimal worst method. Determining a second weight of the evaluation index according to the evaluation indexes of the construction schemes of the plurality of candidate substations; the second weight determination method may use CRITIC method. Then determining a target weight based on the first weight and the second weight; determining target evaluation information of the construction scheme of each candidate substation based on the target weight; and determining a construction scheme of a target substation based on the target evaluation information. Wherein, the evaluation index includes: total cost, capacity assessment information, and cost penalty.
Optionally, the manner of determining the construction scheme of the target substation from the construction schemes of the plurality of candidate substations may be: acquiring a first weight of each evaluation index; wherein, the evaluation index includes: total cost, capacity assessment information, and cost penalty; determining a second weight of the evaluation index according to the evaluation indexes of the construction schemes of the plurality of candidate substations; determining a target weight based on the first weight and the second weight; determining target evaluation information of the construction scheme of each candidate substation based on the target weight; and determining a construction scheme of a target substation based on the target evaluation information.
In the present embodiment, the evaluation index includes: total cost, capacity assessment information, and cost penalty. The total cost is determined by the cost function, the capacity assessment information is determined by the capacity assessment information function, and the cost loss is determined by the social cost function.
Specifically, the optimal index and the worst index in the evaluation index system are firstly determined, the optimal index and the worst index are used as standards to be compared with other indexes, and the importance evaluation result based on the optimal index and the worst index is obtained through scoring by a scale of 1-9.
Solving the weight of each index when the xi is minimum through a mathematical programming method: the formula is as follows:
wherein omega B For optimum index weight omega j Is the j index weight omega W For the worst index weight, a Bj A represents the importance evaluation result of the optimal index relative to the index j jW Representation ofImportance evaluation results of the worst index relative index j;
to ensure the rationality of the weights obtained, a consistency check is performed by use. The test formula is as follows:
wherein CI is a reference value obtained in advance with respect to the optimal worst index.
Specifically, the second weight of the evaluation index is determined according to the evaluation indexes of the construction schemes of the plurality of candidate substations, firstly, normalization processing is carried out,
wherein y is ij 、x ij Respectively indicating values before and after normalization processing;respectively the minimum value and the maximum value of the evaluation index.
The contrast intensity is then determined:
wherein m is the number of construction schemes of the candidate substations.
Then determining a conflict correlation coefficient:
wherein i and j are two sets of data respectively; i. j is the average value of the evaluation indexes i and j respectively.
Determining the comprehensive information quantity of each evaluation index:
finally, a second weight is calculated:
and determining a corresponding first coefficient and a corresponding second coefficient based on the first weight and the second weight, and linearly superposing the first weight and the second weight based on the first coefficient and the second coefficient to obtain the target weight.
And taking the maximum value of each column of the normalized matrix as a positive ideal solution and the minimum value as a negative ideal solution. Solving for group benefit values and individual regrets:
wherein: s is S i 、R i Respectively representing a group benefit value and an individual regret value; f (f) ij A j-th decision value representing an i-th scheme; f (f) j +and f j - Representing a positive ideal solution and a negative ideal solution, respectively.
Calculating target evaluation information:
where v is the decision mechanism coefficient. When v is more than 0.5, deciding according to the maximized group benefit; when v is less than 0.5, making a decision according to the minimized individual regrets; when v=0.5, a compromise between maximizing population efficiency and minimizing individual regrets is considered. In this embodiment v=0.5 can be selected. The smaller the target evaluation information is, the better the target evaluation information is, and the scheme with the minimum value of the target evaluation information is selected as the construction scheme of the target substation.
Optionally, the manner of determining the target weight based on the first weight and the second weight may be: determining corresponding first and second coefficients based on the first and second weights; and linearly superposing the first weight and the second weight based on the first coefficient and the second coefficient to obtain the target weight.
Specifically, corresponding first coefficients and second coefficients are determined based on the first weights and the second weights:
wherein beta is 1 For the initial first coefficient, beta 2 Is an initial second coefficient;
and solving the formula to obtain a first coefficient and a second coefficient. Based on the first and second weights linearly superimposed based on the first and second coefficients, a target weight is obtained:
ω＝β 1 ω 1 +β 2 ω 2
the invention discloses a construction decision method of a transformer substation, which comprises the following steps: acquiring basic information of an item to be built; the basic information of the project to be built comprises: project requirement information and a plurality of transformer substation information to be built; constructing a construction decision optimization objective function of the transformer substation according to the basic information; determining target constraint conditions according to the basic information; optimizing and iterating a construction decision optimization objective function of the transformer substation based on the objective constraint condition to obtain construction schemes of a plurality of candidate transformer substations; the construction scheme of the transformer substation comprises at least one target transformer substation and a plurality of evaluation indexes; and determining the construction scheme of a target transformer substation from the construction schemes of the plurality of candidate transformer substations. By using the method, the construction scheme can be analyzed and evaluated from multiple angles of cost, reliability and social cost, and the optimal construction project of the transformer substation can be determined by adopting a scientific method.
Example two
Fig. 2 is a schematic structural diagram of a construction decision device of a transformer substation according to an embodiment of the present invention, where, as shown in fig. 2, the device includes: the system comprises a data acquisition module 210, an objective function construction module 220, a constraint condition determination module 230, an optimization iteration module 240 and a construction scheme evaluation module 250.
A data acquisition module 210, configured to acquire basic information of an item to be built; the basic information of the project to be built comprises: project requirement information and a plurality of transformer substation information to be built;
the objective function construction module 220 is configured to construct a construction decision optimization objective function of the substation according to the basic information;
a constraint condition determining module 230, configured to determine a target constraint condition according to the basic information;
the optimization iteration module 240 is configured to perform optimization iteration on the construction decision optimization objective function of the substation based on the objective constraint condition, so as to obtain construction schemes of multiple candidate substations; the construction scheme of the transformer substation comprises at least one target transformer substation and a plurality of evaluation indexes;
the construction scheme evaluation module 250 is configured to determine a construction scheme of a target substation from the construction schemes of the plurality of candidate substations.
According to the technical scheme provided by the embodiment of the disclosure, the construction scheme can be analyzed and evaluated from multiple angles of cost, reliability and social cost, and the optimal construction project of the transformer substation can be determined by adopting a scientific method.
Further, the data acquisition module 210 may be configured to:
the project requirement information comprises construction limit, capacity of a transformer substation to be constructed, capacity of an existing transformer substation, maximum load of a power grid and user demand load; the information of the substations to be built comprises the cost, the variable capacity and the constraint conditions among the substations to be built.
Further, the objective function construction module 220 may be configured to:
constructing a cost function according to the to-be-constructed substation cost;
constructing a capacity evaluation information function according to the power transformation capacity, the existing transformer substation capacity and the maximum load of the power grid;
constructing a social cost function according to the transformation capacity and the existing transformer substation capacity;
constructing a punishment function according to the to-be-constructed substation cost and the construction limit
And linearly superposing the cost function, the reliability function, the social cost function and the penalty function to obtain a power grid construction decision optimization objective function.
Further, constraint determination module 230 may also be configured to:
determining a first constraint condition according to the user demand load;
determining a second constraint condition according to the construction limit;
determining a third constraint condition according to the constraint conditions among the substations to be built; wherein the target constraint includes the first constraint, the second constraint, and a third constraint.
Further, the optimization iteration module 240 may be configured to:
and carrying out optimization iteration on the construction decision optimization objective function of the transformer substation based on the constraint conditions and a set optimization algorithm to obtain construction schemes of a plurality of candidate transformer substations.
Further, the construction plan evaluation module 250 may also be configured to:
acquiring a first weight of each evaluation index; wherein the evaluation index comprises: total cost, capacity assessment information, and cost penalty;
determining a second weight of the evaluation index according to the evaluation index of the construction schemes of the plurality of candidate substations;
determining a target weight based on the first weight and the second weight;
determining target evaluation information of the construction scheme of each candidate substation based on the target weight;
and determining a construction scheme of a target substation based on the target evaluation information.
Further, the construction plan evaluation module 250 may be configured to:
determining corresponding first and second coefficients based on the first and second weights;
and linearly superposing the first weight and the second weight based on the first coefficient and the second coefficient to obtain a target weight.
The device can execute the method provided by all the embodiments of the invention, and has the corresponding functional modules and beneficial effects of executing the method. Technical details not described in detail in this embodiment can be found in the methods provided in all the foregoing embodiments of the invention.
Example III
Fig. 3 shows a schematic diagram of an electronic device 10 that may be used to implement an embodiment of the present invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 3, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, wherein the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various suitable actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as the construction decision method of the substation.
In some embodiments, the construction decision method of the substation may be implemented as a computer program, which is tangibly embodied on a computer readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the substation construction decision method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the construction decision method of the substation by any other suitable means (e.g. by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (10)
1. The construction decision method of the transformer substation is characterized by comprising the following steps of:
acquiring basic information of an item to be built; the basic information of the project to be built comprises: project requirement information and a plurality of transformer substation information to be built;
constructing a construction decision optimization objective function of the transformer substation according to the basic information;
determining a target constraint condition according to the basic information;
optimizing and iterating a construction decision optimization objective function of the transformer substation based on the objective constraint condition to obtain construction schemes of a plurality of candidate transformer substations; the construction scheme of the transformer substation comprises at least one target transformer substation and a plurality of evaluation indexes;
and determining the construction scheme of a target transformer substation from the construction schemes of the plurality of candidate transformer substations.
2. The method according to claim 1, wherein the project requirement information comprises a construction limit, a capacity of a transformer substation to be constructed, a capacity of an existing transformer substation, a maximum load of a power grid and a user demand load; the information of the substations to be built comprises the cost, the variable capacity and the constraint conditions among the substations to be built.
3. The method of claim 2, wherein constructing a grid construction decision optimization objective function from the base information comprises:
constructing a cost function according to the to-be-constructed substation cost;
constructing a capacity evaluation information function according to the power transformation capacity, the existing transformer substation capacity and the maximum load of the power grid;
constructing a social cost function according to the transformation capacity and the existing transformer substation capacity;
constructing a punishment function according to the to-be-constructed substation cost and the construction limit;
and linearly superposing the cost function, the capacity evaluation information function, the social cost function and the penalty function to obtain a power grid construction decision optimization objective function.
4. The method of claim 2, wherein determining a target constraint from the base information comprises:
determining a first constraint condition according to the user demand load;
determining a second constraint condition according to the construction limit;
determining a third constraint condition according to the constraint conditions among the substations to be built; wherein the target constraint includes the first constraint, the second constraint, and a third constraint.
5. The method of claim 1, wherein optimizing the construction decision optimization objective function of the substation based on the objective constraint condition to obtain a construction solution of a plurality of candidate substations comprises:
and carrying out optimization iteration on the construction decision optimization objective function of the transformer substation based on the constraint conditions and a set optimization algorithm to obtain construction schemes of a plurality of candidate transformer substations.
6. The method of claim 1, wherein determining a construction plan for a target substation from the plurality of candidate substation construction plans comprises:
acquiring a first weight of each evaluation index; wherein the evaluation index comprises: total cost, capacity assessment information, and cost penalty;
determining a second weight of the evaluation index according to the evaluation index of the construction schemes of the plurality of candidate substations;
determining a target weight based on the first weight and the second weight;
determining target evaluation information of the construction scheme of each candidate substation based on the target weight;
and determining a construction scheme of a target substation based on the target evaluation information.
7. The method of claim 6, wherein determining a target weight based on the first weight and the second weight comprises:
determining corresponding first and second coefficients based on the first and second weights;
and linearly superposing the first weight and the second weight based on the first coefficient and the second coefficient to obtain a target weight.
8. A construction decision device of a transformer substation, comprising:
the data acquisition module is used for acquiring basic information of the item to be built; the basic information of the project to be built comprises: project requirement information and a plurality of transformer substation information to be built;
the objective function construction module is used for constructing a construction decision optimization objective function of the transformer substation according to the basic information;
the constraint condition determining module is used for determining a target constraint condition according to the basic information;
the optimization iteration module is used for carrying out optimization iteration on the construction decision optimization objective function of the transformer substation based on the objective constraint condition to obtain construction schemes of a plurality of candidate transformer substations; the construction scheme of the transformer substation comprises at least one target transformer substation and a plurality of evaluation indexes;
and the construction scheme evaluation module is used for determining the construction scheme of a target transformer substation from the construction schemes of the plurality of candidate transformer substations.
9. An electronic device, the electronic device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the construction decision method of the substation of any one of claims 1-7.
10. A computer-readable storage medium, characterized in that it stores computer instructions for causing a processor to implement the construction decision method of the substation according to any one of claims 1-7 when executed.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310760410.5A CN116823044A (en) | 2023-06-26 | 2023-06-26 | Construction decision method, device and equipment of transformer substation and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310760410.5A CN116823044A (en) | 2023-06-26 | 2023-06-26 | Construction decision method, device and equipment of transformer substation and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116823044A true CN116823044A (en) | 2023-09-29 |
Family
ID=88142362
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310760410.5A Pending CN116823044A (en) | 2023-06-26 | 2023-06-26 | Construction decision method, device and equipment of transformer substation and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116823044A (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109784725A (en) * | 2019-01-16 | 2019-05-21 | 国家电网有限公司 | Investment decision method and system for power grid project |
| CN113450031A (en) * | 2021-08-31 | 2021-09-28 | 国网江西省电力有限公司供电服务管理中心 | Method and device for selecting intelligent energy consumption service potential transformer area of residents |
-
2023
- 2023-06-26 CN CN202310760410.5A patent/CN116823044A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109784725A (en) * | 2019-01-16 | 2019-05-21 | 国家电网有限公司 | Investment decision method and system for power grid project |
| CN113450031A (en) * | 2021-08-31 | 2021-09-28 | 国网江西省电力有限公司供电服务管理中心 | Method and device for selecting intelligent energy consumption service potential transformer area of residents |
Non-Patent Citations (2)
| Title |
|---|
| YASHAN HU等: "Multi-objective Particle Swarm Algorithm and VIKOR Method Based on Multi-Objective Grid Investment Decision Optimization Research", 《2023 3RD INTERNATIONAL CONFERENCE ON ENERGY ENGINEERING AND POWER SYSTEMS (EEPS)》, 22 September 2023 (2023-09-22), pages 961 - 967 * |
| 周向红等: "面向云制造协同创新伙伴选择的多源异构VIKOR群决策方法", 《计算机集成制造系统》, vol. 28, no. 1, 31 January 2022 (2022-01-31), pages 1 - 4 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114611845A (en) | Method and apparatus for predicting carbon emission, electronic device, and medium | |
| CN117934135A (en) | Network operation management method and device, electronic equipment and storage medium | |
| CN117592510A (en) | Load prediction method and system based on safety constraint | |
| CN117273450A (en) | Power system risk assessment method, device, equipment and storage medium | |
| CN116823044A (en) | Construction decision method, device and equipment of transformer substation and storage medium | |
| CN116703109A (en) | Method, device, equipment and storage medium for selecting power distribution network project | |
| CN116245253A (en) | Substation planning scheme determining method and device, electronic equipment and storage medium | |
| CN115936379A (en) | Shared vehicle scheduling method, device, equipment and storage medium | |
| CN114723239A (en) | Multi-party collaborative modeling method, device, equipment, medium and program product | |
| CN106301880A (en) | One determines that cyberrelationship degree of stability, Internet service recommend method and apparatus | |
| CN115549213A (en) | Distributed power supply access scale determination method, device, electronic device, storage medium, and program product | |
| CN113435653B (en) | Method and system for predicting saturated power consumption based on logistic model | |
| CN117010712A (en) | Method and device for determining response strategy of virtual power plant and virtual power plant system | |
| Santos et al. | A Probabilistic Framework for Network Security in Matchmaking-Based P2P Energy Trading | |
| CN118350719A (en) | Evaluation method and device of organization architecture, electronic equipment and storage medium | |
| CN115204746A (en) | Engineering risk assessment method, device, equipment and storage medium | |
| ÖZDEMIR | AN APPLICATION FOR AGGREGATING THE CRITERIA WEIGHTS OBTAINED BY DIFFERENT OBJECTIVE WEIGHTING METHODS AND THEIR USE IN COPRAS | |
| CN115829771A (en) | Financial accounting method and device, electronic equipment and storage medium | |
| CN116402231A (en) | Power load prediction method, device, equipment and storage medium | |
| Wang et al. | Nonlinear Programming Model Based on Monte Carlo Simulation | |
| CN117610957A (en) | Equipment development path determining method, device, equipment and medium | |
| CN116302538A (en) | Yun Bianduan coordinated resource management method, device, equipment and medium | |
| CN115455019A (en) | Search intention identification method, device and equipment based on user behavior analysis | |
| Chen et al. | The investment decision-making index system and the grey comprehensive evaluation method under hybrid cloud | |
| CN117422259A (en) | Distributed resource prediction aggregation method, device, equipment and storage 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 |