CN109063978A - Energy Internet resources dispatching method and system, readable storage medium storing program for executing and terminal - Google Patents
Energy Internet resources dispatching method and system, readable storage medium storing program for executing and terminal Download PDFInfo
- Publication number
- CN109063978A CN109063978A CN201810767783.4A CN201810767783A CN109063978A CN 109063978 A CN109063978 A CN 109063978A CN 201810767783 A CN201810767783 A CN 201810767783A CN 109063978 A CN109063978 A CN 109063978A
- Authority
- CN
- China
- Prior art keywords
- resource
- internet resources
- energy internet
- user
- resource request
- 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
- 238000000034 method Methods 0.000 title claims abstract description 37
- 238000003860 storage Methods 0.000 title claims abstract description 10
- 238000004458 analytical method Methods 0.000 claims abstract description 45
- 238000013468 resource allocation Methods 0.000 claims abstract description 34
- 238000013507 mapping Methods 0.000 claims abstract description 12
- 230000008569 process Effects 0.000 claims description 10
- 235000013399 edible fruits Nutrition 0.000 claims description 2
- 230000000875 corresponding effect Effects 0.000 description 23
- 238000009826 distribution Methods 0.000 description 7
- 238000010586 diagram Methods 0.000 description 4
- 238000011156 evaluation Methods 0.000 description 4
- 230000008901 benefit Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000007726 management method Methods 0.000 description 2
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 description 2
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000002457 bidirectional effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000007728 cost analysis Methods 0.000 description 1
- 238000013135 deep learning Methods 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 238000004146 energy storage Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 239000003345 natural gas Substances 0.000 description 1
- 230000008447 perception Effects 0.000 description 1
- 239000003208 petroleum Substances 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 230000002787 reinforcement Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
-
- 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
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06315—Needs-based resource requirements planning or 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06395—Quality analysis or management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—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
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Educational Administration (AREA)
- Marketing (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Development Economics (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Game Theory and Decision Science (AREA)
- General Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- Medical Informatics (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
A kind of energy Internet resources dispatching method and system, readable storage medium storing program for executing and terminal, which comprises obtain the resource request information of user;The resource request information is analyzed, corresponding resource request analysis result is obtained;The resource allocation proposal for meeting the resource request analysis result is calculated using deeply learning algorithm;The mapping of energy Internet resources is carried out to the resource allocation proposal, obtains the resource for distributing to the user.The utilization rate of energy Internet resources can be improved in above-mentioned scheme.
Description
Technical field
The present invention relates to energy Internet technical fields, more particularly to a kind of energy Internet resources dispatching method and are
System, readable storage medium storing program for executing and terminal.
Background technique
Energy internet (Energy Internet, EI) be the advanced power electronic technique of integrated use, information technology and
Intelligent management technology will be largely made of the load of distributed energy acquisition device, distributed energy storage device and various types
Novel electric power network, petroleum network, natural gas network etc. can source node interconnection get up, to realize the energy of energy in bidirectional flow
Peer switch and shared network.
Energy internet is energy interacted system access with new energy, two-way interaction, not only has energy confession
The function of answering provides public energy transaction platform also for all kinds of producers and consumer, the spy for having interconnection open
Property.There are certain independences for all kinds of nodes in energy internet, therefore its resource management system is no longer the simple energy point
With scheduling, and the generating capacity of each node, hair on the basis of realization is combined with Demand-side interactive response, must be comprehensively considered
The factors such as electric cost and schedulable ability formulate dynamic resource dispatching strategy, realize supply-demand mode, Resource dynamic allocation, with
The production cost for improving resource utilization, reducing energy consumption and energy enterprise.
Under energy internet environment, traditional Resource Scheduling Mechanism cannot adapt to resource dynamic variation characteristic completely,
It there is a problem that the level of resources utilization is low.
Summary of the invention
Present invention solves the technical problem that being how to improve the utilization rate of energy Internet resources.
In order to solve the above technical problems, the embodiment of the invention provides a kind of energy Internet resources dispatching method, it is described
Method includes:
Obtain the resource request information of user;
The resource request information is analyzed, corresponding resource request analysis result is obtained;
The resource allocation proposal for meeting the resource request analysis result is calculated using deeply learning algorithm;
The mapping of energy Internet resources is carried out to the resource allocation proposal, obtains the resource for distributing to the user.
Optionally, the resource request analysis result includes the type, quantity, complexity of resource, and including resource benefit
With the resource constraint information including rate, service quality and cost.
Optionally, it is used in user in distributed resource process, the method also includes:
It is analyzed according to service condition of the preset time cycle to the resource distributed, obtains corresponding resource and use
Analyze result;
Using obtained resource using analysis as a result, being adjusted to the resource allocation proposal, until adjusted
The service condition of the corresponding resource of resource allocation proposal meets the resource utilization, service quality and cost resource constraint item
Part.
The embodiment of the invention also provides a kind of energy Internet resources to dispatch system, the system comprises:
Acquiring unit, suitable for obtaining the resource request information of user;
Analytical unit obtains corresponding resource request analysis result suitable for analyzing the resource request information;
Configuration unit, suitable for the money for meeting the resource request analysis result is calculated using deeply learning algorithm
Source allocation plan;
Map unit is suitable for carrying out the mapping of energy Internet resources to the resource allocation proposal, obtains distributing to described
The resource of user.
Optionally, the resource request analysis that the analytical unit is analyzed is as a result, including the type of resource, quantity, answering
Miscellaneous degree, and the resource constraint including resource utilization, service quality and cost.
Optionally, the system also includes dynamic adjustment units, suitable for being used in distributed resource process in user,
It is analyzed according to service condition of the preset time cycle to the resource distributed, obtains corresponding resource and use analysis knot
Fruit;Using obtained resource using analysis as a result, being adjusted to the resource allocation proposal, until resource adjusted is matched
The service condition for setting the corresponding resource of scheme meets the resource utilization, service quality and cost resource constraint.
The embodiment of the invention also provides a kind of computer readable storage mediums, are stored thereon with computer instruction, described
The step of computer instruction executes energy Internet resources dispatching method described in any of the above embodiments when running.
The embodiment of the invention also provides a kind of terminal, including memory and processor, energy is stored on the memory
Enough computer instructions run on the processor, the processor execute any of the above-described when running the computer instruction
The step of described energy Internet resources dispatching method.
Compared with prior art, the technical solution of the embodiment of the present invention has the advantages that
Above-mentioned scheme is analyzed by the resource request to acquired user, obtains corresponding resource request analysis
As a result, and the resource allocation proposal for meeting resource request analysis result is calculated using deeply learning algorithm, most
The mapping of energy Internet resources is carried out to the resource allocation proposal eventually, obtains the resource for distributing to the user, due to using
Deeply learning algorithm configures energy Internet resources, therefore the accuracy of resource distribution can be improved, so as to
Improve the utilization rate of energy Internet resources.
Further, used in user in distributed resource process, by the service condition to the resource distributed into
Row analyzes obtained corresponding resource using analysis as a result, being adjusted to the resource allocation proposal, until adjusted
The service condition of the corresponding resource of resource allocation proposal meets the resource utilization, service quality and cost resource constraint item
The accuracy of distributed resource can be improved in part, further increases the utilization rate of energy Internet resources.
Detailed description of the invention
Fig. 1 is the flow diagram of one of embodiment of the present invention energy Internet resources dispatching method;
Fig. 2 is the structural schematic diagram of one of embodiment of the present invention energy Internet resources scheduling system.
Specific embodiment
Technical solution in the embodiment of the present invention is analyzed by the resource request to acquired user, is obtained corresponding
Resource request analysis is as a result, and the resource for meeting the resource request analysis result is calculated using deeply learning algorithm
Allocation plan finally carries out the mapping of energy Internet resources to the resource allocation proposal, obtains the money for distributing to the user
Due to configuring using deeply learning algorithm to energy Internet resources, therefore the accurate of resource distribution can be improved in source
Property, so as to improve the utilization rate of energy Internet resources.
It is understandable to enable above-mentioned purpose of the invention, feature and beneficial effect to become apparent, with reference to the accompanying drawing to this
The specific embodiment of invention is described in detail.
Fig. 1 is a kind of flow diagram of energy Internet resources dispatching method of the embodiment of the present invention.Referring to Fig. 1, originally
A kind of energy Internet resources dispatching method of inventive embodiments, may include following step:
Step S101: the resource request information of user is obtained.
In specific implementation, the user is the individual in energy internet or equipment;The user needs when
Time can submit corresponding resource request by user terminal.
Step S102: analyzing the resource request information, obtains corresponding resource request analysis result.
It in specific implementation, can be by the resource request when the resource request information for receiving user's submission
Information is parsed, and obtains type, quantity, complexity of required resource etc., and including resource utilization, service quality and at
Resource constraint including this.
Step S103: it is calculated using deeply learning algorithm and meets the resource of resource request analysis result and match
Set scheme.
In specific implementation, when analysis obtains corresponding resource request analysis result, can be learnt using deeply
The resource for meeting the resource request analysis result is calculated in (Deep Reinforcement Learning, DRL) algorithm
Allocation plan.In deeply learning algorithm, deep learning is used for " perception ", and the observation information of target is obtained from environment,
And provide the status information under current environment;Intensified learning is used for " decision ", provides current state and is mapped to corresponding actions, and base
The value of prize movement is punished in adaptive expectations;May finally accomplished target optimal resource distribution, obtain while meeting user
The resource allocation information of demand and resource constraint.
Step S104: the mapping of energy Internet resources is carried out to the resource allocation proposal, obtains distributing to the user
Resource.
In specific implementation, it when obtaining resource allocation proposal, can be obtained according to corresponding resource configuration parameter, mapping
Resource in energy Internet resources pond, namely distribute to the resource of the user.Wherein, in energy Internet resources pond
Resource be to be virtualized to obtain by resources such as the energy, server, storage and networks that will be all in source interconnection net, with
Resource service neatly can be provided for user according to the resource requirement of user, so that resource is fully used, and can be in real time
Dynamically adjust resource allocation.
In specific implementation, in order to improve the accuracy of resource distribution, resource utilization is further increased, the method is also
Include:
Step S105: using in user in distributed resource process, according to the preset time cycle to the money distributed
The service condition in source is analyzed, using obtained resource using analysis as a result, being adjusted to the resource allocation proposal.
In specific implementation, it is used in user in distributed resource process, it can be according to the preset time cycle to institute
The service condition of the resource of distribution is analyzed, such as the analysis of energy analysis, energy efficiency of equipment and cost analysis, and then resource makes
With the analysis of situation as a result, it includes resource utilization and service quality and Cost Evaluation that it is corresponding that resource scheduling scheme, which is calculated,
Equal evaluation index inside, and the obtained evaluation including resource utilization and service quality and Cost Evaluation etc. is referred to
It is denoted as being adjusted resource allocation proposal using deeply learning algorithm, thus to distributing to user's for feedback information
Resource is timed update, realizes that the dynamic of resource is precisely dispatched, so as to improve in energy Internet resources scheduling process
Overall resource utilization.
Above-mentioned scheme analyzes the resource request of acquired user, obtain the analysis of corresponding resource request as a result,
And the resource allocation proposal for meeting the resource request analysis result is calculated using deeply learning algorithm, finally to institute
It states resource allocation proposal and carries out the mapping of energy Internet resources, obtain the resource for distributing to the user, due to strong using depth
Change learning algorithm to configure energy Internet resources, therefore the accuracy of resource distribution can be improved, so as to improve energy
The utilization rate of source interconnection net resource.
The above-mentioned method in the embodiment of the present invention is described in detail, below will be to the above-mentioned corresponding dress of method
It sets and is introduced.
Fig. 2 is the structural schematic diagram of one of embodiment of the present invention energy Internet resources scheduling system.Referring to fig. 2,
One of embodiment of the present invention energy Internet resources dispatch system, may include 201 analytical unit 202 of acquiring unit, match
Set unit 203 and map unit 204, in which:
The acquiring unit 201, suitable for obtaining the resource request information of user.
The analytical unit 202 obtains corresponding resource request analysis suitable for analyzing the resource request information
As a result.Wherein, the analysis of the analytical unit is analyzed resource request as a result, include type, quantity, the complexity of resource,
And the resource constraint including resource utilization, service quality and cost.
The configuration unit 203 meets the resource request analysis suitable for being calculated using deeply learning algorithm
As a result resource allocation proposal.
The map unit 204 is suitable for carrying out the mapping of energy Internet resources to the resource allocation proposal, be distributed
To the resource of the user.
In specific implementation, the system can also include dynamic adjustment unit 205, in which:
The dynamic adjustment unit 205, suitable for being used in distributed resource process in user, according to preset week time
Phase analyzes the service condition for the resource distributed, and obtains corresponding resource and uses analysis result;Using obtained money
Source is using analysis as a result, being adjusted to the resource allocation proposal, until the corresponding resource of resource allocation proposal adjusted
Service condition meet the resource utilization, service quality and cost resource constraint.
The embodiment of the invention also provides a kind of computer readable storage mediums, are stored thereon with computer instruction, described
The step of energy Internet resources dispatching method is executed when computer instruction is run.Wherein, the energy internet
Resource regulating method refers to being discussed in detail for preceding sections, repeats no more.
The embodiment of the invention also provides a kind of terminal, including memory and processor, energy is stored on the memory
Enough computer instructions run on the processor, the processor execute the energy when running the computer instruction
The step of Internet resources dispatching method.Wherein, the energy Internet resources dispatching method refers to the detailed of preceding sections
It is thin to introduce, it repeats no more.
Using the above scheme in the embodiment of the present invention, the resource request of acquired user is analyzed, is corresponded to
Resource request analysis as a result, and the money for meeting resource request analysis result is calculated using deeply learning algorithm
Source allocation plan finally carries out the mapping of energy Internet resources to the resource allocation proposal, obtains distributing to the user's
Due to configuring using deeply learning algorithm to energy Internet resources, therefore the standard of resource distribution can be improved in resource
True property, so as to improve the utilization rate of energy Internet resources.
Further, used in user in distributed resource process, by the service condition to the resource distributed into
Row analyzes obtained corresponding resource using analysis as a result, being adjusted to the resource allocation proposal, until adjusted
The service condition of the corresponding resource of resource allocation proposal meets the resource utilization, service quality and cost resource constraint item
The accuracy of distributed resource can be improved in part, further increases the utilization rate of energy Internet resources.
Those of ordinary skill in the art will appreciate that all or part of the steps in the various methods of above-described embodiment is can
It is completed with instructing relevant hardware by program, which can store in computer readable storage medium, and storage is situated between
Matter may include: ROM, RAM, disk or CD etc..
Although present disclosure is as above, present invention is not limited to this.Anyone skilled in the art are not departing from this
It in the spirit and scope of invention, can make various changes or modifications, therefore protection scope of the present invention should be with claim institute
Subject to the range of restriction.
Claims (8)
1. a kind of energy Internet resources dispatching method characterized by comprising
Obtain the resource request information of user;
The resource request information is analyzed, corresponding resource request analysis result is obtained;
The resource allocation proposal for meeting the resource request analysis result is calculated using deeply learning algorithm;
The mapping of energy Internet resources is carried out to the resource allocation proposal, obtains the resource for distributing to the user.
2. energy Internet resources dispatching method according to claim 1, which is characterized in that the resource request analysis knot
Fruit includes the type, quantity, complexity of resource, and the resource constraint including resource utilization, service quality and cost
Conditional information.
3. energy Internet resources dispatching method according to claim 2, which is characterized in that use and distributed in user
In resource process, further includes:
It is analyzed according to service condition of the preset time cycle to the resource distributed, obtains corresponding resource and use analysis
As a result;
Using obtained resource using analysis as a result, being adjusted to the resource allocation proposal, until resource adjusted
The service condition of the corresponding resource of allocation plan meets the resource utilization, service quality and cost resource constraint.
4. a kind of energy Internet resources dispatch system characterized by comprising
Acquiring unit, suitable for obtaining the resource request information of user;
Analytical unit obtains corresponding resource request analysis result suitable for analyzing the resource request information;
Configuration unit is met the resource of resource request analysis result and matched suitable for being calculated using deeply learning algorithm
Set scheme;
Map unit is suitable for carrying out the mapping of energy Internet resources to the resource allocation proposal, obtains distributing to the user
Resource.
5. energy Internet resources according to claim 4 dispatch system, which is characterized in that the analytical unit is analyzed
Arrive resource request analysis as a result, include resource type, quantity, complexity, and including resource utilization, service quality and
Resource constraint including cost.
6. energy Internet resources according to claim 5 dispatch system, which is characterized in that further include: dynamic adjusts single
Member, suitable for being used in distributed resource process in user, according to the preset time cycle to the use feelings for the resource distributed
Condition is analyzed, and is obtained corresponding resource and is used analysis result;Using obtained resource using analysis as a result, to the resource
Allocation plan is adjusted, until the service condition of the corresponding resource of resource allocation proposal adjusted meets the utilization of resources
Rate, service quality and cost resource constraint.
7. a kind of computer readable storage medium, is stored thereon with computer instruction, which is characterized in that the computer instruction fortune
Perform claim requires the step of 1 to the 3 described in any item energy Internet resources dispatching methods when row.
8. a kind of terminal, which is characterized in that including memory and processor, storing on the memory can be in the processing
The computer instruction run on device, perform claim requires described in 1 to 3 any one when the processor runs the computer instruction
The energy Internet resources dispatching method the step of.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810767783.4A CN109063978A (en) | 2018-07-12 | 2018-07-12 | Energy Internet resources dispatching method and system, readable storage medium storing program for executing and terminal |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810767783.4A CN109063978A (en) | 2018-07-12 | 2018-07-12 | Energy Internet resources dispatching method and system, readable storage medium storing program for executing and terminal |
Publications (1)
Publication Number | Publication Date |
---|---|
CN109063978A true CN109063978A (en) | 2018-12-21 |
Family
ID=64816324
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201810767783.4A Pending CN109063978A (en) | 2018-07-12 | 2018-07-12 | Energy Internet resources dispatching method and system, readable storage medium storing program for executing and terminal |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN109063978A (en) |
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110198344A (en) * | 2019-05-05 | 2019-09-03 | 网宿科技股份有限公司 | A kind of resource regulating method and system |
CN111026549A (en) * | 2019-11-28 | 2020-04-17 | 国网甘肃省电力公司电力科学研究院 | Automatic test resource scheduling method for power information communication equipment |
CN111553616A (en) * | 2020-05-13 | 2020-08-18 | 支付宝(杭州)信息技术有限公司 | Resource delivery method and system |
CN111953070A (en) * | 2020-07-21 | 2020-11-17 | 浙江中新电力工程建设有限公司 | Power optimization scheduling system and strategy method based on source network load and storage coordination |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101541044A (en) * | 2008-03-18 | 2009-09-23 | 华为技术有限公司 | Scheduling method and scheduling processing device |
CN107590612A (en) * | 2017-09-21 | 2018-01-16 | 深圳低碳城综合能源有限公司 | Demand response system, demand response method, apparatus and computer-processing equipment |
CN107888669A (en) * | 2017-10-31 | 2018-04-06 | 武汉理工大学 | A kind of extensive resource scheduling system and method based on deep learning neutral net |
-
2018
- 2018-07-12 CN CN201810767783.4A patent/CN109063978A/en active Pending
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101541044A (en) * | 2008-03-18 | 2009-09-23 | 华为技术有限公司 | Scheduling method and scheduling processing device |
CN107590612A (en) * | 2017-09-21 | 2018-01-16 | 深圳低碳城综合能源有限公司 | Demand response system, demand response method, apparatus and computer-processing equipment |
CN107888669A (en) * | 2017-10-31 | 2018-04-06 | 武汉理工大学 | A kind of extensive resource scheduling system and method based on deep learning neutral net |
Non-Patent Citations (1)
Title |
---|
程乐峰等: "信息–物理–社会融合的智慧能源调度机器人及其知识自动化:框架、技术与挑战", 《中国电机工程学报》 * |
Cited By (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110198344A (en) * | 2019-05-05 | 2019-09-03 | 网宿科技股份有限公司 | A kind of resource regulating method and system |
US11153370B2 (en) | 2019-05-05 | 2021-10-19 | Wangsu Science & Technology Co., Ltd. | Resource scheduling method and system |
CN111026549A (en) * | 2019-11-28 | 2020-04-17 | 国网甘肃省电力公司电力科学研究院 | Automatic test resource scheduling method for power information communication equipment |
CN111026549B (en) * | 2019-11-28 | 2022-06-10 | 国网甘肃省电力公司电力科学研究院 | Automatic test resource scheduling method for power information communication equipment |
CN111553616A (en) * | 2020-05-13 | 2020-08-18 | 支付宝(杭州)信息技术有限公司 | Resource delivery method and system |
CN111953070A (en) * | 2020-07-21 | 2020-11-17 | 浙江中新电力工程建设有限公司 | Power optimization scheduling system and strategy method based on source network load and storage coordination |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Chen et al. | Deploying data-intensive applications with multiple services components on edge | |
CN109063978A (en) | Energy Internet resources dispatching method and system, readable storage medium storing program for executing and terminal | |
Zhou et al. | Hybrid teaching–learning-based optimization of correlation-aware service composition in cloud manufacturing | |
Li et al. | Demand response using linear supply function bidding | |
Chen et al. | Dynamic ensemble wind speed prediction model based on hybrid deep reinforcement learning | |
Simaria et al. | A genetic algorithm based approach to the mixed-model assembly line balancing problem of type II | |
Tesauro | Reinforcement learning in autonomic computing: A manifesto and case studies | |
CN114721833B (en) | Intelligent cloud coordination method and device based on platform service type | |
CN109240818A (en) | Task discharging method based on user experience in a kind of edge calculations network | |
CN109669452A (en) | A kind of cloud robot task dispatching method and system based on parallel intensified learning | |
CN109492774A (en) | A kind of cloud resource dispatching method based on deep learning | |
Zhao et al. | A deep reinforcement learning approach to resource management in hybrid clouds harnessing renewable energy and task scheduling | |
CN110503199A (en) | Method for splitting and device, the electronic equipment and storage medium of operation node | |
Liu et al. | S-ABC-A Service-oriented artificial bee colony algorithm for global optimal services selection in concurrent requests environment | |
Almadhor et al. | A new offloading method in the green mobile cloud computing based on a hybrid meta-heuristic algorithm | |
CN105426247B (en) | A kind of HLA federal members programming dispatching method | |
Amoretti et al. | Efficient autonomic cloud computing using online discrete event simulation | |
CN117493020A (en) | Method for realizing computing resource scheduling of data grid | |
CN109634719A (en) | A kind of dispatching method of virtual machine, device and electronic equipment | |
Liu et al. | Effective Task Scheduling in Cloud Computing Based on Improved Social Learning Optimization Algorithm. | |
CN116149855A (en) | Method and system for optimizing performance resource cost under micro-service architecture | |
Shuang et al. | Task scheduling based on Grey Wolf optimizer algorithm for smart meter embedded operating system | |
Abdul-Rahman et al. | Toward a genetic algorithm based flexible approach for the management of virtualized application environments in cloud platforms | |
Sharma et al. | Multi-Faceted Job Scheduling Optimization Using Q-learning With ABC In Cloud Environment | |
CN114327925A (en) | Power data real-time calculation scheduling optimization method and system |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
RJ01 | Rejection of invention patent application after publication | ||
RJ01 | Rejection of invention patent application after publication |
Application publication date: 20181221 |