CN108156226A - The industrial Internet of Things cognition energy management system and computational methods of a kind of cloud and mist fusion - Google Patents
The industrial Internet of Things cognition energy management system and computational methods of a kind of cloud and mist fusion Download PDFInfo
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Abstract
The invention discloses the industrial Internet of Things cognition energy management system and its computational methods of a kind of fusion of cloud and mist, structure includes industrial equipment layer, industrial cloud and mist cognition computation layer and energy management layer.Wherein industrial cloud and mist cognition computation layer includes industrial cloud computing and is calculated with industrial mist；Energy management layer is responsible for providing diversified energy management application as the top layer of framework, including energy sensing module, energy analysis module, energy forecast module and energy source optimization module.The present invention can provide unlimited resources using cloud computing and alleviate mist computing resource finiteness problem, high latency, network congestion, low integrity problem caused by marginal information processing capacity alleviates cloud computing are calculated using mist, realize that cloud and mist merges with building saturated model between cloud computing by being calculated in mist, under the guiding for minimizing cloud and mist consumed resource, cause energy management service reasonable distribution between cloud and mist, realize that cloud and mist resource rationally efficiently utilizes, so as to fulfill IIoT high efficiency of energy management.
Description
Technical field
The invention belongs to Internet of Things energy field applied technical field, and in particular to a kind of industrial object of cloud and mist fusion
Networking cognition energy management system and computational methods.
Background technology
Domestic manufacturing transition means that powerful promotion industrial information plays the industry internet epoch important push away
Action is used.Industry internet is the industrial revolution+network revolution, is not industry+internet, and industrial Internet of Things belongs to industrial interconnection
By existing Internet of Things (IoT) technology and big data (Big Data) technology, prediction is used in industry manufacture field for net
Conventional machines equipment is connected with automation algorithm, to realize more stable human-computer interaction.
However, with the continuous development of industrial Internet of Things (IIoT), the energy consumption of sustainable growth and serious environment are dirty
Dye problem causes the extensive concern of people from all walks of life.Thus the energy management mode of a kind of efficient green of active demand, to reduce
Energy consumption mitigates environmental pollution, and is directed to many-sided characteristics such as IIoT is in large scale, accuracy requirement is high, delay sensitive,
IIoT proposes energy management following demand：1. high speed reliable network transmittability, 2. mass data storage calculate energy
Power, 3. intellectual analysis decision-making capability, 4. security assurance information, 5. interaction effect is intelligent.
At present, it is focused primarily upon both at home and abroad about the research of IIoT energy managements by cloud computing (Cloud Computing)
Technology is dissolved into energy management, solves the problems, such as that traditional energy management is resource-constrained, expansion difficulty is big.However, cloud computing is given
IIoT energy managements also bring huge challenge while offering convenience.As IIoT is constantly ripe, magnanimity will necessarily be generated
Multi-energy data information if being calculated for being all moved to data to store in cloud, will necessarily be caused between cloud center and industrial equipment
Input/output bottleneck so that entire IIoT transmission rates substantially reduce, while bring serious network congestion and data
It is stored entirely in cloud that also there are larger security risks.On the one hand industry internet energy management framework of the prior art should
No longer stick to cloud computing, mist calculate (Fog Computing) have can on industrial equipment (or between devices, net
On network) data storage and computing capability are carried out, consider mist computing technique being also dissolved into energy management.On the other hand, it is based on
The energy management model of cloud is only handled multi-energy data information, lacks processing edge-of-network data ability, and do not have
Alleviate IIoT congestions, assuring data security ability.
In existing patent document, the patent application No. is 201505000110.X discloses a kind of work of view-based access control model modeling
Industry Internet of Things energy management method according to an industrial technology for Internet of things system and the technical specification of functional component, is realized and is used
Activity and function derived from method visual angle model and function visual angle model pass through " activity " to " functional component " to " realizing component "
Realize mapping, the realization mapping of critical system characteristic (marginal layer, podium level, enterprises level).One complete industry is completed with this
Internet of Things energy management system.Its main process is as shown in Figure 1.It can realize that marginal layer collects data from industrial control system,
Send podium level to；And from podium level receive for industrial control system control command, podium level from enterprises level receive, from
It manages and forwards control command to marginal layer；It can also converge, handle from marginal layer and forward data, enterprise to enterprises level
Layer realizes the application of specific area, DSS, and provides application interface to end subscriber.The document is for Internet of Things
One basic patent of energy management system modeling has carried out more high-rise technology for the information security of industrial Internet of Things
The structure of system.But the deficiency of the technology is not for the theoretical puzzle of industrial Internet of Things, is asked including intelligent Problems, digitlization
Topic, integrity problem, Controllability and safety issue, particularly with physical security, information security, system self-healing 3
System performance does not provide the solution of the technical system completely supported.
Application No. is 201423274662.X patent document disclose it is a kind of based on the industrial Internet of Things network converged
It supports modeling method, by communicating, servicing and 3 angles of information, proposes the structural system of industrial Internet of Things：Ubiquitous Network body
Architecture, application layer overlay network architecture and Services Oriented Achitecture.This method combines industrial Internet of Things and makees
The technical issues of palpus faced solves is manufactured for wisdom.Its main process is as shown in Figure 2.This method passes through in service-oriented layer
Internet gateway or intermediate server, authorized user can access the facility information directly extracted by object network, service at this time
Device serves as the receiver in object network, performs from each object and collects data；Ubiquitous network network layers act as internet high in the clouds and
Interface between object network, including heterogeneous access networks, 3G nets and WLAN, there are interoperabilities；Application layer nerve of a covering
It can be the form of wireless sensor network or factory's ad-hoc network.Various forms of networks cause access and multi-operator ring more
Collaboration and synergy in border is more preferable, while the communications conduit of high quality is to be served by providing new chance.Patent text
It offers and carries out technological incorporation using the data perception of cloud computing, collection, storage and computing capability and industrial Internet of Things.However, the party
Method does not have the information flow ability and quick transmittability between optimal cloud center and industrial equipment, while there is also larger
Security risk.
Invention content
In view of the above shortcomings of the prior art, the purpose of the present invention is cloud computing is relied on to provide unlimited resources technology, mist meter
The industrial Internet of Things cognition energy management scheme that marginal information treatment technology proposes a kind of cloud and mist fusion is calculated, it will be by being calculated in mist
Structure infiltration cognitive model realizes that cloud and mist merges between cloud computing, under the guiding for minimizing cloud and mist consumed resource so that energy
Source control service reasonable distribution between cloud and mist realizes that cloud and mist resource rationally efficiently utilizes, so as to fulfill IIoT high efficiency of energy pipes
Reason solves high latency, network congestion, low integrity problem.
In order to achieve the above objectives, the technical solution adopted by the present invention recognizes the energy for a kind of industrial Internet of Things of cloud and mist fusion
Management system, structure include industrial equipment layer, industrial cloud and mist cognition computation layer and energy management layer, wherein industrial equipment layer packet
Include data acquisition equipment, communication equipment and central apparatus, carried out respectively using these physical equipments data acquisition, transformation, upwards
Layer transmission and Local or Remote control；Industrial cloud and mist cognition computation layer includes industrial cloud computing and is calculated with industrial mist, industrial cloud
As centralized calculating center, abundant storage computing resource is provided for energy management, collection is played to entire IIoT energy managements
The effect of middle control, industrial mist provide real-time storage computing resource, industrial mist and industrial cloud for energy management in a distributed way
Between by permeate cognitive model improve resource utilization；Energy management layer is responsible for providing diversified energy as the top layer of framework
Source control application including energy sensing module, energy analysis module, energy forecast module and energy source optimization module, is on the one hand used
In conveying energy management instruction to lower floor, on the other hand good man-machine interaction environment is provided for IIoT user.
Further, above-mentioned energy sensing module is responsible for perceiving unordered, scattered, not system prime energy data information,
And by certain standard sort out and summarize, so as to simplify firsthand information, visualization, systematization.
Above-mentioned energy analysis module analyzes data information by the method for statistical calculation, reflects prime energy data information
Trend, dispersion degree and correlation intensity.
Above-mentioned energy forecast module carries out energy-output ratio prediction and the prediction of energy supply amount.
Above-mentioned energy source optimization module is based on real time data and historical data is established between industrial equipment execution performance and energy consumption
Relational model, using multiobjective optimal control algorithm, find optimal energy management scheme, keep industrial equipment excellent in performance
While reduce energy consumption.
The present invention is it is further proposed that a kind of industrial Internet of Things cognition energy management system of above-mentioned cloud and mist fusion used
Computational methods include the following steps:
Step 1：The complicated order D that upper strata energy conservation module is assigned is decomposed into multiple energy management services
Step 2：Industrial cloud and mist layer is responsible for these services siCarry out classification processing；
Step 3：Solute is formed by the quantity SM, energy storage power SS and computing capability SC of industrial cloud and mist server, utilizes infiltration
Principle services these and adjusts and distribute into Mobile state；
Step 4：S is serviced with energy managementiAs solvent, recognized according to the difference of semi-permeable membrane both sides industry cloud and mist resource
Know movement, with the concentration at balance film both ends, realize service reasonable distribution；
Step 5：Consider that some following factor carries out semi-permeable membrane configuration：Energy management service balancing Lbalance, processing delay
Section Di(i=Cloud, Fog, Avg) and cloud and mist calculate boundEnsure its intelligence
Property, and then control the flow direction of energy management service；
Step 6：To the quantity SM of industrial cloud and mist server, energy storage power SS in the process of osmosis serviced between industrial cloud and mist
Tunable configuration is carried out with computing capability SC, migratory direction of the service between industrial cloud and mist is determined according to the difference f of configuration.
Compared with prior art, the beneficial effects of the present invention are：
1, the present invention can provide unlimited resources using cloud computing and alleviate mist computing resource finiteness problem, and side is calculated using mist
Edge information processing capability alleviates high latency, network congestion, low integrity problem caused by cloud computing.
2, and realize that cloud and mist merges with building saturated model between cloud computing by being calculated in mist, minimizing cloud and mist resource
Under the guiding of consumption so that energy management service reasonable distribution between cloud and mist realizes that cloud and mist resource rationally efficiently utilizes, from
And realize IIoT high efficiency of energy management.
Description of the drawings
Fig. 1 is a kind of industry internet energy management model of view-based access control model modeling.
Fig. 2 is a kind of based on the industrial Internet of Things network support model converged.
The industrial Internet of Things of cloud and mist fusion that Fig. 3 is the present invention recognizes energy management model.
Specific embodiment
The specific embodiment of the present invention is further described in conjunction with attached drawing.
The architecture of the industrial Internet of Things cognition energy management of cloud and mist proposed by the present invention fusion as shown in figure 3, including
Industrial equipment layer, industrial cloud and mist cognition computation layer and energy management layer.Wherein：
Industrial equipment layer：Data acquisitions, transformation are carried out using industrial physical equipment, to upper layer transport and Local or Remote
Control.
Industrial cloud and mist recognizes computation layer：On the one hand it for storing analysis bottom multi-energy data information, is provided for energy management
Data safeguard；On the other hand corresponding energy management service is provided for upper strata energy management, bottom physical equipment is controlled, such as
Industrial equipment is configured, Virtual Cluster moves in and out.
Energy management layer：On the one hand it is used to convey energy management instruction to lower floor, on the other hand be provided for IIoT user good
Good man-machine interaction environment.
It is briefly described：In IIoT environment, industrial equipment is ceaselessly engaged in production activity, consumes mass energy.It can source capsule
Abundant computing resource ought to be obtained with from industrial cloud and mist cognition computation layer, the Command Resolution that different energy sources management module is assigned
For energy management service, then these services are assigned in different industrial clouds and mists and are performed, industrial equipment is controlled, will finally perform
As a result it returns again to corresponding energy conservation module.
For three above level, specific research contents is described below：
(1) industrial equipment layer：I.e. industrial layers of physical devices, capital equipment include data acquisition equipment, communication equipment and in
Heart equipment.
Data acquisition equipment solves the data transformation problem of human world and industrial world, they are responsible for collection industry and set
Standby multi-energy data information simultaneously passes through communication equipment by data to upper layer transport, to obtain more potential energy source information.
Central apparatus is that industrial equipment is carried out in IIoT, is energy main consumer, is that energy management is mainly controlled
Object processed, they can be by local control, can also be remotely controlled.
These equipment may be regarded as the node in IIoT, and node can according to the difference of function, position and action scope
To be divided into different sub-networks, Virtual Cluster is formed.Each Virtual Cluster has an a pair with the industrial mist in upper strata again
The mapping relations answered.Meanwhile node (equipment) can be free to exit or be added to according to the variation of environment, time and oneself state
In any Virtual Cluster, and industrial mist corresponding to upper strata disconnects or establishes connection.Industrial mist can be according to own resource to these
Node (equipment) carries out loaded self-adaptive adjusting.
(2) industrial cloud and mist cognition computation layer：The layer includes industrial cloud computing and is calculated with industrial mist.Industrial cloud is as centralization
Calculating center provides abundant storage computing resource for energy management, and central controlled work is played to entire IIoT energy managements
With；Industrial mist provides real-time storage computing resource as in a distributed way for energy management, prolongs caused by alleviating industrial cloud
Late, congestion and safety issue.And resource utilization is improved by permeating cognitive model between industrial mist and industrial cloud.
(3) energy management layer：This layer is responsible for providing diversified energy management application as the top layer of framework, including the energy
Sensing module, energy analysis module, energy forecast module and energy source optimization module.
Energy sensing module：The module is responsible for perceiving unordered, scattered, not system prime energy data information, and press
Certain standard, which sort out, to summarize, so as to simplify firsthand information, visualization, systematization.
Energy analysis module：Data information is analyzed by the method for statistical calculation, reflection prime energy data information
Trend, dispersion degree and correlation intensity.For example, when will be seen that each workshop highest, minimum unit by statistical analysis module
Between energy consumption and its time of occurrence.
Energy forecast module：There are two main aspects for the module, are on the one hand energy-output ratio predictions, are on the other hand energy
Source supply prediction.Energy-output ratio refers to the energy consumption of the various energy consumption equipments of IIoT in the regular period, including raw coal and crude oil
And its product, natural gas, electric power etc..Production of energy amount refers to the supply of the various energy of IIoT in the regular period, including raw coal,
Crude oil, natural gas, water power, nuclear energy power generation amount, biomass energy, solar energy etc..
Energy source optimization module：Its function is namely based on real time data and historical data, establish industrial equipment execution performance with
Relational model between energy consumption using multiobjective optimal control algorithm, finds optimal energy management scheme, is keeping industrial equipment
Energy consumption is reduced while excellent in performance.
The computational methods of industrial Internet of Things cognition energy management system based on the fusion of above-mentioned cloud and mist, it is main to be recognized using infiltration
Know mechanism, similarly the infiltration in chemistry, balance film both sides solution concentration is recognized by semi-permeable membrane.Include the following steps:
Step 1：First, the complicated order D that upper strata energy conservation module is assigned is decomposed into multiple energy managements and services si
(i=1,2,3 ..., n)；
Step 2：Industrial cloud and mist layer is responsible for these services siCarry out classification processing；
Step 3：Quantity SM, energy storage power SS and computing capability SC by industrial cloud and mist server etc. form solute, using oozing
Saturating principle services these and adjusts and distribute into Mobile state；
Step 4：Energy management service s at this timeiAs solvent, according to the difference of semi-permeable membrane both sides industry cloud and mist resource into
Row cognition movement with the concentration at balance film both ends, realizes service reasonable distribution；
Step 5：Semi-permeable membrane must take into consideration many factors, such as energy management service balancing Lbalance, processing delay area
Between Di(i=Cloud, Fog, Avg) and cloud and mist calculate boundEnsure that its is intelligent,
And then control the flow direction of energy management service；
Step 6：In addition, tunable configuration is carried out to resource in the process of osmosis serviced between industrial cloud and mist, according to configuration
Difference f determines migratory direction of the service between industrial cloud and mist.
Various physical equipments, a cloud data center, multiple mist data centers, industry wireless network, intelligence are included at one
Energy control device, intelligently under the industrial production scene of production, packaging, transporting equipment etc., the industrial equipment in the scene is all intelligence
Energy equipment is integrated with multi-energy data information in intelligence sensor energy real-time collecting industrial production, and these equipment also have company
Net function can go out these information sharings.
In addition, these intelligent industrial equipment have certain computing capability, multiple smart machines by combination of network together,
Industrial mist is formed, industrial mist can provide indigenous energy management service and these equipment are carried out with local control.Between multiple industry mists
It can be in communication with each other, can also communicate with industrial cloud.
Therefore, industrial cloud understands entire industrial scene operating state and energy consumption situation, and entire scene is carried out complete
Office's energy management, Supervised Control are happened at the local energy management in industrial mist.User is counted by the intelligence in the industry scene
Calculation machine, participates in energy management system, not only can intuitively check the scene Energy consumption, can also assign the energy
Management instruction, completes specific energy management function.
Compare the industrial Internet of Things energy that traditional energy management framework is merged with based on cloud and mist in such industrial scene
The energy management effect of management framework：
1st, to industrial equipment, Energy Consumption Cost compares per hour, work under the energy management framework based on cloud and mist fusion
Industry equipment day part Energy Consumption Cost is less, and for conventional architectures, and the fluctuation of day part Energy Consumption Cost is smaller,
Entire industry scene energy consumption is stablized.Specifically, the total energy consuming cost of industrial equipment is about 13200 yuan under the framework, far
21538 yuan lower much smaller than conventional architectures of totle drilling cost, more efficiently, energy management effect is more preferable.
2nd, to industrial equipment, pollutant discharge amount compares per hour, big under the energy management framework based on cloud and mist fusion
Partial period pollutant discharge amount is less, and total release 1208kg is less than 1759kg under conventional architectures, more green, environmental protection.
It should be noted that above-described embodiment provided by the present invention only has schematically, without the restriction present invention's
The effect of the range of specific implementation.Protection scope of the present invention should for those of ordinary skill in the art be shown including those
And the transformation being clear to or alternative solution.
Claims (6)
1. the industrial Internet of Things cognition energy management system of a kind of cloud and mist fusion, it is characterised in that its structure includes industrial equipment
Layer, industrial cloud and mist cognition computation layer and energy management layer, wherein industrial equipment layer include data acquisition equipment, communication equipment and in
Heart equipment is carried out data acquisition, transformation using these physical equipments, is controlled to upper layer transport and Local or Remote respectively；Work
Industry cloud and mist cognition computation layer includes industrial cloud computing and is calculated with industry mist, and industrial cloud is as centralized calculating center, for energy source capsule
Reason provides abundant storage computing resource, plays the role of to entire IIoT energy managements central controlled, and industrial mist is in a distributed manner
Mode provides real-time storage computing resource for energy management, and resource is improved by permeating cognitive model between industrial mist and industrial cloud
Utilization rate；Energy management layer is responsible for providing diversified energy management application as the top layer of framework, including energy sensing module,
On the one hand energy analysis module, energy forecast module and energy source optimization module are used to convey energy management instruction to lower floor, another
Aspect provides good man-machine interaction environment for IIoT user.
2. the industrial Internet of Things cognition energy management system of cloud and mist fusion according to claim 1, it is characterised in that described
Energy sensing module is responsible for perceiving unordered, scattered, not system prime energy data information, and by certain standard sorted out
Summarize, so as to simplify firsthand information, visualization, systematization.
3. the industrial Internet of Things cognition energy management system of cloud and mist fusion according to claim 1, it is characterised in that described
Energy analysis module analyzes data information by the method for statistical calculation, reflects the trend, discrete of prime energy data information
Degree and correlation intensity.
4. the industrial Internet of Things cognition energy management system of cloud and mist fusion according to claim 1, it is characterised in that described
Energy forecast module carries out energy-output ratio prediction and the prediction of energy supply amount.
5. the industrial Internet of Things cognition energy management system of cloud and mist fusion according to claim 1, it is characterised in that described
Energy source optimization module establishes the relational model between industrial equipment execution performance and energy consumption based on real time data and historical data, should
With multiobjective optimal control algorithm, optimal energy management scheme is found, energy is reduced while industrial equipment excellent in performance is kept
Source consumes.
6. the computational methods that a kind of industrial Internet of Things cognition energy management system of cloud and mist fusion described in claim 1 uses,
It is characterized by comprising following steps:
Step 1：The complicated order D that upper strata energy conservation module is assigned is decomposed into multiple energy management service si(i=1,2,
3,…,n)；
Step 2：Industrial cloud and mist layer is responsible for these services siCarry out classification processing；
Step 3：Solute is formed by the quantity SM, energy storage power SS and computing capability SC of industrial cloud and mist server, utilizes penetration theory
These are serviced and adjusts and distributes into Mobile state；
Step 4：S is serviced with energy managementiAs solvent, cognition shifting is carried out according to the difference of semi-permeable membrane both sides industry cloud and mist resource
It is dynamic, with the concentration at balance film both ends, realize service reasonable distribution；
Step 5：Consider that some following factor carries out semi-permeable membrane configuration：Energy management service balancing Lbalance, processing delay section Di
(i=Cloud, Fog, Avg) and cloud and mist calculate bound(i=min, max) ensures that its is intelligent, and then
Control the flow direction of energy management service；
Step 6：To the quantity SM, energy storage power SS and calculating of industrial cloud and mist server in the process of osmosis serviced between industrial cloud and mist
Ability SC carries out tunable configuration, and migratory direction of the service between industrial cloud and mist is determined according to the difference f of configuration.
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| CN114629931A (en) * | 2020-12-10 | 2022-06-14 | 桂林理工大学 | Biogas engineering production monitoring and control system construction method based on cloud and mist collaborative computing and Internet of things communication technology |
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