CN104636815B - A kind of cement production enterprise energy information integrated management system - Google Patents
A kind of cement production enterprise energy information integrated management system Download PDFInfo
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P80/00—Climate change mitigation technologies for sector-wide applications
- Y02P80/10—Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
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Abstract
The present invention relates to a kind of cement production enterprise energy information integrated management system, including coal, electricity, three kinds of multi-energy data collection networks of water, energy management server, energy source optimization server and the issue of multi-energy data Intranet.Multi-energy data gathers network and is connected by fiber optical transceiver with DCS system for coal, electricity, the collection of three kinds of multi-energy datas of water, transmission.Energy management server carries out data interconnection with DCS system by EPA, obtains various energy-relevant datas, carries out all kinds of multi-energy data management.The related multi-energy data that energy source optimization server by utilizing OPC Client are read in DCS OPC Server is write result in DCS system after optimization computing by OPC Client again, realizes the energy source optimization to production process.The Ethernet interface module and OPC Server that the present invention is provided using original cement production enterprise DCS system are organically integrated in one four parts by more than, have the advantages that easy of integration, inexpensive, realize the collection of cement production enterprise multi-energy data, storage, analysis and manage.
Description
Technical field
The present invention relates to cement production process energy management field, net is gathered more particularly, to cement production enterprise energy information
Network, the scheduling of cement production process energy source optimization and management.
Background technology
New Type Dry-process Cement Production generally based on " kiln three is ground ", constitutes different process areas, while also phase
Raw material, intermediate material repository and the conveying equipment answered, as shown in Figure 1.Need to consume substantial amounts of coal work in whole production process
Clinker burning is completed for fuel, consumes substantial amounts of electric energy to drive large-scale milling equipment to complete the powder of raw material, coal and finished cement
Mill, clinker energy consumption accounts for 7~8 one-tenth of manufacture of cement total energy consumption, and each large high-voltage motor power consumption accounts for manufacture of cement electricity
The 65% of consumption.
At present, the exploitation for energy information management system of cement production enterprise generally there are following problem：
（1）Lack collection and management to electricity, Water Energy dielectric dissipation data.The existing electric power meter degree of accuracy of enterprise is low,
And there is calculating of the electrical power to electric energy, miss by a mile；Water meter typically uses old-fashioned pointer-type water meter, and the degree of accuracy is low and needs people
Work meter reading.The monitoring device of electric energy and water falls behind, it is impossible to realize electricity, the online acquisition of Water Energy dielectric dissipation data and management.
（2）Each workshop energy information of cement production enterprise is independent, lacks the shared of each workshop energy information.
（3）Lack the Optimized Operation to the cement production process energy.Due to the independent accounting of each workshop, cause existing life
Management system is produced with each minimum target of production unit energy resource consumption, raw mill, coal mill often cause frequency because of overproduction
The start and stop of numerous ground, cause substantial amounts of energy waste.
Accordingly, it would be desirable to according to cement production process feature, research and implement the collection of cement production process energy information with it is excellent
Change scheduling synthetical compositive evaluating, realize the collection of cement production enterprise multi-energy data, storage, display, share and Real-Time Scheduling.The system
Have great importance for improving cement production enterprise energy management level, reduction cement production enterprise energy consumption.
Existing cement production enterprise Distributed Control System（DCS）Support a variety of industrial interfaces and communication standard, such as EPA
Interface, Modbus and Profibus field-bus interfaces, OPC industrial standard communications protocol etc., have cement production enterprise communication network
There is scalability.Cement production enterprise energy resource collecting network is expanded on the basis of original cement production enterprise Distributed Control System network
Exhibition so that the energy resource collecting network has the advantages that easy of integration, inexpensive.Therefore, it is necessary to develop a kind of based on cement production enterprise
The energy resource collecting and management system of Distributed Control System.
The content of the invention
The deficiency with utilizing is gathered for current cement production enterprise energy information, the technical problem to be solved in the present invention is to provide
A kind of energy resource collecting network and Optimal Scheduling based on original cement production enterprise Distributed Control System, realize the cement production enterprise energy
Information gathering, shared, management and the comprehensive integration application of Optimized Operation.
The technical scheme that is used to achieve the above object of the present invention is：A kind of cement production enterprise energy information integrated management system
System, including DCS system and its Ethernet module, the OPC interface of offer, in addition to
Coal, electricity, the collection network of three kinds of multi-energy datas of water：Coal powder consumption data acquisition instrument is adopted by DCS I/O data
Truck is connected with DCS system, and electricity, Water Energy data acquisition instrument are connected by energy resource collecting optical fiber ring network with DCS system, are used for
Coal, electricity, the collection and transmission of three kinds of multi-energy datas of water；
Energy management server：Data interconnection is carried out by EPA with DCS system, for obtaining various energy numbers
According to, each production link efficiency is calculated, and each multi-energy data is stored, carry out the inquiry of historical data, statistics, trend and show and efficiency pair
Mark；
Energy source optimization server：For realizing the dynamic of raw material and the coal dust production process energy using energy source optimization scheduling model
State Optimized Operation；
Inquire about terminal：To be one or more, pass through B/S network structures and taken with the energy source optimization server, energy management
Business device is connected, for inquiring about energy real time data and statistical report form.
The coal powder consumption data acquisition instrument is coal powder metering device, and coal powder consumption data are by DCS system from scene
Read.
The electricity, Water Energy data acquisition instrument are the digital water meter and digital electric meter that each workshop is installed.
The live real time data information storage of enterprise is arrived background data base system by the energy management server, then is pressed
Time or production order of classes or grades at school count, analyze and draw various trend curves as needed, realize inquiry and the statistics of historical data.
The energy management server is by inside the real-time multi-energy data collected and national standard, provincial standard, industry
Standard is contrasted.
The energy source optimization server sets up production process energy dynamic model, and DCS OPC are read using OPC Client
Related multi-energy data in Server, result is write in DCS system, realize by OPC Client again after optimization computing
To the energy source optimization of production process.
Dispatching algorithm in the energy source optimization server includes：
1）Object function
The target of dynamic price response optimization problem is exactly the maximum profit for producing raw material, i.e. production cost CTIt is minimum；
The phase of being intended to is denoted as T, is averaged and is divided into some period Δ t, and object function is represented by：
In formula：
- electric cost；
Cost in-production process, referred to as processing cost, are fixed cost, do not produce influence on object function；
- start the cost produced；
The carrying cost of-part, is fixed cost, does not produce influence on object function；
Electric costIt can be calculated according to below equation：
In formula：
πtElectricity price in-t-th period；
The electricity that grinding machine is consumed in-time period t；
Grinding machine power consumption in time period tIt is related to the yield of grinding machine in time period t；Power consumption of the millIt is expressed as
The yield n of grinding machine in time period ttFunctionProduce power consumptionIn normal range of operation, with adding material
Amount is approximately linear relationship, and its mathematic(al) representation is：
In formula：
A, b-be curve matching coefficient；
ntThe yield of grinding machine in-time period t；
When grinding machine puts into production again, can all there is extra cost consumption, the consumption of this departmental cost is designated as opening
Dynamic costIts calculation formula is：
In formula：
βsThe fixed cost consumed in-start-up course, such as maintenance cost or idle running cost；
utThe start and stop state of-t period raw mills, works as utWhen=1, represent to be in production process；utWhen=0, represent to be in
Halted state；
2）Decision variable：For the yield of grinding machine in time period t.
3）Constraints
A. yield is constrained：
WhereinWithThe lower and upper limit of mill output in the difference t periods；
B. storage constraint：
No more than its storage capacity to greatest extent, its constraints is the stored number of surge bunker:
WhereinWithThe upper and lower bound of surge bunker storage capacity in the difference t periods；
C. inventory balance is constrained：
The storage of surge bunker will meet demand of the following clinker production hourly to raw materialIts expression formula is：
Wherein StFor the amount of storage of t period surge bunkers, St-1For the amount of storage of t-1 period surge bunkers, ntFor grinding machine in the t periods
Yield,The demand to raw material is produced for t periods clinker
D. whole story stock constrains：
In order to guarantee to meet the demand beyond prediction, surge bunker should ensure that certain stock is remaining, its constraints
For:
SO-ST≤ε (17)
Wherein SOAnd STRespectively plan the quantity in stock of the phase whole story, ε is maximum for the permission of the difference of plan phase whole story quantity in stock
Value；
The formula shows that in the plan phase is all that the product produced by the same time is met to raw materials requirement amount, is considered
The inventory balance of each period constrains the Constraints of Equilibrium obtained in plan phase T：
If demand has relatively large deviation, it is necessary to re-establish optimal models with expected situation, by that section rethought
The quantity in stock that time starts is set to SO。
The present invention has advantages below and beneficial effect：
（1）Each link coal of manufacture of cement, electricity, the precise acquisition of Water Energy data, storage, analysis can be completed with being managed to mark
Reason, the implementation dispatched for cement production enterprise energy source optimization provides multi-energy data basis；
（2）Raw material and coal dust cost minimization can be realized by rolling energy source optimization scheduling online；
（3）The Intranet issue of multi-energy data can be realized, makes energy behaviour in service transparence, is easy to production and the energy
Management and running；
（4）The network interface provided using original cement Distributed Control System, realizes energy information collection network, the energy
Optimize the organic integration of server and the issue of multi-energy data Intranet, reduce the development cost of enterprise energy network.
Brief description of the drawings
Fig. 1 new dry process for cement production flows；
Fig. 2 cement production enterprise energy information integrated system structure charts；
Fig. 3 cement production enterprise energy information integrated system network architecture diagrams；
Fig. 4 raw material and coal dust production process energy source optimization server architecture and functional diagram.
Embodiment
Below in conjunction with the accompanying drawings and embodiment the present invention is described in further detail.
A kind of cement production enterprise energy information integrated management system of the present invention includes energy information collection network, energy management clothes
Be engaged in device, energy source optimization server and Web Server, and the network architecture diagram of the system is as shown in Figure 3.Its hardware mainly includes
Intelligent electric meter, intellectual water meter, serial port device network server, fiber optical transceiver, the cement DCS of Modbus communications protocol is supported to control
System processed, energy management central server, Web Server, inquiry terminal, software mainly include multi-energy data and analyzed with managing
Software, SQL Server2005, OPC Server, OPC Client.
The energy information collection network includes supporting intelligent electric meter, intellectual water meter, the serial ports of Modbus communications protocol to set
Standby networked server, fiber optical transceiver and original enterprise DCS production data acquisition systems.
Coal, electricity, Water Energy data acquisition are divided into coal powder consumption information gathering mode and electricity, water energy by the difference of collection network
Source information acquisition mode.Coal powder consumption information gathering is based on old enterprise's DCS system.Cement production enterprise coal powder consumption has two portions
Point, a part is rotary kiln end coal powder injection, and another part is dore furnace furnace bottom coal powder injection, and two-part coal amount of feeding all is to use rotor
Coal powder consumption data are uploaded to DCS controllers by scale on-line metering, data by DCS I/O data collecting cards.In energy management
Central server is connected by EPA with DCS controllers, and multi-energy data is ultimately stored in energy management central server.
Electric energy and the collection network of water consumption are by supporting intelligent electric meter, intellectual water meter, the serial equipment networking of Modbus communications protocol to take
Device, fiber optical transceiver, the cement DCS control systems of being engaged in are constituted.Acquisition terminal receives ammeter and data of water meter signal, and carries out data
Processing, is connected by Modbus with serial port device network server, and serial port device network server is connected by optical fiber, is formed superfluous
Remaining energy resource collecting optical fiber ring network, optical fiber ring network is connected by fiber optical transceiver with the ethernet communication module that DCS is controlled, and is formed
Electricity, Water Energy information gathering network.Electricity, Water Energy data upload eventually through EPA and are stored in energy management center
In server.The real-time collection of all electrical equipment energy informations of this collection real-time performance and water consumption and monitoring, Ke Yiwei
Business electrical and the accurate management offer data support with water；Metering device failure and abnormal conditions can be found in time, improved
The managerial skills of field apparatus；Remote meter-reading function can be realized, the time cost and human cost of meter reading is reduced, improves meter reading
Accuracy and operating efficiency.This collection network is based on original DCS frameworks, can reduce the investments of most acquisition system hardware into
This, and can further reduce construction（Network is set up to be laid with hardware）With the cost and workload of maintenance.
The energy management server hardware includes the computer for being connected to EPA, and software uses SQL
Server2005 and energy analysis and management software.Energy management server is connected by EPA with DCS system, by energy
Three kinds of multi-energy datas of coal, electricity, water that source collection network is collected are stored in SQL Server historical data bases.Coal and water make
With a Relatively centralized（Coal powder consumption is main in rotary kiln end coal powder injection, dore furnace furnace bottom coal powder injection, and water consumption is mainly in cogeneration
Boiler and preheater conditioning Tower）, using centrally stored mode.Power consumption distribution is wide, collection point is more, therefore power storage is used and pressed
Activity Classification method, it is as shown in table 1 by the power storage of Activity Classification.
Table 1 presses the power storage table of Activity Classification
Coal, three kinds of energy mediums of electricity and water can by the hour, order of classes or grades at school, day, the moon, inquired about in year and statistical analysis, realize not
Biconditional operation and the performance appraisal of administrative staff.It can also carry out collecting calculating simultaneously according to different query objects, different query ranges
Shown in the form of curve, pie chart, block diagram and form.
All production process datas are collected at energy management center, and each period energy medium consumption is entered with product yield
Row real-time statistics are calculated, and by the coal of each period, electricity and three kinds of energy medium consumptions of water and national standard, provincial standard and
Industry internal standard is contrasted.Enterprise energy in time, accurately can be grasped to mark by efficiency and utilize present situation.
The framework of the energy source optimization server is as shown in Figure 4.Original cement DCS system provides OPC Server, permits
Perhaps whole DCS system variables carry out third party's read-write.OPC Client read the feeding energy source optimization service of OPC Server data
Device.Energy source optimization server calculates production process controlled quentity controlled variable and writing by OPC by rolling energy source optimization dispatching algorithm online
Function write-in DCS system realizes raw material and coal dust cost minimization.Energy source optimization server has following function：Cross number of passes
Calculated according to collection, display, raw material and coal dust production process energy dynamic optimization and advise function, parameter setting with equipment running status
Function.
The online rolling energy source optimization dispatching algorithm is to use Demand Side Response technology, and the problem is converted into production week
Dynamic price response optimization problem in phase, model is set up in the dynamic response behavior to the current electricity prices of grinding machine, and is simulated
Analysis, on the premise of the given production schedule, repair schedule, system current state, it is determined that meeting the optimal of production energy demand
Allocative decision, can save the electric energy use cost of raw material production and pulverized coal preparation, improve energy use efficiency.In clinker
In actual production process, the production capacity of raw mill and coal mill produces consumed raw material and coal dust, therefore raw material commonly greater than clinker
Raw material silo is provided between mill and cement kiln, surge bunker is used as provided with Pulverized Coal Bin between same coal mill and cement kiln.Surge bunker is deposited
Adjusted alloing mill load when the need for meeting clinker production to raw material according to the change of electricity price or network load
It is whole, make the energy cost of unit product minimum.The following is the core of the energy source optimization algorithm：
1）Object function
The target of dynamic price response optimization problem is exactly the maximum profit for producing raw material, i.e. production cost CTIt is minimum；
The phase of being intended to is denoted as T, is averaged and is divided into some period Δ t, and object function is represented by：
In formula：
- electric cost；
Cost in-production process, referred to as processing cost, are fixed cost, do not produce influence on object function；
- start the cost produced；
The carrying cost of-part, is fixed cost, does not produce influence on object function；
Electric costIt can be calculated according to below equation：
In formula：
πtElectricity price in-t-th period；
The electricity that grinding machine is consumed in-time period t；
Grinding machine power consumption in time period tIt is related to the yield of grinding machine in time period t；Power consumption of the millIt is expressed as
The yield n of grinding machine in time period ttFunctionProduce power consumptionIn normal range of operation, with adding material
Amount is approximately linear relationship, and its mathematic(al) representation is：
In formula：
A, b-be curve matching coefficient；
ntThe yield of grinding machine in-time period t；
When grinding machine puts into production again, can all there is extra cost consumption, the consumption of this departmental cost is designated as opening
Dynamic costIts calculation formula is：
In formula：
βsThe fixed cost consumed in-start-up course, such as maintenance cost or idle running cost；
utThe start and stop state of-t period raw mills, works as utWhen=1, represent to be in production process；utWhen=0, represent to be in
Halted state；
2）Decision variable：For the yield of grinding machine in time period t.
3）Constraints
A. yield is constrained：
WhereinWithThe lower and upper limit of mill output in the difference t periods；
B. storage constraint：
No more than its storage capacity to greatest extent, its constraints is the stored number of surge bunker:
WhereinWithThe upper and lower bound of surge bunker storage capacity in the difference t periods；
C. inventory balance is constrained：
The storage of surge bunker will meet demand of the following clinker production hourly to raw materialIts expression formula is：
Wherein StFor the amount of storage of t period surge bunkers, St-1For the amount of storage of t-1 period surge bunkers, ntFor grinding machine in the t periods
Yield,The demand to raw material is produced for t periods clinker
D. whole story stock constrains：
In order to guarantee to meet the demand beyond prediction, surge bunker should ensure that certain stock is remaining, its constraints
For:
SO-ST≤ε (26)
Wherein SOAnd STRespectively plan the quantity in stock of the phase whole story, ε is maximum for the permission of the difference of plan phase whole story quantity in stock
Value；
The formula shows that in the plan phase is all that the product produced by the same time is met to raw materials requirement amount, is considered
The inventory balance of each period constrains the Constraints of Equilibrium obtained in plan phase T：
If demand has relatively large deviation, it is necessary to re-establish optimal models with expected situation, by that section rethought
The quantity in stock that time starts is set to SO。
The multi-energy data Web Publishing is to realize multi-energy data Web Publishing by Web Server and EPA.
Real time data, historical data are generated dynamic page to scheme by the analysis at energy management center and statistics by Web Server
Literary form refreshes in real time, and inner-mesh network querying node terminal can pass through browser real-time query and retrieval.
Claims (6)
1. a kind of cement production enterprise energy information integrated management system, including DCS system and its Ethernet module, the OPC of offer connect
Mouthful, it is characterised in that also include
Coal, electricity, the collection network of three kinds of multi-energy datas of water：The I/O data collecting cards that coal powder consumption data acquisition instrument passes through DCS
Be connected with DCS system, electricity, Water Energy data acquisition instrument be connected by energy resource collecting optical fiber ring network with DCS system, for coal,
Electricity, the collection and transmission of three kinds of multi-energy datas of water；
Energy management server：Data interconnection is carried out by EPA with DCS system, for obtaining various multi-energy datas,
Each production link efficiency is calculated, and stores each multi-energy data, progress the inquiry of historical data, statistics, trend are shown and efficiency is to mark；
Energy source optimization server：For realizing that the dynamic of raw material and the coal dust production process energy is excellent using energy source optimization scheduling model
Change scheduling；
Inquire about terminal：To be one or more, pass through B/S network structures and the energy source optimization server, energy management server
It is connected, for inquiring about energy real time data and statistical report form；
Dispatching algorithm in the energy source optimization server includes：
1) object function
The target of dynamic price response optimization problem is exactly the maximum profit for producing raw material, i.e. production cost CTIt is minimum；It is intended to
Phase is denoted as T, is averaged and is divided into some period Δ t, and object function is expressed as：
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In formula：
- electric cost；
Cost in-production process, referred to as processing cost, are fixed cost, do not produce influence on object function；
- start the cost produced；
The carrying cost of-part, is fixed cost, does not produce influence on object function；
Electric costIt can be calculated according to below equation：
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In formula：
πtElectricity price in-t-th period；
The electricity that grinding machine is consumed in-time period t；
Grinding machine power consumption in time period tIt is related to the yield of grinding machine in time period t；Power consumption of the millIt is expressed as the time
The yield n of grinding machine in section ttFunctionProduce power consumptionIt is near with adding inventory in normal range of operation
It is seemingly linear relationship, its mathematic(al) representation is：
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In formula：
A, b-be curve matching coefficient；
ntThe yield of grinding machine in-time period t；
When grinding machine puts into production again, can all there is extra cost consumption, the consumption of this departmental cost is designated as starting into
ThisIts calculation formula is：
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In formula：
βsThe maintenance cost or idle running cost consumed in-start-up course, is fixed cost；
utThe start and stop state of-t period raw mills, works as utWhen=1, represent to be in production process；utWhen=0, represent to be in and stop
Only state；
2) decision variable：For the yield of grinding machine in time period t；
3) constraints
A. yield is constrained：
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WhereinNWithThe lower and upper limit of mill output in the difference t periods；
B. storage constraint：
No more than its storage capacity to greatest extent, its constraints is the stored number of surge bunker:
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</munder>
<mo>&le;</mo>
<mi>S</mi>
<mo>&le;</mo>
<mover>
<mi>S</mi>
<mo>&OverBar;</mo>
</mover>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>6</mn>
<mo>)</mo>
</mrow>
</mrow>
WhereinWithSThe upper and lower bound of surge bunker storage capacity in the difference t periods；
C. inventory balance is constrained：
The storage of surge bunker will meet demand of the following clinker production hourly to raw materialIts expression formula is：
<mrow>
<msup>
<mi>S</mi>
<mi>t</mi>
</msup>
<mo>=</mo>
<msup>
<mi>S</mi>
<mrow>
<mi>t</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
<mo>+</mo>
<msup>
<mi>n</mi>
<mi>t</mi>
</msup>
<mo>-</mo>
<msubsup>
<mi>N</mi>
<mi>D</mi>
<mi>t</mi>
</msubsup>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>7</mn>
<mo>)</mo>
</mrow>
</mrow>
Wherein StFor the amount of storage of t period surge bunkers, St-1For the amount of storage of t-1 period surge bunkers, ntProduced for grinding machine in the t periods
Amount,The demand to raw material is produced for t periods clinker
D. whole story stock constrains：
In order to guarantee to meet the demand beyond prediction, surge bunker should ensure that certain stock is remaining, and its constraints is:
|SO-ST|≤ε (8)
Wherein SOAnd STRespectively plan the quantity in stock of the phase whole story, ε is the permission maximum of the difference of plan phase whole story quantity in stock；
The formula shows that in the plan phase is all that the product produced by the same time is met to raw materials requirement amount, is considered each
The inventory balance of period constrains the Constraints of Equilibrium obtained in plan phase T：
<mrow>
<mo>|</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>t</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>T</mi>
</munderover>
<msup>
<mi>n</mi>
<mi>t</mi>
</msup>
<mo>-</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>t</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>T</mi>
</munderover>
<msubsup>
<mi>N</mi>
<mi>D</mi>
<mi>t</mi>
</msubsup>
<mo>|</mo>
<mo>&le;</mo>
<mi>&epsiv;</mi>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>9</mn>
<mo>)</mo>
</mrow>
</mrow>
If demand has relatively large deviation, it is necessary to re-establish optimal models with expected situation, by that time rethought
The quantity in stock of startup is set to SO。
2. a kind of cement production enterprise energy information integrated management system according to claim 1, it is characterised in that the coal dust
Consumption data acquisition instrument is coal powder metering device, and coal powder consumption data are read by DCS system from scene.
3. a kind of cement production enterprise energy information integrated management system according to claim 1, it is characterised in that the electricity,
Water Energy data acquisition instrument is the digital water meter and digital electric meter that each workshop is installed.
4. a kind of cement production enterprise energy information integrated management system according to claim 1, it is characterised in that the energy
The live real time data information storage of enterprise is arrived background data base system by management server, then carries out temporally or produce order of classes or grades at school system
Meter, analysis simultaneously draw various trend curves as needed, realize inquiry and the statistics of historical data.
5. a kind of cement production enterprise energy information integrated management system according to claim 1, it is characterised in that the energy
Management server is contrasted the real-time multi-energy data collected with national standard, provincial standard, industry internal standard.
6. a kind of cement production enterprise energy information integrated management system according to claim 1, it is characterised in that the energy
Optimization server sets up production process energy dynamic model, and the correlation energy in DCS OPC Server is read using OPC Client
Source data, result is write in DCS system, realize the energy to production process by OPC Client again after optimization computing
Optimization.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104819650A (en) * | 2015-04-09 | 2015-08-05 | 重庆华诚远志节能环保科技有限公司 | Intelligent control system of industrial furnace |
| CN106227181A (en) * | 2016-10-19 | 2016-12-14 | 玉门市华事达能源有限公司 | A kind of quick lime production line energy consumption intelligent monitor system |
| CN106656563B (en) * | 2016-11-10 | 2019-11-08 | 广东电网有限责任公司电力科学研究院 | ABB system control optimization data communication method and system based on mixed mode |
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| CN107666480A (en) * | 2017-09-01 | 2018-02-06 | 国网四川省电力公司绵阳供电公司 | Wisdom cell energy management system, hardware structure and information interacting method |
| CN109426205B (en) * | 2017-09-05 | 2021-03-16 | 万洲电气股份有限公司 | Industrial intelligent optimization energy-saving system |
| CN110501946A (en) * | 2019-08-22 | 2019-11-26 | 万洲电气股份有限公司 | A kind of energy management system based on coal mill energy-saving analysis diagnosis |
| CN111701697A (en) * | 2020-05-26 | 2020-09-25 | 上海万澄环保科技有限公司 | Cement raw material grinding system and automatic optimization control method thereof |
| TWI768545B (en) * | 2020-11-16 | 2022-06-21 | 臺泥資訊股份有限公司 | Method of controlling coal management system |
| CN113093674B (en) * | 2021-04-01 | 2022-09-20 | 万洲电气股份有限公司 | Cement production comprehensive unit consumption automatic analysis optimization system based on big data analysis |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1838006A (en) * | 2006-04-13 | 2006-09-27 | 上海交通大学 | Energy source consumption metering system for cement production enterprise |
| CN103106553A (en) * | 2012-11-12 | 2013-05-15 | 成都锦瑞投资有限公司 | Intelligent property resource management system based on Internet of Things and implementation method thereof |
-
2013
- 2013-11-15 CN CN201310572692.2A patent/CN104636815B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1838006A (en) * | 2006-04-13 | 2006-09-27 | 上海交通大学 | Energy source consumption metering system for cement production enterprise |
| CN103106553A (en) * | 2012-11-12 | 2013-05-15 | 成都锦瑞投资有限公司 | Intelligent property resource management system based on Internet of Things and implementation method thereof |
Non-Patent Citations (2)
| Title |
|---|
| 基于MES的水泥企业能效分析研究;许文梦;《中国优秀硕士学位论文全文数据库 工程科技Ⅰ辑》;20130415;第B015-85页，第7-8,16,18-24,29-30,32,42-43,48页 * |
| 基于群体平衡的球磨机粉磨过程动态仿真;吴星刚 等;《控制工程》;20110531;第18卷(第3期);第380-384页 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11853023B2 (en) | 2020-11-11 | 2023-12-26 | Tcc Information Systems Corp. | Method of controlling coal management system for reducing coal usage |
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