CN102156467A - Steel production planning-based energy forecasting method - Google Patents
Steel production planning-based energy forecasting method Download PDFInfo
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- CN102156467A CN102156467A CN2011100791150A CN201110079115A CN102156467A CN 102156467 A CN102156467 A CN 102156467A CN 2011100791150 A CN2011100791150 A CN 2011100791150A CN 201110079115 A CN201110079115 A CN 201110079115A CN 102156467 A CN102156467 A CN 102156467A
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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
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- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P80/00—Climate change mitigation technologies for sector-wide applications
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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
- Y02P90/80—Management or planning
Abstract
The invention provides steel production planning-based energy forecasting system and forecasting method. The forecasting system consists of a data acquisition network, an industrial ring network and a management network, wherein field real-time data of a measuring instrument and a programmable logic controller (PLC) is acquired through the data acquisition network, and output and consumption forecasting of an energy consumption unit in the future is realized by the energy forecasting module according to data of production plan, maintenance plan and equipment state acquired from enterprise resource planning (ERP) and manufacturing executive system (MES). The system can accurately forecast the energy output and consumption of a single unit or the whole enterprise according to the production plan, the maintenance plant and equipment state and other real time data, and provides basis for reasonable dispatching of energy of steel enterprises, thereby effectively reducing energy waste of the steel enterprises.
Description
Technical field
The invention belongs to iron and steel enterprise energy forecast field, particularly based on the energy forecast method of Iron and Steel Production plan.
Background technology
In the Iron and Steel Production total cost, energy cost accounts for 13%-15%.Energy prices are still in rising trend, and this will bring the huge market competitive pressure to the iron and steel enterprise of energy-dissipating type.This shows, energy savings, cut down the consumption of energy, increase the benefit and to be the strategic long-term objectives that steel and iron industry is taked in intense market competition.The general energy scheduling mode of iron company is a kind of artificial management mode of scheduling afterwards at present, can not carry out rational allocation, the balanced production of energy source and power in advance, reduces energy dissipation.
Summary of the invention
Provide the energy to produce the consumption data in order to reach 12 hours in advance to the dispatcher,, the invention provides a kind of energy forecast method based on the Iron and Steel Production plan to reduce energy dissipation.
The present invention adjusts principle definition energy consumption unit with critical process, the equipment of iron and steel enterprise according to product, as carrying out the quantity of energy collection in the system, producing the least unit that consumes statistics and energy forecast, calculates enterprise energy consumption.
The present invention need obtain real-time amount, the cumulative amount of each energy (produce, transform and consume) of all energy consumption units, unit duty, the production schedule, turnaround plan, information such as product yield.Each energy consumption unit is carried out by gathering these data real time data monitors, statistical study, and to crucial medium lack, long-term forecasting, be the service of producing to greatest extent.
Hardware net of the present invention comprises that with energy scheduling operating terminal and server system be the managerial grid that the basis is set up, and set up data acquisition network with the instrument of energy consumption unit, connect by optical fiber, realize between each server, the data interaction between terminal and the server.
The software supporting with said system comprises the data acquisition module program, the data interface module program, the data processing module program, the energy forecast modular program, it has realized the data acquisition of energy consumption unit, unit historical data statistics, based on the multipotency source medium forecast function of the production schedule.
Network of the present invention is the compound network of the multi-service form of the data acquisition of a collection field instrument, energy monitor, energy management, data backup and one, total system is made of three-layer network, the data acquisition network that ground floor is made up of commercial unit and instrument, remote-terminal unit (RTU), the second layer is industrial looped network, the 3rd layer of supervising the network of being made up of the energy management network equipment and server.
Described industrial looped network is made of industrial switch and 1000M optical fiber ring network, according to plant area's location distribution of iron and steel enterprise's energy process system, forms a looped network.
Described commercial unit and instrument are connected respectively on each substation of industrial looped network, form the Star Network structure.
Supervising the network carries the communication work of database server, model service device, fire wall and each terminal, and unique path of data also is provided as ERP system simultaneously.
Server system of the present invention comprises data acquisition server, database server, model service device, external interface server.
Data acquisition server is used for storing on-the-spot real time data, by the Standards Code driver real time data of data acquisition equipment and on-the-spot PLC is imported in the data acquisition real-time data base.
Data acquisition server is connected on respectively on industrial switch and the core switch.Solaris10 operating system, distributing real-time data bank system are installed on data acquisition server.Data acquisition server is finished intermediate quantity calculating, semi-invariant calculating, trend, warning, data and function such as is filed in short-term.
The energy management database server is installed Windows Sever operating system, the Oracle relational database is stored on-the-spot energy consumption unit per 15 minutes energy inputs, production equipment virtual condition, device fabrication plan, turnaround plan data by interface server.
The external interface server by network with the data transmission of data acquisition server, outside ERP system in the management database server, and the total interface data are preserved, provide foundation for inquiring about problem data from now on.The model service device is installed Windows Sever operating system, the model of the historical energy consumption statistic of energy consumption unit, energy forecast, and the data storing of the various energy forecasts that will calculate is in the energy management database server at last.
The effect of described data acquisition module program is to collect the basic energy resource data that native system needs by being distributed in each data acquisition station of full company.The running status, the energy resource consumption data that comprise main power consumption unit; Electric weight (peak, flat, paddy, total meritorious) and power signal are gathered in electric system.These data are gathered various instrument in real time by remote-terminal unit (RTU), and per 10 seconds is a collection period.The data transmission of above-mentioned collection in the MOSAIC real-time data base, is done initial analysis to these data and handled in real-time data base, the range of data is converted to unified engineering unit, data are carried out high lower bound relatively.
The data interface module program comprises: relational database and real-time dataBase system interface, with factory process control L2 system interface, with the ERP/MES system interface.With the interactive information of real-time data base be mainly actual rate-of flow (Nm3/min, kg/min, L/min, kW ...), the rate-of flow of accumulation (Nm3, kg, L, kWh ...) and etc. consumption information; Be mainly the practical production status of energy consumption unit with the interactive information of factory process control L2 system; With the interactive information of ERP/MES system be the production schedule and the turnaround plan data of energy consumption unit.
The data processing module program is that the instrumented data of real-time collection is handled, and calculates the power consumption data of each energy consumption unit.For each energy consumption unit, calculated the once consumption of corresponding energy medium in per 15 minutes, be used to predict the trend of unit energy consumption.Each data that enters system all will be carried out data processing, guarantee the validity of input data.The function of this module has the validity check of data and data to replace two functions.
The energy forecast modular program is to set up the energy forecast model, more than the effect of 3 modules be that module is prepared data for this reason.The per 15 minutes energy that the energy forecast model of this module is based on equipment produce consumption historical data, Iron and Steel Production plan, turnaround plan and unit production status, have set up the method for a cover energy forecast.
Energy forecast is divided into two kinds of short-term and long-term forecastings.Short-term forecasting is produced consumption to the energy in 12 hours and is predicted, calculates once in per 15 minutes, and purpose is the foundation that Optimization Dispatching is provided to energy scheduling.Long-term forecasting is predicted the energy-output ratio in 7 days, calculates once in per 1 day, and purpose is to provide the outsourcing quantity of energy to iron and steel enterprise, produces energy outsourcing plan.
Energy forecast method based on the Iron and Steel Production plan comprises the steps:
1, builds the network system of energy management, set up industrial looped network and energy management network, on-the-spot energy measurement instrument is connected to industrial looped network by remote-terminal unit, the PLC of production control system is connected to industrial looped network, on looped network, set up gps clock, keep time synchronized between server.Be connected with network between other external system and set up fire wall;
2. connect energy data acquisition server, interface server, model service device, database server at the energy management network, and corresponding operating system and application software are installed;
3. data acquisition server is arrived in the real-time product consumption data acquisition of field apparatus, and store several adopting in the real-time data base of server into the form of label;
4. by data interface module real time data and external system ERP, MES, the production schedule of L2, turnaround plan, device status data are collected in the interface server, interface server docking port data are done short-term storage, and with data transmission in database server;
5. installation data processing module and energy forecast module in the model service device, data processing module carries out efficiency analysis with the data that interface server transmits up, with the data that data conversion can be used for the energy forecast module, wherein the efficiency analysis of data comprises several aspects down:
I, numerical range inspection: lower limit≤energy produces consumption value≤upper limit;
Ii, maximum recruitment: check whether current data and previous data deviation surpass the maximum deviation amount;
Iii, balance check: for a unit, all quantity of energy input=unit consumption+excess losses;
The state that iv, flag data are checked.
When the data value status indication is invalid, a replacement value will be provided, these are marked as by the values of replacing functionality change or insertion and are positive status more; Its replacement method comprises following several:
I, exceed bound when data, can select to ignore mistake, use current value through judging;
Ii, gather when wrong, use a correct numerical value when certain instrumented data;
Iii, data are all gathered mistake in a period of time, use the mean value of a period of time;
Iv, the value that can use other several measured values to calculate are calculated;
6. carry out system modelling according to all data, generate energy forecast curve and form; Can carry out manual adjustment to the input data.System modelling is made up of following step:
I, read energy measurement semi-invariant data, calculate per 15 minutes energy consumption datas of energy consumption unit.As: the energy medium of certain energy consumption unit has media such as electricity, oxygen, argon gas, water.Then calculate the consumption figures of various media respectively.
Then:
The energy I of per 15 minutes internal consumptions
Poweri=Q
i-Q
I-1(1)
In the formula: Q
i-current semi-invariant data; Q
I-1Semi-invariant data before-15 minutes; I
PoweriEnergy resource consumption value in the-set time.
If the consumption data in the computation period T, then
The various media of this energy consumption unit all will calculate, and the energy source data of each time period all is kept in the database server.The calculating that is not always the case of each energy consumption unit.
Ii, generate to produce the consumption curve according to the Iron and Steel Production plan.If it is to produce in 0-45 hourly minute that certain energy consumption unit is produced the production schedule of certain steel grade, standby in 46-60 minute, with reference to historical energy consumption data, the energy resource consumption data in conjunction with before 15 minutes then generate the intraday energy resource consumption curve of this unit.Formula is as follows:
M(t)＝M_Fixed+(M_var(t)×Corr(prod(t)) (3)
M_var(t)＝m_var×rate_prod(t) (4)
In the formula: the energy medium consumption in M (t)-predicted time t; The fixed sources of energy proportion of goods damageds of M_Fixed-unit draw according to the empirical value when unit is unloaded; M_var (t)-according to the variable unit specific consumption of iron and steel output; The correction parameter of different product attribute in Corr (prod (t))-identical steel grade (for example size, initial and final temperature) is adjusted into suitable numerical value according to on-site actual situations; The scaduled sequence of prod (t)-product number; The different steel grade energy-output ratios of m_var-, every kind of medium is a preset parameter, obtains by the Iron and Steel Production experience; Rate_prod (t)-planned product output obtains from ERP and MES;
Iii, adjust energy curve according to turnaround plan, program can be adjusted energy curve according to the parking maintenance plan of unit after generating energy curve, after generating energy curve as electric furnace according to the production schedule, and want the temporary parking maintenance at the 7-9 point, then need the typing repair time, Automatic Program is adjusted energy curve;
Iv, detection set state are divided into ordinary production, shutdown, three kinds of power consumption states of standby to unit.If prediction power consumption state is consistent with the unit current state, then do not adjust energy curve, if predicted state and set state are inconsistent, then recomputate energy curve.
V, draw the All Media energy forecast curve of each energy consumption unit at last, all unit energy curves stacks of iron and steel enterprise are drawn the total energy forecast curve of whole enterprise.
7. utilize terminal to check that the energy produces the consumption data and generates form.The terminal of native system can be with B/S and two kinds of method link models of C/S server.
The present invention is by analyzing the historical data of Iron and Steel Production equipment energy resource consumption, short-term/long-term production plan, turnaround plan in conjunction with Iron and Steel Production, set up multimedium energy forecast model based on the production schedule, can produce consumption to the energy of single unit or whole enterprise and do accurately predicting, for rationally arranging energy scheduling that foundation is provided, reduced the energy dissipation of iron and steel enterprise effectively.
Description of drawings
Fig. 1 is a hardware net synoptic diagram of the present invention.
Fig. 2 is a functional module block scheme of the present invention.
Fig. 3 is a process flow diagram of the present invention.
Among the figure, 1, the model service device, 2, database server, 3, interface server, 4, fire wall, 5, data acquisition server, 6, gps clock, 7, terminal computer, 8, steel rolling PLC, 9, technology instrument, 10, steel-making PLC, 11, measuring instrument, 12, stokehold PLC.
Embodiment
Embodiment: Fig. 1, Fig. 2, shown in Figure 3, the hardware of present embodiment comprises that energy scheduling operating terminal and server reach the supervising the network of setting up for the basis with its system, and set up data acquisition network with the instrument of energy consumption unit, connect by optical fiber, realize between each server, the data interaction between terminal and the server.
The software supporting with said system comprises the data acquisition module program, the data interface module program, the data processing module program, the energy forecast modular program, it has realized the data acquisition of energy consumption unit, unit historical data statistics, based on the multipotency source medium forecast function of the production schedule.
Network of the present invention is the compound network of the multi-service form of the data acquisition of a collection field instrument, energy monitor, energy management, data backup and one, total system is made of three-layer network, the data acquisition network that ground floor is made up of commercial unit and instrument 9,11, remote-terminal unit (RTU), the second layer is industrial looped network, the 3rd layer of supervising the network of being made up of the energy management network equipment and server.
Described industrial looped network is made of industrial switch and 1000M optical fiber ring network, according to plant area's location distribution of iron and steel enterprise's energy process system, forms a looped network.
Described commercial unit and instrument are connected respectively on each substation of industrial looped network, form the Star Network structure.
Supervising the network carries the communication work of database server 2, model service device 1, fire wall 4 and each terminal, and unique path of data also is provided as ERP system simultaneously.
Server system of the present invention comprises data acquisition server 5, database server 2, model service device 1, external interface server 3.
Data acquisition server is used for storing on-the-spot real time data, by the Standards Code driver data acquisition equipment and on-the-spot PLC11,8 real time data is imported in the data acquisition real-time data base.
Data acquisition server is connected on respectively on industrial switch and the core switch.Solaris10 operating system, distributing real-time data bank system are installed on data acquisition server.Data acquisition server is finished intermediate quantity calculating, semi-invariant calculating, trend, warning, data and function such as is filed in short-term.
The energy management database server is installed Windows Sever operating system, the Oracle relational database is stored on-the-spot energy consumption unit per 15 minutes energy inputs, production equipment virtual condition, device fabrication plan, turnaround plan data by interface server.
The external interface server by network with the data transmission of data acquisition server, outside ERP system in the management database server, and the total interface data are preserved, provide foundation for inquiring about problem data from now on.The model service device is installed Windows Sever operating system, the model of the historical energy consumption statistic of energy consumption unit, energy forecast, and the data storing of the various energy forecasts that will calculate is in the energy management database server at last.
The effect of data acquisition module program is to collect the basic energy resource data that native system needs by being distributed in each data acquisition station of full company.The running status, the energy resource consumption data that comprise main power consumption unit; Electric weight (peak, flat, paddy, total meritorious) and power signal are gathered in electric system.These data are gathered various instrument in real time by remote-terminal unit (RTU), and per 10 seconds is a collection period.The data transmission of above-mentioned collection in the MOSAIC real-time data base, is done initial analysis to these data and handled in real-time data base, the range of data is converted to unified engineering unit, data are carried out high lower bound relatively.
Data interface module comprises: relational database and real-time dataBase system interface, with factory process control L2 system interface, with the ERP/MES system interface.With the interactive information of real-time data base be mainly actual rate-of flow (Nm3/min, kg/min, L/min, kW ...), the rate-of flow of accumulation (Nm3, kg, L, kWh ...) and etc. consumption information; Be mainly the practical production status of energy consumption unit with the interactive information of factory process control L2 system; With the interactive information of ERP/MES system be the production schedule and the turnaround plan data of energy consumption unit.
Energy forecast method based on the Iron and Steel Production plan comprises the steps:
1, builds the network system of energy management, set up industrial looped network and energy management network, on-the-spot energy measurement instrument is connected to industrial looped network by remote-terminal unit, the PLC of production control system is connected to industrial looped network, on looped network, set up gps clock 6, keep time synchronized between server.Be connected with network between other external system and set up fire wall 4;
2. connect energy data acquisition server, interface server, model service device, database server at the energy management network, and corresponding operating system and application software are installed;
3. data acquisition server is arrived in the real-time product consumption data acquisition of field apparatus, and store several adopting in the real-time data base of server into the form of label;
4. by data interface module real time data and external system ERP, MES, the production schedule of L2, turnaround plan, device status data are collected in the interface server, interface server docking port data are done short-term storage, and with data transmission in database server;
5. installation data processing module and energy forecast module in the model service device, data processing module carries out efficiency analysis with the data that interface server transmits up, with the data that data conversion can be used for the energy forecast module, wherein the efficiency analysis of data comprises several aspects down:
I, numerical range inspection: lower limit≤energy produces consumption value≤upper limit;
Ii, maximum recruitment: check whether current data and previous data deviation surpass the maximum deviation amount;
Iii, balance check: for a unit, all quantity of energy input=unit consumption+excess losses;
The state that iv, flag data are checked; Wherein when the data value status indication be invalid, a replacement value will be provided, these are marked as by the values of replacing functionality change or insertion and are positive status more, its replacement method comprises following several:
I, exceed bound when data, can select to ignore mistake, use current value through judging;
Ii, gather when wrong, use a correct numerical value when certain instrumented data;
Iii, data are all gathered mistake in a period of time, use the mean value of a period of time;
Iv, the value that can use other several measured values to calculate are calculated;
6. carry out system modelling according to all data, generate energy forecast curve and form; Can carry out manual adjustment to the input data.System modelling is made up of following step:
I, read energy measurement semi-invariant data, calculate per 15 minutes energy consumption datas of energy consumption unit.As: the energy medium of certain energy consumption unit has media such as electricity, oxygen, argon gas, water.Then calculate the consumption figures of various media respectively.
Then:
The energy I of per 15 minutes internal consumptions
Poweri=Q
i-Q
I-1(1)
In the formula: Q
i-current semi-invariant data; Q
I-1Semi-invariant data before-15 minutes; I
PoweriEnergy resource consumption value in the-set time.
If the consumption data in the computation period T, then
The various media of this energy consumption unit all will calculate, and the energy source data of each time period all is kept in the database server.The calculating that is not always the case of each energy consumption unit.
Ii, generate to produce the consumption curve according to the Iron and Steel Production plan.If it is to produce in 0-45 hourly minute that certain energy consumption unit is produced the production schedule of certain steel grade, standby in 46-60 minute, with reference to historical energy consumption data, the energy resource consumption data in conjunction with before 15 minutes then generate the intraday energy resource consumption curve of this unit.Formula is as follows:
M(t)＝M_Fixed+(M_var(t)×Corr(prod(t)) (3)
M_var(t)＝m_var×rate_prod(t) (4)
In the formula: the energy medium consumption in M (t)-predicted time t; The fixed sources of energy proportion of goods damageds of M_Fixed-unit draw according to the empirical value when unit is unloaded; M_var (t)-according to the variable unit specific consumption of iron and steel output; The correction parameter of different product attribute in Corr (prod (t))-identical steel grade (for example size, initial and final temperature) is adjusted into suitable numerical value according to on-site actual situations; The scaduled sequence of prod (t)-product number; The different steel grade energy-output ratios of m_var-, every kind of medium is a preset parameter, obtains by the Iron and Steel Production experience; Rate_prod (t)-planned product output obtains from ERP and MES;
Iii, adjust energy curve according to turnaround plan, program can be adjusted energy curve according to the parking maintenance plan of unit after generating energy curve, after generating energy curve as electric furnace according to the production schedule, and want the temporary parking maintenance at the 7-9 point, then need the typing repair time, Automatic Program is adjusted energy curve;
Iv, detection set state are divided into ordinary production, shutdown, three kinds of power consumption states of standby to unit.If prediction power consumption state is consistent with the unit current state, then do not adjust energy curve, if predicted state and set state are inconsistent, then recomputate energy curve.
V, draw the All Media energy forecast curve of each energy consumption unit at last, all unit energy curves stacks of iron and steel enterprise are drawn the total energy forecast curve of whole enterprise.
7. utilize terminal to check that the energy produces the consumption data and generates form.The terminal of native system can be with B/S and two kinds of method link models of C/S server.
Claims (7)
1. based on the energy forecast method of Iron and Steel Production plan, comprise that with energy scheduling operating terminal and server system be the managerial grid that the basis is set up, and set up data acquisition network with the instrument of energy consumption unit, connect by optical fiber, realize between each server, the data interaction between terminal and the server system, server system comprises data acquisition server, database server, model service device, external interface server, data acquisition server is connected on respectively on industrial switch and the core switch, it is characterized in that comprising the steps:
(1). build the network system of energy management, set up industrial looped network and energy management network, on-the-spot energy measurement instrument is connected to industrial looped network by remote-terminal unit, the PLC of production control system is connected to industrial looped network, on looped network, set up gps clock, keep time synchronized between server, be connected with network between other external system and set up fire wall;
(2). connect energy data acquisition server, interface server, model service device, database server in the energy management network system, and corresponding operating system and application software are installed;
(3). data acquisition server is arrived in the real-time product consumption data acquisition of field apparatus, and store several adopting in the real-time data base of server into the form of label;
(4). by data interface module real time data and external system ERP, MES, the production schedule of L2, turnaround plan, device status data are collected in the interface server, interface server docking port data are done short-term storage, and with data transmission in database server;
(5). installation data processing module and energy forecast module in the model service device, data processing module carries out efficiency analysis with the data that interface server transmits up, the data that data conversion can be used for the energy forecast module;
(6). carry out system modelling according to all data, generate energy forecast curve and form;
(7). utilize terminal to check that the energy produces the consumption data and generates form.
2. the energy forecast method based on the Iron and Steel Production plan according to claim 1, it is characterized in that described managerial grid is made of three-layer network, the data acquisition network that ground floor is made up of commercial unit and instrument, remote-terminal unit, the second layer is industrial looped network, the 3rd layer of supervising the network of being made up of the energy management network equipment and server.
3. the energy forecast method based on the Iron and Steel Production plan according to claim 2, it is characterized in that described industrial looped network is made of industrial switch and 1000M optical fiber ring network, plant area's location distribution according to iron and steel enterprise's energy process system, form a looped network, commercial unit and instrument are connected respectively on each substation of industrial looped network, form the Star Network structure.
4. the energy forecast method based on the Iron and Steel Production plan according to claim 1, it is characterized in that described data acquisition server is used for storing on-the-spot real time data, by the Standards Code driver real time data of data acquisition equipment and on-the-spot PLC is imported in the data acquisition real-time data base, Solaris10 operating system is installed on data acquisition server, the distributing real-time data bank system, data acquisition server is finished the function that intermediate quantity calculating, semi-invariant calculating, trend, warning, data are filed in short-term.
5. the energy forecast method based on the Iron and Steel Production plan according to claim 1, it is characterized in that described energy management database server installation Windows Sever operating system, the Oracle relational database is stored on-the-spot energy consumption unit per 15 minutes energy inputs, production equipment virtual condition, device fabrication plan, turnaround plan data by interface server.
6. the energy forecast method based on the Iron and Steel Production plan according to claim 1, it is characterized in that described external interface server by network with the data transmission of data acquisition server, outside ERP system in the management database server, and the total interface data are preserved, provide foundation for inquiring about problem data from now on, the model service device is installed WindowsSever operating system, the model of the historical energy consumption statistic of energy consumption unit, energy forecast, the data storing of the various energy forecasts that will calculate is in the energy management database server at last.
7. the energy forecast method based on the Iron and Steel Production plan according to claim 1 is characterized in that described system modelling is made up of following step:
(1) reads energy measurement semi-invariant data, calculate per 15 minutes energy consumption datas of energy consumption unit, and the energy source data of each time period all is kept in the database server energy I of wherein per 15 minutes internal consumptions
Poweri=Q
i-Q
I-1, the consumption data in the period T is
(2) generate product consumption curve according to the Iron and Steel Production plan, formula is as follows:
M(t)＝M_Fixed+(M_var(t)×Corr(prod(t))
M_var(t)＝m_var×rate_prod(t)
(3) adjust energy curve according to turnaround plan, program can be adjusted energy curve according to the parking maintenance plan of unit behind the generation energy curve;
(4) detect set state, unit is divided into ordinary production, shutdown, three kinds of power consumption states of standby,, does not then adjust energy curve if prediction power consumption state is consistent with the unit current state, if predicted state and set state are inconsistent, then recomputate energy curve;
(5) draw the All Media energy forecast curve of each energy consumption unit, all unit energy curves stacks of iron and steel enterprise are drawn the total energy forecast curve of whole enterprise.
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Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102419834A (en) * | 2011-09-24 | 2012-04-18 | 山西太钢不锈钢股份有限公司 | Enterprise energy settlement system |
| CN102682197A (en) * | 2012-04-25 | 2012-09-19 | 深圳市海亿达能源科技股份有限公司 | Monitoring method and monitoring device for predicating change trend of energy consumption of single equipment in real time |
| CN103136895A (en) * | 2013-01-25 | 2013-06-05 | 东北大学 | Furnace group energy consumption system and method in fused magnesia smelting process |
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| CN107091571A (en) * | 2017-04-12 | 2017-08-25 | 东华大学 | A kind of online real-time alarm system of sintering machine energy resource consumption and method |
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| CN112711229A (en) * | 2020-12-09 | 2021-04-27 | 万洲电气股份有限公司 | Intelligent optimization energy-saving system based on multi-correlation factor energy consumption prediction |
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| CN102419834B (en) * | 2011-09-24 | 2015-02-25 | 山西太钢不锈钢股份有限公司 | Enterprise energy settlement system |
| CN102419834A (en) * | 2011-09-24 | 2012-04-18 | 山西太钢不锈钢股份有限公司 | Enterprise energy settlement system |
| CN102682197A (en) * | 2012-04-25 | 2012-09-19 | 深圳市海亿达能源科技股份有限公司 | Monitoring method and monitoring device for predicating change trend of energy consumption of single equipment in real time |
| CN103136895A (en) * | 2013-01-25 | 2013-06-05 | 东北大学 | Furnace group energy consumption system and method in fused magnesia smelting process |
| CN106292584A (en) * | 2016-08-16 | 2017-01-04 | 苏州朋泰智能科技有限公司 | A kind of flexible manufacturing system based on modular control unit |
| CN106325242A (en) * | 2016-08-16 | 2017-01-11 | 苏州朋泰智能科技有限公司 | MES system based on modularized control units |
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| CN107091571A (en) * | 2017-04-12 | 2017-08-25 | 东华大学 | A kind of online real-time alarm system of sintering machine energy resource consumption and method |
| CN108303947A (en) * | 2018-02-28 | 2018-07-20 | 广东闻扬环境科技有限公司 | Applied to the data processing method of MVR vapo(u)rization systems, device, computer equipment and storage medium |
| CN108677408A (en) * | 2018-05-07 | 2018-10-19 | 襄阳信正纺织有限公司 | A kind of yarn dyeing and finishing technology |
| CN108677416A (en) * | 2018-05-07 | 2018-10-19 | 襄阳信正纺织有限公司 | A kind of yarn processing method |
| CN108677415A (en) * | 2018-05-07 | 2018-10-19 | 襄阳信正纺织有限公司 | A kind of yarn sizing method |
| CN108677408B (en) * | 2018-05-07 | 2021-03-16 | 襄阳信正纺织有限公司 | Yarn dyeing and finishing process |
| CN108677416B (en) * | 2018-05-07 | 2021-06-08 | 襄阳信正纺织有限公司 | Yarn processing method |
| CN108646692A (en) * | 2018-07-11 | 2018-10-12 | 山东聚鑫集团钢结构有限公司 | A kind of C-type steel manufactures process data monitoring system |
| CN111930721A (en) * | 2020-09-11 | 2020-11-13 | 山东钢铁集团日照有限公司 | Method for integrating multi-attribute continuous industrial production data |
| CN112711229A (en) * | 2020-12-09 | 2021-04-27 | 万洲电气股份有限公司 | Intelligent optimization energy-saving system based on multi-correlation factor energy consumption prediction |
| CN113050573A (en) * | 2021-03-26 | 2021-06-29 | 山东莱钢永锋钢铁有限公司 | Production rhythm-based energy-saving method for air compressor |
| CN114694356A (en) * | 2022-02-25 | 2022-07-01 | 阳春新钢铁有限责任公司 | Automatic identification and alarm system for hidden danger level of steel production equipment |
| CN114694356B (en) * | 2022-02-25 | 2024-03-19 | 阳春新钢铁有限责任公司 | Automatic identification alarm system for hidden danger level of steel production equipment |
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