CN111798103B - Real-time evaluation method and system for energy efficiency of anode furnace - Google Patents

Real-time evaluation method and system for energy efficiency of anode furnace Download PDF

Info

Publication number
CN111798103B
CN111798103B CN202010545601.6A CN202010545601A CN111798103B CN 111798103 B CN111798103 B CN 111798103B CN 202010545601 A CN202010545601 A CN 202010545601A CN 111798103 B CN111798103 B CN 111798103B
Authority
CN
China
Prior art keywords
anode furnace
consumption
furnace
anode
natural gas
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202010545601.6A
Other languages
Chinese (zh)
Other versions
CN111798103A (en
Inventor
阙锦龙
姚俊峰
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Xiamen University
Original Assignee
Xiamen University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Xiamen University filed Critical Xiamen University
Priority to CN202010545601.6A priority Critical patent/CN111798103B/en
Publication of CN111798103A publication Critical patent/CN111798103A/en
Application granted granted Critical
Publication of CN111798103B publication Critical patent/CN111798103B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/04—Manufacturing
    • 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

Landscapes

  • Business, Economics & Management (AREA)
  • Human Resources & Organizations (AREA)
  • Engineering & Computer Science (AREA)
  • Strategic Management (AREA)
  • Economics (AREA)
  • Development Economics (AREA)
  • Theoretical Computer Science (AREA)
  • Marketing (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Educational Administration (AREA)
  • Tourism & Hospitality (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • General Health & Medical Sciences (AREA)
  • Manufacturing & Machinery (AREA)
  • Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Game Theory and Decision Science (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Vertical, Hearth, Or Arc Furnaces (AREA)

Abstract

The invention provides an anode furnace energy efficiency evaluation method and system, wherein the method comprises the following steps: and (4) acquiring six indexes of natural gas consumption of unit products of the anode furnace, oxygen consumption of unit products of the anode furnace, nitrogen consumption of unit products of the anode furnace, compressed air consumption of unit products of the anode furnace, electric energy consumption of unit products of the anode furnace and comprehensive energy consumption of unit products of the anode furnace in a statistical period to optimize and evaluate the anode furnace. The invention can realize the comprehensive evaluation of the energy efficiency of the anode furnace.

Description

Real-time evaluation method and system for energy efficiency of anode furnace
Technical Field
The application relates to the technical field of industry, in particular to a real-time evaluation method and system for energy efficiency of an anode furnace.
Background
The anode furnace is important equipment in the copper smelting process and also important energy-consuming equipment. The fuel and the reducing agent of the anode furnace both adopt natural gas, the oxidizing agent is compressed air, and a gas permeable brick stirring system using nitrogen is added at the bottom of the furnace. The essence of the anode furnace blister copper converting is to remove impurities in the copper by oxidation and to produce a blister copper product of desired grade, the blister copper and cold copper are fed into the anode furnace and after reaction in the anode furnace, refined copper liquor is fed out with concomitant production of slag, fumes and dust, which requires a suitable oxygen amount for the oxidation reaction given different raw materials and different feed amounts. However, in the copper smelting production process, the physical and chemical processes in the furnace are very complicated, and the expected effect cannot be achieved by depending on manual experience under the condition of large-scale industrial production. Therefore, it is necessary to research an energy efficiency real-time evaluation model, which describes various energy consumptions in the furnace by a mathematical method, and is used for calculating optimal process parameters under different process conditions, so as to achieve the purposes of stable product quality, reduced energy consumption and prolonged furnace body life.
The anode furnace has large consumption in the working process, and at present, no scientific evaluation method aiming at the energy efficiency of the anode furnace exists. How to evaluate the energy efficiency of the anode furnace better and more comprehensively and provide a reference basis for the improvement of the anode furnace is a technical problem to be solved urgently by technical personnel in the field at present.
Disclosure of Invention
In view of the above-mentioned drawbacks and deficiencies of the prior art, an object of the present invention is to provide a method and a system for real-time evaluation of anode furnace energy efficiency, so as to achieve comprehensive evaluation of anode furnace energy efficiency. To help the anode furnace reduce energy consumption and find the best combination of electricity, natural gas, oxygen, electrical energy, nitrogen and compressed air.
In a first aspect, an embodiment of the present application provides a method for evaluating energy efficiency of an anode furnace in real time, where the method includes: 1. a real-time evaluation method for energy efficiency of an anode furnace is characterized by comprising the following steps:
step 1: collecting the operation data of the anode furnace in a statistical period;
specifically, consumption data of the anode furnace in a statistical period are collected, wherein the consumption data comprise electricity, natural gas, oxygen, electric energy, nitrogen and compressed air, delta t is used as a time unit in the statistical period, k is the number of the time unit, and a numerical reading mode comprises a DCS (distributed control system) online reading value, an artificial set value and an artificial input value of each furnace period, wherein the DCS online reading value is an instantaneous value, a sampling period is 1 minute, the acquisition is carried out at the whole time, the artificial input value of each furnace period aims at the characteristic of intermittent production of the anode furnace, and when heat balance calculation is carried out on each furnace period, a value required by the corresponding furnace period is input according to a report of the same day to carry out calculation on the heat efficiency; step 2: constructing an anode furnace energy efficiency evaluation index model:
2.1, calculating the consumption natural gas quantity Q of the anode furnace in the statistical periodAR_AF1_mathane：
Figure BDA0002540591820000021
Wherein
Figure BDA0002540591820000022
t1To count the initial time of the period, t2K is the number of time units, N is the time unit contained in the statistic period, qAR_AF1_methane1(k.DELTA.t) is the natural gas flow rate for reduction at the time of k.DELTA.t in Nm3/h，
qAR_AF1_methane2(k. DELTA.t) is the natural gas flow rate for combustion at the time k. DELTA.t in Nm3/h，tAR_AF1_startIs the initial moment of the statistical period; t is tAR_AF1_endFor the end time of the statistical period, t is set under the current sampling periodAR_AF1_start-tAR_AF1_endOne furnace period of the anode furnace;
2.2, calculating oxygen consumption QAR _ AF1_ Q2 of the anode furnace in the statistical period:
Figure BDA0002540591820000023
wherein,
Figure BDA0002540591820000027
is the oxygen flow of a J tube of the anode furnace, and has the unit of Nm3/h,
Figure BDA0002540591820000028
the oxygen flow rate of an L pipe of the anode furnace is Nm3/h, and the anode furnace inputs oxygen through a J pipe and the L pipe;
2.3, calculating QAR _ AF1_ N2 of nitrogen consumption of the anode furnace in the statistical period:
Figure BDA0002540591820000024
wherein,
Figure BDA0002540591820000025
the nitrogen flow rate for the reduction at time k.DELTA.t, in Nm3/h,
Figure BDA0002540591820000026
the nitrogen flow rate of the air brick at the time k.DELTA.t is measured in Nm3/h；
2.4, calculating the quantity Q of the compressed air consumed by the anode furnace in the statistical periodAR_AF1_comp_air：
Figure BDA0002540591820000031
Wherein,
Figure BDA0002540591820000032
the compressed air flow rate at time k.DELTA.t is in Nm3/h；
2.5, calculating the electric energy consumption Q of the anode furnace in the statistical periodAR_AF1_electric：
QAR_AF1_electric＝Qelectric_AF1_low_electric，
Wherein Q iselectric_AF1_low_electricFor the anode furnace in the statistical period, the low-voltage distribution chamber of the anode furnace is opposite to the anode furnaceThe unit of the power supply is kW.h;
2.6, calculating the comprehensive energy consumption E of the anode furnace in the statistical periodP：
Ep＝∑QAF1_i×pi，
Wherein: qAF1_i(i＝methane,Q2,N2Comp _ air) is the consumption of various energy consuming working media, piCalculating the energy conversion coefficient according to the conversion standard coal coefficient of the energy or the energy value of the energy consumption working medium and the like;
2.7, calculating the anode copper yield MAR _ AF1_ hopper of one furnace period of the anode furnace:
Figure BDA0002540591820000033
wherein m isM_AR_disk_outThe copper yield per hour of the disc casting machine is represented by t/h; delta tAR_AF1_JZThe length of the casting time of the furnace period is h;
2.8, calculating the natural gas consumption of the unit product of the anode furnace in the statistical period eAR _ AF1_ methane:
Figure BDA0002540591820000034
2.9, calculating the oxygen consumption of the anode furnace unit product in the statistical period eAR _ AF1_ Q2:
Figure BDA0002540591820000035
2.10, calculating the nitrogen consumption e of the unit product of the anode furnace in the statistical periodAR_AF1_N2：
Figure BDA0002540591820000036
2.11, calculating the compressed air consumption e of the unit product of the anode furnace in the statistical periodAR_AF1_Q2：
Figure BDA0002540591820000037
2.13, calculating the electric energy consumption e of the unit product of the anode furnace in the statistical periodAR_AF1_electric：
Figure BDA0002540591820000041
2.13, calculating the comprehensive energy consumption e of the unit product of the anode furnace in the statistical periodp1：
ep1＝∑(ei×pi),tce/t；
Wherein e isi＝methane,Q2,N2Comp _ air and electric respectively represent five main energy sources consumed by the anode furnace; p is a radical of formulaiAnd calculating the conversion coefficient of the energy i according to the conversion standard coal coefficient of the energy or the energy value of the energy consumption working medium and the like.
And 3, optimizing and evaluating the anode furnace based on six indexes of natural gas consumption of unit products of the anode furnace, oxygen consumption of unit products of the anode furnace, nitrogen consumption of unit products of the anode furnace, compressed air consumption of unit products of the anode furnace, electric energy consumption of unit products of the anode furnace and comprehensive energy consumption of unit products of the anode furnace, and displaying the evaluation result.
In a second aspect, the present application provides an anode furnace energy efficiency real-time evaluation system, which is characterized in that the system includes: the DCS module is used for acquiring data acquisition services deployed on a production site and used for acquiring real-time production data of an anode furnace workshop and other workshops, wherein the data comprises natural gas, oxygen, nitrogen, compressed air, electric energy and product yield data required by anode furnace energy efficiency evaluation;
the data synchronization module is used for synchronizing the DCS data to the MongoDB database so as to be stored for a long time;
the MongDB module is used for storing the production data synchronized by the DCS module and the service data used by the energy efficiency evaluation system;
the energy efficiency evaluation service module is used for acquiring production data from the MongoDB in real time and calculating the energy efficiency of the anode furnace in real time through the anode furnace energy efficiency evaluation index model;
the Web service module is used for providing inquiry, statistics and analysis services of energy efficiency evaluation based on the energy efficiency evaluation calculation result; and the client display module is used for inquiring the anode furnace energy efficiency evaluation result in real time.
In a third aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program is configured to:
which when executed by a processor implements a method as described in embodiments of the present application.
Drawings
Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
FIG. 1 is a schematic diagram illustrating a real-time evaluation flow of energy efficiency of an anode furnace provided by an embodiment of the application;
FIG. 2 shows a schematic view of an anode furnace;
FIG. 3 shows an architecture diagram of an anode furnace energy efficiency evaluation system.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
The main energy sources consumed by the anode furnace are electricity, natural gas, oxygen, electric energy, nitrogen and compressed air. The processing capacity of the anode furnace can be represented by the production capacity of the anode furnace in a statistical period. The real-time evaluation index of the anode furnace energy efficiency is measured by six indexes, namely natural gas consumption of unit products of the anode furnace, oxygen consumption of unit products of the anode furnace, nitrogen consumption of unit products of the anode furnace, compressed air consumption of unit products of the anode furnace, electric energy consumption of unit products of the anode furnace and comprehensive energy consumption of unit products of the anode furnace.
The production flow of the anode furnace is as follows:
inputting raw copper and cold copper into an anode furnace;
inputting natural gas as fuel and reducing agent of the anode furnace, inputting compressed air as oxidant, using electric energy as energy source, and adding a gas permeable brick stirring system using nitrogen at the bottom of the furnace;
outputting refined copper liquid, and carrying out disc casting;
and step four, treating the flue gas, the smoke dust and the slag.
Referring to fig. 1, fig. 1 shows a schematic flow chart of real-time evaluation of energy efficiency of an anode furnace according to an embodiment of the present application.
As shown in fig. 1, the method includes:
step 1: collecting the operation data of the anode furnace in a statistical period;
specifically, consumption data of the anode furnace in a statistical period are collected, wherein the consumption data comprise electricity, natural gas, oxygen, electric energy, nitrogen and compressed air, delta t is used as a time unit in the statistical period, k is the number of the time units, and a numerical reading mode comprises a DCS (distributed control system) online reading value, an artificial set value and an artificial input value of each furnace period, wherein the DCS online reading value is an instantaneous value, a sampling period is 1 minute, the whole time is collected, the artificial input value of each furnace period aims at the characteristic of intermittent production of the anode furnace, and when heat balance calculation is carried out on each furnace period, values required by the corresponding furnace period are input according to a report on the same day to carry out calculation of heat efficiency; step 2: constructing an anode furnace energy efficiency evaluation index model:
2.1, calculating the consumption natural gas quantity Q of the anode furnace in the statistical periodAR_AF1_mathane：
Figure BDA0002540591820000061
Wherein
Figure BDA0002540591820000062
t1To count the initial time of the period, t2K is the number of time units, N is the time unit contained in the statistic period, qAR_AF1_methane1(k. DELTA.t) is the natural gas flow rate for reduction at the time k. DELTA.t in Nm3/h，
qAR_AF1_methane2(k. DELTA.t) is the natural gas flow rate for combustion at the time k. DELTA.t in Nm3/h，tAR_AF1_startIs the initial moment of the statistical period; t is tAR_AF1_endFor the end time of the statistical period, t is set under the current sampling periodAR_AF1_start-tAR_AF1_endOne furnace period of the anode furnace;
2.2, calculating the oxygen consumption Q of the anode furnace in the statistical periodAR_AF1_Q2:
Figure BDA0002540591820000063
Wherein,
Figure BDA0002540591820000064
is the oxygen flow of a J tube of the anode furnace, and has the unit of Nm3/h,
Figure BDA0002540591820000065
the oxygen flow rate of an L pipe of the anode furnace is Nm3/h, and the anode furnace inputs oxygen through a J pipe and the L pipe;
2.3, calculating QAR _ AF1_ N2 of nitrogen consumption of the anode furnace in the statistical period:
Figure BDA0002540591820000066
wherein,
Figure BDA0002540591820000067
the nitrogen flow rate for the reduction at time k.DELTA.t, in Nm3/h,
Figure BDA0002540591820000068
the nitrogen flow of the air brick at the time k.delta.t is in unit of Nm 3/h;
2.4, calculating the quantity Q of the compressed air consumed by the anode furnace in the statistical periodAR_AF1_comp_air：
Figure BDA0002540591820000069
Wherein,
Figure BDA00025405918200000610
compressed air flow rate at time k.DELTA.t in Nm3/h；
2.5, calculating the electric energy consumption Q of the anode furnace in the statistical periodAR_AF1_electric：
QAR_AF1_electric＝Qelectric_AF1_low_electric，
Wherein Q iselectric_AF1_low_electricThe power supply amount of the anode furnace by the low-voltage distribution chamber of the anode furnace in the statistical period is kW.h;
2.6, calculating the comprehensive energy consumption E of the anode furnace in the statistical periodP：
Ep＝∑QAF1_i×pi，
Wherein: qAF1_i(i＝methane,Q2,N2Comp _ air) is the consumption of various energy consuming working media, piIn order to convert the coefficient of energy into the coefficient,
calculating according to the standard coal coefficient of energy or the energy equivalent value of energy consumption working medium;
2.7, calculating the anode copper yield MAR _ AF1_ hopper of one furnace period of the anode furnace:
MAR_AF1_copper＝△tAR_AF1_JZ·mM_AR_disk_out，
wherein m isM_AR_disk_outThe copper yield per hour of the disc casting machine is represented by t/h; delta tAR_AF1_JZThe length of the casting time of the furnace period is h;
2.8, calculating the natural gas consumption of the unit product of the anode furnace in the statistical period eAR _ AF1_ methane:
Figure BDA0002540591820000071
2.9, calculating the oxygen consumption of the anode furnace unit product in the statistical period eAR _ AF1_ Q2:
Figure BDA0002540591820000072
2.10, calculating the nitrogen consumption e of the unit product of the anode furnace in the statistical periodAR_AF1_N2：
Figure BDA0002540591820000073
2.11, calculating the compressed air consumption e of the unit product of the anode furnace in the statistical periodAR_AF1_Q2：
Figure BDA0002540591820000074
2.14, calculating the electric energy consumption e of the unit product of the anode furnace in the statistical periodAR_AF1_electric：
Figure BDA0002540591820000075
2.13, calculating the comprehensive energy consumption e of the unit product of the anode furnace in the statistical periodp1：
ep1＝∑(ei×pi),tce/t；
Wherein e isi＝methane,Q2,N2Comp _ air and electric respectively represent five main energy sources consumed by the anode furnace; p is a radical ofiAnd calculating the conversion coefficient of the energy i according to the conversion standard coal coefficient of the energy or the energy value of the energy consumption working medium and the like.
And 3, optimizing and evaluating the anode furnace based on six indexes of natural gas consumption of unit products of the anode furnace, oxygen consumption of unit products of the anode furnace, nitrogen consumption of unit products of the anode furnace, compressed air consumption of unit products of the anode furnace, electric energy consumption of unit products of the anode furnace and comprehensive energy consumption of unit products of the anode furnace, and displaying the evaluation result.
Preferably, a natural gas flow sensor, an oxygen flow sensor, a nitrogen flow sensor and a compressed air flow sensor are respectively arranged at a natural gas input port, an oxygen input port, a nitrogen input port and a compressed air input port of the anode furnace, and then a natural gas pressure sensor, an oxygen pressure sensor, a nitrogen pressure sensor and a compressed air pressure sensor are respectively arranged at the natural gas input port, the oxygen input port, the nitrogen input port and the compressed air input port, wherein the flow sensors measure the flow of gas, and the pressure sensors measure the pressure of the gas;
installing an energy efficiency real-time estimator for the anode furnace, and calculating and displaying the natural gas consumption of unit products of the anode furnace, the oxygen consumption of unit products of the anode furnace, the nitrogen consumption of unit products of the anode furnace, the compressed air consumption of unit products of the anode furnace, the electric energy consumption of unit products of the anode furnace and the comprehensive energy consumption of unit products of the anode furnace in real time;
a furnace body controller is arranged for the anode furnace, and receives real-time sensing values of all flow sensors and pressure sensors and an evaluation value of an energy efficiency real-time evaluator.
Preferably, when the flow and the pressure of the natural gas, the oxygen, the nitrogen and the compressed air are all larger than the preset threshold value, the furnace body controller controls the furnace body to rotate and start;
after the furnace body is started, the energy efficiency real-time evaluator is used for calculating the natural gas consumption of the unit product of the anode furnace, the oxygen consumption of the unit product of the anode furnace, the nitrogen consumption of the unit product of the anode furnace, the compressed air consumption of the unit product of the anode furnace, the electric energy consumption of the unit product of the anode furnace and the comprehensive energy consumption of the unit product of the anode furnace in real time.
Preferably, when the anode furnace is normally produced, a curve of the natural gas consumption of a unit product of the anode furnace, the oxygen consumption of the unit product of the anode furnace, the nitrogen consumption of the unit product of the anode furnace, the compressed air consumption of the unit product of the anode furnace, the electric energy consumption of the unit product of the anode furnace and the comprehensive energy consumption of the unit product of the anode furnace is drawn in real time;
and recording the flow values and pressure values of natural gas, oxygen, nitrogen and compressed air when the unit product comprehensive energy consumption of the anode furnace is at the lowest value in the curve, and controlling the flow values and pressure values of the natural gas, oxygen, nitrogen and compressed air of the anode furnace at the data when the unit product comprehensive energy consumption is at the lowest value, so that the unit product comprehensive energy consumption of the anode furnace is kept at the lowest value.
Preferably, adjusting the flow value and the pressure value of the input natural gas, keeping the flow value and the pressure value of the oxygen, the nitrogen and the compressed air unchanged, drawing a natural gas consumption curve of a unit product of the anode furnace, and recording the flow value and the pressure value of the natural gas when the curve value is the lowest;
when the natural gas reserve is low or the cost is high, the natural gas flow value and the pressure value when the curve value is the lowest are used for controlling the use of the natural gas;
the use of oxygen, nitrogen and compressed air was controlled in the same manner as described above.
Preferably, the optimization experiment is carried out on the anode furnace, and specifically, the optimization experiment comprises the following steps: randomly generating flow values and pressures of natural gas, oxygen, nitrogen and compressed air which are higher than a preset threshold value;
inputting the flow values and the pressure combinations of the four randomly generated input gases into the anode furnace, and drawing a curve of the comprehensive energy consumption of the unit product of the anode furnace in real time;
recording flow values and pressure values of natural gas, oxygen, nitrogen and compressed air when the comprehensive energy consumption of the unit product of the anode furnace in the curve is at the lowest value, combining the flow values and the pressures of four randomly generated input gases as samples to be input into a neural network, predicting the possible combination values of the natural gas, the oxygen, the nitrogen and the compressed air when the comprehensive energy consumption of the unit product of the anode furnace is the lowest, actually inputting the predicted combination values into the anode furnace for verification, and recording the comprehensive energy consumption of the unit product of the anode furnace;
and finding out the lowest value of the comprehensive energy consumption of the unit product of the anode furnace in the record and the corresponding flow values and pressure values of natural gas, oxygen, nitrogen and compressed air as an optimal experimental combination.
As another aspect, the present application further provides an anode furnace energy efficiency real-time evaluation system, which is characterized by comprising: the DCS module is used for acquiring data acquisition services deployed on a production site and used for acquiring real-time production data of an anode furnace workshop and other workshops, wherein the data comprises natural gas, oxygen, nitrogen, compressed air, electric energy and product yield data required by anode furnace energy efficiency evaluation;
the data synchronization module is used for synchronizing the DCS data to the MongoDB database so as to be stored for a long time;
the MongDB module is used for storing the production data synchronized by the DCS module and the service data used by the energy efficiency evaluation system;
the energy efficiency evaluation service module is used for acquiring production data from the MongoDB in real time and calculating the energy efficiency of the anode furnace in real time through the anode furnace energy efficiency evaluation index model;
the Web service module is used for providing query, statistics and analysis services of energy efficiency evaluation based on the energy efficiency evaluation calculation result; and the client display module is used for inquiring the anode furnace energy efficiency evaluation result in real time.
The anode furnace energy efficiency evaluation index model comprises:
a natural gas consumption submodule for counting the natural gas consumption Q of the anode furnace in the periodAR_AF1_mathane：
Figure BDA0002540591820000091
Wherein
Figure BDA0002540591820000092
t1To count the initial time of the period, t2K is the number of time units, N is the time unit contained in the statistic period, qAR_AF1_methane1(k. DELTA.t) is the natural gas flow rate for reduction at the time k. DELTA.t in Nm3/h，
qAR_AF1_methane2(k. DELTA.t) is the flow rate of the combustion natural gas at the time k. DELTA.t, in units ofNm3/h，tAR_AF1_startIs the initial moment of the statistical period; t is tAR_AF1_endFor the end time of the statistical period, t is set under the current sampling periodAR_AF1_start-tAR_AF1_endOne furnace period of the anode furnace;
the oxygen consumption sub-module is used for calculating the oxygen consumption QAR _ AF1_ Q2 of the anode furnace in the statistical period:
Figure BDA0002540591820000101
wherein,
Figure BDA0002540591820000102
is the oxygen flow of a J tube of the anode furnace, and has the unit of Nm3/h,
Figure BDA0002540591820000103
the oxygen flow rate of an L pipe of the anode furnace is Nm3/h, and the anode furnace inputs oxygen through a J pipe and the L pipe;
and the nitrogen consumption sub-module is used for calculating the nitrogen consumption QAR _ AF1_ N2 of the anode furnace in the statistical period:
Figure BDA0002540591820000104
wherein,
Figure BDA0002540591820000105
nitrogen flow rate in Nm for reduction at time k.DELTA.t3/h，
Figure BDA0002540591820000106
The nitrogen flow rate of the air brick at the time k.DELTA.t is measured in Nm3/h；
A compressed air consumption submodule for calculating the compressed air consumption Q of the anode furnace in the statistical periodAR_AF1_comp_air：
Figure BDA0002540591820000107
Wherein q isAR_AF1_comp_airThe compressed air flow rate at time k.DELTA.t is in Nm3/h；
An electric energy consumption submodule for calculating the electric energy consumption Q of the anode furnace in the statistical periodAR_AF1_electric：
QAR_AF1_electric＝Qelectric_AF1_low_electric，
Wherein Q iselectric_AF1_low_electricThe power supply amount of the anode furnace by the low-voltage distribution chamber of the anode furnace in the statistical period is kW.h;
an anode furnace comprehensive energy consumption submodule for calculating the anode furnace comprehensive energy consumption E in the statistical periodP：
Ep＝∑QAF1_i×pi，
Wherein: qAF1_i(i＝methane,Q2,N2Comp _ air) is the consumption of various energy consuming working media, piCalculating the energy conversion coefficient according to the conversion standard coal coefficient of the energy or the energy value of the energy consumption working medium and the like;
an anode copper yield submodule for calculating the anode copper yield M of the anode furnace in one furnace periodAR_AF1_copper：
Figure BDA0002540591820000111
Wherein m isM_AR_disk_outThe copper yield per hour of the disc casting machine is represented by t/h; delta tAR_AF1_JZThe length of the casting time of the furnace period is h;
and the unit product natural gas consumption submodule is used for calculating the unit product natural gas consumption eAR _ AF1_ methane of the anode furnace in the statistical period:
Figure BDA0002540591820000112
a unit product oxygen consumption submodule for calculatingOxygen consumption e of unit anode furnace product in statistical periodAR_AF1_Q2：
Figure BDA0002540591820000113
A unit product nitrogen consumption submodule used for calculating the unit product nitrogen consumption e of the anode furnace in the statistical periodAR_AF1_N2：
Figure BDA0002540591820000114
A unit product compressed air consumption submodule for calculating the compressed air consumption e of the unit product of the anode furnace in the statistical periodAR_AF1_Q2：
Figure BDA0002540591820000115
A unit product electric energy consumption submodule for calculating the unit product electric energy consumption e of the anode furnace in the statistical periodAR_AF1_electric：
Figure BDA0002540591820000116
A unit product comprehensive energy consumption submodule used for calculating the unit product comprehensive energy consumption e of the anode furnace in the statistical periodp1：
ep1＝∑(ei×pi),tce/t；
Wherein e isi＝methane,Q2,N2Comp _ air and electric respectively represent five main energy sources consumed by the anode furnace, namely natural gas, oxygen, nitrogen, compressed air and electric energy; p is a radical ofiAnd calculating the conversion coefficient of the energy i according to the conversion standard coal coefficient of the energy or the energy value of the energy consumption working medium and the like.
As another aspect, the present application also provides a computer-readable storage medium, which may be the computer-readable storage medium included in the foregoing device in the foregoing embodiment; or it may be a separate computer readable storage medium not incorporated into the device. The computer-readable storage medium stores one or more programs for use by one or more processors in performing the anode furnace energy efficiency real-time evaluation method described herein.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic Gate circuit for realizing a logic function for a data signal, an asic having an appropriate combinational logic Gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), and the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.

Claims (8)

1. A real-time evaluation method for energy efficiency of an anode furnace is characterized by comprising the following steps:
step 1: collecting the operation data of the anode furnace in a statistical period;
specifically, consumption data of the anode furnace in a statistical period are collected, wherein the consumption data comprise electricity, natural gas, oxygen, electric energy, nitrogen and compressed air, delta t is used as a time unit in the statistical period, k is the number of the time units, and a numerical reading mode comprises a DCS (distributed control system) online reading value, an artificial set value and an artificial input value of each furnace period, wherein the DCS online reading value is an instantaneous value, a sampling period is 1 minute, the whole time is collected, the artificial input value of each furnace period aims at the characteristic of intermittent production of the anode furnace, and when heat balance calculation is carried out on each furnace period, values required by the corresponding furnace period are input according to a report on the same day to carry out calculation of heat efficiency;
step 2: constructing an anode furnace energy efficiency evaluation index model:
2.1, calculating the consumption natural gas quantity Q of the anode furnace in the statistical periodAR_AF1_mathane：
Figure FDA0003552536000000011
Wherein
Figure FDA0003552536000000012
t1To count the initial time of the period, t2K is the number of time units, N is the time unit contained in the statistic period, qAR_AF1_methane1(k. DELTA.t) is the natural gas flow rate for reduction at the time k. DELTA.t in Nm3/h，
qAR_AF1_methane2(k. DELTA.t) is the natural gas flow rate for combustion at the time k. DELTA.t in Nm3/h，tAR_AF1_startFor counting the initial time of the period；tAR_AF1_endFor the end time of the statistical period, t is set under the current sampling periodAR_AF1_start-tAR_AF1_endOne furnace period of the anode furnace;
2.2, calculating oxygen consumption QAR _ AF1_ Q2 of the anode furnace in the statistical period:
Figure FDA0003552536000000013
wherein,
Figure FDA0003552536000000014
is the oxygen flow of a J tube of the anode furnace, and the unit is Nm3/h，
Figure FDA0003552536000000015
Is the oxygen flow of the L pipe of the anode furnace, and the unit is Nm3The anode furnace inputs oxygen through a J pipe and an L pipe;
2.3, calculating QAR _ AF1_ N2 of nitrogen consumption of the anode furnace in the statistical period:
Figure FDA0003552536000000021
wherein,
Figure FDA0003552536000000022
nitrogen flow rate in Nm for reduction at time k.DELTA.t3/h，
Figure FDA0003552536000000023
The nitrogen flow rate of the air brick at the time k.DELTA.t is measured in Nm3/h；
2.4, calculating the quantity Q of the compressed air consumed by the anode furnace in the statistical periodAR_AF1_comp_air：
Figure FDA0003552536000000024
Wherein q isAR_AF1_comp_airThe compressed air flow rate at time k.DELTA.t is in Nm3/h；
2.5, calculating the electric energy consumption Q of the anode furnace in the statistical periodAR_AF1_electric：
QAR_AF1_electric＝Qelectric_AF1_low_electric，
Wherein Q iselectric_AF1_low_electricThe power supply amount of the anode furnace by the low-voltage distribution chamber of the anode furnace in the statistical period is kW.h;
2.6, calculating the comprehensive energy consumption E of the anode furnace in the statistical periodP：
Ep＝∑QAF1_i×pi，
Wherein: qAF1_i(i＝methane,Q2,N2Comp _ air) is the consumption of various energy consuming working media, piCalculating the energy conversion coefficient according to the conversion standard coal coefficient of the energy or the energy value of the energy consumption working medium and the like;
2.7, calculating the anode copper yield MAR _ AF1_ copper of one furnace period of the anode furnace:
MAR_AF1_copper＝△tAR_AF1_JZ·mM_AR_disk_out，
wherein m isM_AR_disk_outThe copper yield per hour of the disc casting machine is represented by t/h; delta tAR_AF1_JZThe length of the casting time of the furnace period is h;
2.8, calculating the natural gas consumption of the unit product of the anode furnace in the statistical period eAR _ AF1_ methane:
Figure FDA0003552536000000025
2.9, calculating the oxygen consumption of the anode furnace unit product in the statistical period eAR _ AF1_ Q2:
Figure FDA0003552536000000031
2.10, calculating nitrogen consumption of unit anode furnace products in a statistical period eAR _ AF1_ N2:
Figure FDA0003552536000000032
2.11, calculating the compressed air consumption e of the unit product of the anode furnace in the statistical periodAR_AF1_Q2：
Figure FDA0003552536000000033
2.12, calculating the electric energy consumption e of the unit product of the anode furnace in the statistical periodAR_AF1_electric：
Figure FDA0003552536000000034
2.13, calculating the comprehensive energy consumption e of the unit product of the anode furnace in the statistical periodp1：
ep1＝∑(ei×pi),tce/t；
Wherein e isi＝methane,Q2,N2Comp _ air and electric respectively represent five main energy sources consumed by the anode furnace, namely natural gas, oxygen, nitrogen, compressed air and electric energy; p is a radical ofiCalculating the conversion coefficient of the energy i according to the conversion standard coal coefficient of the energy or the energy value of the energy consumption working medium and the like;
and 3, optimizing and evaluating the anode furnace based on six indexes of natural gas consumption of unit products of the anode furnace, oxygen consumption of unit products of the anode furnace, nitrogen consumption of unit products of the anode furnace, compressed air consumption of unit products of the anode furnace, electric energy consumption of unit products of the anode furnace and comprehensive energy consumption of unit products of the anode furnace, and displaying the evaluation result.
2. The method of claim 1, further comprising:
a natural gas flow sensor, an oxygen flow sensor, a nitrogen flow sensor and a compressed air flow sensor are respectively arranged at a natural gas input port, an oxygen input port, a nitrogen input port and a compressed air input port of the anode furnace, and a natural gas pressure sensor, an oxygen pressure sensor, a nitrogen pressure sensor and a compressed air pressure sensor are respectively arranged at the natural gas input port, the oxygen input port, the nitrogen input port and the compressed air input port of the anode furnace;
installing an energy efficiency real-time estimator for the anode furnace, and calculating and displaying the natural gas consumption of unit products of the anode furnace, the oxygen consumption of unit products of the anode furnace, the nitrogen consumption of unit products of the anode furnace, the compressed air consumption of unit products of the anode furnace, the electric energy consumption of unit products of the anode furnace and the comprehensive energy consumption of unit products of the anode furnace in real time;
a furnace body controller is arranged for the anode furnace, and receives real-time sensing values of all flow sensors and pressure sensors and an evaluation value of an energy efficiency real-time evaluator.
3. The method of claim 2, further comprising:
when the flow and the pressure of the natural gas, the oxygen, the nitrogen and the compressed air are all larger than the preset threshold value, the furnace body controller controls the rotation and the starting of the furnace body;
after the furnace body is started, the energy efficiency real-time evaluator is used for calculating the natural gas consumption of the unit product of the anode furnace, the oxygen consumption of the unit product of the anode furnace, the nitrogen consumption of the unit product of the anode furnace, the compressed air consumption of the unit product of the anode furnace, the electric energy consumption of the unit product of the anode furnace and the comprehensive energy consumption of the unit product of the anode furnace in real time.
4. The method of claim 3, further comprising:
when the anode furnace is normally produced, curves of the unit product natural gas consumption, the unit product oxygen consumption, the unit product nitrogen consumption, the unit product compressed air consumption, the unit product electric energy consumption and the unit product comprehensive energy consumption of the anode furnace are drawn in real time;
recording the flow values and pressure values of natural gas, oxygen, nitrogen and compressed air when the comprehensive energy consumption of the unit product of the anode furnace in the curve is at the lowest value,
the flow and pressure values of the natural gas, the oxygen, the nitrogen and the compressed air of the anode furnace are controlled to be data when the comprehensive energy consumption of the unit product is at the lowest value, so that the comprehensive energy consumption of the unit product of the anode furnace is kept at the lowest value.
5. The method of claim 3, further comprising:
adjusting the flow value and the pressure value of the input natural gas, keeping the flow value and the pressure value of oxygen, nitrogen and compressed air unchanged, drawing a natural gas consumption curve of a unit product of the anode furnace, and recording the flow value and the pressure value of the natural gas when the curve value is the lowest; when the natural gas reserve is low or the cost is high, the natural gas flow value and the pressure value when the curve value is the lowest are used for controlling the use of the natural gas;
the use of oxygen, nitrogen and compressed air was controlled in the same manner as described above.
6. The method of claim 3, further comprising:
the optimization experiment of the anode furnace specifically comprises the following steps: randomly generating flow values and pressures of natural gas, oxygen, nitrogen and compressed air which are higher than a preset threshold value;
inputting the flow values and the pressure combinations of the four randomly generated input gases into the anode furnace, and drawing a curve of the comprehensive energy consumption of the unit product of the anode furnace in real time;
recording the flow values and pressure values of natural gas, oxygen, nitrogen and compressed air when the comprehensive energy consumption of the unit product of the anode furnace in the curve is at the lowest value,
the method comprises the steps of inputting a flow value and pressure combination of four randomly generated input gases into a neural network as a sample, predicting a combination value of natural gas, oxygen, nitrogen and compressed air when the unit product comprehensive energy consumption of the anode furnace is the lowest, actually inputting the predicted combination value into the anode furnace for verification, and recording the unit product comprehensive energy consumption of the anode furnace;
and finding out the lowest value of the comprehensive energy consumption of the unit product of the anode furnace in the record and the corresponding flow values and pressure values of natural gas, oxygen, nitrogen and compressed air as an optimal experimental combination.
7. An anode furnace energy efficiency real-time evaluation system is characterized by comprising:
the DCS module is deployed in a data acquisition service of a production field and is used for acquiring real-time production data of the anode furnace workshop, and the data comprises natural gas, oxygen, nitrogen, compressed air, electric energy and product yield data required by anode furnace energy efficiency evaluation; the data synchronization module is used for synchronizing the DCS data to the MongoDB database so as to be stored for a long time;
the MongDB module is used for storing the production data synchronized by the DCS module and the service data used by the energy efficiency evaluation system;
the energy efficiency evaluation service module is used for acquiring production data from the MongoDB in real time and calculating the energy efficiency of the anode furnace in real time through the anode furnace energy efficiency evaluation index model;
the Web service module is used for providing inquiry, statistics and analysis services of energy efficiency evaluation based on the energy efficiency evaluation calculation result; the client display module is used for inquiring the energy efficiency evaluation result of the anode furnace in real time;
wherein, the anode furnace energy efficiency evaluation index model comprises:
a natural gas consumption submodule for counting the natural gas consumption Q of the anode furnace in the periodAR_AF1_mathane：
Figure FDA0003552536000000051
Wherein
Figure FDA0003552536000000052
t1To count the initial time of the period, t2K being the end of the statistical periodNumber, N is the time unit contained in the statistical period, qAR_AF1_methane1(k. DELTA.t) is the natural gas flow rate for reduction at the time k. DELTA.t in Nm3/h，
qAR_AF1_methane2(k. DELTA.t) is the natural gas flow rate for combustion at the time k. DELTA.t in Nm3/h，tAR_AF1_startIs the initial moment of the statistical period; t is tAR_AF1_endFor the end time of the statistical period, t is set under the current sampling periodAR_AF1_start-tAR_AF1_endOne furnace period of the anode furnace;
the oxygen consumption submodule is used for calculating the oxygen consumption Q of the anode furnace in the statistical periodAR_AF1_Q2:
Figure FDA0003552536000000053
Wherein,
Figure FDA0003552536000000054
is the oxygen flow of J tube of the anode furnace, and the unit is Nm3/h，
Figure FDA0003552536000000055
Is the oxygen flow of the L pipe of the anode furnace, and the unit is Nm3The anode furnace inputs oxygen through a J pipe and an L pipe;
and the nitrogen consumption sub-module is used for calculating the nitrogen consumption QAR _ AF1_ N2 of the anode furnace in the statistical period:
Figure FDA0003552536000000061
wherein,
Figure FDA0003552536000000062
nitrogen flow rate in Nm for reduction at time k.DELTA.t3/h，
Figure FDA0003552536000000063
The nitrogen flow rate of the air brick at the time k.DELTA.t is measured in Nm3/h；
A compressed air consumption submodule for calculating the compressed air consumption Q of the anode furnace in the statistical periodAR_AF1_comp_air：
Figure FDA0003552536000000064
Wherein q isAR_AF1_comp_airThe compressed air flow rate at time k.DELTA.t is in Nm3/h；
The electric energy consumption submodule is used for calculating the electric energy consumption Q of the anode furnace in the statistical periodAR_AF1_electric：
QAR_AF1_electric＝Qelectric_AF1_low_electric，
Wherein Q iselectric_AF1_low_electricThe power supply quantity of the anode furnace by the low-voltage distribution chamber of the anode furnace in the statistical period is kW.h;
and the anode furnace comprehensive energy consumption submodule is used for calculating the anode furnace comprehensive energy consumption EP in the statistical period:
Ep＝∑QAF1_i×pi，
wherein: QAF1_ i (i is methane, Q2, N2, comp _ air) is consumption of various energy consumption working media, pi is an energy conversion coefficient, and the energy conversion coefficient is calculated according to the conversion standard coal coefficient of energy or the energy equivalent value of the energy consumption working media;
an anode copper yield submodule for calculating an anode copper yield MAR _ AF1_ copper for one furnace period of the anode furnace:
MAR_AF1_copper＝△tAR_AF1_JZ·mM_AR_disk_out，
wherein m isM_AR_disk_outThe copper yield per hour of the disc casting machine is represented by t/h; delta tAR_AF1_JZThe length of the casting time of the furnace period is h;
and the unit product natural gas consumption submodule is used for calculating the unit product natural gas consumption eAR _ AF1_ methane of the anode furnace in the statistical period:
Figure FDA0003552536000000071
a unit product oxygen consumption submodule for calculating the unit product oxygen consumption e of the anode furnace in the statistical periodAR_AF1_Q2：
Figure FDA0003552536000000072
A unit product nitrogen consumption submodule used for calculating the unit product nitrogen consumption e of the anode furnace in the statistical period
AR_AF1_N2：
Figure FDA0003552536000000073
A unit product compressed air consumption submodule used for calculating the unit product compressed air consumption e of the anode furnace in the statistical periodAR_AF1_Q2：
Figure FDA0003552536000000074
The unit product electric energy consumption submodule is used for calculating the unit product electric energy consumption of the anode furnace in the statistical period eAR _ AF1_ electric:
Figure FDA0003552536000000075
a unit product comprehensive energy consumption submodule for calculating the unit product comprehensive energy consumption e of the anode furnace in the statistical periodp1：
ep1＝∑(ei×pi),tce/t；
Wherein e isi＝methane,Q2,N2Comp _ air and electric respectively represent five main energy sources consumed by the anode furnaceNatural gas, oxygen, nitrogen, compressed air and electric energy; p is a radical ofiAnd calculating the conversion coefficient of the energy i according to the conversion standard coal coefficient of the energy or the energy value of the energy consumption working medium and the like.
8. A computer-readable storage medium having stored thereon a computer program for:
the computer program, when executed by a processor, implements the method of any one of claims 1-6.
CN202010545601.6A 2020-06-16 2020-06-16 Real-time evaluation method and system for energy efficiency of anode furnace Active CN111798103B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010545601.6A CN111798103B (en) 2020-06-16 2020-06-16 Real-time evaluation method and system for energy efficiency of anode furnace

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010545601.6A CN111798103B (en) 2020-06-16 2020-06-16 Real-time evaluation method and system for energy efficiency of anode furnace

Publications (2)

Publication Number Publication Date
CN111798103A CN111798103A (en) 2020-10-20
CN111798103B true CN111798103B (en) 2022-05-17

Family

ID=72804332

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010545601.6A Active CN111798103B (en) 2020-06-16 2020-06-16 Real-time evaluation method and system for energy efficiency of anode furnace

Country Status (1)

Country Link
CN (1) CN111798103B (en)

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140052503A1 (en) * 2011-04-21 2014-02-20 E3 Corporation System, technology, and method for a universal energy efficiency optimization platform for energy consuming devices, appliances and systems at residential, commercial, and industrial facilities
CN109972171A (en) * 2017-12-27 2019-07-05 江西省丰城市鑫颖金属制品有限公司 A kind of refined copper production environmental protecting device
CN109543750A (en) * 2018-11-22 2019-03-29 广东省智能制造研究所 A kind of power consumption user energy efficiency evaluating method
CN110991043B (en) * 2019-12-03 2023-05-16 北京中计开元科技有限公司 Energy consumption modeling and evaluating method of energy consumption system

Also Published As

Publication number Publication date
CN111798103A (en) 2020-10-20

Similar Documents

Publication Publication Date Title
CN102419591B (en) facility monitoring method
CN111593155B (en) Blast furnace diagnosis system and method
CN104268433B (en) Method for monitoring unit power generation coal consumption deviation caused by variation of gas boiler operating parameters
CN102226643B (en) Rotary kiln automatic control system and method
CN112226563A (en) Method and system for controlling emission source of sulfur dioxide in flue gas of iron-making hot blast stove
CN111798103B (en) Real-time evaluation method and system for energy efficiency of anode furnace
WO2021200118A1 (en) Optimum calculation method for energy management condition at iron mill, optimum calculation device for energy management condition at iron mill, and operational method of iron mill
CN112403452B (en) Method and system for online judging activated carbon analysis efficiency and controlling total amount of heat source
CN116738863A (en) External refining CO based on digital twin operation 2 Method for constructing digital model
CN110598185A (en) Coke oven coking unit consumption influence factor sequencing method and system
CN112650786B (en) AI intelligent monitoring system of multi-zone air separation equipment
CN106527382A (en) Coke oven thermal efficiency online monitoring method
CN113652518B (en) Converter and prediction method and prediction system for gas reserves of converter gas holder of converter
CN102243117B (en) Method for testing dynamic thermal balance of steel rolling industrial furnace
CN115935784A (en) Method and system for analyzing fuel data in combustion system of architectural ceramic kiln
CN109315030B (en) Arc melting system and method for monitoring length of electrode in the system
CN112176135B (en) Energy-saving optimization method and system based on blast furnace energy efficiency analysis
CN115234936B (en) Identification processing method for combustion efficiency of biomass combustor
CN216445299U (en) Automatic control regulating system of biomass carbonization furnace purification device
CN117054734B (en) Method and system for monitoring smelting energy consumption of copper plate
CN118272612A (en) RH furnace decarburization control method, RH furnace decarburization control system, RH furnace decarburization control equipment and RH furnace decarburization control storage medium
CN115186900B (en) Dynamic blast furnace gas generation amount prediction method and system suitable for multiple working condition categories
TW202400930A (en) Prediction system for nitrogn supply and demand
CN116822907A (en) Method and system for real-time monitoring and optimizing aluminum plate production based on Internet of things
KR20160041689A (en) Thermal efficiency calculating system of heating furnace

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant