CN109214709B - Method for optimizing distribution of oxygen generation system of iron and steel enterprise - Google Patents
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- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 title claims abstract description 143
- 239000001301 oxygen Substances 0.000 title claims abstract description 143
- 229910052760 oxygen Inorganic materials 0.000 title claims abstract description 143
- 238000009826 distribution Methods 0.000 title claims abstract description 43
- 238000000034 method Methods 0.000 title claims abstract description 26
- 229910000831 Steel Inorganic materials 0.000 title claims abstract description 25
- 239000010959 steel Substances 0.000 title claims abstract description 25
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 title claims description 34
- 229910052742 iron Inorganic materials 0.000 title claims description 17
- 239000006185 dispersion Substances 0.000 claims abstract description 4
- 238000003860 storage Methods 0.000 claims description 20
- 239000007789 gas Substances 0.000 claims description 13
- 238000004519 manufacturing process Methods 0.000 claims description 13
- 238000012360 testing method Methods 0.000 claims description 10
- 239000011159 matrix material Substances 0.000 claims description 8
- 238000009628 steelmaking Methods 0.000 claims description 7
- 238000009792 diffusion process Methods 0.000 claims description 6
- 239000013598 vector Substances 0.000 claims description 5
- MYMOFIZGZYHOMD-UHFFFAOYSA-N Dioxygen Chemical compound O=O MYMOFIZGZYHOMD-UHFFFAOYSA-N 0.000 claims description 4
- 230000003139 buffering effect Effects 0.000 claims description 4
- 230000008859 change Effects 0.000 claims description 4
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- 238000004458 analytical method Methods 0.000 claims description 2
- 230000008569 process Effects 0.000 abstract description 8
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- 230000036284 oxygen consumption Effects 0.000 description 4
- 238000003723 Smelting Methods 0.000 description 2
- 239000000872 buffer Substances 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 238000005520 cutting process Methods 0.000 description 2
- 238000004134 energy conservation Methods 0.000 description 2
- 238000005265 energy consumption Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 150000001875 compounds Chemical class 0.000 description 1
- 238000009749 continuous casting Methods 0.000 description 1
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- 230000000694 effects Effects 0.000 description 1
- 238000009499 grossing Methods 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 238000011031 large-scale manufacturing process Methods 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
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Abstract
An optimized distribution method for an oxygen generation system of a steel enterprise belongs to the technical field of oxygen system scheduling. The first stage establishes equations that reference the amount of modulation to reduce or increase the pressure to within a specified range and take into account the user's dispersion. And in the second stage, according to the demand characteristics of different users, the aerobic users are divided into stable users and fluctuation users, the integral pressure constraint is determined, and a constraint equation is formed. The solution model may obtain a global optimal solution or a boundary of optimal solutions for the distribution problem. The solution algorithm plans the distribution scheme by an optimal solution, which may provide an optimal solution to the oxygen distribution problem. The method has the advantages that the efficiency of directly distributing the oxygen to the users is high, and meanwhile, the oxygen utilization rate is improved and the energy is saved when the pressure of the oxygen pipe network is in a specified range in the oxygen dispatching process.
Description
Technical Field
The invention belongs to the technical field of oxygen system scheduling, and particularly provides a method for optimizing distribution of an oxygen generation system of a steel enterprise, which makes full use of oxygen generated by an oxygen generator so as to improve the utilization rate of the oxygen.
Background
Iron and steel enterprises are industries with high energy consumption, high pollution and high emission, an oxygen system is essential energy equipment in the smelting process, and the enterprises use a large amount of oxygen and simultaneously bring about the problem of unreasonable consumption. In the optimized distribution of the oxygen system, the energy conservation of the monomer equipment and the energy conservation of the whole system are considered, so that the energy is saved and the benefit is improved. As the scale of iron and steel enterprises is increasing, the demand for oxygen is increasing rapidly. The oxygen consumption of steel enterprises accounts for 2/3 of total oxygen industrial output, and an oxygen generation system is also a high-energy-consumption device in the energy conversion process of the steel enterprises in China. The oxygen distribution amount of the oxygen system is closely related to the actual production condition, and when the production working condition changes, the problems of imbalance of the oxygen system, oxygen diffusion and the like are caused, so that the energy waste is caused.
At present, the research of the oxygen optimized distribution of the iron and steel enterprises mainly has two aspects of a prediction control theory and a scheduling theory. By analyzing the production, storage, use and the like of the oxygen system, constraint conditions are established in a targeted manner, so that an integral oxygen generation distribution scheme is established. In the research of oxygen systems in China, data sources are diversified and difficult to unify, and the practical systems still adopt experience estimation and manual operation to occupy the main scheduling mode, so that the technical information of equipment is not fully explored, and the dynamic characteristic research has limitations. The goal of oxygen system allocation is to classify among the enterprise-defined users and, based on the characteristics of the different types of users, determine the optimal allocation scheme to meet the demand for production oxygen. Some empirical scheduling cannot effectively consider the safety of the system, the distribution scheme is obtained through prediction, repeated adjustment is needed, the operation safety and economy are difficult to guarantee, and the decision made by scheduling personnel is influenced. The invention expresses the distribution method as an objective function, and takes the limits of ensuring production safety, equipment safety and stable oxygen supply as constraint conditions.
The invention aims at the optimal economic benefit of the reasonable distribution of oxygen, realizes the optimized distribution of the oxygen system according to the production, storage, buffering and consumption processes and characteristics of the oxygen system of the iron and steel enterprise, meets the production requirements of the enterprise, and provides guidance for production scheduling and energy-saving control.
Disclosure of Invention
The invention provides an optimal distribution method for an oxygen generation system of a steel enterprise, which is used for distributing oxygen by using a balance constraint equation and a user characteristic constraint method, can provide reference for smelting operators through a reasonable distribution scheme, and increases economic benefits for the enterprise.
The oxygen system consists of a production system, a buffer storage system (including a pipe network) and a use system, most of steel enterprises adopt a cryogenic oxygen generation technology, and the cryogenic oxygen generation technology is suitable for large-scale production enterprises; the oxygen storage system consists of an oxygen tank, a liquid oxygen tank and a pipe network. The pipe network transmits the produced oxygen to the user, and buffers partial oxygen simultaneously, and the storage tank has the effect of storage and buffering with the oxygen pipe network, for consuming the user and providing the air feed guarantee, under abnormal conditions, the liquid storage tank can in time provide required oxygen through quick vaporizing device, ensures the normal of production.
The oxygen using system mainly comprises blast furnace iron making and converter steel making, and other users with small oxygen consumption, such as continuous casting billet cutting, steel rolling heating furnace oxygen enrichment process, liquid oxygen and the like. The oxygen demand varies with the characteristics of the user of the oxygen system.
The specific modeling process is as follows:
in the first stage: establishing equilibrium constraint equations for oxygen systems
The balance constraint equation established by the invention enables the system to reach dynamic balance, and in order to enable the system to normally run, the pressure of a pipe network is a limiting condition, and the equation can be established only within a specified range. When the network pressure approaches the highest (lowest) pressure limit, the pressure is reduced (increased) to within a specified range using a regulated amount.
Introducing regulating quantity delta V [ delta ] Q [ ]1,△Q2,…△Qj]When the oxygen content of the pipe network exceeds the maximum pressure limit, delta Qj<0; when the oxygen amount of the pipe network is lower than the lowest pressure limit, delta Qj>0; when the pipe network operates within the specified range, the delta Qj＝0。
1) Let the current gas storage volume of the oxygen spherical tank as vector V ═ Q1,Q2,…Qj]The internal elements of the oxygen system respectively represent the current gas storage value of each spherical tank of the oxygen system;
2) let the oxygen yield be Y ═ Y 1,y2,…yl]And the inner element represents the oxygen generation capacity of each oxygen generator. From the above analysis, the oxygen system equilibrium constraint equation is obtained as follows.
Wherein F ═ F1,f2,…fn]For different users, M is the amount converted to liquid oxygen.
For n oxygen users, a user matrix X is formed with:
X＝[x1,x2,…xn]
by setting the coefficient matrix a, namely:
A＝[a1,a2,…an]
in the formula (I), the compound is shown in the specification,
and a second stage: user constraint model
According to the invention, aerobic users are divided into stable users and fluctuation users according to the demand characteristics of different users.
1) And (4) smoothing the user. The oxygen-balanced user means that the oxygen demand in the production process is relatively stable and does not change greatly along with the change of time, and the oxygen enrichment rate of the blast furnace is determined and the oxygen demand is fixed under the normal condition.
Vmin≤xi≤Vmax
Vmin、VmaxThe minimum and maximum oxygen requirement of the blast furnace.
2) The user is fluctuated. The steel-making users have larger fluctuation among all oxygen users, and the oxygen law of the steel-making users has influence on the oxygen balance and the oxygen diffusion, so that the constraint equations of the steel-making users need to be specially processed.
Wherein m is the number of converters and YmaxThe oxygen quantity of the oxygen generator.
Meanwhile, the overall pressure constraint needs to be determined, and a constraint equation is given according to the overall pressure constraint:
In the formula, Pmin、PmaxThe amount of oxygen representing the minimum and maximum pressure of the system, respectively.
The spherical tank is used as an oxygen buffering device, the designed storage capacity of the spherical tank also needs to be constrained, and the specific constraint equation is as follows:
wherein
The minimum and maximum capacity, Q, which can be borne by the gas storage tankjThe current gas storage amount of the gas storage tank.
And a third stage: optimizing allocation objective function
The oxygen dispatching of the iron and steel enterprises takes the minimum diffusion as a dispatching target, and the optimized distribution objective function takes the minimum oxygen demand M as a target. For an oxygen system consisting of a plurality of users, the objective function of the distribution is as follows:
(4) solving step
The global optimal solution or the boundary of the optimal solution of the distribution problem can be obtained by simplifying assumptions and solving models. The solution algorithm plans the distribution scheme with an optimal solution, which may provide an optimal solution to the oxygen distribution problem.
The solving process of the model comprises the following specific steps:
1) the general linear programming is converted into a standard form, and an initial feasible basis is constructed. If the constraint condition is less than or equal to, introducing a non-negative relaxation variable xn+1Forming an m-order initial feasible basis; if the constraint condition is'>"or" artificial variable "is introduced if the coefficient matrix does not have m-order unit matrix as the sub-matrix.
2) An initial base feasible solution is determined. Assuming an initial feasible solution, the variables of the initial feasible solution are the basic variables. The basic variable is not equal to zero, and the initial variable is obtained by introducing a variable as an initial basic variable. As can be seen from the introduction of the variables, the basic variables have positive unit coefficients, only one equation is provided, and the objective function does not contain the basic variables.
3) Optimality tests, i.e. testing the number of tests sigma for non-fundamental variablesj，σjIs the basis for judging the optimal. x is the number ofjOf (a) a test number σj＝cj-zjThere are three situations:
if the check number σjAnd (5) when the obtained feasible base solution is 0, the optimal solution is obtained, and the calculation is stopped. Among the non-base variables satisfying the optimal base theorem, the check number of some non-base variables is equal to 0, and the problem has multiple optimal solutions.
If the check number σj>0，σjAnd if all the components of the corresponding column vectors are less than 0, the objective function value has no upper bound and an unbounded solution exists, and the calculation is stopped.
If the check number σj<And 0, if the corresponding column vector has a positive component, the obtained basis is not the optimal basis, and the basis transformation is carried out to shift to the next step.
4) And (4) base transformation. If the basic feasible solution is not the optimal solution, another feasible solution for reducing the value of the objective function needs to be found, namely, the feasible solution is turned from one vertex of the feasible region to another adjacent vertex, so that the value of the objective function is reduced. When sigma is jNot less than 0, the change-in variable x is determined when the change-in base is carried outjDetermining sigma when the test number is positivek＝max{σj|σj>0} and its corresponding variable xkI.e., the base-shifted variable.
When the coefficient column of the swap-in variable has a positive component, the basis variable is swapped out:
determining a swap-out basis variable xl。
5) With aikAnd (4) performing rotation operation as a main element to obtain a new basic feasible solution. And turning to 3), carrying out optimality test until an optimal solution is obtained.
So far, the model of the oxygen optimal distribution method of the iron and steel enterprise is solved through the steps 1), 2), 3), 4), 5); and finally, reasonably using oxygen according to the distribution result.
The first stage equations are built to reference the amount of modulation to reduce (increase) the pressure to within a specified range and take into account the user's dispersion.
And in the second stage, according to the demand characteristics of different users, the aerobic users are divided into stable users and fluctuation users, the integral pressure constraint is determined, and a constraint equation is formed.
The solution model may obtain a global optimal solution or a boundary of optimal solutions for the distribution problem. The solution algorithm plans the distribution scheme by an optimal solution, which may provide an optimal solution to the oxygen distribution problem.
The oxygen optimized distribution method for the iron and steel enterprises is strong in practicability and capable of effectively calculating the distribution result. The method improves the utilization rate of oxygen, reduces the diffusion of oxygen, reduces the total cost of an oxygen system, and can meet the requirements of users, reasonable pressure of a pipe network, economic benefits and the like.
The scheduling and distributing method for systematically researching the oxygen system is provided, the utilization efficiency of the technical gas field of the iron and steel enterprises can be further improved, the economic combination operation of the oxygen system is finally achieved, the best point of cost and benefit is found, and more gas energy sources are saved for the enterprises.
Drawings
FIG. 1 is a diagram showing the basic components of an oxygen system for a steel enterprise according to the present invention.
FIG. 2 is a flow chart of an oxygen distribution solution method of the present invention.
Detailed Description
An example is given below to describe in further detail the specific implementation of the present invention.
A certain iron and steel enterprise is provided with two sets of oxygen generating units for providing low-pressure oxygen and medium-pressure oxygen, the oxygen required by a workshop is supplied by a whole plant pipe network, each conveying pipeline at the entrance of the workshop is provided with a flow, pressure and temperature measuring device, a filter, a cutting device and the like, and then the oxygen is sent to each user for use.
Average oxygen consumption of user in certain period
Firstly, setting the oxygen generation amount y of the oxygen generator in the current time period1＝75000，y163750. When the current gas storage amount of the oxygen spherical tank is vector 0<V<1000m3，△Q j0; when the stored oxygen amount of the spherical tank is higher than the maximum value of the safety range,
△Qj-2000; when the amount of stored oxygen in the spherical tank is lower than the minimum value of the safety range, 
△QjThe equilibrium constraint equation for the oxygen scheduling system can be obtained at 2000.
Restriction of blast furnace users: 20533 is less than or equal to xi≤35400
Constraint of converter users:
and finally, sorting the basic scheduling data and parameters of the iron and steel enterprise, and performing iterative operation by using a solving algorithm.
According to the constraints, a corresponding oxygen distribution scheme can be obtained by solving an algorithm, and the obtained result mainly comprises information such as oxygen generation distribution amount, user condition, oxygen consumption and the like in a period of time.
After the whole distribution target is completely finished, the efficiency of directly distributing the oxygen to the users is high in the aspect of oxygen utilization, and the pressure of an oxygen pipe network in the distribution process of the oxygen is in a specified range, so that the dynamic allocation of the oxygen system is realized.
The invention can fully utilize the oxygen generated by the oxygen generator, realize the rationalization of the oxygen generation amount and the use amount of users, effectively reduce the energy cost and improve the economic benefit of enterprises. The basis of economic dispatching of the oxygen system of the iron and steel enterprise is an oxygen optimization distribution model, and different dynamic oxygen supply modes can be formulated for different users under the idea of advocating high-efficiency performance, so that oxygen diffusion is effectively reduced.
The above examples are provided for illustrative purposes only and are not intended to limit the present invention.
Claims (2)
1. A method for optimizing distribution of an oxygen generation system of a steel enterprise, which is characterized in that,
firstly, establishing a model by using a balance constraint equation and a user characteristic constraint method, classifying the model in users determined by an enterprise, and determining an optimal allocation scheme meeting the requirement of oxygen production according to the characteristics of different types of users; the method comprises the following specific steps:
the first stage is as follows: establishing equilibrium constraint equations for oxygen systems
When the pressure of the pipe network is close to the highest or lowest pressure limit, the pressure is reduced or increased to a specified range by using the regulating quantity;
introducing regulating quantity delta V [ delta ] Q [ ]1,△Q2,…△Qj]When the oxygen content of the pipe network exceeds the maximum pressure limit, delta Qj<0; when the oxygen amount of the pipe network is lower than the lowest pressure limit, delta Qj>0; when the pipe network is operated in the specified range, delta Qj＝0；
1) Let the current gas storage volume of the oxygen spherical tank as vector V ═ Q1,Q2,…Qj]The internal elements of the oxygen system respectively represent the current gas storage value of each spherical tank of the oxygen system;
2) let the oxygen yield be Y ═ Y1,y2,…yl]The internal elements represent the oxygen generation capacity of each oxygen generator; from the above analysis, the oxygen system equilibrium constraint equation is obtained as follows:
wherein F ═ F1,f2,…fn]For different user's dispersion amount, M is the amount converted into liquid oxygen；
For n oxygen users, a user matrix X is formed with:
X＝[x1,x2,…xn]
And a second stage: user constraint model
Dividing aerobic users into stationary users and fluctuating users;
1) smooth user: the oxygen-stable user means that the oxygen demand is relatively stable in the production process, the change is not large along with the change of time, under the normal condition, the oxygen enrichment rate of the blast furnace is determined, and the oxygen demand is fixed and unchanged;
Vmin≤xi≤Vmax
Vmin、Vmaxthe minimum value and the maximum value of the oxygen required by the blast furnace;
2) fluctuating user: the steel-making users have larger fluctuation among all oxygen users, and the oxygen rule of the steel-making users has influence on the balance and the diffusion of oxygen, so that the constraint equation of the steel-making users needs to be specially processed;
wherein m is the number of converters and YmaxThe oxygen quantity of the oxygen generator is obtained;
meanwhile, the overall pressure constraint needs to be determined, and a constraint equation is given according to the overall pressure constraint:
in the formula, Pmin、PmaxThe amount of oxygen representing the minimum and maximum pressure of the system, respectively;
the spherical tank is used as an oxygen buffering device, the designed storage capacity of the spherical tank also needs to be constrained, and the specific constraint equation is as follows:
wherein
The minimum and maximum capacity, Q, which can be borne by the gas storage tankjThe current gas storage amount of the gas storage tank;
and a third stage: optimizing allocation objective function
The oxygen dispatching of the iron and steel enterprises takes the minimum dispersion as a dispatching target, the optimal distribution objective function takes the minimum oxygen demand M as a target, and for an oxygen system consisting of a plurality of users, the distributed objective function is as follows:
A fourth stage: by simplifying assumptions, solving models
1) The general linear programming is converted into a standard form, and an initial feasible basis is constructed; if the constraint condition is less than or equal to, introducing a non-negative relaxation variable xn+1Forming an m-order initial feasible basis; if the constraint condition is'>"or" artificial variable "is introduced when the m-order unit matrix does not exist in the coefficient matrix and is used as the submatrix;
2) determining an initial basic feasible solution: assuming an initial feasible solution, wherein variables of the initial feasible solution are basic variables; the basic variable is not equal to zero, and the initial variable is obtained by introducing a variable as an initial basic variable; the introduction of the variables can be seen that the basic variables have positive unit coefficients, only one equation is provided, and the objective function does not contain the basic variables;
3) optimality tests, i.e. testing the number of tests sigma for non-fundamental variablesj，σjIs the basis for judging the optimal;
4) base transformation: when the obtained basic feasible solution is not the optimal solution, another feasible solution for reducing the objective function value needs to be found, namely, one vertex of the feasible domain is turned to another adjacent vertex, so that the value of the objective function is reduced; when sigma isjNot less than 0, the change-in variable x is determined when the change-in base is carried outjExamination ofDetermining sigma when the exponent is positive k＝max{σj|σj>0} and its corresponding variable xkI.e. a base-changed variable;
when the coefficient column of the swap-in variable has a positive component, the basis variable is swapped out:
determining a swap-out basis variable xl；
5) With aikAs a main element, performing rotation operation to obtain a new basic feasible solution; turning to 3), carrying out optimality test until an optimal solution is solved;
so far, the model of the oxygen optimal distribution method of the iron and steel enterprise is solved through the steps 1), 2), 3), 4), 5); and finally, reasonably using oxygen according to the distribution result.
2. The method for optimizing distribution of an oxygen generation system for an iron and steel enterprise as claimed in claim 1, wherein the global optimal solution or the boundary of the optimal solution of the distribution problem is obtained by simplifying assumptions and solving models; the solution algorithm plans the distribution scheme by an optimal solution, providing an optimal solution to the oxygen distribution problem.
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| CN114091784B (en) * | 2021-12-01 | 2023-05-23 | 重庆大学 | Uncertain optimization scheduling method and system for oxygen system of iron and steel enterprise |
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040117236A1 (en) * | 2002-12-13 | 2004-06-17 | Dharmashankar Subramanian | Automated optimization tool for electric utility sypply services |
| CN1753010A (en) * | 2005-09-21 | 2006-03-29 | 浙江大学 | Classification model construction and rolling derivation for energy source optimization management of iron and steel enterprise |
| CN103439926A (en) * | 2013-07-26 | 2013-12-11 | 同济大学 | Gas optimization scheduling device of iron and steel enterprise |
| CN104102212A (en) * | 2014-07-29 | 2014-10-15 | 浙江中控软件技术有限公司 | Dispatching method, apparatus and system for gas and steam system in iron and steel enterprises |
| CN104239981A (en) * | 2014-10-11 | 2014-12-24 | 中冶南方工程技术有限公司 | Multi-objective optimization algorithm based energy dynamic balancing and optimal dispatching method |
| CN104463360A (en) * | 2014-12-02 | 2015-03-25 | 大连理工大学 | Oxygen and nitrogen energy optimized scheduling method used for metallurgical enterprises and based on mathematical programming |
| US20160140448A1 (en) * | 2014-11-17 | 2016-05-19 | Massachusetts Institute Of Technology | Systems and methods for improving petroleum fuels production |
-
2018
- 2018-10-11 CN CN201811181626.1A patent/CN109214709B/en not_active Expired - Fee Related
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040117236A1 (en) * | 2002-12-13 | 2004-06-17 | Dharmashankar Subramanian | Automated optimization tool for electric utility sypply services |
| CN1753010A (en) * | 2005-09-21 | 2006-03-29 | 浙江大学 | Classification model construction and rolling derivation for energy source optimization management of iron and steel enterprise |
| CN103439926A (en) * | 2013-07-26 | 2013-12-11 | 同济大学 | Gas optimization scheduling device of iron and steel enterprise |
| CN104102212A (en) * | 2014-07-29 | 2014-10-15 | 浙江中控软件技术有限公司 | Dispatching method, apparatus and system for gas and steam system in iron and steel enterprises |
| CN104239981A (en) * | 2014-10-11 | 2014-12-24 | 中冶南方工程技术有限公司 | Multi-objective optimization algorithm based energy dynamic balancing and optimal dispatching method |
| US20160140448A1 (en) * | 2014-11-17 | 2016-05-19 | Massachusetts Institute Of Technology | Systems and methods for improving petroleum fuels production |
| CN104463360A (en) * | 2014-12-02 | 2015-03-25 | 大连理工大学 | Oxygen and nitrogen energy optimized scheduling method used for metallurgical enterprises and based on mathematical programming |
Non-Patent Citations (1)
| Title |
|---|
| 钢铁企业氧气***的优化模型研究;谷悦 等;《第八届全国能源与热工学术年会》;20150826;第334-340页 * |
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