CN112053003B - Scheduling method for intermediate storage tank in crude oil conveying process - Google Patents
Scheduling method for intermediate storage tank in crude oil conveying process Download PDFInfo
- Publication number
- CN112053003B CN112053003B CN202010958598.0A CN202010958598A CN112053003B CN 112053003 B CN112053003 B CN 112053003B CN 202010958598 A CN202010958598 A CN 202010958598A CN 112053003 B CN112053003 B CN 112053003B
- Authority
- CN
- China
- Prior art keywords
- oil
- storage tank
- tanker
- crude oil
- representing
- 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
Links
- 239000010779 crude oil Substances 0.000 title claims abstract description 102
- 238000012432 intermediate storage Methods 0.000 title claims abstract description 89
- 238000000034 method Methods 0.000 title claims abstract description 61
- 238000005457 optimization Methods 0.000 claims abstract description 48
- 238000005096 rolling process Methods 0.000 claims abstract description 30
- 238000004519 manufacturing process Methods 0.000 claims abstract description 10
- 238000012544 monitoring process Methods 0.000 claims abstract description 7
- 238000004364 calculation method Methods 0.000 claims abstract description 6
- 238000012937 correction Methods 0.000 claims abstract description 5
- 239000003921 oil Substances 0.000 claims description 166
- 238000003860 storage Methods 0.000 claims description 86
- 238000012546 transfer Methods 0.000 claims description 18
- 238000012163 sequencing technique Methods 0.000 claims description 10
- 239000000463 material Substances 0.000 claims description 6
- 238000010606 normalization Methods 0.000 claims description 3
- 230000001172 regenerating effect Effects 0.000 claims description 3
- 238000013439 planning Methods 0.000 claims description 2
- 238000012913 prioritisation Methods 0.000 claims 1
- NINIDFKCEFEMDL-UHFFFAOYSA-N Sulfur Chemical compound [S] NINIDFKCEFEMDL-UHFFFAOYSA-N 0.000 description 16
- 229910052717 sulfur Inorganic materials 0.000 description 16
- 239000011593 sulfur Substances 0.000 description 16
- 239000002253 acid Substances 0.000 description 11
- 238000007670 refining Methods 0.000 description 8
- 238000012423 maintenance Methods 0.000 description 7
- 238000004088 simulation Methods 0.000 description 6
- 230000002159 abnormal effect Effects 0.000 description 5
- 230000000737 periodic effect Effects 0.000 description 3
- 230000001105 regulatory effect Effects 0.000 description 2
- FGUUSXIOTUKUDN-IBGZPJMESA-N C1(=CC=CC=C1)N1C2=C(NC([C@H](C1)NC=1OC(=NN=1)C1=CC=CC=C1)=O)C=CC=C2 Chemical compound C1(=CC=CC=C1)N1C2=C(NC([C@H](C1)NC=1OC(=NN=1)C1=CC=CC=C1)=O)C=CC=C2 FGUUSXIOTUKUDN-IBGZPJMESA-N 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
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
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- 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
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
-
- 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)
- Economics (AREA)
- Strategic Management (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Entrepreneurship & Innovation (AREA)
- Marketing (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Quality & Reliability (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Manufacturing & Machinery (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Pipeline Systems (AREA)
Abstract
The invention discloses a dispatching method of intermediate storage tanks in the crude oil conveying process, which is characterized in that the intermediate storage tanks in the crude oil conveying process from a wharf to a factory are dispatched and produced by adopting similar sorting, continuous monitoring, model correction and rolling optimization methods, one dispatching period is divided into a plurality of short periods, and the solved short-period dispatching schemes are combined to form a total dispatching scheme after each short period is optimized in a rolling mode. The method has the advantages of small calculation scale and high solving speed, can timely sense the emergency such as equipment faults, can efficiently arrange the dump of crude oil from the tanker to the intermediate storage tank, reduces the lead time cost of the tanker, and reduces the production cost.
Description
Technical Field
The invention relates to the field of production scheduling of refining enterprises, in particular to a scheduling method of an intermediate storage tank in a crude oil conveying process.
Background
In daily production of a refining enterprise, the dispatching of the intermediate storage tank is often finished manually, and because the process of an oil pipeline is complex, the flow restriction is more, for example, the property of the crude oil stored in the storage tank at present is the same as or similar to that of the crude oil conveyed by the oil pipeline, and the like; furthermore, the number and capacity of tanks is limited and the single scheduling time span is long, which makes the scheduling of oil delivery schemes difficult.
The existing crude oil storage and transportation scheduling methods mostly adopt pure mixed integer programming methods, and the methods have the following problems:
1) Instability of optimal solution yield: the scheduling problem is converted into the mixed integer programming problem by the method for planning the pure mixed integers to be solved so as to obtain the optimal feasible scheme, but the model established by the method has huge solving scale, so that the solving time is long, the optimal solution output is unstable, and the normal storage and transportation arrangement of oil refining enterprises is directly influenced.
2) Does not have adaptive adjustment capability: the method of pure mixed integer programming is often one-time optimization, long-term execution. Therefore, when abnormal conditions such as equipment faults occur in the oil refining process, the scheduling scheme cannot be quickly adjusted according to the equipment conditions fed back by the system, so that the scheduling self-adaptive adjusting capability is weak.
Disclosure of Invention
Aiming at the problems, the invention provides a scheduling method of an intermediate storage tank in the crude oil conveying process, aiming at reducing the problem solving scale, reducing the solving time, improving the stability of the optimal solution output and timely sensing the equipment fault adjustment scheduling scheme. The method has the characteristics of similarity sequencing, continuous monitoring, model correction and rolling optimization, and specifically comprises the following steps of:
1) The alternative oil receiving storage tanks are ordered according to the similarity degree of crude oil properties from high to low, and the specific steps are as follows:
a) Checking the availability of the intermediate storage tank, wherein the available storage tank is used as an alternative, and the unavailable storage tank is removed;
b) Normalizing the crude oil property index:
in the formula (1), Q Nor,j Normalized index representing property of jth crude oil, Q j Index before normalization indicating property of jth crude oil, Q j,min Representing the minimum value, Q, of the j-th crude oil property index in all tankers and intermediate tanks j,max Representing the maximum value of the j-th crude oil property index in all tankers and intermediate tanks;
c) Calculating the Euclidean distance between the property of the crude oil stored in the oil tanker and the property of the crude oil stored in the intermediate storage tank:
q in (2) ST,n,j The j-th crude oil property index representing the current oil storage of the n-th intermediate storage tank, Q V,v,j A j-th crude oil property index representing the current oil storage of the v-th tanker, dst (n, v, u) representing the Euclidean distance between the u-th crude oil property stored in the v-th tanker and the u-th crude oil property stored in the n-th intermediate storage tank, and the smaller Dst (n, v, u) is, the more similar the crude oil properties of the two are;
d) Sequencing the priorities of the oil receiving storage tanks according to the Euclidean distance from small to large to obtain a sequencing queue Seq { d of the oil receiving storage tanks i I=1 … STN, d }, where i Representing the number of intermediate tanks, STN representing the total number of intermediate tanks;
2) The method comprises the following specific steps of:
a) Determining decision variables, specifically comprising: flow rate F of oil pipeline VS Flow rate f of key components of crude oil in oil pipeline VS Oil storage capacity V of oil tanker V Oil storage volume V of intermediate storage tank S Oil storage mass M of intermediate storage tank S Mass M of key components of crude oil in intermediate storage tank Comp 0-1 decision variable D for operating a tanker to transfer crude oil to an intermediate storage tank VS ；
b) The optimization objective is determined as an objective function for minimizing the operation cost, specifically:
in equation (3), min (Cost) represents the objective of the objective function to minimize the operating Cost, C WAIT,v Representing the hold-up costs of the V-th tanker at each moment in time for berthing the quay, V V,v,t The time t is denoted by the oil storage capacity of the oil tanker with the number v, the TC is the time number contained in the scheduling production time period, and the VN is the number of the oil tankers reaching the wharf in the scheduling period.
c) Determining a constraint condition set COTs which accords with the crude oil storage and transportation link requirements of the intermediate storage tank in the oil refining process in the optimization model, wherein the constraint condition set COTs specifically comprises the following constraint conditions:
i. the operation rule is that the v-th tanker can only dump crude oil to one storage tank at any time t:
d in (4) VS,v,n,t Is a 0-1 decision variable which represents the v-th tanker at the moment t to decide whether to transfer oil to the n-th intermediate storage tank, 0 is no oil transfer, 1 is oil transfer, S VN For the set of arrival tankers {1,.. TC For a set of time intervals within a scheduling period {1,., TC };
ii. tanker material balance constraint:
v in (5) V,v,t Indicating the oil storage capacity of the V-th oil ship at the moment t, V V,v,0 Representing the initial oil storage capacity of the v-th tanker in the current dispatching cycle, F VS,v,n,i Representing the flow F of the oil delivery pipeline when the v-th oil ship delivers oil to the n-th intermediate storage tank at the moment i VS Wherein i is<＝t；
intermediate tank material balance constraint:
v in (6) S,n,t Indicating the oil storage capacity of the nth intermediate storage tank at the time t, V S,n,0 Representing the initial oil storage capacity of the nth intermediate tank in the current dispatching cycle, S STN Representing a set of intermediate tanks { 1..stn } within a scheduling period;
m in formula (7) S,n,t Representing the oil storage quality of the nth intermediate storage tank at the moment t, M S,n,0 Representing the initial oil storage quality, ρ, of the nth intermediate tank in the current scheduling period V,v Representing the density of crude oil stored in the v-th tanker;
oil pipeline flow constraints:
f in (8) VS,v,n,min Representing minimum flow of oil pipeline when oil is transferred from v-th oil tanker to n-th intermediate storage tank, F VS,v,n,max Representing maximum flow from the v-th tanker to the n-th intermediate tank pipeline, F VS,v,n,t Representing the flow F of the oil delivery pipeline when the v-th oil tanker delivers oil to the n-th intermediate storage tank at the moment t VS ；
And v. constraint of oil storage capacity of the intermediate storage tank:
v in formula (9) S,n,min Represents the lower limit value of the oil storage capacity of the nth intermediate storage tank, V S,n,max Indicating the upper limit value of the oil storage capacity of the nth intermediate storage tank;
tanker oil storage constraint:
v in (10) S,n,min Indicating the v-th tanker for storing oilLower limit value of quantity, V S,n,max Representing the upper limit value of the oil storage capacity of the v-th oil tanker;
material balance constraint of key component p in intermediate storage tank:
m in formula (11) Comp,p,n,t Representing the mass, M, of the key component p of the nth intermediate tank at time t Comp,p,n,0 Representing the initial mass, f, of the nth intermediate tank key component, p, during a scheduling period VS,p,v,n,i Representing the mass flow of the key component p in the pipeline when the v-th tanker is transporting oil to the n-th intermediate storage tank at the moment i, wherein i<=t, the calculation formula is as follows:
omega in formula (12) V,v,q Represents the concentration of the key component p of the v-th tanker, S Comp Represents a set of key components { 1..cn };
reserve constraint of key component p in intermediate tank:
omega in formula (13) S,n,p,min Represents the lower limit, ω, of the concentration of the nth intermediate tank key component p S,n,p,max Indicating the upper limit of the concentration of the n-th intermediate tank key component p.
3) Length of total scheduling time T all Divided into r rolling optimization periods with time length of TC, T all =tc×r, r is the number of rolling cycles;
4) And (3) performing r-wheel rolling optimization, wherein the specific steps of each wheel of rolling optimization are as follows:
a) Determining the input variable of the optimization solver as the oil storage capacity V of the oil tanker V Oil storage volume V of intermediate storage tank S Oil storage mass M of intermediate storage tank S Mass M of key components of crude oil in intermediate storage tank Comp 0-1 decision variable D for operating a tanker to transfer crude oil to an intermediate storage tank VS Upper limit F of oil pipeline flow VS,max And lower limit F VS,min ；
b) Determining an initial value V of the oil storage capacity of the variable oil tanker input by the optimization solver according to the current conditions of the oil tanker, the storage tank and the oil pipeline V,0 Initial value V of oil storage capacity of intermediate storage tank S,0 Initial mass M of oil stored in intermediate storage tank S,0 Initial value M of key component quality of intermediate storage tank Comp,0 Initial value D of 0-1 decision variable for operating oil tanker to transport crude oil to intermediate storage tank VS,0 Initial value F of upper limit of flow of oil pipeline VS,max,0 And a lower limit initial value F VS,min,0 ；
c) Solving an objective function to obtain a scheduling scheme of the intermediate storage tank with the time length TC;
d) C, judging whether rolling optimization of all rounds is completed, merging the scheduling scheme of current round prediction with the previous round optimization solving result when the rolling optimization of all rounds is not completed, and continuing the step e; if so, ending the current round rolling optimization process and outputting a total scheduling scheme, wherein the total scheduling scheme indicates that all r rounds of rolling optimization are completed;
e) Continuously monitoring the current conditions of the oil tanker, the storage tank and the oil pipeline and updating;
f) Correcting the scheduling model according to the updated current condition, and regenerating the Seq { d } i -and COTs;
g) The output variable Sol (F) VS )、Sol(V V )、Sol(V S )、Sol(D VS ) And Sol (V) Comp ) The last solving result is set as the initial value V of the input variable in the next round of rolling optimization V,0 、V S,0 、M S,0 、M Comp,0 、D VS,0 、F VS,max,0 And F VS,min,0 Turning to the step a;
5) Outputting the time length TC obtained by combining all r-round rolling optimization solving results, and the span reaches T all Time intermediate tank scheduling scheme.
The beneficial effects are that:
compared with the traditional scheduling and production scheduling method, the method improves the stability of the optimal solution yield, reduces the solution time, has good self-adaptive capacity, can sense equipment faults in real time and adjust a scheduling scheme in time, and efficiently schedules the crude oil to be dumped from the tanker to the intermediate storage tank. The method has important significance in improving the efficiency of conveying crude oil from the tanker to the intermediate storage tank, reducing the dead period cost of the tanker and improving the economic benefit of enterprises.
Drawings
FIG. 1 is a flow chart of a pipeline transportation process of a refinery according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a method for rolling optimization segmentation scheduling period in an embodiment of the present invention;
fig. 3 is a flow chart of a method for scheduling intermediate storage tanks for crude oil storage and transportation in an embodiment of the invention.
Detailed Description
The invention will be further described with reference to the accompanying drawings and specific examples, which illustrate the effect of the method in crude oil scheduling by specific operational procedures. The present embodiment is implemented on the premise of the technical scheme of the present invention, but the protection scope of the present invention is not limited to the following examples.
The scheduling method of the invention is specifically aimed at a flow part of crude oil transportation from a tanker to an intermediate storage tank in an oil transportation process of a certain oil refinery, as shown in fig. 1: the oil tanker stopped at the oil unloading dock transfers crude oil to the middle storage tank through the dock-middle storage tank pipeline, and the crude oil is transferred through the oil transfer pump group. In this process, the flow rate of the oil pipeline can be regulated by regulating the oil pump group and the valve.
The present embodiment is a simulation example, and the entity data included in the simulation example is shown in table 1:
table 1 schedule simulation instance initial parameters
In a refining enterprise, the sulfur content and the acid value are often used as key components of crude oil, and in the embodiment, the enterprise requires that the sulfur content of the intermediate storage tank is in the range of 0.5-2.0 wt% and the acid value is in the range of 0-0.5 mgKOH/g so as to meet the requirements of the refining enterprise on the properties of the crude oil.
The flow of the embodiment is shown in fig. 3, and specific implementation steps are as follows:
1) Checking the usability of the storage tank, wherein the storage tank can be used as an alternative, and the unavailable storage tank is removed;
2) Normalizing various property indexes of crude oil:
the property indexes of the crude oil after normalization treatment are shown in table 2:
table 2 initial parameters of crude oil property index normalized by scheduling simulation example
| Oil tanker | Sulfur content | Acid value | Density of |
| V1 | 0 | 0 | 0.1875 |
| Intermediate storage tank | Sulfur content | Acid value | Density of |
| ST1 | 0 | 0 | 0 |
| ST2 | 0.25 | 0.5 | 0.1875 |
| ST3 | 0 | 0 | 0.1875 |
| ST4 | 0.5 | 0 | 0.625 |
| ST5 | 1 | 1 | 1 |
3) Calculating the Euclidean distance between the property of the crude oil stored in the oil tanker and the property of the crude oil stored in the intermediate storage tank:
the Euclidean distance between 3 crude oil properties of the crude oil stored in the 1 ST tanker and 3 crude oil properties of the crude oil stored in the 1 ST intermediate tank ST1 is calculated according to the formula (2):
the Euclidean distances between 3 crude oil properties of the crude oil stored in the oil tanker V1 and 3 crude oil properties of the crude oil stored in the rest intermediate storage tanks ST2, ST3, ST4 and ST5 are 0.5590, 0, 0.5781 and 1.63 respectively;
4) Sequencing the priorities of the oil receiving storage tanks according to the Euclidean distance from small to large to obtain a sequencing queue Seq {3,1,2,4,5}, namely, the intermediate storage tanks receive oil according to the sequence of ST3, ST1, ST2, ST4 and ST 5;
5) And establishing a mixed integer programming model.
First, determining the decision variable as the oil pipeline flow F VS Flow rate f of key components of crude oil in oil pipeline VS Oil storage capacity V of oil tanker V Oil storage volume V of intermediate storage tank S Oil storage mass M of intermediate storage tank S Mass M of key components of crude oil in intermediate storage tank Comp 0-1 decision variable D for operating a tanker to transfer crude oil to an intermediate storage tank VS The key components of crude oil in the case refer to sulfur content and acid value of crude oil;
the objective function that is targeted to minimize the cost of operation is:wherein the scheduling and scheduling time period TC is 1 hour, vn=1 in the present embodiment;
finally, determining constraint condition sets COTs meeting the requirements of crude oil storage and transportation links of the intermediate storage tank in the oil refining process in the optimization model, wherein the constraint condition sets COTs are as follows:
wherein, according to the parameters shown in table 1, the specific parameters of the constants in the above formula are as follows:
6) As shown in fig. 2The total scheduling time length T all The number of the rolling optimization cycles is 21, and the time length of the rolling optimization cycles is TC=1h;
7) The rolling optimization of 21 rounds is carried out, and the specific implementation steps of the rolling optimization of the ith round are as follows:
a) Determining the input variable of the optimization solver as the oil storage capacity V of the oil tanker V Oil storage volume V of intermediate storage tank S Critical component reserves V of crude oil in intermediate storage tank Comp 0-1 decision variable D for operating a tanker to transfer crude oil to an intermediate storage tank VS Upper limit F of oil pipeline flow VS,max And lower limit F VS,min ；
b) Determining an initial value V of the oil storage capacity of the variable oil tanker input by the optimization solver according to the current conditions of the oil tanker, the storage tank and the oil pipeline V,0 Initial value V of oil storage capacity of intermediate storage tank S,0 Initial value V of key component reserve of intermediate storage tank Comp,0 Initial value D of 0-1 decision variable for operating oil tanker to transport crude oil to intermediate storage tank VS,0 Initial value F of upper limit of flow of oil pipeline VS,max,0 And a lower limit initial value F VS,min,0 ；
c) The optimization solver carries out optimization solving on the objective function according to the established mixed integer programming model, the determined decision variable, the input variable and the initial value thereof;
d) The optimal solver solves to obtain the output variable result Sol (F VS )、Sol(V V )、Sol(V S )、Sol(D VS ) And Sol (V) Comp )；
e) Judging whether rolling optimization of all rounds is completed, if not, merging the scheduling scheme predicted by the current round i with the previous round optimization solution results, and continuing the step f; when the completion is finished, the current round of rolling optimization process is finished, and a total scheduling scheme is output, which indicates that all 21 rounds of rolling optimization are finished;
f) Continuously monitoring the current conditions of the oil tanker, the storage tank and the oil pipeline and updating;
g) Regenerating the Seq { d } according to the updated current condition correction model i And COTs, the flow restriction adjustment of the pipeline can be initiated by changing the input variables at the next round of rolling optimizationValue F VS,max,0 And F VS,min,0 To realize the method;
h) The output variable Sol (F) VS )、Sol(V V )、Sol(V S )、Sol(M S )、Sol(D VS ) And Sol (M) Comp ) The last solving result is set as the initial value V of the optimized input variable of the next round of scrolling V,0 、V S,0 、M S,0 、M Comp,0 、D VS,0 Namely, the following formula should be satisfied:
wherein the (i+1) parameter represents the value of the (i+1) th scroll optimized round, and the (i) parameter represents the value of the (i) th scroll optimized round.
i) Turning to step a, starting the rolling optimization of the (i+1) th round and letting i=i+1;
8) Outputting the time length TC and the span T obtained by combining all 21-round rolling optimization solving results all The time intermediate tank scheduling schemes are shown in tables 3, 4,5, 6, 7, respectively.
TABLE 3 scheduling schemes (unit: m) for normally scheduling and scheduling oil storage capacities of lower tankers and intermediate tanks 3 )
TABLE 4 scheduling scheme for sulfur content of crude oil stored in various intermediate tanks under normal scheduling and production (unit: wt%)
TABLE 5 scheduling scheme for acid value of crude oil stored in each intermediate tank under normal scheduling and scheduling (unit: mgKOH/g)
TABLE 6 scheduling scheme for crude oil density stored in each intermediate tank under normal scheduling (unit: g/cm) 3 )
TABLE 7 flow scheduling scheme (unit: m) for normally scheduling production and production pipelines 3 /h)
As can be seen from tables 3, 4,5, 6 and 7, the scheduling method can well complete the solution of the scheduling scheme of each process variable under the condition that each equipment works well in the oil transportation process, and completely meets the requirements of sulfur content and acid value in the crude oil transportation process.
In order to verify the self-adaptation capability of the method of the invention, the invention is demonstrated by two additional abnormal situations.
The first abnormal condition is that the oil delivery pump fails, the number of the operable oil delivery pumps is reduced, the flow rate of the oil delivery pipeline is limited at the 3 rd to the 4 th moments, and the allowable adjustment range is 1000-3000 m 3 Simulation results are shown in tables 8, 9, 10, 11, and 12.
TABLE 8 scheduling schemes (unit: m) for oil storage capacities of tankers and intermediate tanks under failure of oil transfer pump 3 )
TABLE 9 scheduling schemes for sulfur content of crude oil stored in respective intermediate tanks (unit: wt%)
TABLE 10 scheduling scheme for acid value of crude oil stored in each intermediate tank under failure of oil transfer pump (unit: mgKOH/g)
TABLE 11 scheduling schemes (units: g/cm) for the density of crude oil stored in each intermediate tank in case of failure of the transfer pump 3 )
TABLE 12 flow scheduling scheme for oil pipeline under failure of oil pump (unit: m) 3 /h)
It can be seen from table 12 that after the flow rate of the oil pipeline is limited due to the failure of the oil pump, the scheduling method of the invention can adjust the flow rate of the oil pipeline in time according to the current situation, and the scheduling schemes of each process parameter can be correspondingly adjusted according to tables 8, 9, 10 and 11, so as to meet the requirements of sulfur content and acid value in the crude oil transportation process. Therefore, the scheduling method has self-adaptive adjustment capability when facing the fault of the burst equipment.
The second abnormal situation is that since the intermediate tank ST3 needs maintenance at time 3, the intermediate tank ST cannot be used for receiving crude oil temporarily due to maintenance from time 3 to time 21, and simulation results are shown in tables 13, 14, 15, 16, and 17, respectively.
Table 13 ST3 scheduling scheme for oil storage capacity of tanker and intermediate tanks during periodic maintenance
TABLE 14 scheduling of sulfur content of crude oil stored in various intermediate tanks (unit: wt%)
| Abnormal case 2 | ST1 sulfur content | ST2 sulfur content | ST3 sulfur content | ST4 sulfur content | ST5 sulfur content |
| Initial setting | 1.600％ | 1.700％ | 1.600％ | 1.800％ | 2.000％ |
| Time 1 | 1.600％ | 1.699％ | 1.600％ | 1.800％ | 2.000％ |
| Time 2 | 1.600％ | 1.699％ | 1.600％ | 1.800％ | 2.000％ |
| Time 3 | 1.600％ | 1.699％ | 1.600％ | 1.800％ | 2.000％ |
| Time 4 | 1.600％ | 1.699％ | 1.600％ | 1.800％ | 2.000％ |
| …… | …… | …… | …… | …… | …… |
| Time 18 | 1.600％ | 1.604％ | 1.600％ | 1.800％ | 2.000％ |
| Time 19 | 1.600％ | 1.604％ | 1.600％ | 1.762％ | 2.000％ |
| Time 20 | 1.600％ | 1.604％ | 1.600％ | 1.736％ | 2.000％ |
| Time 21 | 1.600％ | 1.604％ | 1.600％ | 1.718％ | 2.000％ |
TABLE 15 ST3 scheduling scheme for acid value of crude oil stored in each intermediate tank (unit: mgKOH/g) for periodic maintenance
/>
TABLE 16 ST3 scheduling schemes (units: g/cm) for the density of crude oil stored in each intermediate tank at the time of periodic maintenance 3 )
Table 17 ST3 flow scheduling scheme (unit: m) for oil pipeline at regular maintenance 3 /h)
From Table 17, it can be seen that from time 4 to time 21 after maintenance of intermediate tank ST3, the scheduling scheme no longer schedules delivery of oil to ST3, but instead orders the queue Seq { d) according to the new oil-receiving tank after ST3 removal i Oil is transported to other intermediate storage tanks, and the scheduling method can well complete solving and adjusting of the scheduling scheme according to the requirements of sulfur content and acid value in the crude oil transportation process as can be seen from tables 13, 14, 15 and 16.
In summary, the method completes solving of the crude oil scheduling scheme of the intermediate storage tank through similar sequencing, continuous monitoring, model correction and rolling optimization, and simultaneously adjusts the scheduling scheme in time according to the current equipment condition, so that the self-adaptability of the scheduling scheme and the production efficiency of enterprises are improved, and further the operation cost and the loss caused by equipment faults are reduced.
Claims (5)
1. A scheduling method of intermediate storage tanks in a crude oil conveying process is characterized in that the intermediate storage tanks in the crude oil conveying process from a wharf to a factory are scheduled and produced by adopting similar sequencing, continuous monitoring, model correction and rolling optimization, and the scheduling method comprises the following steps:
1) Checking the availability of the intermediate storage tank, wherein the available storage tank is used as an alternative, and the unavailable storage tank is removed;
2) Sequencing the alternative oil receiving storage tanks from high to low according to the similarity of crude oil properties to obtain an oil receiving storage tank sequencing queue Seq{d i I=1 … STN, d }, where i Representing the number of intermediate tanks, STN representing the total number of intermediate tanks;
3) Determining decision variables, an objective function min (Cost) and constraint condition sets COTs, and establishing a mixed integer programming scheduling model; the decision variable of the mixed integer planning model is the oil pipeline flow F VS Flow rate f of key components of crude oil in oil pipeline VS Oil storage capacity V of oil tanker V Oil storage volume V of intermediate storage tank S Oil storage mass M of intermediate storage tank S Mass M of key components of crude oil in intermediate storage tank Comp 0-1 decision variable D for operating a tanker to transfer crude oil to an intermediate storage tank VS The method comprises the steps of carrying out a first treatment on the surface of the The objective function in the established mixed integer programming model is as follows:
in equation (3), min (Cost) represents the objective of the objective function to minimize the operating Cost, C WAIT,v Representing the hold-up costs of the V-th tanker at each moment in time for berthing the quay, V V,v,t The method comprises the steps that the oil storage capacity of a tanker with a time number v is represented at t, TC represents the time number contained in a scheduling production time period, and VN represents the number of tankers arriving at a wharf in the scheduling period;
the constraint condition set COTs contained in the established mixed integer programming model comprises the following constraint conditions:
(3-1) operating rules, at any time t, the v-th tanker can dump only crude oil to one tank:
d in (4) VS,v,n,t Is a 0-1 decision variable which represents the v-th tanker at the moment t to decide whether to transfer oil to the n-th intermediate storage tank, 0 is no oil transfer, 1 is oil transfer, S VN For the set of arrival tankers {1,.. TC For a set of time intervals within a scheduling period {1,., TC };
(3-2) tanker material balance constraint:
v in (5) V,v,t Indicating the oil storage capacity of the V-th oil ship at the moment t, V V,v,0 Representing the initial oil storage capacity of the v-th tanker in the current dispatching cycle, F VS,v,n,i Representing the flow F of the oil delivery pipeline when the v-th oil ship delivers oil to the n-th intermediate storage tank at the moment i VS Wherein i is<＝t；
(3-3) intermediate tank material balance constraint:
v in (6) S,n,t Indicating the oil storage capacity of the nth intermediate storage tank at the time t, V S,n,0 Representing the initial oil storage capacity of the nth intermediate tank in the current dispatching cycle, S STN Representing a set of intermediate tanks { 1..stn } within a scheduling period;
m in formula (7) S,n,t Representing the oil storage quality of the nth intermediate storage tank at the moment t, M S,n,0 Representing the initial oil storage quality, ρ, of the nth intermediate tank in the current scheduling period V,v Representing the density of crude oil stored in the v-th tanker;
(3-4) oil pipeline flow restriction:
f in (8) VS,v,n,min Representing minimum flow of oil pipeline when oil is transferred from v-th oil tanker to n-th intermediate storage tank, F VS,v,n,max Representing the most significant transfer of oil from the v-th tanker to the n-th intermediate tankHigh flow, F VS,v,n,t Representing the flow F of the oil delivery pipeline when the v-th oil tanker delivers oil to the n-th intermediate storage tank at the moment t VS ；
(3-5) intermediate tank storage capacity constraint:
v in formula (9) S,n,min Represents the lower limit value of the oil storage capacity of the nth intermediate storage tank, V S,n,max Indicating the upper limit value of the oil storage capacity of the nth intermediate storage tank;
(3-6) tanker oil storage constraint:
v in (10) S,n,min Indicating the lower limit value of the oil storage capacity of the V-th oil tanker, V S,n,max Representing the upper limit value of the oil storage capacity of the v-th oil tanker;
(3-7) material balance constraint of key component p in intermediate storage tank:
m in formula (11) Comp,p,n,t Representing the mass, M, of the key component p of the nth intermediate tank at time t Comp,p,n,0 Representing the initial mass, f, of the nth intermediate tank key component, p, during a scheduling period VS,p,v,n,i Representing the mass flow of the key component p in the pipeline when the v-th tanker is transporting oil to the n-th intermediate storage tank at the moment i, wherein i<=t, the calculation formula is as follows:
omega in formula (12) V,v,q Represents the concentration of the key component p of the v-th tanker, S Comp Representing a set of key components{1...CN}；
(3-8) reserve constraint of key component p in intermediate storage tank:
omega in formula (13) S,n,p,min Represents the lower concentration limit, omega, of the key component p of the nth intermediate storage tank S,n,p,max Represents the upper concentration limit of the key component p of the nth intermediate tank;
4) Length of total scheduling time T all Divided into r rolling optimization periods with time length of TC, T all =tc×r, r is the number of rolling cycles;
5) Determining an input variable and an output variable of the optimization solver and an initial value of the input variable;
6) Collecting the current conditions of the oil tanker, the storage tank and the oil pipeline, and obtaining a scheduling scheme of the middle storage tank with the time length TC according to the optimization calculation of the current conditions;
7) Judging whether optimization calculation of all rounds is completed, and merging the scheduling scheme of current round prediction with the previous round optimization solving result when the optimization calculation of all rounds is not completed, and then turning to the step 8; if so, merging the scheduling schemes obtained after the r-wheel rolling optimization to output a total scheduling scheme;
8) Continuously monitoring the current conditions of the oil tanker, the storage tank and the oil pipeline and updating;
9) Correcting the mixed integer programming scheduling model according to the updated current condition, and regenerating the Seq { d } i -and COTs;
10 Setting the last result of the output variable which is obtained by the previous round of optimization as the initial value of the current round of optimization, returning to the step 6, and starting the new round of rolling optimization.
2. The method of claim 1 wherein the intermediate tank prioritization uses euclidean distance to determine the similarity of crude oil properties to sequentially deliver crude oil to tanks with higher to lower similarity, the steps of:
(2-1) normalizing the crude oil property index:
in the formula (1), Q Nor,j Normalized index representing property of jth crude oil, Q j Index before normalization indicating property of jth crude oil, Q j,min Representing the minimum value, Q, of the j-th crude oil property index in all tankers and intermediate tanks j,max Representing the maximum value of the j-th crude oil property index in all tankers and intermediate tanks;
(2-2) calculating the euclidean distance between the property of the crude oil stored in the tanker and the property of the crude oil stored in the intermediate storage tank according to the normalized property index:
in the formula (2), Q ST,n,j The j-th crude oil property index representing the current oil storage of the n-th intermediate storage tank, Q V,v,j A j-th crude oil property index representing the current oil storage of the v-th tanker, dst (n, v, u) representing the Euclidean distance between the u-th crude oil property stored in the v-th tanker and the u-th crude oil property stored in the n-th intermediate storage tank, the smaller Dst (n, v, u) is, the more similar the crude oil properties of the two are;
(2-3) sequencing the priorities of the oil receiving storage tanks according to the Euclidean distance from small to large to obtain the Seq { d } i },i＝1...STN。
3. The method of claim 1 wherein the optimization solver input variable is a tanker reserve V V Oil storage volume V of intermediate storage tank S Oil storage mass M of intermediate storage tank S Mass M of key components of crude oil in intermediate storage tank Comp 0-1 decision variable D for operating a tanker to transfer crude oil to an intermediate storage tank VS Upper limit F of oil pipeline flow VS,max And lower limit F VS,min 。
4. Method according to claim 1, characterized in that the optimization solver outputs the flow scheduling result Sol (F VS ) Results of the tanker oil storage scheduling Sol (V) V ) Storage capacity scheduling result Sol (V) S ) Storage tank preselection scheduling results Sol (D) VS ) And intermediate tank key component reserves scheduling results Sol (V Comp )。
5. The method of claim 1, wherein the initial value of the input variable to the optimization solver is an initial value of the oil reservoir V V,0 Initial value V of oil storage capacity of intermediate storage tank S,0 Initial mass M of oil stored in intermediate storage tank S,0 Initial value M of key component quality of intermediate storage tank Comp,0 Initial value D of 0-1 decision variable for operating oil tanker to transport crude oil to intermediate storage tank VS,0 Initial value F of upper limit of flow of oil pipeline VS,max,0 And a lower limit initial value F VS,min,0 。
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010958598.0A CN112053003B (en) | 2020-09-14 | 2020-09-14 | Scheduling method for intermediate storage tank in crude oil conveying process |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010958598.0A CN112053003B (en) | 2020-09-14 | 2020-09-14 | Scheduling method for intermediate storage tank in crude oil conveying process |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112053003A CN112053003A (en) | 2020-12-08 |
| CN112053003B true CN112053003B (en) | 2023-12-12 |
Family
ID=73610203
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010958598.0A Active CN112053003B (en) | 2020-09-14 | 2020-09-14 | Scheduling method for intermediate storage tank in crude oil conveying process |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112053003B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112947325B (en) * | 2021-01-28 | 2022-11-08 | 南京富岛信息工程有限公司 | Storage tank dynamic scheduling method for crude oil blending |
| CN113110336B (en) * | 2021-04-20 | 2022-07-15 | 南京富岛信息工程有限公司 | Crude oil dynamic blending method considering scheduling constraint |
| CN113537748B (en) * | 2021-07-07 | 2023-12-22 | 浙江中控技术股份有限公司 | Multi-period blending scheduling production scheduling method and system for crude oil storage and transportation |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102567847A (en) * | 2011-12-20 | 2012-07-11 | 华北电网有限公司 | Intraday dispatching optimization method |
| CN102804083A (en) * | 2009-06-24 | 2012-11-28 | 埃克森美孚研究工程公司 | Tools For Assisting In Petroleum Product Transportation Logistics |
| CN104008431A (en) * | 2014-05-30 | 2014-08-27 | 南京富岛信息工程有限公司 | Crude oil tank farm scheduling method |
| CN106022563A (en) * | 2016-03-04 | 2016-10-12 | 浙江大学 | Anti-interference crude oil dispatching method based on petrochemical enterprise |
| CN106372753A (en) * | 2016-08-31 | 2017-02-01 | 湖南大唐先科技有限公司 | Coal carrier scheduling method and system |
| CN111156419A (en) * | 2020-01-07 | 2020-05-15 | 南京富岛信息工程有限公司 | Variable speed scheduling method and system for long-distance pipeline crude oil mixed transportation |
| CN111612649A (en) * | 2020-05-23 | 2020-09-01 | 上海轻叶能源股份有限公司 | Mobile big data management system for oil storage and transportation |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2809011C (en) * | 2012-11-06 | 2018-07-17 | Mcmaster University | Adaptive energy management system |
-
2020
- 2020-09-14 CN CN202010958598.0A patent/CN112053003B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102804083A (en) * | 2009-06-24 | 2012-11-28 | 埃克森美孚研究工程公司 | Tools For Assisting In Petroleum Product Transportation Logistics |
| CN102567847A (en) * | 2011-12-20 | 2012-07-11 | 华北电网有限公司 | Intraday dispatching optimization method |
| CN104008431A (en) * | 2014-05-30 | 2014-08-27 | 南京富岛信息工程有限公司 | Crude oil tank farm scheduling method |
| CN106022563A (en) * | 2016-03-04 | 2016-10-12 | 浙江大学 | Anti-interference crude oil dispatching method based on petrochemical enterprise |
| CN106372753A (en) * | 2016-08-31 | 2017-02-01 | 湖南大唐先科技有限公司 | Coal carrier scheduling method and system |
| CN111156419A (en) * | 2020-01-07 | 2020-05-15 | 南京富岛信息工程有限公司 | Variable speed scheduling method and system for long-distance pipeline crude oil mixed transportation |
| CN111612649A (en) * | 2020-05-23 | 2020-09-01 | 上海轻叶能源股份有限公司 | Mobile big data management system for oil storage and transportation |
Non-Patent Citations (5)
| Title |
|---|
| A Data-Driven Rolling-Horizon Online Scheduling Model for Diesel Production of a Real-World Refinery;Cao Cuiwen 等;《AICHE JOURNAL》;第59卷(第4期);第1160-1174页 * |
| An-effective lagrangian relaxation approach for multiple-mode crude oil transportation optimization;Qingning Shen 等;《2010 IEEE International Conference on Mechatronics and Automation》;第360-366页 * |
| 原油混炼优化在炼油生产调度中的应用;宫向阳 等;《计算机与应用化学》;第28卷(第9期);第1203-1205页 * |
| 炼油企业生产调度研究;罗春鹏;《中国博士学位论文全文数据库 经济与管理科学辑》(第6期);第J145-34页 * |
| 面向在线调合的原油调度系统关键技术研究;陈伟睿;《中国优秀硕士学位论文全文数据库 工程科技Ⅰ辑》(第3期);第B019-296页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112053003A (en) | 2020-12-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112053003B (en) | Scheduling method for intermediate storage tank in crude oil conveying process | |
| US20240211897A1 (en) | Methods and internet of things (iot) systems for predicting demand for maintenance materials of smart gas pipeline networks | |
| CN103645705B (en) | A kind of LNG multiple spot cargo ship transport power forecast dispatching method | |
| CN103606021A (en) | Dynamic spot goods forecasting and scheduling method for liquefied natural gas (LNG) receiving station | |
| CN106022563A (en) | Anti-interference crude oil dispatching method based on petrochemical enterprise | |
| JP6740860B2 (en) | Safety stock determination device, method and program | |
| CN103632214A (en) | Maintenance and spare part supply combined optimization method for use in absence of inventory degradation data | |
| CN111860968A (en) | Surface mine vehicle scheduling method and system and computer equipment | |
| CN114742502B (en) | Finished oil pipeline conveying coordination optimization system | |
| CN111080052A (en) | Berth scheduling optimization method and system suitable for refinery plant | |
| CN112487608A (en) | Short-term production optimization scheduling method applied to crude oil treatment of oil refinery | |
| Tang et al. | Investigation of berth allocation problem in container ports considering the variety of disruption | |
| CN111291467A (en) | Method for analyzing and optimizing logistics simulation result of ship pipeline production line | |
| CN114742422A (en) | Crude oil scheduling optimization method and device considering low-carbon emission constraint | |
| CN112700086A (en) | Refinery berth scheduling method and device based on hierarchical constraint conditions | |
| US20230252395A1 (en) | A quay crane operation method | |
| KR102645756B1 (en) | Docking schedule system and method of ship based on weather condition and tide | |
| Peng et al. | Reliability based optimal preventive maintenance policy of series-parallel systems | |
| CN111815148B (en) | Scheduling method, scheduling device, electronic equipment and computer readable storage medium | |
| CN113065708A (en) | LNG receiving station demand reserve determination control method based on dynamic programming | |
| CN116384718B (en) | Intelligent decision-based supplier joint scheduling method, system and equipment | |
| CN115660642B (en) | Operation and maintenance optimization method for dry bulk cargo port loading and unloading operation system based on opportunity maintenance | |
| CN116957284A (en) | Tug scheduling method | |
| CN112947325B (en) | Storage tank dynamic scheduling method for crude oil blending | |
| US6785662B1 (en) | Refinery scheduling of incoming crude oil using a genetic algorithm |
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 |