CN117592620A - Cement enterprise-oriented production plan optimization method - Google Patents
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Abstract
The invention discloses a cement enterprise-oriented production plan optimization method, and relates to the technical field of production optimization. The method comprises the following steps: basic data collection: acquiring equipment information and production procedure information on a cement production line; generating a topological relation: representing equipment on a cement production line as a box, inserting nodes and directed line segments between the equipment with production links, and mapping the cement production line into a topological graph formed by the box, the nodes and the directed line segments; and (3) constructing a mathematical model: establishing a physical model of each device on a cement production line and a network topology model based on nodes to form an optimized objective function with minimum running cost as a target; solving an optimization problem: and solving the optimization problem by adopting a branch-and-bound algorithm to obtain a start-stop plan, a production scheme, response capacity and operation cost of each device, and compiling a next-day production plan. The invention can assist the production decision of cement enterprises and obviously reduce the power consumption cost of the enterprises.
Description
Technical Field
The invention relates to the technical field of production optimization, in particular to a cement enterprise-oriented production plan optimization method.
Background
As a traditional consumer with large energy consumption, the electricity cost of the cement production industry generally accounts for more than 50% of the total operation cost of enterprises. Therefore, the development of optimization of the production plan of cement enterprises has important value for improving the production benefits of the enterprises. At present, most cement manufacturing enterprises have rough management modes, lack production adjustment means aiming at time-sharing dynamic electricity price and demand side response, and the production plan cannot adapt to a market electricity price mechanism in time. Particularly, resources such as photovoltaic and energy storage managed by cement enterprises are mostly in a fixed mode, and cannot be coordinated with a production plan, so that the cost reduction and synergy potential of the enterprises cannot be fully exploited. Therefore, how to build a comprehensive optimization model with the minimum electricity cost as a goal, and further realize the whole-flow optimization of cement production is one of the difficulties to be solved.
Disclosure of Invention
In order to solve at least one technical problem in the background art, the invention aims to provide a cement enterprise-oriented production plan optimization method which can assist in the production decision of cement enterprises and remarkably reduce the power consumption cost of the enterprises.
To achieve the above object, in a first aspect, the present invention provides a cement-enterprise-oriented production plan optimization method, including the steps of:
s1, basic data collection: acquiring equipment information and production procedure information on a cement production line, wherein the equipment information comprises equipment types, parameters and maintenance plans;
s2, generating a topological relation: according to the production procedure information, equipment on a cement production line is represented as a square frame, nodes and directed line segments are inserted between the equipment with production connection, and the cement production line is mapped into a topological graph formed by the square frame, the nodes and the directed line segments;
s3, constructing a mathematical model: according to the topological relation, establishing a physical model of each device on the cement production line and a network topological model based on nodes to form an optimized objective function with minimum running cost as a target;
s4, solving an optimization problem: and solving the optimization problem by adopting a branch-and-bound algorithm to obtain a start-stop plan, a production scheme, response capacity and operation cost of each device, and compiling a next-day production plan.
In certain embodiments of the first aspect of the present invention, the device physical model comprises:
a crusher model, a raw material mill model, a coal mill model and a cement mill model;
a raw material bin model, a clinker bin model and a cement bin model;
a conveyor belt model;
and (5) a rotary kiln model.
In certain embodiments of the first aspect of the present invention, the breaker model, the feedstock mill model, the coal mill model, the cement mill model comprise the following constraints:
1) Minimum run-time constraint: once the device is turned on, it is operated continuously for at least a period of time;
2) Minimum downtime constraints: once the equipment is shut down, at least one period of continuous shutdown is required;
3) The fixed operating condition constraints include:
initial state constraints: the equipment just returns to the running state from the maintenance state, and the running state is kept until the minimum running time requirement is met due to the existence of the minimum continuous running time;
the necessary stop period constraint: the device must be shut down for some period of time;
the necessary on period constraint: the device must operate for some period of time;
4) And (5) restraining the start and stop times: the equipment is not allowed to start and stop for more than a specified number of times in a specified number of time periods;
5) Production mode constraint: introducing a production mode variable to indicate whether the equipment produces a corresponding class of material for a specified period of time;
6) Input-output constraint: in a prescribed period, the amount of material output by the device to the output side node is equal to the product of the amount of material acquired from the input side node and the input-output conversion coefficient; if the equipment is in an operation state, the power consumption of the equipment is equal to the rated power consumption of the equipment, otherwise, the power consumption of the equipment is zero.
In certain embodiments of the first aspect of the present invention, the raw bin model, delicatessen model, cement bin model comprise the following constraints:
1) Warehouse balance constraint: the material entering and exiting of each period meets the balance constraint;
2) Material stock constraint: the material storage amount of the warehouse is in the minimum storage capacity and the maximum storage capacity range;
3) Initial inventory constraints: in the initial state, the material storage amount of the warehouse is the set initial stock;
4) Terminating the inventory constraint: the ending inventory should be greater than or equal to the sum of the initial inventory and the lowest inventory increment.
In certain embodiments of the first aspect of the invention, the conveyor belt model comprises the following constraints:
1) Delivery capacity constraint: the material quantity obtained by the conveyor belt from the node in each period does not exceed the maximum conveying capacity of the conveyor belt;
2) Input-output constraint: in a specified period, the input material quantity of the conveyor belt is equal to the output material quantity; if the conveyor belt is in an operating state, the power consumption of the conveyor belt is equal to the rated power consumption of the equipment, otherwise, the power consumption of the conveyor belt is zero.
In certain embodiments of the first aspect of the present invention, the rotary kiln model comprises the following constraints:
1) Input-output constraint: in a specified period, the input material quantity and the output material quantity of each rotary kiln are respectively equal to the rated input material quantity and the rated output material quantity of the rotary kiln; the electric power used is equal to the opposite number of the rated electric power generated.
In certain embodiments of the first aspect of the present invention, the network topology model includes a node model, a photovoltaic energy storage model, a gateway metering model, and a demand response model.
In certain embodiments of the first aspect of the present invention, the node model includes the following constraints:
1) Material balance constraint: for the nodes, the input material quantity and the output material quantity of each period are equal;
2) Node type constraint:
each node introduces a material input variable and a material output variable, and the node type is modeled under the following three conditions:
when the node has output or no input, the material input variable introduced by the node is greater than or equal to zero, and the material output variable is equal to zero;
when the node has input and output, the material input variable introduced by the node is equal to zero, and the material output variable is greater than or equal to zero;
when the node has input and output, the material input variable introduced by the node is equal to zero, and the material output variable is equal to zero.
In certain embodiments of the first aspect of the present invention, the photovoltaic energy storage model comprises the following constraints:
1) Electric quantity balance constraint: the charge and discharge power and the residual electric quantity of the light storage in each period are kept balanced;
2) Optical storage power constraint: in a specified period, the charge and discharge power of the optical storage does not exceed the upper limit of the charge and discharge power; the actual photovoltaic output of the photo-store does not exceed the predicted photovoltaic output; the total active power of the photo-store is equal to the sum of the charging power minus the discharging power and the actual photovoltaic output;
3) Remaining capacity constraint: the remaining capacity of the photo-storage is between the set minimum remaining capacity and the set maximum remaining capacity.
In certain embodiments of the first aspect of the present invention, the gateway metering model includes the following constraints:
1) And (5) internet power constraint: at the same time, only one of the two states of selling electricity to the power grid by the enterprise and purchasing electricity from the power grid by the enterprise exists;
2) Power backoff limit: if the enterprise is not allowed to sell electricity to the power grid, the variable of the internet surfing power is fixed to be 0;
3) Power balance constraint: the power purchase and power consumption of enterprises in each period are balanced.
In certain embodiments of the first aspect of the present invention, the demand response model includes the following constraints:
1) Event participation constraint: the demand response capacity is between the minimum response capacity and the maximum response capacity required by the demand response event;
2) Responding to capacity constraints: the demand response capacity does not exceed the load shedding value for each period.
In certain embodiments of the first aspect of the present invention, the optimization objective function is expressed as:
wherein:、/>respectively istThe time period enterprises purchase electricity from the power grid and sell electricity to the power grid; />Capacity response for demand; />Is thattThe period of time electricity purchase price from the power grid; />Is thattElectricity price of selling electricity to the power grid in a period; />Compensating the price for the demand response;/>for each period duration; />Time is executed for the demand response event.
In a second aspect, the present invention provides a cement-enterprise-oriented production plan optimization system comprising:
the data acquisition unit is used for acquiring equipment information and production procedure information on the cement production line, wherein the equipment information comprises equipment types, parameters and maintenance plans;
the topology generation unit is used for representing equipment on a cement production line as a block according to the production procedure information, inserting nodes and directed line segments between the equipment with production connection, and mapping the cement production line into a topology graph formed by the block, the nodes and the directed line segments;
the model construction unit is used for constructing physical models of all equipment on the cement production line and a network topology model based on nodes according to the topological relation to form an optimization objective function with minimum running cost as a target;
and the optimization solving unit is used for solving the optimization problem by adopting a branch-and-bound algorithm to obtain a start-stop plan, a production scheme, response capacity and operation cost of each device and compile a next-day production plan.
Compared with the prior art, the invention has the beneficial effects that:
on the basis of collecting various production data of enterprises, the invention maps various working procedures in cement production into a production line flow chart by using a topology modeling method, and then considers time-sharing dynamic electricity price, demand side response, various equipment constraints such as crushers, raw material mills, rotary kilns, cement bins, optical storage systems and the like, establishes a comprehensive optimization model with minimum electricity consumption cost as a target, and realizes the whole-flow optimization of cement production. The production plan optimization method provided by the invention can effectively assist the production decision of cement enterprises, obviously reduce the power consumption cost of the enterprises, is very flexible in modeling strategy, can cope with different types of cement production scenes, and has good practical application value.
Drawings
Fig. 1 is a flowchart of an overall method according to a first embodiment of the present invention.
Fig. 2 is a schematic topology diagram of a first embodiment of the present invention.
Fig. 3 is time-of-use electricity price information of an enterprise location and electricity consumption conditions of each period of the enterprise after optimization according to the first embodiment of the present invention.
Fig. 4 is a production electricity plan of a part of equipment according to the embodiment of the present invention.
Fig. 5 is a system block diagram of a second embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely, and it is apparent that the described embodiments are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Referring to fig. 1, the present embodiment provides a cement-enterprise-oriented production plan optimization method, which includes the following steps:
s1, basic data collection: and acquiring equipment information and production procedure information on the cement production line, wherein the equipment information comprises equipment types, parameters and maintenance plans. Specifically, the type and parameters of the device can be obtained from the nameplate of the device; the overhaul plan is included in cement production line production plan information, which includes other information such as various material target yields, stock of storage materials, raw material supply information, and the like, in addition to the overhaul plan. Other production necessary information is also obtained, including photovoltaic predicted force, demand response event (including compensation price and response time period), baseline load, energy storage residual capacity and the like.
Taking a certain cement production enterprise as an example, information such as various equipment accounts, production procedure relations, cement production types and target yield, historical load levels, photovoltaic predicted output, time-of-use electricity prices, daily average production cost and the like of the cement enterprise is obtained through investigation and investigation. The partial device information is shown in tables 1 and 2.
TABLE 1
| Device name | Rated power/kW | Rated material output/t | Conversion coefficient of material | Minimum number of operating time periods | Minimum number of outage periods |
| Crusher 1 | 800 | 400 | 1.0 | 40 | 4 |
| Raw material mill 1 | 8900 | 900 | 1.0 | 40 | 16 |
| Cement mill 1 | 9000 | 500 | 0.8 | 40 | 16 |
TABLE 2
S2, generating a topological relation: in order to facilitate mathematical modeling and improve portability of the model, the method comprises the steps of representing equipment on a cement production line as a box according to the production procedure information, inserting nodes and directed line segments between the equipment with production links, and mapping the cement production line into a topological graph formed by the box, the nodes and the directed line segments.
The topological diagram is drawn according to the actual condition of the enterprise, and is provided with 15 nodes, 3 crushers, 1 raw material bin, 2 raw material mills, 2 raw material bins, 3 conveyor belts, 2 rotary kilns, 2 acquisitions bins, 2 cement mills and 2 cement bins, and the equipment numbers are marked in the figure 2.
S3, constructing a mathematical model: according to the topological relation, establishing a physical model of each device on the cement production line and a network topological model based on nodes to form an optimized objective function with minimum running cost as a target;
the plant physical model can be broadly divided into the following four categories:
a crusher model, a raw material mill model, a coal mill model and a cement mill model;
a raw material bin model, a clinker bin model and a cement bin model;
a conveyor belt model;
and (5) a rotary kiln model.
The following describes the four types of equipment physical models one by one:
1. the crusher model, the raw material mill model, the coal mill model and the cement mill model comprise the following constraints:
1) Minimum runtime constraints
Once equipment such as a crusher, a raw material mill, a coal mill, a cement mill and the like in the cement production line is started, the equipment at least needs to continuously run for a period of time; the available constraints are expressed as
(1)
Wherein:is a devicekAt the position oftThe running state of the time period is taken as 1 to represent running, 0 to represent shutdown/maintenance,k/>{ crusher, raw mill, coal mill, cement mill }; />Is a devicekIs provided for the minimum number of consecutive operating periods.
2) Minimum downtime constraints
Once equipment such as a crusher, a raw material mill, a coal mill, a cement mill and the like in the cement production line is shut down, the equipment is at least required to be continuously shut down for a period of time; the available constraints are expressed as
(2)
Wherein:is a devicekA minimum number of consecutive outage periods.
3) Fixed operating condition constraints
(1) Initial state constraints
To ensure continuity of operation/maintenance schedule, the effect of the minimum start-up time of the last cycle on the initial state of the equipment is also considered after entering a new production cycle. Such as an apparatuskUpon restoration from the service state to the operational state, due to the presence of the minimum continuous operational time, it should remain in the operational state until the minimum operational time requirement is met.
(3-a)
Wherein:is a devicekTaking 0 to represent shutdown maintenance and taking 1 to represent in-service operation;is a devicekIt is also necessary to maintain its initial state +.>Is a minimum number of time periods of (a).
The setting rules are as follows:
a) If enter the new round of optimization, the equipmentkIs in the initial state of (2)And apparatuskIs->State traceback has at least maintained +.>Time period->Otherwise->Therefore there is->；
b) If enter the new round of optimization, the equipmentkIs in the initial state of (2)And apparatuskIs->State traceback has at least maintained +.>Time period->Otherwise->Therefore there is->。
(2) Must stop time period constraint
Considering the actual production requirements, the devicekMust be shut down for a certain period of time, i.e
(3-b)
In the method, in the process of the invention,Sis a set of keep-out periods.
(3) Time-of-day constraint
Considering the actual production requirements, the devicekMust operate within certain time periods, i.e
(3-c)
In the method, in the process of the invention,Rto open a set of time periods.
4) Start-stop times constraint
To avoid frequent start-stop and reduce the service life of the equipment, the equipment is provided withkIn the presence ofTThe start and stop times in each period are not allowed to exceedSecondary, i.e
(4)
(5)
(6)
Wherein:is a devicekAt the position oftThe time period is relative to%t-1) number of time period state changes.
5) Production mode constraints
Because the same equipment can produce different types of materials (such as a cement mill can produce different types of cement), the variable of the production mode is introducedFor representingtTime period devicekWhether or not to produce the firstmClass material, taking into account production shift requirements of each class material>Then there is
(7)
(8)
(9)
(10)
Wherein:is thattTime period devicekMaterialmWhether 0-1 variable is produced, 1 is taken to represent production, and 0 is taken to represent no production;is a devicekAt the position oftThe time period is relative to%t-1) number of time period production pattern changes; />Is the firstmMaximum production shift of class material; />Is a devicekThe number of types of materials that can be produced.
6) Input-output constraints
Apparatus and method for controlling the operation of a devicekThe material input and output and the electric power can be expressed by the following formulas
(11)
(12)
(13)
(14)
Wherein:is thattTime period devicekFrom the input side nodeiAcquired firstmAmount of material class->Is a devicekInput devicemRating of the class material quantity; />Is a devicekMaterialmIs a conversion coefficient of input and output; />Is thattTime period devicekTo the output side nodejOutput ofmThe amount of the class material; />Is a devicekMaterialmIs the lowest target yield of (2); />Is a devicekAt the position oftThe power consumption of the period of time; />Is a devicekIs used for the rated power.
2. The raw material bin model, the cement bin model comprise the following constraints:
1) Storage balance constraint
The material in-warehouse and out-warehouse of each period should meet balance constraint, namely
(15)
Wherein:is a warehousekAt the position oftStock of material in time period; />H for each period duration.
2) Material inventory constraint
The material storage amount of the warehouse is within the minimum storage capacity and the maximum storage capacity, namely
(16)
Wherein:、/>respectively isWarehousekMinimum and maximum inventory amounts of (a).
3) Initial inventory constraints
In the initial state, the material storage quantity of the warehouse is set as initial stock, namely
(17)
Wherein:is a warehousekIs a new stock of stock.
4) Terminating inventory constraints
The ending inventory should be greater than or equal to the sum of the initial inventory and the lowest inventory increment, i.e
(18)
Wherein:is a warehousekIs the lowest inventory increment of (c).
3. The conveyor belt model includes the following constraints:
1) Delivery capacity constraints
Conveyor belt for each time periodkSlave nodeiThe amount of material obtained should not exceed its maximum conveying capacity, i.e
(19)
Wherein:is a conveyor beltkAn upper limit of the transport capacity.
2) Input-output constraints
The input material amount of the conveyor belt is equal to the output material amount, if the conveyor belt is in an operation state, the power consumption of the conveyor belt is equal to the rated power consumption of the equipment, otherwise, the power consumption of the conveyor belt is zero, namely
(20)
(21)
Wherein:、/>for connecting nodesiSum nodejIs a belt conveyor of (a)kAt the position oftThe input material amount and the output material amount of the time period; />Is a conveyor beltkAt the position oftElectric power for time period->For its nominal value.
4. The rotary kiln model includes the following constraints:
rotary kiln for calcining cement clinker, the mathematical model of which can be expressed as
1) Input-output constraints
In a specified period, the input material quantity and the output material quantity of each rotary kiln are respectively equal to the rated input material quantity and the rated output material quantity of the rotary kiln; by electric powerEqual to the opposite of the rated power, i.e.
(22)
(23)
(24)
Wherein:is a rotary kilnkIs a nominal input material quantity; />Is a rotary kilnkIs a rated output material quantity; />Is a rotary kilnkIs set in the power supply system.
The network topology model comprises a node model, a photovoltaic energy storage model, a gateway metering model and a demand response model. The models are described one by one as follows:
5. the node model includes the following constraints:
1) Material balance constraint
For nodesiThe input material amount and the output material amount of each period should be equal, i.e
(25)
Wherein:、/>respectively are and nodesiRelated devicesk（k=1,2,…，K) Material input and output variables of>，IThe number of nodes; when->When (I)>、/>Respectively nodesiThe input variable and the output variable of the material are introduced by the self.
2) Node type constraints
Each node introduces a material input variable and a material output variable, and the node type is modeled under the following three conditions:
(1) when the nodeiWith or without input of output, i.e.iThe output end of the node is connected with equipment, and the input end is not connected with equipment, if
，/>(26)
(2) When the nodeiWith input or no output, i.e.iThe input end of the node is connected with equipment, and the output end is not connected with equipment, if
，/>(27)
(3) When the nodeiWith input or output, i.e.iThe input end of the node is connected with equipment, and the output end of the node is connected with equipment, if
，/>(28)
6. The photovoltaic energy storage model includes the following constraints:
1) Electric quantity balance constraint
The charge and discharge power and the residual electric quantity of the stored energy in each period of time are balanced, namely
(29)
Wherein:to store energykAt the position oftResidual capacity in a period of time, kWh; />、/>Respectively is energy storagekAt the position oftCharge and discharge power of the period; />、/>Respectively is energy storagekIs provided.
2) Optical storage power constraint
In a specified period, the charge and discharge power of the optical storage does not exceed the upper limit of the charge and discharge power; the actual photovoltaic output of the photo-store does not exceed the predicted photovoltaic output; the total active power of the photo-store is equal to the sum of the charging power minus the discharging power and the actual photovoltaic output, namely
(30)
(31)
(32)
(33)
Wherein:、/>respectively is energy storagekCharging and discharging power of (a)An upper limit; />Is an optical storage systemkAt the position oftActual photovoltaic output of the time period; />Is an optical storage systemkAt the position oftPredicted photovoltaic output for a period of time; />Is an optical storage systemkIs not limited to the total active power of (a).
3) Remaining capacity constraint
In order to avoid the reduction of service life due to overcharge and overdischarge of the stored energy, the remaining energy of the stored energy should be within a safe range (set minimum remaining energy and maximum remaining energy), i.e
(34)
Wherein:、/>respectively is energy storagekOf (2), wherein +.>，/>，/>、The initial and final amounts of energy storage are respectively.
7. The gateway metering model includes the following constraints:
1) Internet power constraints
At the same time, the enterprise sells electricity to the power grid and the enterprise purchases electricity from the power grid, and only one of the two states exists, namely
(35)
(36)
Wherein:for the online power variable, 1 is taken to represent that the enterprise sells electricity to the power grid, and 0 is taken to represent that the enterprise purchases electricity from the power grid.
2) Power foldback limit
If the enterprise is not allowed to sell electricity to the power grid, there is
(37)
3) Power balance constraint
The electricity purchasing and electricity consumption of enterprises in each period are balanced, namely
(38)
，/>(39)
Wherein:、/>respectively istAnd (5) purchasing electricity and surfing power from the power grid by a time period enterprise, and kW.
8. Demand response model
1) Event participation constraint
The demand response capacity is between the minimum response capacity and the maximum response capacity required by the demand response event, i.e
(40)
Wherein:to determine whether to participate in the demand response 0-1 variable, 1 is taken to represent participation, and 0 is taken to represent non-participation; />Capacity response for demand; />、/>The minimum and maximum response capacities required for the demand response event, respectively.
2) Responsive capacity constraints
Demand response capacityLoad reduction values not exceeding the respective time period, i.e.
(41)
Wherein:is thattHistorical baseline load for a period is averaged from the past five weekdays or non-weekdays power loads.
9. Optimizing an objective function
With the minimum electricity cost of enterprises as an objective function, the objective function can be expressed as
(42)
Wherein:is thattThe period of time is from the electricity price of the power grid, yuan/kWh; />Is thattThe electricity selling price (the online electricity price) of the power grid is carried out in a period, and the electricity selling price is the element/kWh; />Compensating the price for demand response, meta/kWh; />For each period of time duration, hours; />Time, hours, for the demand response event to execute.
For example: and substituting the parameters and the topology information of the equipment into the formulas (1) to (42) according to the data collected in the step S1 and the topology diagram in the step S2, and establishing a production optimization model of the enterprise. For example, the input end of the crusher 1 (number 15) is connected with the node 1, the output end is connected with the node 2, and for the 1 st period, the material input variable isThe material output variable is. Node 1 has an output or not (node 1 input is a dotted line in FIG. 2), and has +.>，/>. Node 2 has an input/output (node 2 input/output is solid in FIG. 2), and has +_according to equation (28)>，/>. Node 14 has an input or an output (the output of node 14 is shown as a dotted line in FIG. 2), and has +.>，/>. Taking nodes 1, 2 and 14 as examples, the node material balance equation of the 1 st period can be written according to the formula (25) as follows
/>
Other constraints may be obtained by similar methods as described above and are not described in detail herein.
S4, solving an optimization problem: and solving the optimization problem by adopting a branch-and-bound algorithm to obtain a start-stop plan, a production scheme, response capacity and operation cost of each device, and compiling a next-day production plan.
Taking the cement production enterprise as an example, the total running cost is 12.2805 ten thousand yuan, the production cost of the cement production enterprise is reduced by 7.10 percent compared with that of the cement production enterprise before optimization, and the cost is obviously reduced after calculation, and the problem solving time is 9.73 seconds. Fig. 3 shows time-of-use electricity price information of the enterprise location and electricity consumption conditions of the optimized enterprise in each period, and fig. 4 shows a production electricity plan of the optimized partial equipment. Therefore, the method of the invention optimizes the enterprise production plan, ensures the completion of the production task, and reasonably arranges the operation condition of each device of the production line, reduces the electricity consumption at the time of peak electricity price, thereby reducing the energy consumption cost of enterprises and improving the economic benefit.
Example two
Referring to fig. 5, the present embodiment provides a cement-enterprise-oriented production plan optimization system, which includes:
the data acquisition unit is used for acquiring equipment information and production procedure information on the cement production line, wherein the equipment information comprises equipment types, parameters and maintenance plans;
the topology generation unit is used for representing equipment on a cement production line as a block according to the production procedure information, inserting nodes and directed line segments between the equipment with production connection, and mapping the cement production line into a topology graph formed by the block, the nodes and the directed line segments;
the model construction unit is used for constructing physical models of all equipment on the cement production line and a network topology model based on nodes according to the topological relation to form an optimization objective function with minimum running cost as a target;
and the optimization solving unit is used for solving the optimization problem by adopting a branch-and-bound algorithm to obtain a start-stop plan, a production scheme, response capacity and operation cost of each device and compile a next-day production plan.
The details (including specific constraints of the device physical model and the network topology model) and the specific working principles of the embodiment are the same as those of the first embodiment, and are not described herein again.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
Claims (12)
1. The cement enterprise-oriented production plan optimization method is characterized by comprising the following steps of:
s1, basic data collection: acquiring equipment information and production procedure information on a cement production line, wherein the equipment information comprises equipment types, parameters and maintenance plans;
s2, generating a topological relation: according to the production procedure information, equipment on a cement production line is represented as a square frame, nodes and directed line segments are inserted between the equipment with production connection, and the cement production line is mapped into a topological graph formed by the square frame, the nodes and the directed line segments;
s3, constructing a mathematical model: according to the topological relation, establishing a physical model of each device on the cement production line and a network topological model based on nodes to form an optimized objective function with minimum running cost as a target;
s4, solving an optimization problem: and solving the optimization problem by adopting a branch-and-bound algorithm to obtain a start-stop plan, a production scheme, response capacity and operation cost of each device, and compiling a next-day production plan.
2. The cement-enterprise-oriented production plan optimization method of claim 1, wherein the plant physical model comprises:
a crusher model, a raw material mill model, a coal mill model and a cement mill model;
a raw material bin model, a clinker bin model and a cement bin model;
a conveyor belt model;
and (5) a rotary kiln model.
3. The cement-enterprise-oriented production plan optimization method of claim 2, wherein the crusher model, the raw mill model, the coal mill model, the cement mill model comprise the following constraints:
1) Minimum run-time constraint: once the device is turned on, it is operated continuously for at least a period of time;
2) Minimum downtime constraints: once the equipment is shut down, at least one period of continuous shutdown is required;
3) The fixed operating condition constraints include:
initial state constraints: the equipment just returns to the running state from the maintenance state, and the running state is kept until the minimum running time requirement is met due to the existence of the minimum continuous running time;
the necessary stop period constraint: the device must be shut down for some period of time;
the necessary on period constraint: the device must operate for some period of time;
4) And (5) restraining the start and stop times: the equipment is not allowed to start and stop for more than a specified number of times in a specified number of time periods;
5) Production mode constraint: introducing a production mode variable to indicate whether the equipment produces a corresponding class of material for a specified period of time;
6) Input-output constraint: in a prescribed period, the amount of material output by the device to the output side node is equal to the product of the amount of material acquired from the input side node and the input-output conversion coefficient; if the equipment is in an operation state, the power consumption of the equipment is equal to the rated power consumption of the equipment, otherwise, the power consumption of the equipment is zero.
4. The cement-enterprise-oriented production plan optimization method of claim 2, wherein the raw bin model, cement bin model include the following constraints:
1) Warehouse balance constraint: the material entering and exiting of each period meets the balance constraint;
2) Material stock constraint: the material storage amount of the warehouse is in the minimum storage capacity and the maximum storage capacity range;
3) Initial inventory constraints: in the initial state, the material storage amount of the warehouse is the set initial stock;
4) Terminating the inventory constraint: the ending inventory should be greater than or equal to the sum of the initial inventory and the lowest inventory increment.
5. A cement-enterprise-oriented production plan optimization method in accordance with claim 2, wherein the conveyor belt model comprises the following constraints:
1) Delivery capacity constraint: the material quantity obtained by the conveyor belt from the node in each period does not exceed the maximum conveying capacity of the conveyor belt;
2) Input-output constraint: in a specified period, the input material quantity of the conveyor belt is equal to the output material quantity; if the conveyor belt is in an operating state, the power consumption of the conveyor belt is equal to the rated power consumption of the equipment, otherwise, the power consumption of the conveyor belt is zero.
6. A cement-enterprise-oriented production plan optimization method in accordance with claim 2, wherein the rotary kiln model comprises the following constraints:
1) Input-output constraint: in a specified period, the input material quantity and the output material quantity of each rotary kiln are respectively equal to the rated input material quantity and the rated output material quantity of the rotary kiln; the electric power used is equal to the opposite number of the rated electric power generated.
7. The cement-enterprise-oriented production plan optimization method of claim 1, wherein the network topology model comprises a node model, a photovoltaic energy storage model, a gateway metering model, and a demand response model.
8. The cement-enterprise-oriented production plan optimization method of claim 7, wherein the node model includes the following constraints:
1) Material balance constraint: for the nodes, the input material quantity and the output material quantity of each period are equal;
2) Node type constraint:
each node introduces a material input variable and a material output variable, and the node type is modeled under the following three conditions:
when the node has output or no input, the material input variable introduced by the node is greater than or equal to zero, and the material output variable is equal to zero;
when the node has input and output, the material input variable introduced by the node is equal to zero, and the material output variable is greater than or equal to zero;
when the node has input and output, the material input variable introduced by the node is equal to zero, and the material output variable is equal to zero.
9. The cement-enterprise-oriented production plan optimization method of claim 7, wherein the photovoltaic energy storage model comprises the following constraints:
1) Electric quantity balance constraint: the charge and discharge power and the residual electric quantity of the light storage in each period are kept balanced;
2) Optical storage power constraint: in a specified period, the charge and discharge power of the optical storage does not exceed the upper limit of the charge and discharge power; the actual photovoltaic output of the photo-store does not exceed the predicted photovoltaic output; the total active power of the photo-store is equal to the sum of the charging power minus the discharging power and the actual photovoltaic output;
3) Remaining capacity constraint: the remaining capacity of the photo-storage is between the set minimum remaining capacity and the set maximum remaining capacity.
10. The cement-enterprise-oriented production plan optimization method of claim 7, wherein the gateway metering model comprises the following constraints:
1) And (5) internet power constraint: at the same time, only one of the two states of selling electricity to the power grid by the enterprise and purchasing electricity from the power grid by the enterprise exists;
2) Power backoff limit: if the enterprise is not allowed to sell electricity to the power grid, the variable of the internet surfing power is fixed to be 0;
3) Power balance constraint: the power purchase and power consumption of enterprises in each period are balanced.
11. The cement-enterprise-oriented production plan optimization method of claim 7, wherein the demand response model includes the following constraints:
1) Event participation constraint: the demand response capacity is between the minimum response capacity and the maximum response capacity required by the demand response event;
2) Responding to capacity constraints: the demand response capacity does not exceed the load shedding value for each period.
12. The cement-enterprise-oriented production plan optimization method of claim 1, wherein the optimization objective function is expressed as:
wherein:、/>respectively istThe time period enterprises purchase electricity from the power grid and sell electricity to the power grid; />Capacity response for demand; />Is thattThe period of time electricity purchase price from the power grid; />Is thattElectricity price of selling electricity to the power grid in a period; />Compensating the price for the demand response;for each period duration; />Time is executed for the demand response event.
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