CN112686467A - Large-user production operation optimization method and device containing self-contained power plant and terminal equipment - Google Patents
Large-user production operation optimization method and device containing self-contained power plant and terminal equipment Download PDFInfo
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Abstract
The application provides a method, a device, terminal equipment and a computer-readable storage medium for optimizing production and operation of a large user including a self-contained power plant; the method comprises the steps of establishing a large-user production operation optimization model with the aim of minimizing the operation cost of the self-contained power plant; solving the large-user production operation optimization model to calculate a model optimal solution; and controlling the production equipment of the self-contained power plant to work according to the optimal solution of the model. According to the method, the production operation optimization model of the large user is established, the production power demand is optimized, the power generation power of the self-contained power plant is further optimized, the economic operation of the self-contained power plant is realized, and the production energy cost of the large user is reduced.
Description
Technical Field
The application relates to the technical field of power systems and automation thereof, in particular to a method and a device for optimizing production and operation of a large user including a self-contained power plant, terminal equipment and a computer readable storage medium.
Background
In order to ensure the reliability and economy of power consumption, users with large power loads such as industrial production often build self-contained power plants according to self power consumption requirements, and generate power according to the production process of enterprises.
The automatic water flow workshop of the large user has strong control capability on the production equipment, can accurately control the start-stop time sequence of the production equipment, and optimizes the production process of products. The change of the production time sequence of the large user does not influence the total production capacity of the product in one day, so that for the large user provided with the self-contained power plant, the production power consumption requirement of the large user is optimized by optimizing the production process of the product, and the power generation and energy consumption cost of the large user can be effectively reduced by matching with the economic operation of the self-contained power plant.
At present, a method for optimizing the production process of a large user is not available, so that an optimization method needs to be provided urgently.
Content of application
In view of this, the embodiment of the present application provides a method for optimizing production and operation of a large user including a self-contained power plant, a terminal device, and a computer-readable storage medium, so as to overcome the problem that resource waste is easily caused due to the lack of a method for optimizing a production process of the large user in the prior art.
In a first aspect, an embodiment of the present application provides a method for optimizing production and operation of a large user including a self-contained power plant, where the method includes:
establishing a large-user production operation optimization model aiming at minimizing the operation cost of the self-contained power plant;
solving the large user production operation optimization model to calculate a model optimal solution;
and controlling the production equipment of the self-contained power plant to work according to the optimal solution of the model.
In a second aspect, an embodiment of the present application provides a large-user production operation optimization device including a self-contained power plant, including:
the optimization model establishing module is used for establishing a large-user production operation optimization model with the aim of minimizing the operation cost of the self-contained power plant;
the optimal solution calculation module is used for solving the large user production operation optimization model and calculating a model optimal solution;
and the control module is used for controlling the production equipment of the self-contained power plant to work according to the optimal solution of the model.
In a third aspect, an embodiment of the present application provides a terminal device, including: a memory; one or more processors coupled with the memory; one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, the one or more applications configured to perform the method for optimizing large-customer production operations including a self-contained power plant as provided by the first aspect.
In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, where a program code is stored in the computer-readable storage medium, and the program code may be invoked by a processor to execute the method for optimizing production and operation of a large user including a self-contained power plant provided in the first aspect.
According to the large-user production operation optimization method including the self-contained power plant, the terminal device and the computer readable storage medium, a large-user production operation optimization model with the aim of minimizing the operation cost of the self-contained power plant is established; solving the large-user production operation optimization model to calculate a model optimal solution; and controlling the production equipment of the self-contained power plant to work according to the optimal solution of the model. According to the method, the production operation optimization model of the large user is established, the production power demand is optimized, the power generation power of the self-contained power plant is further optimized, the economic operation of the self-contained power plant is realized, and the production energy cost of the large user is reduced.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a schematic view of an application scenario of a large-user production operation optimization method including a self-contained power plant according to an embodiment of the present application;
FIG. 2 is a schematic flow diagram of a method for optimizing production operations of a large customer including a self-contained power plant according to an embodiment of the present application;
FIG. 3 is a schematic flow diagram of a flower pollination optimization algorithm provided in one embodiment of the present application;
FIG. 4 is a schematic diagram of a large customer production operation optimization device including a self-contained power plant provided in an embodiment of the present application;
fig. 5 is a schematic structural diagram of a terminal device provided in an embodiment of the present application;
fig. 6 is a schematic structural diagram of a computer-readable storage medium provided in an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described clearly and completely below, and it should be understood that the described embodiments are only a part of the embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
For a more detailed description of the present application, a method, an apparatus, a terminal device and a computer storage medium for optimizing production operation of a large-scale customer including a self-contained power plant provided by the present application are described in detail below with reference to the accompanying drawings.
Referring to fig. 1, fig. 1 is a schematic diagram illustrating an application scenario of a large-user production operation optimization method including a self-contained power plant provided in an embodiment of the present application, where the application scenario includes a terminal device 100 provided in an embodiment of the present application, and the terminal device 100 may be various electronic devices (such as block diagrams of 102, 104, 106, and 108) having a display screen, including but not limited to a smart phone and a computer device, where the computer device may be at least one of a desktop computer, a portable computer, a laptop computer, a tablet computer, and the like. The terminal device 100 may be generally referred to as one of a plurality of terminal devices, and the present embodiment is only illustrated by the terminal device 100. Those skilled in the art will appreciate that the number of terminal devices described above may be greater or fewer. For example, the number of the terminal devices may be only a few, or the number of the terminal devices may be tens of or hundreds, or may be more, and the number and the type of the terminal devices are not limited in the embodiment of the present application. The terminal device 100 may be used to perform a method for optimizing production operations of a large customer including a self-contained power plant provided in the embodiments of the present application.
In an optional implementation manner, the application scenario may include a server in addition to the terminal device 100 provided in the embodiment of the present application, where a network is disposed between the server and the terminal device. Networks are used as the medium for providing communication links between terminal devices and servers. The network may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
It should be understood that the number of terminal devices, networks, and servers are merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation. For example, the server may be a server cluster composed of a plurality of servers. Wherein, the terminal device interacts with the server through the network to receive or send messages and the like. The server may be a server that provides various services. The server can be used for executing the large-user production operation optimization method comprising the self-contained power plant provided by the embodiment of the application.
Based on the method, the embodiment of the application provides a method for optimizing the production and operation of a large user comprising a self-contained power plant. Referring to fig. 2, fig. 2 is a schematic flow chart illustrating a method for optimizing production operation of a large-scale customer including a self-contained power plant according to an embodiment of the present application, which is described by taking the method as an example for being applied to the terminal device in fig. 1, and includes the following steps:
step S110, establishing a large-user production operation optimization model with the aim of minimizing the operation cost of the self-contained power plant;
in particular, optimization of production operations for large users including self-contained power plants is a problem that targets the minimization of the self-contained power plant operating costs. In this embodiment, a large-customer production operation optimization model is established that targets the minimum of the operating costs of the self-contained power plant. In which large-user production operation optimization is typically performed on a daily basis, so the self-contained plant operating cost may be the total cost of all periods of the day.
Step S120, solving the large user production operation optimization model, and calculating a model optimal solution;
after the large-user production operation optimization model is established, the optimization model is solved, and therefore the optimal solution of the model is obtained. The model optimal solution is the generated power of the self-contained power plant in each period. Since the self-contained power plant is used for providing electric energy for the production of large users, the optimal solution of the model can also be the electric power consumed by the production equipment of the large users in each period. The model optimal solution can reflect the production quantity of the products of the user in each period and the power consumption of the production equipment corresponding to the production quantity of the products.
And S130, controlling the production equipment of the self-contained power plant to work according to the optimal solution of the model.
Specifically, the production quantity of the products of the user in each time period and the electric power of the production equipment corresponding to the production of the quantity of products can be determined according to the optimal solution of the model, and then the working state of each production equipment is controlled according to the production quantity of the products in each time period and the electric power of the production equipment corresponding to the production of the quantity of products.
According to the method for optimizing the production and operation of the large user including the self-contained power plant, a large user production and operation optimization model with the aim of minimizing the operation cost of the self-contained power plant is established; solving the large-user production operation optimization model to calculate a model optimal solution; and controlling the production equipment of the self-contained power plant to work according to the optimal solution of the model. According to the method, the production operation optimization model of the large user is established, the production power demand is optimized, the power generation power of the self-contained power plant is further optimized, the economic operation of the self-contained power plant is realized, and the production energy cost of the large user is reduced.
In one embodiment, prior to the step of establishing a large-customer production operation optimization model that targets self-contained plant operating cost minimization, comprising: and establishing a large-user production power demand model.
In one embodiment, the large user production electricity demand model comprises a maximum production electricity power model; in the step of establishing the large user production power demand model, the method comprises the following steps: establishing a maximum production power utilization model, wherein the expression of the maximum production power utilization model is as follows:
wherein the content of the first and second substances,
maximum power for production for large users; h is the type number of workshop production equipment; n is a radical ofmMaximum product throughput in one hour for the plant; beta is aiThe number of workpieces produced by the consumption equipment i required by a production unit finished product;
minimum processing time for equipment i; pi onFor the power of the device i in the operating state, Pi offIs the power of device i in standby state.
In one embodiment, the large user production electricity demand model includes a daily total electricity usage model; in the step of establishing the large user electricity demand model, the method further comprises the following steps: establishing a daily total power consumption model according to a daily production plan of a large user, wherein the expression of the daily total power consumption model is as follows:
wherein E isplanThe total daily electricity consumption of a large user; n is a radical ofDDaily planned production capacity of finished products for a flow shop factory.
Specifically, a large-user production power demand model is constructed based on a production plan; generally, one hour is taken as a time interval, and therefore, in this embodiment, the electricity demand for large user production may be the electricity demand for large user production in one hour.
The method specifically comprises the following steps: (1) determining the maximum production power of the user, limited by the production capacity of the flow shop, wherein the power of the user has an upper limit value (namely establishing a maximum production power model):
wherein the content of the first and second substances,
maximum power for production for large users; h is the type number of workshop production equipment; n is a radical ofmMaximum product throughput in one hour for the plant; beta is aiThe number of workpieces produced by the consumption equipment i required by a production unit finished product;
minimum processing time for equipment i; pi onAnd Pi offPower of the device i in the running state and the standby state, respectively.
Maximum product throughput N of the plant in one hourmThe following can be calculated:
in this embodiment, the maximum production electricity power may be the maximum production electricity amount for one hour for the user. For example, the maximum electricity consumption in one hour is 100kWh, and the maximum electricity consumption is 100 kW. The maximum production power is determined by the production capacity of the flow shop, and the maximum production power is the same at different time intervals.
(2) Determining the total required power consumption according to the daily production plan of the large user, wherein the user establishes a daily total power consumption model for meeting the daily production plan (namely according to the daily production plan of the large user):
wherein E isplanThe power consumption corresponding to the daily production planned amount of a large user; n is a radical ofDDaily planned production capacity of finished products for a flow shop factory.
In one embodiment, the step of establishing a large-customer production operation optimization model that aims to minimize the operating cost of the self-contained power plant comprises: establishing a large-user production operation optimization model through the following formula:
minCost＝CostG+CostS
wherein minCost is produced and transported for large usersLine optimization model, CostGCost of electricity generation for self-contained power plantsSFor the start-stop cost of the self-contained power plant, T is the set of the production times of the large users, vtThe binary variable of the running state of the unit in the time period t is shown, wherein 1 is the running state, and 0 is the shutdown state; ptThe generated power of the unit is t time period; a. b and c are coefficients in a generating cost curve of the unit,
for the start-up cost of the unit during the period t,
the shutdown cost of the unit in the time period t is calculated; fsuCost for unit start-up once, FsdWhich is the cost of shutting down a unit once.
Specifically, a large-user production operation optimization model with the aim of minimizing the operation cost of the self-contained power plant is established, and the optimal solution of the model is the optimal production plan of the user, specifically: the optimization of the production operation of the large user comprising the self-contained power plant is a nonlinear programming problem which aims at minimizing the operation cost of the self-contained power plant, and an objective function (namely an expression of a production operation optimization model of the large user) is as follows:
minCost＝CostG+CostS
wherein, the running Cost of the self-contained power plant comprises the Cost of electricity generation CostGAnd start-stop CostS。
The coal consumption characteristic of the generator set is described by a quadratic function, and the power generation cost can be expressed as:
wherein T is a set formed by the production time of a large user; v. oftThe binary variable of the running state of the unit in the time period t is shown, wherein 1 is the running state, and 0 is the shutdown state; ptThe generated power of the unit is t time period; a. and b and c are coefficients in the generating cost curve of the unit.
The start-stop cost of a unit consists of the start-up cost and the shut-down cost, and can be expressed as:
wherein the content of the first and second substances,
and
the starting cost and the shutdown cost of the unit in the time period t are respectively met:
wherein, FsuAnd FsdThe cost of starting and shutting down the unit once respectively.
After the large-user production operation optimization model is established, the constraint conditions of the model need to be determined. In this embodiment, the model constraint conditions include a unit power generation capacity constraint, a unit climbing constraint, a unit minimum on-off time constraint, a large user power consumption constraint and a large user production plan constraint. The method specifically comprises the following steps: A. and (3) constraint of generating capacity of the unit:
vtPmin≤Pt≤vtPmax
wherein, PminAnd PmaxThe minimum and maximum generating power of the unit in the running state are respectively.
B. Unit climbing restraint:
-ΔP≤Pt-Pt-1≤ΔP
wherein, the delta P is the maximum climbing rate of the unit.
C. And (3) constraint of minimum startup and shutdown time of the unit:
wherein, UTimeThe minimum startup running time of the unit; dTimeIs the minimum number of down time operating hours of the unit.
D. And (3) power utilization constraint of large users:
the method is limited by the production capacity of a flow shop, the power consumption of a large user has an upper limit value, and if the power generation of a self-contained power plant is completely supplied to the production needs of the large user, the method comprises the following steps:
wherein the content of the first and second substances,
the maximum power for production of large users.
E. Large user production plan constraints:
the power supply of the self-contained power plant needs to enable a large user to meet the daily production plan, and the following steps are provided:
wherein E isplanThe power consumption corresponding to the production planning quantity of the large user on the day.
In one embodiment, the step of solving the large-user production operation optimization model and calculating the optimal solution of the model includes: and selecting a penalty function to convert the large-user production operation optimization model into an unconstrained mixed integer nonlinear programming formula, and solving by adopting an improved flower pollination optimization algorithm to obtain an optimal solution of the model.
In one embodiment, the step of solving by using the improved flower pollination optimization algorithm to obtain the optimal solution of the model comprises: and introducing a Sigmoid function into a flower pollination optimization algorithm to solve an unconstrained mixed integer nonlinear programming formula.
Specifically, a penalty function is selected to convert a large-user production operation optimization model containing a self-contained power plant into an unconstrained mixed integer nonlinear programming, and an improved flower pollination algorithm is applied to solve the problem, specifically: 1) selecting a penalty function to convert the optimization model into an unconstrained mixed integer nonlinear programming:
firstly, obtaining decision variables of an optimization model:
wherein X is a vector consisting of decision variables.
Secondly, converting the constraint conditions of the optimization model into a standard form:
gi(X)≤0 i＝1,2,...,9
wherein, giAnd (X) is an expression obtained after the constraint condition is shifted.
Finally, a penalty function is constructed to transform the model into an unconstrained optimization problem:
where σ > 0 is a defined parameter.
2) Solving an unconstrained programming problem using an improved flower pollination algorithm
The flower pollination algorithm simulates the pollination phenomenon of a flowering plant in nature, and carries out optimized local search and global search respectively through self-pollination and cross-pollination, and has the characteristics of easiness in operation, strong stability, high efficiency, suitability for parallel operation and the like.
Firstly, setting parameters such as population quantity M and switching probability p, randomly generating initial population, and searching initial speciesOptimal pollen individuals of the population
And secondly, performing self-pollination or cross-pollination in a loop iteration mode until an iteration termination condition is met. When each pollen is optimized in the iteration process, random numbers r uniformly distributed between [0,1] are generated: if r is less than p, performing self-pollination according to a self-pollination formula; otherwise, cross pollination is carried out according to a cross pollination formula.
Self-pollination formula:
wherein the content of the first and second substances,
individuals of ith pollen in the nth generation in the population;
and
is different from the population
Two random individuals of (a); e is in [0,1]Uniformly distributed random numbers.
Cross pollination formula:
wherein the content of the first and second substances,
the optimal pollen individual in the population; l is a random number that follows a Levy distribution.
Since the flower pollination algorithm can only solve the optimization problem for continuous variables, in this exampleThe Sigmoid function is introduced to process mixed integer programming, and for pollen individuals with finished pollination, if the pollen individuals are subjected to pollination
Should be an integer variable, then further operations are required:
finally, outputting the optimal pollen individual X after the iteration is finished*Please refer to fig. 3 for a detailed flow.
It should be understood that although the various steps in the flowcharts of fig. 2-3 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-3 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performing the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.
The embodiment disclosed in the application describes a method for optimizing the production and operation of a large user including a self-contained power plant in detail, and the method disclosed in the application can be realized by adopting various forms of equipment, so that the application also discloses a device for optimizing the production and operation of the large user including the self-contained power plant corresponding to the method, and specific embodiments are given below for detailed description.
Referring to fig. 4, a large-scale customer production operation optimization device including a self-contained power plant disclosed in an embodiment of the present application mainly includes:
an optimization model building module 402, configured to build a large-user production operation optimization model aiming at minimizing the operation cost of the self-contained power plant;
an optimal solution calculation module 404, configured to solve the large user production operation optimization model, and calculate a model optimal solution;
and the control module 406 is used for controlling each production device of the self-contained power plant to work according to the optimal solution of the model.
In one embodiment, the method comprises the following steps: and the demand model establishing module is used for establishing a large-user production power demand model.
In one embodiment, the large user production electricity demand model comprises a maximum production electricity power model; the demand model building module comprises:
the power utilization model establishing module is used for establishing a maximum production power utilization model, wherein the expression of the maximum production power utilization model is as follows:
wherein the content of the first and second substances,
maximum power for production for large users; h is the type number of workshop production equipment; n is a radical ofmMaximum product throughput in one hour for the plant; beta is aiThe number of workpieces produced by the consumption equipment i required by a production unit finished product;
minimum processing time for equipment i; pi onFor the power of the device i in the operating state, Pi offIs the power of device i in standby state.
In one embodiment, the large user production electricity demand model includes a daily total electricity usage model; the demand model building module further comprises:
the system comprises a total power consumption model establishing module, a total power consumption model establishing module and a power consumption model establishing module, wherein the total power consumption model establishing module is used for establishing a daily total power consumption model according to a daily production plan of a large user, and the expression of the daily total power consumption model is as follows:
wherein E isplanThe total daily electricity consumption of a large user; n is a radical ofDDaily planned production capacity of finished products for a flow shop factory.
In one embodiment, the optimization model building module is further configured to build a large-user production operation optimization model by the following formula:
minCost＝CostG+CostS
wherein minCost is a large-user production operation optimization model, and the CostGCost of electricity generation for self-contained power plantsSFor the start-stop cost of the self-contained power plant, T is the set of the production times of the large users, vtThe binary variable of the running state of the unit in the time period t is shown, wherein 1 is the running state, and 0 is the shutdown state; ptThe generated power of the unit is t time period; a. b and c are coefficients in a generating cost curve of the unit,
for units during time tThe cost of the start-up is,
the shutdown cost of the unit in the time period t is calculated; fsuCost for unit start-up once, FsdWhich is the cost of shutting down a unit once.
In one embodiment, the optimal solution calculation module is further configured to select a penalty function to convert the large-user production operation optimization model into an unconstrained mixed integer nonlinear programming formula, and solve the unconstrained mixed integer nonlinear programming formula by using an improved flower pollination optimization algorithm to obtain the optimal solution of the model.
In one embodiment, the optimal solution calculation module is further configured to introduce a Sigmoid function into the flower pollination optimization algorithm to solve the unconstrained mixed integer nonlinear programming formula.
For specific limitations of the production operation optimization device for a large user including a self-contained power plant, see the above limitations for the method, which are not described herein again. The various modules in the above-described apparatus may be implemented in whole or in part by software, hardware, and combinations thereof. The modules can be embedded in a hardware form or independent of a processor in the terminal device, and can also be stored in a memory in the terminal device in a software form, so that the processor can call and execute operations corresponding to the modules.
Referring to fig. 5, fig. 5 is a block diagram illustrating a structure of a terminal device according to an embodiment of the present application. The terminal device 50 may be a computer device. The terminal device 50 in the present application may include one or more of the following components: a processor 52, a memory 54, and one or more applications, wherein the one or more applications may be stored in the memory 54 and configured to be executed by the one or more processors 52, the one or more applications configured to perform the methods described in the above method embodiments applied to a terminal device, and also configured to perform the methods described in the above method embodiments applied to data aggregation.
The Memory 54 may include a Random Access Memory (RAM) or a Read-Only Memory (Read-Only Memory). The memory 54 may be used to store instructions, programs, code sets, or instruction sets. The memory 54 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing various method embodiments described below, and the like. The storage data area may also store data created by the terminal device 50 in use, and the like.
Those skilled in the art will appreciate that the structure shown in fig. 5 is a block diagram of only a portion of the structure relevant to the present application, and does not constitute a limitation on the terminal device to which the present application is applied, and a particular terminal device may include more or less components than those shown in the drawings, or combine certain components, or have a different arrangement of components.
In summary, the terminal device provided in the embodiment of the present application is used to implement the corresponding method for optimizing production and operation of a large user including a self-contained power plant in the foregoing method embodiment, and has the beneficial effects of the corresponding method embodiment, which are not described herein again.
Referring to fig. 6, a block diagram of a computer-readable storage medium according to an embodiment of the present disclosure is shown. The computer readable storage medium 60 stores program code that can be invoked by a processor to perform the method described in the above embodiment of the method for optimizing production and operation of a large user including an autonomous power plant, and can also be invoked by a processor to perform the method described in the above embodiment of the method for optimizing production and operation of a large user including an autonomous power plant.
The computer-readable storage medium 60 may be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read only memory), an EPROM, a hard disk, or a ROM. Alternatively, the computer-readable storage medium 60 includes a non-transitory computer-readable storage medium. The computer readable storage medium 60 has storage space for program code 62 for performing any of the method steps of the method described above. The program code can be read from or written to one or more computer program products. The program code 62 may be compressed, for example, in a suitable form.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method for optimizing production operation of a large customer comprising a self-contained power plant, the method comprising:
establishing a large-user production operation optimization model aiming at minimizing the operation cost of the self-contained power plant;
solving the large user production operation optimization model to calculate a model optimal solution;
and controlling the production equipment of the self-contained power plant to work according to the optimal solution of the model.
2. The method of claim 1, prior to the step of establishing a large-customer production operation optimization model that targets self-contained plant operating cost minimization, comprising:
and establishing a large-user production power demand model.
3. The method of claim 2, wherein the large user production power demand model comprises a maximum production power model; in the step of establishing the large user production power demand model, the method comprises the following steps:
establishing a maximum production power consumption model, wherein the expression of the maximum production power consumption model is as follows:
wherein the content of the first and second substances,
maximum power for production for large users; h is the type number of workshop production equipment; n is a radical ofmMaximum product throughput in one hour for the plant; beta is aiThe number of workpieces produced by the consumption equipment i required by a production unit finished product;
minimum processing time for equipment i; pi onFor the power of the device i in the operating state, Pi offIs the power of device i in standby state.
4. The method of claim 3, wherein the large consumer production electricity demand model comprises a total daily electricity usage model; in the step of establishing the large user electricity demand model, the method further comprises the following steps:
establishing the daily total power consumption model according to a daily production plan of a large user, wherein the expression of the daily total power consumption model is as follows:
wherein E isplanThe total daily electricity consumption of a large user; n is a radical ofDDaily planned production capacity of finished products for a flow shop factory.
5. The method of claim 4, wherein the step of establishing a large-customer production operation optimization model that targets self-contained plant operating cost minimization comprises:
establishing the large user production operation optimization model through the following formula:
minCost＝CostG+CostS
wherein minCost is the production operation optimization model of the large user, and the CostGCost of electricity generation for self-contained power plantsSFor the start-stop cost of the self-contained power plant, T is the set of the production times of the large users, vtThe binary variable of the running state of the unit in the time period t is shown, wherein 1 is the running state, and 0 is the shutdown state; ptThe generated power of the unit is t time period; a. b and c are coefficients in a generating cost curve of the unit,
for the start-up cost of the unit during the period t,
the shutdown cost of the unit in the time period t is calculated; fsuCost for unit start-up once, FsdWhich is the cost of shutting down a unit once.
6. The method according to any one of claims 1 to 5, wherein the step of solving the optimization model of the large-scale user production operation and calculating the optimal solution of the model comprises:
and selecting a penalty function to convert the large-user production operation optimization model into an unconstrained mixed integer nonlinear programming formula, and solving by adopting an improved flower pollination optimization algorithm to obtain the optimal solution of the model.
7. The method of claim 6, wherein the step of solving using the improved flower pollination optimization algorithm to obtain the optimal solution of the model comprises:
and introducing a Sigmoid function into a flower pollination optimization algorithm to solve an unconstrained mixed integer nonlinear programming formula.
8. A large-user production operation optimization device including a self-contained power plant, the device comprising:
the optimization model establishing module is used for establishing a large-user production operation optimization model with the aim of minimizing the operation cost of the self-contained power plant;
the optimal solution calculation module is used for solving the large user production operation optimization model and calculating a model optimal solution;
and the control module is used for controlling the production equipment of the self-contained power plant to work according to the optimal solution of the model.
9. A terminal device, comprising:
a memory; one or more processors coupled with the memory; one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, the one or more applications configured to perform the method of any of claims 1-7.
10. A computer-readable storage medium, having stored thereon program code that can be invoked by a processor to perform the method according to any one of claims 1 to 7.
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