CN113313281B - Thermal power enterprise multi-coal cost optimization method and system based on electric power market - Google Patents
Thermal power enterprise multi-coal cost optimization method and system based on electric power market Download PDFInfo
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Abstract
The invention discloses a thermal power enterprise multi-coal cost optimization method and system based on an electric power market. The thermal power enterprise multi-coal cost optimization method based on the electric power market comprises the following steps: acquiring a basic data sample from a historical operation database of a thermal power enterprise; calculating to obtain a unit operation coal consumption data sample; establishing a coal cost matrix by combining the load and the coal purchase price; under the constraint of power generation load and the constraint of coal inventory; and solving the coal type selection matrix by adopting an optimization method. Many coal types of cost optimization system of thermal power enterprise based on electric power market includes: the system comprises a data acquisition unit, a corresponding relation acquisition unit, a cost matrix construction unit, a constraint condition acquisition unit and a coal type selection processing unit.
Description
Technical Field
The invention relates to a thermal power enterprise multi-coal cost optimization method and system based on an electric power market.
Background
In the face of the new trend of power system innovation and complex and changeable energy industry, power generation enterprises can cultivate and enhance market competitiveness, grasp market opportunities, meet challenges, further improve the competitiveness of the power generation industry and become a common subject for the development of the power enterprises.
In the electric power market, the main cost of a power generation enterprise is the cost of power generation coal, and the power generation cost of a thermal power enterprise is usually converted into the standard coal unit price at present, but because the coal type and load have great influence on the coal consumption, the coal type and load are not considered in the coal cost calculation, so that the coal cost calculation of the thermal power enterprise is rough, the actual power generation cost cannot be reflected, the optimal coal type cannot be selected under the condition of multiple coal types, and unnecessary waste is caused. In the power market environment, thermal power enterprises need to establish a plurality of coal cost optimization methods to enhance market competitiveness.
The invention provides a multi-coal cost model of a power generation enterprise and a cost optimization method and system based on cost composition of the power generation enterprise in a power market and by combining a typical settlement method of the power market.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provide a thermal power enterprise multi-coal cost optimization method and system based on an electric power market.
The technical scheme adopted by the invention for solving the problems is as follows: a thermal power enterprise multi-coal cost optimization method based on an electric power market is characterized by comprising the following steps:
acquiring a basic data sample from a historical operation database of a thermal power enterprise; calculating to obtain a unit coal consumption data sample according to a preset clustering algorithm and the basic value data sample; wherein the unit coal consumption data sample comprises: indexes of coal quality, load and coal consumption;
respectively acquiring corresponding relations among the coal quality, the load and the coal consumption and a coal consumption curve according to the unit coal consumption data sample; meanwhile, correcting standard environmental conditions according to an environmental correction curve obtained by a unit design manufacturer or a performance test;
according to the actual coal quality, load and coal consumption and the corresponding coal type coal price of actual purchase, the coal cost of power generation of the thermal power enterprise is calculated, and the calculation formula is as follows: the coal cost of power generation of thermal power enterprises is equal to coal price multiplied by load multiplied by coal consumption.
Further, a multi-coal-type coal cost matrix is established according to the coal types, coal prices and load curves which can be purchased by thermal power enterprises.
Further, according to the established multi-coal-type coal cost matrix, a cost optimal function is set, and constraint conditions of thermal power enterprises are combined: power generation load constraints and coal inventory constraints; and performing cost optimal solution, selecting the coal type of each load section to obtain a coal type selection matrix, wherein the coal type selection matrix meets the requirements of each coal type inventory in the calculation time period to meet all the calculation time period requirements, and the coal type supply of each load section meets the power generation load requirements.
The invention also provides a thermal power enterprise multi-coal cost optimization system based on the electric power market, which is characterized by comprising the following steps: the system comprises a data acquisition unit, a corresponding relation acquisition unit, a cost matrix construction unit, a constraint condition acquisition unit and a coal type selection processing unit; wherein:
the data acquisition unit receives and stores real-time production data and relational data uploaded by thermal power enterprises from a historical operation database of the thermal power enterprises to acquire basic data samples; integrating and analyzing data information, integrating and analyzing production operation data acquired on site, eliminating gross errors and random errors in original data, completing incomplete data, performing data correction to finally form a basic data sample, and calculating to obtain a unit coal consumption data sample according to a preset clustering algorithm and the basic data sample; wherein, the unit coal consumption data sample emphasis includes: indexes of coal quality, load and coal consumption;
the corresponding relation obtaining unit is used for carrying out online calculation on the equipment performance index of the generator set according to the coal consumption data sample of the generator set, and obtaining the corresponding relation of the specific coal quality, load and coal consumption of the running performance of the generator set based on the real-time calculated value of the equipment performance index of the generator set by adopting a data mining analysis method; meanwhile, standard environmental condition correction is carried out according to an environmental correction curve obtained by a unit design manufacturer or a performance test;
the cost matrix construction unit calculates the power generation coal cost of the thermal power enterprise according to the actual coal quality, load and coal consumption and the corresponding coal type and coal price purchased actually, and the calculation formula is as follows: the cost of the power generation coal of the thermal power enterprise is equal to the coal price multiplied by the load multiplied by the coal consumption; meanwhile, a multi-coal-type coal cost matrix is established according to the coal types, coal prices and load curves which can be purchased by thermal power enterprises;
the constraint condition acquisition unit acquires corresponding power generation load curve constraint conditions according to the power grid dispatching curve plan; acquiring a coal inventory constraint condition according to the coal inventory of the thermal power enterprise production management system;
the coal type selection processing unit sets a cost optimal function according to the established coal cost matrix of the multiple coal types, and combines constraint conditions of thermal power enterprises: power generation load constraints and coal inventory constraints; carrying out cost optimal solution, selecting the coal type of each load section, and simultaneously meeting the constraint conditions: the inventory of each coal type in the calculation time period meets the total coal quantity requirement of all the calculation time periods, and the coal supply of each load period meets the power generation load requirement.
The present invention also provides a computer terminal device, comprising:
one or more processors;
a memory coupled to the processor for storing one or more programs;
when executed by the one or more processors, the one or more programs cause the one or more processors to implement the method for optimizing the cost of multiple coals for a thermal power plant based on an electric power market as described above.
The invention also provides a computer readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method and the system for optimizing the multiple coal costs of the thermal power enterprise based on the electric power market are implemented.
Compared with the prior art, the invention has the following advantages and effects:
according to the method, the coal type optimization of each load section can be established by combining the coal inventory and the power generation load constraint through the corresponding relation among the coal types, the loads and the coal consumption, so that the aim of optimizing the cost of multiple coal types is fulfilled, and workers are prompted to select and optimize the coal types under the conditions of different loads and coal prices, so that the aims of reducing the power generation cost of thermal power enterprises and improving the competitiveness of the thermal power enterprises are fulfilled.
Drawings
FIG. 1 is a flow chart of a multi-coal cost optimization method of the present invention.
FIG. 2 is a schematic diagram of a multi-coal cost optimization system according to the present invention.
Fig. 3 is a diagram of a calculation process in an embodiment of the invention.
FIG. 4 is a graph of coal consumption rate in an embodiment of the present invention.
Fig. 5 is a load graph in an embodiment of the invention.
FIG. 6 is a graph of coal consumption in an example of the present invention.
Detailed Description
The present invention will be described in further detail below by way of examples with reference to the accompanying drawings, which are illustrative of the present invention and are not to be construed as limiting the present invention.
Examples are given.
In this embodiment, a cycle of 7 days is assumed; the coal is burnt for the last time within 8 hours, and the same coal type is burnt within 8 hours; a load point of the electric power market within 15 minutes is combined with coal price to establish a multi-coal-type cost optimization method, a coal-type selection matrix is completed, and the overall steps are shown in figure 3.
Adopting power plant test data to integrate and analyze data information and establish coal type b i Load p el Coal consumption f i (b i ,p el ) Fitting a relation curve by using the load rate as an independent variable and the coal consumption rate as a dependent variable, wherein the relation curve is shown in figure 4;
simulating a power grid dispatching curve, as shown in figure 5;
the simulated coal purchase price is assumed to have 3 suppliers and slightly different prices, and is shown in a table 2;
the simulated production management system coal inventory, again assuming 3 suppliers, is shown in table 3;
according to the medium-long term contract and the electric power spot market load curve P EL Establishing a power generation coal consumption model:
wherein T is cost The calculation results are shown in FIG. 6 for coal consumption.
And calculating the power generation coal cost of the thermal power enterprise according to the corresponding coal price of the coal, wherein the calculation formula is that the power generation coal cost of the thermal power enterprise is equal to the coal price multiplied by the load multiplied by the coal consumption.
On the premise of constraining the coal inventory table 3, a cost optimal model is established, namely all coals in a 7-day period are the lowest in cost, and the constraint conditions are as follows: power generation load constraints, and coal inventory constraints. And obtaining the optimal cost according to assumed conditions by adopting an optimal solution method, and simultaneously obtaining a coal type selection matrix table 5 and a coal type demand matrix table 6 in a calculation time period.
TABLE 1 design parameters
TABLE 2 coal Integrated costs
Yuan/ton
TABLE 3 coal inventory
Ton of
TABLE 4 coal selection matrix
TABLE 5 coal requirement matrix
Ton of
TABLE 6 coal demand matrix
Ton of
Specifically, the calculation period can be further prolonged or shortened according to the requirements of the thermal power enterprise.
Specifically, if the coal charging time is shorter each time or there are multiple coal types, the calculation period may be further subdivided by time period.
Those not described in detail in this specification are well within the skill of the art.
Although the present invention has been described with reference to the above embodiments, it should be understood that the scope of the present invention is not limited thereto, and that various changes and modifications can be made by those skilled in the art without departing from the spirit and scope of the present invention.
Claims (2)
1. A thermal power enterprise multi-coal cost optimization method based on an electric power market is characterized by comprising the following steps:
acquiring a basic data sample from a historical operation database of a thermal power enterprise; calculating to obtain a unit coal consumption data sample according to a preset clustering algorithm and the basic value data sample; wherein the unit coal consumption data sample comprises: indexes of coal quality, load and coal consumption;
respectively acquiring corresponding relations among the coal quality, the load and the coal consumption and a coal consumption curve according to the unit coal consumption data sample; meanwhile, standard environmental condition correction is carried out according to an environmental correction curve obtained by a unit design manufacturer or a performance test;
according to the actual coal quality, load and coal consumption and the corresponding coal type coal price of actual purchase, the coal cost of power generation of the thermal power enterprise is calculated, and the calculation formula is as follows: the power generation coal cost of a thermal power enterprise = coal price x load x coal consumption;
establishing a multi-coal-type coal cost matrix according to the coal types, coal prices and load curves which can be purchased by thermal power enterprises;
setting a cost optimal function according to the established multi-coal-type coal cost matrix, and combining constraint conditions of thermal power enterprises: power generation load constraints and coal inventory constraints; and performing cost optimal solution, selecting the coal type of each load section to obtain a coal type selection matrix, wherein the coal type selection matrix meets the requirements of each coal type inventory in the calculation time period to meet all the calculation time period requirements, and the coal type supply of each load section meets the power generation load requirements.
2. A system for operating the thermal power enterprise multi-coal cost optimization method based on the electric power market as claimed in claim 1, characterized by comprising: the system comprises a data acquisition unit, a corresponding relation acquisition unit, a cost matrix construction unit, a constraint condition acquisition unit and a coal type selection processing unit; wherein:
the data acquisition unit receives and stores real-time production data and relational data uploaded by thermal power enterprises from a historical operation database of the thermal power enterprises to acquire basic data samples; integrating and analyzing data information, integrating and analyzing production operation data acquired on site, eliminating gross errors and random errors in original data, completing incomplete data, performing data correction to finally form a basic data sample, and calculating to obtain a unit coal consumption data sample according to a preset clustering algorithm and the basic data sample; wherein the unit coal consumption data sample comprises: indexes of coal quality, load and coal consumption;
the corresponding relation obtaining unit is used for carrying out online calculation on the equipment performance index of the generator set according to the coal consumption data sample of the generator set, and obtaining the corresponding relation of the specific coal quality, load and coal consumption of the running performance of the generator set based on the real-time calculated value of the equipment performance index of the generator set by adopting a data mining analysis method; meanwhile, standard environmental condition correction is carried out according to an environmental correction curve obtained by a unit design manufacturer or a performance test;
the cost matrix construction unit calculates the power generation coal cost of the thermal power enterprise according to the actual coal quality, load and coal consumption and the corresponding coal type and coal price purchased actually, and the calculation formula is as follows: the coal cost = coal price x load x coal consumption; meanwhile, a multi-coal-type coal cost matrix is established according to the coal types, coal prices and load curves which can be purchased by thermal power enterprises;
the constraint condition obtaining unit is used for obtaining corresponding power generation load curve constraint conditions according to the power grid dispatching curve plan; acquiring a coal inventory constraint condition according to the coal inventory of the thermal power enterprise production management system;
the coal type selection processing unit sets a cost optimal function according to the established coal cost matrix of the multiple coal types, and combines constraint conditions of thermal power enterprises: power generation load constraints and coal inventory constraints; carrying out cost optimal solution, selecting the coal type of each load section, and simultaneously meeting the constraint conditions: and each coal type inventory in the calculation time period meets the total coal amount requirement of all the calculation time periods, and the coal type supply of each load period meets the power generation load requirement.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5033004A (en) * | 1988-12-23 | 1991-07-16 | Vandivier Iii John C | Method and system for blending coal and other natural resources |
| CN104915746A (en) * | 2014-10-21 | 2015-09-16 | 安波 | Purchase before ironmaking and molten iron cost integration management system |
| CN105320116A (en) * | 2015-11-19 | 2016-02-10 | 华润电力登封有限公司 | A thermal power plant fuel total value optimizing method and system |
| CN109034445A (en) * | 2018-06-08 | 2018-12-18 | 广东红海湾发电有限公司 | A kind of market-oriented electric power management system and method |
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- 2021-04-06 CN CN202110369468.8A patent/CN113313281B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5033004A (en) * | 1988-12-23 | 1991-07-16 | Vandivier Iii John C | Method and system for blending coal and other natural resources |
| CN104915746A (en) * | 2014-10-21 | 2015-09-16 | 安波 | Purchase before ironmaking and molten iron cost integration management system |
| CN105320116A (en) * | 2015-11-19 | 2016-02-10 | 华润电力登封有限公司 | A thermal power plant fuel total value optimizing method and system |
| CN109034445A (en) * | 2018-06-08 | 2018-12-18 | 广东红海湾发电有限公司 | A kind of market-oriented electric power management system and method |
Non-Patent Citations (1)
| Title |
|---|
| 精益化调试在火电基建项目中的理论探索与工程实践;李国敏等;《节能与环保》;20201231(第010期);全文 * |
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