Method and system for calculating optimal production strategy of combined cycle steam extraction heat supply power plant
By combining data mining and performance modeling, the accuracy and applicability of the optimal production strategy in combined cycle extraction steam heating power plants were solved, achieving a plant-wide optimized production strategy with the lowest fuel consumption and satisfying multiple constraints.
Patent Information
- Application Number
- CN202511335399.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-17
- Publication Date
- 2026-01-13
AI Technical Summary
Existing technologies are insufficient to accurately determine the optimal production strategy in combined cycle extraction heating and heating power plants. They fail to effectively consider constraints such as total heat and electricity load balance, maximum heat supply, maximum power generation, and NOx emissions, resulting in insufficient applicability and accuracy of the optimization results.
Predictive equations are established using data mining methods. Combined with performance models and historical operating data, the solution algorithm is optimized through multiple linear fitting and neural network algorithms to determine the optimal production strategy for the entire plant, including the objective function and constraints, to ensure that fuel consumption is minimized and all constraints are met.
This improves the applicability and accuracy of the optimization results, meets the prediction requirements of unit energy consumption characteristics under actual production conditions, and achieves the optimal production strategy for the entire plant with the lowest fuel consumption.
Smart Images
Figure CN121329720A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The application belongs to the field of thermal power engineering, and particularly relates to a calculation method and system for optimal production strategy of a combined cycle steam extraction heat supply power plant. BACKGROUND
[0002] The application belongs to the field of thermal power engineering, and particularly relates to a calculation method and system for optimal production strategy of a combined cycle steam extraction heat supply power plant. SUMMARY
[0003] The application aims to provide a calculation method and system for optimal production strategy of a combined cycle steam extraction heat supply power plant, which can accurately determine the optimal production strategy of the whole plant.
[0004] In order to achieve the above-mentioned purpose, the application adopts the following technical scheme: A calculation method for optimal production strategy of a combined cycle steam extraction heat supply power plant comprises the following steps: S1: retrieve historical operation data of each unit in the whole plant, and after preprocessing, obtain a prediction equation of the relationship between the heat supply of each unit and the heat supply valve opening degree and unit load of each unit by using a data mining method; S2: calculate and determine the maximum heat supply of each unit when the heat supply valve opening degree is 100% at different loads by using the prediction equation; S3: retrieve historical operation data of each combined cycle unit when the gas turbine runs at full load, and after preprocessing, obtain an equation of the maximum power generation of each unit and the atmospheric temperature and heat supply by using a data mining method, and calculate the maximum power generation of each unit at different atmospheric temperatures and heat supplies; S4: retrieve historical operation data of each unit, and analyze to obtain the minimum power generation load of each unit that meets the NOx emission standard; S5: establish a performance model of each combined cycle unit, obtain an energy consumption prediction equation of each unit at a wide load condition by using a theoretical calculation method, and correct the energy consumption prediction equation by using historical operation data or test data; S6: determine a target function of the optimal production strategy of the whole plant, and the target function is the minimum total fuel consumption of the whole plant, and comprises the energy consumption prediction equation of each unit at a wide load condition; S7: determine a constraint condition corresponding to the target function, including a total heat and power load balance constraint of the whole plant, a maximum heat supply constraint of each unit, a maximum power generation constraint of each unit, and a minimum power generation load constraint of each unit that meets the NOx emission standard; S8: solve the target function with the constraint condition by using a solving algorithm, and obtain the optimal power load and heat supply load of each unit of the whole plant.
[0005] The further improvement of the present application is that in the step S1, the historical operation data of each unit in the multiple units of the whole plant are called, and after pre-processing, the prediction equation of the relationship between the heat supply of each unit and the opening of the unit heat supply valve and the unit load is obtained by using the data mining method, wherein the pre-processing adopts the working condition stability judgment and the significant error data elimination.
[0006] The further improvement of the present application is that in the steps S1 and S3, the data mining method used includes a multiple linear fitting algorithm and a neural network algorithm.
[0007] The further improvement of the present application is that in the step S5, the wide load working condition is a wide range change of the multi-dimensional operation boundary condition of power, heat supply and atmospheric parameters.
[0008] The further improvement of the present application is that in the step S6, the objective function of the optimal production strategy of the whole plant should be formulated according to the actual situation, and the objective function is as follows:
[0009] In the formula: The total fuel consumption of the whole plant at time t; The fuel consumption of the i-th unit at time t; N The total number of units of the whole plant; The value of the external factor affecting the consumption of the i-th unit at time t; The power generation of the i-th unit at time t; The heat / cold load of the i-th unit of the whole plant at time t; The running state of the i-th unit of the whole plant at time t, 0 represents shutdown and 1 represents running; The energy consumption prediction equation of the i-th unit under the wide load working condition.
[0010] The further improvement of the present application is that in the step S8, the solving algorithm includes a priority order method, a local optimization method, an exhaustive method, a dynamic programming method and a numerical solution method of Lagrange relaxation.
[0011] A calculation system of an optimal production strategy of a combined cycle steam extraction heat supply power plant, comprising: A prediction equation acquisition module, which calls the historical operation data of each unit in the multiple units of the whole plant, and after pre-processing, obtains the prediction equation of the relationship between the heat supply of each unit and the opening of the unit heat supply valve and the unit load by using the data mining method. The first calculation module calculates the maximum heat supply of each unit corresponding to the heat supply valve opening degree of 100% at different loads by using a prediction equation; The second calculation module retrieves historical operation data of each combined cycle unit when the gas turbine of the unit is operated at full load, and obtains an equation of the maximum power generation of each unit and the atmospheric temperature and heat supply by using a data mining method after preprocessing, so as to calculate the maximum power generation of each unit at different atmospheric temperatures and heat supplies; The minimum power generation load taking module retrieves historical operation data of each unit, and analyzes to obtain the minimum power generation load of each unit meeting the NOx emission standard; The energy consumption prediction equation taking module establishes a performance model of each combined cycle unit, obtains an energy consumption prediction equation of each unit at a wide load condition by using a theoretical calculation method, and corrects the energy consumption prediction equation by using historical operation data or test data; The target function determining module determines a target function of the optimal production strategy of the whole plant, and the target function is the minimum total fuel consumption of the whole plant, and the target function includes the energy consumption prediction equation of each unit at a wide load condition; The constraint condition determining module determines a constraint condition corresponding to the target function, including a total heat and power load balance constraint, a maximum heat supply constraint of each unit, a maximum power generation constraint of each unit, and a minimum power generation load constraint of each unit meeting the NOx emission standard; The third calculation module uses a solving algorithm to solve the target function with the constraint condition, and obtains the optimal power load and heat supply load of each unit of the whole plant.
[0012] Further improvement of the application is that in the prediction equation obtaining module, historical operation data of each unit of multiple units of the whole plant are retrieved, a prediction equation of the relationship among the heat supply of each unit, the unit heat supply valve opening degree and the unit load is obtained by using a data mining method after preprocessing, and the preprocessing adopts condition stability judgment and significant error data elimination.
[0013] An electronic device comprises a processor and a memory coupled to the processor, the memory storing a computer program, and the computer program is executed by the processor to implement the steps of the optimal production strategy calculation method of the combined cycle extraction heat supply power plant.
[0014] A computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the optimal production strategy calculation method of the combined cycle extraction heat supply power plant.
[0015] Compared with the prior art, the application has at least the following beneficial technical effects: The application provides a calculation method and system for optimal production strategy of a combined cycle steam extraction heat supply power plant, which comprehensively considers constraint conditions of total heat and power load balance of the whole plant, maximum heat supply of each unit, maximum power generation of each unit, minimum power generation load of each unit meeting NOx emission standard and the like, so that the constraint conditions are in line with actual production conditions and applicability of the optimization result is improved; in addition, an accurate unit energy consumption characteristic prediction equation is obtained by combining performance model theory calculation and historical operation data and test data correction, so that the accuracy of the optimization result is improved. BRIEF DESCRIPTION OF DRAWINGS
[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative effort on the basis of these drawings.
[0017] Figure 1 The figure is a heat supply characteristic curve of a single unit (taking unit #1 and steam supply main pipe pressure of 0.7 MPa.g as an example); Figure 2 The figure is a schematic diagram of maximum heat supply capacity of a single unit; Figure 3 The figure is a schematic diagram of verification result of a test set (taking unit #1 as an example); Figure 4 The figure is a NOx emission characteristic curve in summer; X Figure 5 The figure is a NOx emission characteristic curve in winter; X Figure 6 The figure is a schematic diagram of relative error between theoretical energy consumption characteristic and operation data; Figure 7 The figure is a schematic diagram of relative error between energy consumption characteristic after self-adaptive correction and operation data; Figure 8 The figure is a main solving flowchart of the present application; Figure 9 The figure is a schematic diagram of fuel gas consumption before and after optimization of an optimal distribution scheme Figure 10 The figure is a structural block diagram of a calculation system for optimal production strategy of a combined cycle steam extraction heat supply power plant according to the present application. DETAILED DESCRIPTION
[0018] In the following, certain exemplary embodiments are simply described. As those skilled in the art can recognize, the described embodiments can be modified in various different ways without departing from the spirit or scope of the present application. Therefore, the drawings and description are to be regarded as illustrative in nature rather than restrictive.
[0019] In the description of the present application, it is to be understood that the terms "including", "comprising", "having" and "with" when used in this specification and in the following claims indicate the presence of the stated features, integers, steps, operations, elements, and / or components but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.
[0020] It should also be understood that the terminology used in the description of the present application merely describes specific embodiments and does not limit the application. As used in the description of the application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
[0021] It should further be understood that the term "and / or" used in the description of the present application and the appended claims, means any combination of one or more of the associated listed items and all possible combinations thereof.
[0022] Various structural diagrams according to the disclosed embodiments of the present application are shown in the drawings. These diagrams are not drawn to scale, in which certain details are exaggerated for clarity of presentation and can omit certain details. The shapes and relative sizes of the various regions, layers, and their relative positions illustrated in the drawings are merely exemplary, and in actuality can deviate due to manufacturing tolerances or technical limitations, and regions / layers with different shapes, sizes, and relative positions can be additionally designed by those skilled in the art according to actual needs.
[0023] The embodiments of the present application are described in detail below with reference to the accompanying drawings.
[0024] Embodiment 1 A gas-steam combined cycle steam extraction heating power plant is configured with two gas-steam combined cycle steam extraction heating units to jointly supply external power and heat. The current basic operation mode of the in-plant heating system is as follows: (1) When #1 and #2 units are operated in dual mode (i.e., both units are in operation), high-temperature and high-pressure heating extraction steam is extracted from the reheated cold section pipe of the steam turbine of each unit, respectively, and after temperature and pressure reduction, it enters the auxiliary steam header of each #1 and #2 combined cycle unit, respectively. The auxiliary steam headers of #1 and #2 units are connected to the heating header, and finally the heating steam is extracted from the heating header and enters the heating main pipe to supply external heat; (2) When #1 and #2 units are operated independently (i.e. one of the combined cycle units is in a shutdown state), high-temperature and high-pressure heating extraction steam is extracted from the reheating cold section pipeline of the steam turbine of the combined cycle unit in the running state, enters the auxiliary steam header after temperature and pressure reduction, the auxiliary steam header is connected with the heating header, and finally the heating steam is extracted from the heating header and enters the heating main pipe to supply heat to the outside.
[0025] The application provides a kind of combined cycle extraction heating power plant optimal production strategy calculation method, comprising the following steps: S1: retrieve 18 months of historical operation data of each unit in the multiple units of the whole plant. After condition judgment and significant error data elimination, a prediction model of the relationship between heating flow and unit heating valve opening degree and unit load of each unit is obtained by using a multivariate linear fitting method, and typical calculation results are as shown in Figure 1 .
[0026] S2: retrieve 18 months of historical operation data of two units for analysis, and make a relationship diagram of unit heating capacity and heating valve opening degree, as shown in Figure 2 , when the heating valve opening degree (reheating cold section steam regulating valve) of a single combined cycle unit reaches 100%, the heating steam flow is about 50t / h, therefore, the maximum heating capacity of a single combined cycle unit is about 50t / h.
[0027] S3: retrieve 18 months of historical operation data of the power plant, obtain 3105 groups of stable historical operation data after condition judgment and significant error data elimination, and randomly arrange the 3105 groups of data, take 70% of the data as the training set, and take 30% of the data as the test set. The function relationship between unit combined cycle power and unit compressor inlet temperature and unit heating flow is trained by using a multivariate linear fitting data training method. Figure 3 and Figure 4 The relative error of the model calculation results and the actual values of the training set and the test set and the frequency distribution of the relative error can be seen that most of the errors are within ±1%, indicating that the accuracy of the training model is satisfactory.
[0028] S4: retrieve 18 months of historical operation data of the power plant, and make a relationship curve diagram of unit power generation output and NOx emission in typical seasons such as summer and winter, as shown in Figure 4 and Figure 5 , it can be analyzed from the curves in the diagrams that when the power generation load (under non-heating conditions) is about 120MW during the startup process of the unit, the NOx emission is easy to be higher than 50mg / Nm 3 , which exceeds the standard.
[0029] S5: The method of combined cycle unit mechanism modeling is adopted to establish the performance simulation calculation model of combined cycle unit, and the theoretical energy consumption characteristics of combined cycle unit in wide load condition are obtained through variable condition calculation. The data mining training method of multivariate linear fitting is adopted to obtain the theoretical energy consumption characteristic cluster, as shown in Figure 6 Based on the least square optimization theory, the mathematical model of the theoretical energy consumption characteristic cluster is adaptively corrected by genetic algorithm, and the calculation accuracy of the energy consumption characteristic cluster of combined cycle unit is improved, as shown in Figure 7
[0030] S6: The objective function of determining the optimal production strategy of the whole plant is determined:
[0031] In the formula: The total fuel consumption of the whole plant at time t; The fuel consumption of the i th unit at time t; N The total number of units in the whole plant, N = 2; The value of external factors affecting the energy consumption of the i th unit at time t; The power of the i th unit at time t; The thermal (cold) load of the i th unit in the whole plant at time t; The running state of the i th unit in the whole plant at time t, 0 represents shutdown, and 1 represents running.
[0032] The energy consumption characteristics of the i th unit.
[0033] S7: Determine the constraint condition: 1) Load balance constraint
[0034]
[0035] In the formula: The total electric load of the whole plant at time t; t The total thermal load of the whole plant at time t. t 2) Coupling of unit power and thermal load
[0036]
[0037]
[0038] In the formula: , - the i-th unit at the t-th time point i unit set t minimum and maximum electric load at the t-th time point; , - the i-th unit at the t-th time point
[0039] 3) Pollutant emission constraints
[0040] In the formula: - the i-th unit at the t-th time point i pollutant emission index of the i-th unit at the t-th time point; t - pollutant emission index limit value, usually determined according to local environmental protection requirements.
[0041] S8 The solving step takes the enumeration method as the basic solving method, and uses the vector programming method to realize the synchronous calculation of the electric and thermal load combination optimization scheme of two units, and the time required for one working condition optimization calculation is less than 1 second, meeting the real-time requirements of the calculation results of the online optimization of electric and thermal load combination. Among them, the electric power of each combined cycle unit is taken as the minimum change interval with an amplitude of 1 MW, and the thermal load of each combined cycle unit is taken as the minimum change interval with an amplitude of 1 t / h. The main solving process is as shown in Figure 8 .
[0042] Retrieve the historical operation data of the power plant for a whole year for verification: using the above-mentioned gas-steam combined cycle extraction heating power plant optimal production strategy calculation method, the best electric and thermal load combination optimization distribution scheme of two combined cycle units and the corresponding natural gas saving amount are calculated, as shown in Figure 9 , which verifies the effectiveness of the method.
[0043] Example 2 As shown in Figure 10 , the present application provides a kind of combined cycle extraction heating power plant optimal production strategy calculation system, comprising: a prediction equation acquisition module, which retrieves historical operation data of each unit in the multiple units of the whole plant, and after preprocessing, obtains the prediction equation of the relationship between the heating capacity of each unit and the heating valve opening degree of the unit and the unit load by using data mining method; The first calculation module calculates the maximum heat supply of each unit corresponding to the heat supply valve opening degree of 100% at different loads by using a prediction equation; The second calculation module retrieves historical operation data of each combined cycle unit when the gas turbine of the unit is operated at full load, and obtains an equation of the maximum power generation of each unit and the atmospheric temperature and the heat supply after pretreatment and data mining, and calculates the maximum power generation of each unit at different atmospheric temperatures and heat supplies; The minimum power generation load taking module retrieves historical operation data of each unit, and analyzes to obtain the minimum power generation load of each unit meeting the NOx emission standard; The energy consumption prediction equation taking module establishes a performance model of each combined cycle unit, obtains an energy consumption prediction equation of each unit under wide load conditions by using a theoretical calculation method, and corrects the energy consumption prediction equation by using historical operation data or test data; The objective function determination module determines the objective function of the optimal production strategy of the whole plant, and the objective function is the minimum total fuel consumption of the whole plant, and includes the energy consumption prediction equation of each unit under wide load conditions; The constraint condition determination module determines the constraint condition corresponding to the objective function, including the total heat and power load balance constraint of the whole plant, the maximum heat supply constraint of each unit, the maximum power generation constraint of each unit, and the minimum power generation load constraint of each unit meeting the NOx emission standard; The third calculation module uses a solving algorithm to solve the objective function with the constraint condition, and obtains the best power load and heat supply load of each unit of the whole plant.
[0044] In the prediction equation obtaining module in the embodiment, historical operation data of each unit of multiple units of the whole plant are retrieved, and a prediction equation of the relationship among the heat supply, the unit heat supply valve opening degree and the unit load of each unit is obtained by using data mining after pretreatment, wherein the pretreatment adopts condition stability judgment and significant error data elimination.
[0045] Embodiment 3 The electronic device provided by the application comprises a processor and a memory coupled with the processor, the memory stores a computer program, and the computer program is executed by the processor to realize the steps of the optimal production strategy calculation method of the combined cycle extraction heat supply power plant.
[0046] The electronic device can further include one or more of a multimedia component, an input / output (I / O) interface, and a communication component.
[0047] The processor is configured to control overall operations of the electronic device to complete all or part of the steps in the storage medium sharing method. The memory is configured to store various types of data to support operations of the electronic device, which can include, for example, instructions for any application or method operating on the electronic device, and application-related data, such as contact data, sent and received messages, pictures, audio, video, and the like. The memory can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk. The multimedia component can include a screen and an audio component. The screen can be, for example, a touch screen, and the audio component is configured to output and / or input audio signals. For example, the audio component can include a microphone configured to receive external audio signals. The received audio signals can be further stored in the memory or transmitted through the communication component. The audio component also includes at least one speaker configured to output audio signals. The I / O interface provides an interface between the processor and other interface modules, which can be a keyboard, a mouse, a button, and the like. The buttons can be virtual buttons or physical buttons. The communication component is configured to perform wired or wireless communication between the electronic device and other devices. Wireless communication, such as Wi-Fi, Bluetooth, near field communication (NFC), 2G, 3G, or 4G, or a combination of one or more of them, so the corresponding communication component can include a Wi-Fi module, a Bluetooth module, and an NFC module.
[0048] In an exemplary embodiment, the electronic device can be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors, or other electronic elements for performing the storage medium sharing method.
[0049] Embodiment 4 The application provides a computer readable storage medium, characterized by storing a computer program, wherein the computer program, when executed by a processor, implements steps of the optimal production strategy calculation method for a combined cycle steam extraction heat supply power plant.
[0050] Those skilled in the art should understand that embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage, etc.) containing computer-usable program code.
[0051] The present application is described with reference to the flowcharts and / or block diagrams of the methods, the systems and the computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or the block diagrams, and the combination of the flows and / or the blocks in the flowcharts and / or the block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processing machine, or other programmable data processing devices to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices produce the functions specified in the flowcharts and / or the block diagrams of the methods, the systems and the computer program products. Figure 1 The system that realizes the functions specified in one flow or multiple flows and / or blocks Figure 1 The system that realizes the functions specified in one block or multiple blocks
[0052] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.
[0053] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.
[0054] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the scope of the invention. No reference numerals in the claims should be construed as limiting the scope of the claims.
[0055] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can be appropriately combined to form other embodiments that can be understood by those skilled in the art. The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.
Claims
1. A method for calculating the optimal production strategy of a combined cycle extraction steam power plant, characterized in that, Includes the following steps: S1 retrieves historical operating data for each of the multiple units in the plant. After preprocessing, it uses data mining methods to obtain a predictive equation for the relationship between the heat supply of each unit and the opening of the unit's heat supply regulating valve and the unit's load. S2 uses predictive equations to calculate and determine the maximum heat output of each unit when the opening of the heating regulating valve reaches 100% under different loads. S3 retrieves historical operating data of each combined cycle unit when its gas turbine is operating at full load. After preprocessing, data mining methods are used to obtain the equations of maximum power generation of each unit in relation to atmospheric temperature and heat supply, and the maximum power generation of each unit under different atmospheric temperatures and heat supply conditions is calculated. S4 retrieves historical operating data for each unit and analyzes it to obtain the minimum power generation load for each unit to meet NOx emission standards. S5 establishes a performance model for each combined cycle unit, uses theoretical calculations to obtain the energy consumption prediction equation for each unit under wide load conditions, and uses historical operating data or experimental data to correct the energy consumption prediction equation. S6 determines the objective function of the optimal production strategy for the entire plant. The objective function is to minimize the total fuel consumption of the entire plant and includes the energy consumption prediction equation for each unit under wide load conditions. S7 determines the constraints corresponding to the objective function, including total heat and electricity load balance constraints for the whole plant, maximum heat supply constraints for each unit, maximum power generation constraints for each unit, and minimum power generation load constraints for each unit to meet NOx emission standards. S8 employs a solution algorithm to solve the objective function with constraints, thereby obtaining the optimal electrical load and heating load for each unit in the entire plant.
2. The method for calculating the optimal production strategy of a combined cycle extraction steam heating power plant according to claim 1, characterized in that, In step S1, historical operating data of each of the multiple units in the plant is retrieved. After preprocessing, data mining methods are used to obtain the predictive equation of the relationship between the heat supply of each unit and the opening of the heat supply regulating valve and the unit load. The preprocessing adopts the method of judging the stability of the operating condition and removing data with significant errors.
3. The method for calculating the optimal production strategy of a combined cycle extraction steam heating power plant according to claim 1, characterized in that, The data mining methods used in steps S1 and S3 include multiple linear fitting algorithms and neural network algorithms.
4. The method for calculating the optimal production strategy of a combined cycle extraction steam heating power plant according to claim 1, characterized in that, In step S5, the wide load condition is a wide range of multi-dimensional operating boundary conditions for power, heat supply and atmospheric parameters.
5. The method for calculating the optimal production strategy of a combined cycle extraction steam heating power plant according to claim 1, characterized in that, In step S6, the objective function of the optimal production strategy for the entire plant should be formulated based on the actual situation, and the objective function is as follows: In the formula: —Total fuel consumption of the entire plant at time t; —The fuel consumption of the i-th unit at time t; N —The total number of generating units in the entire plant; —The value of the external factors affecting the consumption of the i-th unit at time t; —The generating capacity of the i-th unit at time t; —The heat / cooling load of the i-th unit at time t in the entire plant; —The operating status of the i-th unit at time t for the entire plant, where 0 represents shutdown and 1 represents operation; f i —Energy consumption prediction equation for the i-th unit under wide load conditions.
6. The method for calculating the optimal production strategy of a combined cycle extraction steam heating power plant according to claim 1, characterized in that, In step S8, the solution algorithms include priority order method, local optimization method, exhaustive search method, dynamic programming method and Lagrange relaxation method numerical solution.
7. A calculation system for optimal production strategy in a combined cycle extraction steam power plant, characterized in that, include: The prediction equation acquisition module retrieves historical operating data for each of the multiple units in the plant. After preprocessing, it uses data mining methods to obtain the prediction equations for the relationship between the heat supply of each unit and the opening of the unit's heat supply regulating valve and the unit's load. The first calculation module uses prediction equations to calculate and determine the maximum heat output of each unit when the opening of the heating regulating valve reaches 100% under different loads. The second calculation module retrieves historical operating data of each combined cycle unit when its gas turbine is operating at full load. After preprocessing, it uses data mining methods to obtain the equations of the maximum power generation of each unit in relation to atmospheric temperature and heat supply, and calculates the maximum power generation of each unit under different atmospheric temperatures and heat supply conditions. The minimum power generation load acquisition module retrieves historical operating data for each unit and analyzes it to obtain the minimum power generation load for each unit to meet NOx emission standards. The energy consumption prediction equation load-taking module establishes a performance model for each combined cycle unit, uses theoretical calculation methods to obtain the energy consumption prediction equation for each unit under wide load conditions, and uses historical operating data or experimental data to correct the energy consumption prediction equation. The objective function determination module determines the objective function of the optimal production strategy for the entire plant. The objective function is to minimize the total fuel consumption of the entire plant and includes the energy consumption prediction equation for each unit under wide load conditions. The constraint determination module determines the constraints corresponding to the objective function, including total plant heat and electricity load balance constraints, maximum heat supply constraints for each unit, maximum power generation constraints for each unit, and minimum power generation load constraints for each unit to meet NOx emission standards. The third calculation module uses a solution algorithm to solve the objective function with constraints, thereby obtaining the optimal electrical load and heating load for each unit in the plant.
8. The optimal production strategy calculation system for a combined cycle extraction steam heating power plant according to claim 7, characterized in that, In the prediction equation acquisition module, historical operating data of each of the multiple units in the plant is retrieved. After preprocessing, data mining methods are used to obtain the prediction equation of the relationship between the heat supply of each unit and the opening of the unit's heat supply regulating valve and the unit's load. The preprocessing adopts the method of judging the stability of the operating condition and removing data with significant errors.
9. An electronic device, characterized in that, include: A processor and a memory coupled to the processor, the memory storing a computer program that, when executed by the processor, implements the steps of the method for calculating the optimal production strategy of a combined cycle extraction steam heating power plant according to any one of claims 1-6.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the method for calculating the optimal production strategy of a combined cycle extraction steam heating power plant according to any one of claims 1-6.