Energy-saving optimization method and system for boiler of thermal power plant

Abstract

The invention relates to the technical field of thermal power generation, and discloses a thermal power plant boiler energy-saving optimization method and system.The method comprises the steps that whether an energy-saving control instruction is triggered or not is judged according to a plurality of real-time boiler combustion state parameters, if yes, the energy-saving control instruction is generated, and if not, the energy-saving control instruction is executed; the energy-saving control instruction comprises a plurality of optimized energy-saving control parameters, a plurality of first state parameters to be regulated and controlled and corresponding first values to be regulated and controlled; and obtaining real-time state data of the plurality of first state parameters to be regulated and controlled based on the test time node, obtaining a plurality of real-time regulation and control quantity value change curves, generating a comprehensive application coefficient of the energy-saving control instruction according to the plurality of sub-application coefficients, judging whether the energy-saving control instruction is corrected or not, if yes, generating an energy-saving control optimization instruction, and if not, performing energy-saving control optimization. The formulation rationality of the energy-saving control instruction is improved, the application effect is accurately evaluated, the energy-saving control instruction is found and adjusted in time, and the energy-saving optimization effect is improved.

Description

Technical Field

[0001] The present application relates to the field of thermal power generation technology, and in particular to an energy-saving optimization method for a thermal power plant boiler. Background Art

[0002] Thermal power plants are a vital component of my country's power industry, but they are also a major source of energy consumption and pollutant emissions. Boilers are a major contributor to energy consumption in thermal power plants, and optimizing boiler combustion is a crucial measure for energy conservation and emission reduction. With the country's increasing environmental protection requirements, energy conservation and emission reduction efforts in thermal power plant boilers are becoming increasingly important.

[0003] In the existing technology, energy-saving optimization methods for boiler combustion mostly rely on monitoring operation data for energy-saving regulation. However, the operation data is large and the analysis and processing volume is large, resulting in unreasonable energy-saving control strategy formulation or poor application effect, and failure to timely discover deficiencies and adjust energy-saving control strategies, thereby reducing boiler combustion efficiency and energy-saving optimization effects. Summary of the Invention

[0004] In order to solve the above technical problems, the present application provides an energy-saving optimization method and system for a thermal power plant boiler, which determines whether an energy-saving control instruction is triggered based on the real-time boiler combustion state parameters. If so, an energy-saving control instruction is generated, and a comprehensive application coefficient of the energy-saving control instruction is generated based on the real-time control value change curve. Based on the comprehensive application coefficient, it is determined whether the energy-saving control instruction is optimized, the rationality of the formulation of the energy-saving control instruction is improved, the application effect is accurately evaluated, the energy-saving control instruction is discovered and adjusted in a timely manner, and the energy-saving optimization effect is improved.

[0005] In some embodiments of the present application, a method for optimizing energy conservation of a thermal power plant boiler is provided, comprising: collecting a number of real-time boiler combustion state parameters at a real-time monitoring time node, determining whether an energy-saving control instruction is triggered based on the number of real-time boiler combustion state parameters, and if so, generating an energy-saving control instruction, the energy-saving control instruction including a number of preferred energy-saving control parameters, a number of first state parameters to be adjusted, and corresponding first values to be adjusted; Presetting an inspection period and several inspection time nodes, acquiring real-time state data of several first state parameters to be regulated based on the inspection time nodes and performing curve fitting to obtain several real-time regulation value change curves; Generate a sub-application coefficient corresponding to the optimal energy-saving control parameter according to each real-time control value change curve, and generate a comprehensive application coefficient of the energy-saving control instruction according to several sub-application coefficients; Determine whether to modify the energy-saving control instruction based on the comprehensive application coefficient. If so, filter out the second state parameter to be adjusted and determine the second value to be adjusted. Generate the energy-saving control optimization instruction based on the second state parameter to be adjusted and the second value to be adjusted.

[0006] In some embodiments of the present application, determining whether to trigger an energy-saving control instruction based on several real-time boiler combustion state parameters includes: Pre-set several energy-saving evaluation indicators; Calculating the correlation degree between each real-time boiler combustion state parameter and each energy-saving evaluation index, and determining the associated boiler combustion state parameter of each energy-saving evaluation index according to the correlation degree; Compare the boiler combustion state parameters associated with each energy-saving evaluation index with the corresponding standard combustion state parameters, and generate an energy-saving sub-evaluation value of the corresponding energy-saving evaluation index based on the comparison result and the weight coefficient of the corresponding associated boiler combustion state parameter; Generate a comprehensive energy-saving evaluation value based on the energy-saving sub-evaluation values of several energy-saving evaluation indicators and corresponding weight coefficients; Pre-set energy-saving evaluation value threshold; If the comprehensive energy-saving evaluation value is less than the energy-saving evaluation value threshold, it is determined that the energy-saving control instruction is triggered.

[0007] In some embodiments of the present application, the energy-saving control instruction includes a plurality of first state parameters to be regulated and corresponding first values to be regulated, including: When it is determined that an energy-saving control instruction is triggered, the optimal control duration of the energy-saving control instruction is set and energy-saving evaluation indicators with energy-saving sub-evaluation values less than the energy-saving sub-evaluation value threshold are selected; Determine several initial state parameters to be regulated for the selected energy-saving evaluation indicators based on the comparison results of the associated boiler combustion state parameters in the selected energy-saving evaluation indicators and the corresponding standard combustion state parameters; Combining a plurality of initial state parameters to be regulated according to the energy-saving sub-evaluation value differences of the screened energy-saving evaluation indicators to obtain a plurality of initial state parameter combinations to be regulated, wherein each initial state parameter combination to be regulated includes at least one initial state parameter to be regulated, and each initial state parameter to be regulated is mapped to a corresponding initial value to be regulated; Constructing an energy-saving control strategy reference library for each energy-saving evaluation index, wherein the energy-saving control strategy reference library includes preset control values of boiler combustion state parameters associated with the corresponding energy-saving evaluation index, and each preset control value is mapped to a corresponding preset energy-saving control parameter; Compare and analyze the energy-saving control strategy reference library with the initial state parameters to be regulated in each initial state parameter combination and the mapped initial state parameter values to be regulated, and construct an energy-saving control strategy corresponding to the initial state parameter combination to be regulated using the preset energy-saving control parameters with the smallest difference in the state parameter values to be regulated for the same associated boiler combustion state parameter; Based on the historical dynamic relationship between the energy-saving control strategy, the initial state parameters to be regulated in the corresponding initial state parameter combination to be regulated, and the mapped initial state values to be regulated, each initial state parameter to be regulated in the corresponding initial state parameter combination to be regulated is predicted to obtain a plurality of first predicted control values for each initial state parameter to be regulated; Establishing a time reference line according to the optimal control duration, setting a number of preset time nodes according to a preset time interval, performing time mapping based on the number of preset time nodes and a number of first predicted control values, and obtaining a predicted control change sequence corresponding to the initial state parameter to be controlled according to the mapping result; Calculating the control sub-evaluation value of the corresponding initial state parameter to be controlled according to the predicted control change sequence, and generating a comprehensive control evaluation value according to the control sub-evaluation value of each initial state parameter to be controlled in the same combination of initial state parameters to be controlled; The initial state parameter combination to be regulated and the corresponding energy-saving control strategy with the largest comprehensive regulation evaluation value are set as the preferred state parameter combination to be regulated and the corresponding preferred energy-saving control strategy corresponding to the selected energy-saving evaluation index; Each initial state parameter to be regulated and the corresponding initial value to be regulated in the selected preferred state parameter combination to be regulated of the energy-saving evaluation index are set as a plurality of first state parameters to be regulated and the corresponding first values to be regulated, and a weight coefficient of the first state parameter to be regulated is set according to the regulation sub-evaluation value; Setting the energy-saving control parameters involved in the preferred energy-saving control strategy corresponding to the preferred combination of state parameters to be regulated to a plurality of preferred energy-saving control parameters; The preferred energy-saving control parameter is mapped one-to-one with the first state parameter to be regulated and the corresponding first value to be regulated.

[0008] In some embodiments of the present application, calculating the control sub-evaluation value corresponding to the initial state parameter to be controlled based on the predicted control change sequence includes: The first preset time node at which the first predicted control value of each initial state parameter to be controlled satisfies the initial control value of the corresponding initial state parameter to be controlled is set as a characteristic time node, and a first predicted control duration is obtained according to the characteristic time node; Generate a first control evaluation value corresponding to the initial state parameter to be controlled according to the first predicted control duration; Calculating the difference between first predicted control values of adjacent preset time nodes in the first predicted control duration of the predicted control change sequence of each initial state parameter to be controlled, and generating a second control evaluation value corresponding to the initial state parameter to be controlled based on the first predicted control value difference; Calculating a first predicted control cost for each initial state parameter to be controlled in the first predicted control duration, and generating a third control evaluation value according to the first predicted control cost; A control sub-evaluation value is generated according to the first control evaluation value, the second control evaluation value and the third control evaluation value of each initial state parameter to be controlled.

[0009] In some embodiments of the present application, several real-time control value change curves are obtained, including: Setting a test period according to the optimal control duration, and setting a number of test time nodes in the test period based on a weight coefficient of each first state parameter to be regulated; Acquire real-time state data corresponding to the first state parameter to be regulated based on the inspection time node, and obtain the real-time regulation value at each inspection time node; A real-time control value variation curve corresponding to the first state parameter to be regulated is generated according to the real-time control value at a plurality of inspection time nodes corresponding to the current first state parameter to be regulated.

[0010] In some embodiments of the present application, generating a sub-application coefficient corresponding to a preferred energy-saving control parameter according to each real-time control value change curve includes: Generate a standard control value change curve corresponding to the first state parameter to be controlled according to the predicted control change sequence corresponding to each initial state parameter to be controlled in the preferred combination of state parameters to be controlled, and intercept the standard control value change curve based on the corresponding inspection time node to obtain a standard control value change curve segment; Based on the same time comparison principle, the real-time control value change curve of each first state parameter to be controlled is analyzed for similarity with the corresponding standard control value change curve segment to obtain similarity; Pre-set similarity threshold; If the similarity is less than the similarity threshold, the real-time control value change curve of the corresponding first state parameter to be controlled is extrapolated to obtain a predicted control value change curve segment of the corresponding first state parameter to be controlled in the remaining period of the optimal control time, wherein the predicted control value change curve segment includes the second predicted control value at several monitoring time nodes in the remaining period; The first monitoring time node at which the second predicted control value in the predicted control value change curve segment satisfies the first to-be-controlled value of the corresponding first to-be-controlled state parameter is set as a characteristic monitoring node, and the second predicted control duration is determined according to the characteristic monitoring node; Calculating a plurality of second predicted control value differences and a second predicted control cost in a second predicted control duration of the first state parameter to be controlled; Generate a first sub-application coefficient according to a difference between a second predicted control duration and a first predicted control duration for the same state parameter to be controlled; Generate a predicted degree of fluctuation according to a plurality of second predicted control value differences, and generate a second sub-application coefficient according to a difference between the predicted degree of fluctuation and a predicted degree of fluctuation of a preset degree of fluctuation threshold; generating a third sub-application coefficient according to a predicted control cost difference between a second predicted control cost and a first predicted control cost of the same state parameter to be controlled; Generate a sub-application coefficient of the preferred energy-saving control parameter mapped to the first state parameter to be regulated according to the first sub-application coefficient, the second sub-application coefficient, and the third sub-application coefficient; When the similarity is less than the similarity threshold, the calculation formula of the sub-application coefficient Y1 is: ; Among them, z1 is the first sub-application conversion coefficient, a1 is the weight coefficient of the first sub-application coefficient, is the predicted control time difference, z2 is the second sub-application conversion coefficient, a2 is the weight coefficient of the second sub-application coefficient, is the predicted volatility difference, z3 is the third sub-application conversion coefficient, a3 is the weight coefficient of the third sub-application coefficient, To predict the difference in regulatory costs; If the similarity is greater than the similarity threshold, generating a sub-application coefficient of the preferred energy-saving control parameter mapped to the first state parameter to be regulated according to the similarity; When the similarity is greater than the similarity threshold, the calculation formula of the sub-application coefficient Y2 is: ; Where z4 is the fourth sub-application conversion coefficient, n is the number of test time nodes in the test period, is the difference in the curve value at the i-th test time node, is the difference in the slope of the curve at the i-th test time node, is the difference in curve shape between the i-th inspection time node and the previous inspection time node, x1 is the first similarity conversion coefficient, c1 is the weight coefficient of the curve value difference, x2 is the second similarity conversion coefficient, c2 is the weight coefficient of the curve slope difference, x3 is the third similarity conversion coefficient, c3 is the weight coefficient of the curve shape difference, and d0 is the similarity threshold.

[0011] In some embodiments of the present application, a comprehensive application coefficient of an energy-saving control instruction is generated based on a plurality of sub-application coefficients, including: Obtaining the sub-application coefficient of the first state parameter to be regulated mapped to the same preferred energy-saving control parameter and the weight coefficient corresponding to the first state parameter to be regulated, and calculating the weighted average to obtain the average of the sub-application coefficients of each preferred energy-saving control parameter; The comprehensive application coefficient of the corresponding energy-saving control instruction is generated according to the average value of the sub-application coefficients of several preferred energy-saving control parameters in the energy-saving control instruction.

[0012] In some embodiments of the present application, determining whether to modify the energy-saving control instruction based on the comprehensive application coefficient, and if so, screening out a second state parameter to be regulated and determining a second value to be regulated includes: Pre-set comprehensive application coefficient threshold; If the comprehensive application coefficient is greater than the comprehensive application coefficient threshold, the energy-saving control instruction is not corrected; If the comprehensive application coefficient is less than the comprehensive application coefficient threshold, the energy-saving control instruction is modified; Comparing the sub-application coefficients of the first state parameter to be regulated mapped to the plurality of preferred energy-saving control parameters in the energy-saving control instruction with a preset sub-application coefficient threshold, screening out the first state parameter to be regulated whose sub-application coefficient is less than the preset sub-application coefficient threshold and setting it as the second state parameter to be regulated, and generating a second value to be regulated for the second state parameter to be regulated according to the difference in the sub-application coefficients; Based on the energy-saving evaluation index to which the second parameter to be regulated belongs, a corresponding energy-saving control strategy reference library is determined, and the second state parameter to be regulated and the corresponding second value to be regulated are analyzed, and an energy-saving control optimization instruction is generated according to the analysis result.

[0013] In some embodiments of the present application, an energy-saving optimization system for a thermal power plant boiler is also included: a collection module for collecting a plurality of real-time boiler combustion state parameters at a real-time monitoring time node, determining whether an energy-saving control instruction is triggered based on the plurality of real-time boiler combustion state parameters, and if so, generating an energy-saving control instruction, the energy-saving control instruction including a plurality of preferred energy-saving control parameters, a plurality of first state parameters to be regulated, and corresponding first values to be regulated; An inspection module is used to pre-set an inspection period and several inspection time nodes, obtain real-time state data of several first state parameters to be regulated based on the inspection time nodes, and perform curve fitting to obtain several real-time regulation value change curves; A calculation module, configured to generate a sub-application coefficient corresponding to the optimal energy-saving control parameter according to each real-time control value change curve, and generate a comprehensive application coefficient of the energy-saving control instruction according to a plurality of sub-application coefficients; The optimization module is used to determine whether to modify the energy-saving control instruction based on the comprehensive application coefficient. If so, the second state parameter to be adjusted is screened out and the second value to be adjusted is determined, and the energy-saving control optimization instruction is generated based on the second state parameter to be adjusted and the second value to be adjusted.

[0014] Compared with the prior art, the energy-saving optimization method and system for a thermal power plant boiler according to the embodiment of the present application have the following advantages: By judging whether the energy-saving control instruction is triggered based on the real-time boiler combustion state parameters, if so, an energy-saving control instruction is generated, and a comprehensive application coefficient of the energy-saving control instruction is generated based on the real-time control value change curve. According to the comprehensive application coefficient, it is judged whether the energy-saving control instruction is optimized, the rationality of the formulation of the energy-saving control instruction is improved, the application effect is accurately evaluated, the energy-saving control instruction is discovered and adjusted in time, and the energy-saving optimization effect is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a flow chart of an energy-saving optimization method for a thermal power plant boiler in an embodiment of the present application; Figure 2 It is a schematic diagram of an energy-saving optimization system for a thermal power plant boiler in an embodiment of the present application. DETAILED DESCRIPTION

[0016] The following embodiments are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0017] In the description of this application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on this application.

[0018] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of such features. Throughout this application, unless otherwise specified, "plurality" means two or more.

[0019] In the description of this application, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in this application based on the specific circumstances.

[0020] like Figure 1 As shown, an energy-saving optimization method for a thermal power plant boiler according to an embodiment of the present application includes: Step S101: collecting a number of real-time boiler combustion state parameters at a real-time monitoring time node, determining whether an energy-saving control instruction is triggered based on the real-time boiler combustion state parameters, and if so, generating an energy-saving control instruction, the energy-saving control instruction including a number of preferred energy-saving control parameters, a number of first state parameters to be adjusted, and corresponding first values to be adjusted; Step S102: presetting an inspection period and several inspection time nodes, obtaining real-time state data of several first state parameters to be regulated based on the inspection time nodes and performing curve fitting to obtain several real-time regulation value change curves; Step S103: generating a sub-application coefficient corresponding to the optimal energy-saving control parameter according to each real-time control value change curve, and generating a comprehensive application coefficient of the energy-saving control instruction according to the plurality of sub-application coefficients; Step S104: Determine whether to modify the energy-saving control instruction based on the comprehensive application coefficient. If so, select the second state parameter to be adjusted and determine the second value to be adjusted. Generate the energy-saving control optimization instruction based on the second state parameter to be adjusted and the second value to be adjusted.

[0021] In some embodiments of the present application, determining whether to trigger an energy-saving control instruction based on several real-time boiler combustion state parameters includes: Pre-set several energy-saving evaluation indicators; Calculating the correlation degree between each real-time boiler combustion state parameter and each energy-saving evaluation index, and determining the associated boiler combustion state parameter of each energy-saving evaluation index according to the correlation degree; Compare the boiler combustion state parameters associated with each energy-saving evaluation index with the corresponding standard combustion state parameters, and generate an energy-saving sub-evaluation value of the corresponding energy-saving evaluation index based on the comparison result and the weight coefficient of the corresponding associated boiler combustion state parameter; Generate a comprehensive energy-saving evaluation value based on the energy-saving sub-evaluation values of several energy-saving evaluation indicators and corresponding weight coefficients; Pre-set energy-saving evaluation value threshold; If the comprehensive energy-saving evaluation value is less than the energy-saving evaluation value threshold, it is determined that the energy-saving control instruction is triggered.

[0022] In this embodiment, the associated boiler combustion state parameter refers to a real-time boiler combustion state parameter whose correlation degree with each energy-saving evaluation index is greater than a preset correlation degree threshold.

[0023] In this embodiment, the energy-saving evaluation indicators include boiler thermal efficiency, flue gas heat loss, flue gas temperature, fly ash and slag carbon content, etc., that is, several energy-saving evaluation indicators are indicators that can significantly reduce coal consumption during boiler combustion and improve the economy and environmental protection of the power plant.

[0024] In this embodiment, the real-time boiler combustion state parameters refer to parameters that can represent the combustion state during the boiler combustion process, such as exhaust gas temperature, flue gas composition, primary air / secondary air ratio, coal powder fineness, furnace negative pressure, etc.

[0025] In some embodiments of the present application, the energy-saving control instruction includes a plurality of first state parameters to be regulated and corresponding first values to be regulated, including: When it is determined that an energy-saving control instruction is triggered, the optimal control duration of the energy-saving control instruction is set and energy-saving evaluation indicators with energy-saving sub-evaluation values less than the energy-saving sub-evaluation value threshold are selected; Determine several initial state parameters to be regulated for the selected energy-saving evaluation indicators based on the comparison results of the associated boiler combustion state parameters in the selected energy-saving evaluation indicators and the corresponding standard combustion state parameters; Combining a plurality of initial state parameters to be regulated according to the energy-saving sub-evaluation value differences of the screened energy-saving evaluation indicators to obtain a plurality of initial state parameter combinations to be regulated, wherein each initial state parameter combination to be regulated includes at least one initial state parameter to be regulated, and each initial state parameter to be regulated is mapped to a corresponding initial value to be regulated; Constructing an energy-saving control strategy reference library for each energy-saving evaluation index, wherein the energy-saving control strategy reference library includes preset control values of boiler combustion state parameters associated with the corresponding energy-saving evaluation index, and each preset control value is mapped to a corresponding preset energy-saving control parameter; Compare and analyze the energy-saving control strategy reference library with the initial state parameters to be regulated in each initial state parameter combination and the mapped initial state parameter values to be regulated, and construct an energy-saving control strategy corresponding to the initial state parameter combination to be regulated using the preset energy-saving control parameters with the smallest difference in the state parameter values to be regulated for the same associated boiler combustion state parameter; Based on the historical dynamic relationship between the energy-saving control strategy, the initial state parameters to be regulated in the corresponding initial state parameter combination to be regulated, and the mapped initial state values to be regulated, each initial state parameter to be regulated in the corresponding initial state parameter combination to be regulated is predicted to obtain a plurality of first predicted control values for each initial state parameter to be regulated; Establishing a time reference line according to the optimal control duration, setting a number of preset time nodes according to a preset time interval, performing time mapping based on the number of preset time nodes and a number of first predicted control values, and obtaining a predicted control change sequence corresponding to the initial state parameter to be controlled according to the mapping result; Calculating the control sub-evaluation value of the corresponding initial state parameter to be controlled according to the predicted control change sequence, and generating a comprehensive control evaluation value according to the control sub-evaluation value of each initial state parameter to be controlled in the same combination of initial state parameters to be controlled; The initial state parameter combination to be regulated and the corresponding energy-saving control strategy with the largest comprehensive regulation evaluation value are set as the preferred state parameter combination to be regulated and the corresponding preferred energy-saving control strategy corresponding to the selected energy-saving evaluation index; Each initial state parameter to be regulated and the corresponding initial value to be regulated in the selected preferred state parameter combination to be regulated of the energy-saving evaluation index are set as a plurality of first state parameters to be regulated and the corresponding first values to be regulated, and a weight coefficient of the first state parameter to be regulated is set according to the regulation sub-evaluation value; Setting the energy-saving control parameters involved in the preferred energy-saving control strategy corresponding to the preferred combination of state parameters to be regulated to a plurality of preferred energy-saving control parameters; The preferred energy-saving control parameter is mapped one-to-one with the first state parameter to be regulated and the corresponding first value to be regulated.

[0026] In this embodiment, each combination of initial state parameters to be regulated can make the energy-saving sub-evaluation value of the screened energy-saving evaluation index greater than the energy-saving sub-evaluation value threshold.

[0027] In this embodiment, the historical dynamic relationship refers to the historical change characteristics of the initial state parameters to be regulated after the historical energy-saving control parameters in the historical log. The historical change characteristics include the historical change trend, the historical change degree and the historical change value. By obtaining the historical dynamic relationship, the change characteristics of each initial state parameter to be regulated after the energy-saving control parameter are predicted, and a predicted control change sequence of each initial state parameter to be regulated is constructed, laying the foundation for the subsequent determination of the preferred combination of state parameters to be regulated and the first state parameter to be regulated, thereby improving energy-saving efficiency.

[0028] In this embodiment, the preferred combination of state parameters to be controlled refers to the initial combination of state parameters to be controlled with the largest comprehensive control evaluation value, under the premise that the energy-saving sub-evaluation value of the screened energy-saving evaluation index is greater than the energy-saving sub-evaluation value threshold, that is, the initial combination of state parameters to be controlled with the largest control stability, the smallest control cost, and the shortest control time.

[0029] In this embodiment, by determining the preferred energy-saving control parameters, several first state parameters to be adjusted and the corresponding first values to be adjusted, an energy-saving control instruction is generated to improve the control accuracy of the energy-saving control instruction and maximize the boiler combustion energy-saving efficiency.

[0030] In some embodiments of the present application, calculating the control sub-evaluation value corresponding to the initial state parameter to be controlled based on the predicted control change sequence includes: The first preset time node at which the first predicted control value of each initial state parameter to be controlled satisfies the initial control value of the corresponding initial state parameter to be controlled is set as a characteristic time node, and a first predicted control duration is obtained according to the characteristic time node; Generate a first control evaluation value corresponding to the initial state parameter to be controlled according to the first predicted control duration; Calculating the difference between first predicted control values of adjacent preset time nodes in the first predicted control duration of the predicted control change sequence of each initial state parameter to be controlled, and generating a second control evaluation value corresponding to the initial state parameter to be controlled based on the first predicted control value difference; Calculating a first predicted control cost for each initial state parameter to be controlled in the first predicted control duration, and generating a third control evaluation value according to the first predicted control cost; A control sub-evaluation value is generated according to the first control evaluation value, the second control evaluation value and the third control evaluation value of each initial state parameter to be controlled.

[0031] In this embodiment, the longer the first prediction and control time is, the smaller the first control evaluation value is, and vice versa. The second control evaluation value is used to evaluate the degree of change of the prediction and control change sequence corresponding to the initial state parameter to be controlled, thereby evaluating the control stability of the corresponding initial state parameter to be controlled. When the degree of change of the difference between several first prediction and control values is greater, the corresponding second control evaluation value is smaller, and vice versa. When the first prediction and control cost is greater, the third control evaluation value is greater, and vice versa.

[0032] In this embodiment, by calculating the control sub-evaluation value of each initial state parameter to be controlled, a comprehensive control evaluation value of each initial state parameter combination to be controlled is obtained, which lays the foundation for the subsequent determination of the first parameter to be controlled and the corresponding first value to be controlled, thereby improving the control efficiency and energy-saving effect of the energy-saving control instruction.

[0033] In some embodiments of the present application, several real-time control value change curves are obtained, including: Setting a test period according to the optimal control duration, and setting a number of test time nodes in the test period based on a weight coefficient of each first state parameter to be regulated; Acquire real-time state data corresponding to the first state parameter to be regulated based on the inspection time node, and obtain the real-time regulation value at each inspection time node; A real-time control value variation curve corresponding to the first state parameter to be regulated is generated according to the real-time control value at a plurality of inspection time nodes corresponding to the current first state parameter to be regulated.

[0034] In this embodiment, the inspection period refers to 1 / 2 of the optimal control time length, the real-time status data refers to the real-time data of the first state parameter to be controlled at each inspection time node, and the real-time control value refers to the difference between the real-time status data of each inspection time node and the previous inspection time node.

[0035] In this embodiment, by determining the real-time control value change curve of each first state parameter to be controlled, the application effect of the preferred energy-saving control parameter mapped by each first state parameter to be controlled is accurately evaluated, and the deficiencies of the energy-saving control instructions are discovered and regulated in time to ensure that the energy-saving control instructions maximize the energy-saving efficiency of boiler combustion.

[0036] In some embodiments of the present application, generating a sub-application coefficient corresponding to a preferred energy-saving control parameter according to each real-time control value change curve includes: Generate a standard control value change curve corresponding to the first state parameter to be controlled according to the predicted control change sequence corresponding to each initial state parameter to be controlled in the preferred combination of state parameters to be controlled, and intercept the standard control value change curve based on the corresponding inspection time node to obtain a standard control value change curve segment; Based on the same time comparison principle, the real-time control value change curve of each first state parameter to be controlled is analyzed for similarity with the corresponding standard control value change curve segment to obtain similarity; Pre-set similarity threshold; If the similarity is less than the similarity threshold, the real-time control value change curve of the corresponding first state parameter to be controlled is extrapolated to obtain a predicted control value change curve segment of the corresponding first state parameter to be controlled in the remaining period of the optimal control time, wherein the predicted control value change curve segment includes the second predicted control value at several monitoring time nodes in the remaining period; The first monitoring time node at which the second predicted control value in the predicted control value change curve segment satisfies the first to-be-controlled value of the corresponding first to-be-controlled state parameter is set as a characteristic monitoring node, and the second predicted control duration is determined according to the characteristic monitoring node; Calculating a plurality of second predicted control value differences and a second predicted control cost in a second predicted control duration of the first state parameter to be controlled; Generate a first sub-application coefficient according to a difference between a second predicted control duration and a first predicted control duration for the same state parameter to be controlled; Generate a predicted degree of fluctuation according to a plurality of second predicted control value differences, and generate a second sub-application coefficient according to a difference between the predicted degree of fluctuation and a predicted degree of fluctuation of a preset degree of fluctuation threshold; generating a third sub-application coefficient according to a predicted control cost difference between a second predicted control cost and a first predicted control cost of the same state parameter to be controlled; Generate a sub-application coefficient of the preferred energy-saving control parameter mapped to the first state parameter to be regulated according to the first sub-application coefficient, the second sub-application coefficient, and the third sub-application coefficient; When the similarity is less than the similarity threshold, the calculation formula of the sub-application coefficient Y1 is: ; Among them, z1 is the first sub-application conversion coefficient, a1 is the weight coefficient of the first sub-application coefficient, is the predicted control time difference, z2 is the second sub-application conversion coefficient, a2 is the weight coefficient of the second sub-application coefficient, is the predicted volatility difference, z3 is the third sub-application conversion coefficient, a3 is the weight coefficient of the third sub-application coefficient, To predict the difference in regulatory costs; If the similarity is greater than the similarity threshold, generating a sub-application coefficient of the preferred energy-saving control parameter mapped to the first state parameter to be regulated according to the similarity; When the similarity is greater than the similarity threshold, the calculation formula of the sub-application coefficient Y2 is: ; Where z4 is the fourth sub-application conversion coefficient, n is the number of test time nodes in the test period, is the difference in the curve value at the i-th test time node, is the difference in the slope of the curve at the i-th test time node, is the difference in curve shape between the i-th inspection time node and the previous inspection time node, x1 is the first similarity conversion coefficient, c1 is the weight coefficient of the curve value difference, x2 is the second similarity conversion coefficient, c2 is the weight coefficient of the curve slope difference, x3 is the third similarity conversion coefficient, c3 is the weight coefficient of the curve shape difference, and d0 is the similarity threshold.

[0037] In this embodiment, similarity analysis refers to the predicted control value differences, slope differences and shape differences between adjacent inspection time nodes at multiple inspection time nodes between the real-time control value change curve of each first state parameter to be controlled and the corresponding standard control value change curve segment, that is, the curve value difference, curve slope difference and curve shape difference. When the curve value difference, curve slope difference and curve shape difference are greater, the corresponding similarity is smaller, and vice versa. When the similarity is greater than the similarity threshold, it means that the first state parameter to be controlled changes according to the standard control value change curve. The greater the similarity, the larger the corresponding sub-application coefficient.

[0038] In this embodiment, when the similarity is less than the similarity threshold, the predicted control value change curve segment of the corresponding first state parameter to be controlled after the inspection period in the optimal control time is obtained, and the first sub-application coefficient, the second sub-application coefficient and the third sub-application coefficient are generated respectively according to the second predicted control time, the second predicted control cost and the predicted fluctuation degree. When the difference in the predicted control time, the predicted control cost and the predicted fluctuation degree is greater, the corresponding first sub-application coefficient, the second sub-application coefficient and the third sub-application coefficient are smaller, that is, the sub-application coefficient is smaller, and vice versa.

[0039] In this embodiment, the sub-application coefficient of the preferred energy-saving control parameter mapped to each first state parameter to be regulated is determined through the similarity comparison result, which lays the foundation for the subsequent evaluation of the comprehensive application effect of the energy-saving control instruction, timely discovers and adjusts the energy-saving control instruction, realizes the energy-saving optimization of the boiler combustion in the thermal power plant, and ensures the maximization of the energy-saving efficiency of the boiler combustion.

[0040] In some embodiments of the present application, a comprehensive application coefficient of an energy-saving control instruction is generated based on a plurality of sub-application coefficients, including: Obtaining the sub-application coefficient of the first state parameter to be regulated mapped to the same preferred energy-saving control parameter and the weight coefficient corresponding to the first state parameter to be regulated, and calculating the weighted average to obtain the average of the sub-application coefficients of each preferred energy-saving control parameter; The comprehensive application coefficient of the corresponding energy-saving control instruction is generated according to the average value of the sub-application coefficients of several preferred energy-saving control parameters in the energy-saving control instruction.

[0041] In some embodiments of the present application, determining whether to modify the energy-saving control instruction based on the comprehensive application coefficient, and if so, screening out a second state parameter to be regulated and determining a second value to be regulated includes: Pre-set comprehensive application coefficient threshold; If the comprehensive application coefficient is greater than the comprehensive application coefficient threshold, the energy-saving control instruction is not corrected; If the comprehensive application coefficient is less than the comprehensive application coefficient threshold, the energy-saving control instruction is modified; Comparing the sub-application coefficients of the first state parameter to be regulated mapped to the plurality of preferred energy-saving control parameters in the energy-saving control instruction with a preset sub-application coefficient threshold, screening out the first state parameter to be regulated whose sub-application coefficient is less than the preset sub-application coefficient threshold and setting it as the second state parameter to be regulated, and generating a second value to be regulated for the second state parameter to be regulated according to the difference in the sub-application coefficients; Based on the energy-saving evaluation index to which the second parameter to be regulated belongs, a corresponding energy-saving control strategy reference library is determined, and the second state parameter to be regulated and the corresponding second value to be regulated are analyzed, and an energy-saving control optimization instruction is generated according to the analysis result.

[0042] In some embodiments of the present application, Figure 2 As shown, it also includes an energy-saving optimization system for thermal power plant boilers: a collection module for collecting a plurality of real-time boiler combustion state parameters at a real-time monitoring time node, determining whether an energy-saving control instruction is triggered based on the plurality of real-time boiler combustion state parameters, and if so, generating an energy-saving control instruction, the energy-saving control instruction including a plurality of preferred energy-saving control parameters, a plurality of first state parameters to be regulated, and corresponding first values to be regulated; An inspection module is used to pre-set an inspection period and several inspection time nodes, obtain real-time state data of several first state parameters to be regulated based on the inspection time nodes, and perform curve fitting to obtain several real-time regulation value change curves; A calculation module, configured to generate a sub-application coefficient corresponding to the optimal energy-saving control parameter according to each real-time control value change curve, and generate a comprehensive application coefficient of the energy-saving control instruction according to a plurality of sub-application coefficients; The optimization module is used to determine whether to modify the energy-saving control instruction based on the comprehensive application coefficient. If so, the second state parameter to be adjusted is screened out and the second value to be adjusted is determined, and the energy-saving control optimization instruction is generated based on the second state parameter to be adjusted and the second value to be adjusted.

[0043] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and replacements can be made without departing from the technical principles of the present application. These improvements and replacements should also be regarded as the scope of protection of the present application.

Claims

1. A method for optimizing energy conservation of a thermal power plant boiler, characterized in that: include: collecting a number of real-time boiler combustion state parameters at a real-time monitoring time node, determining whether an energy-saving control instruction is triggered based on the number of real-time boiler combustion state parameters, and if so, generating an energy-saving control instruction, the energy-saving control instruction including a number of preferred energy-saving control parameters, a number of first state parameters to be adjusted, and corresponding first values to be adjusted; Presetting an inspection period and several inspection time nodes, acquiring real-time state data of several first state parameters to be regulated based on the inspection time nodes and performing curve fitting to obtain several real-time regulation value change curves; Generate a sub-application coefficient corresponding to the optimal energy-saving control parameter according to each real-time control value change curve, and generate a comprehensive application coefficient of the energy-saving control instruction according to several sub-application coefficients; Determine whether to modify the energy-saving control instruction based on the comprehensive application coefficient. If so, filter out the second state parameter to be adjusted and determine the second value to be adjusted. Generate the energy-saving control optimization instruction based on the second state parameter to be adjusted and the second value to be adjusted.

2. The energy-saving optimization method for a thermal power plant boiler according to claim 1, characterized in that: Determine whether to trigger energy-saving control instructions based on several real-time boiler combustion status parameters, including: Pre-set several energy-saving evaluation indicators; Calculating the correlation degree between each real-time boiler combustion state parameter and each energy-saving evaluation index, and determining the associated boiler combustion state parameter of each energy-saving evaluation index according to the correlation degree; Compare the boiler combustion state parameters associated with each energy-saving evaluation index with the corresponding standard combustion state parameters, and generate an energy-saving sub-evaluation value of the corresponding energy-saving evaluation index based on the comparison result and the weight coefficient of the corresponding associated boiler combustion state parameter; Generate a comprehensive energy-saving evaluation value based on the energy-saving sub-evaluation values of several energy-saving evaluation indicators and corresponding weight coefficients; Pre-set energy-saving evaluation value threshold; If the comprehensive energy-saving evaluation value is less than the energy-saving evaluation value threshold, it is determined that the energy-saving control instruction is triggered.

3. The energy-saving optimization method for a thermal power plant boiler according to claim 2, characterized in that: The energy-saving control instruction includes a plurality of first state parameters to be regulated and corresponding first values to be regulated, including: When it is determined that an energy-saving control instruction is triggered, the optimal control duration of the energy-saving control instruction is set and energy-saving evaluation indicators with energy-saving sub-evaluation values less than the energy-saving sub-evaluation value threshold are selected; Determine several initial state parameters to be regulated for the selected energy-saving evaluation indicators based on the comparison results of the associated boiler combustion state parameters in the selected energy-saving evaluation indicators and the corresponding standard combustion state parameters; Combining a plurality of initial state parameters to be regulated according to the energy-saving sub-evaluation value differences of the screened energy-saving evaluation indicators to obtain a plurality of initial state parameter combinations to be regulated, wherein each initial state parameter combination to be regulated includes at least one initial state parameter to be regulated, and each initial state parameter to be regulated is mapped to a corresponding initial value to be regulated; Constructing an energy-saving control strategy reference library for each energy-saving evaluation index, wherein the energy-saving control strategy reference library includes preset control values of boiler combustion state parameters associated with the corresponding energy-saving evaluation index, and each preset control value is mapped to a corresponding preset energy-saving control parameter; Compare and analyze the energy-saving control strategy reference library with the initial state parameters to be regulated in each initial state parameter combination and the mapped initial state parameter values to be regulated, and construct an energy-saving control strategy corresponding to the initial state parameter combination to be regulated using the preset energy-saving control parameters with the smallest difference in the state parameter values to be regulated for the same associated boiler combustion state parameter; Based on the historical dynamic relationship between the energy-saving control strategy, the initial state parameters to be regulated in the corresponding initial state parameter combination to be regulated, and the mapped initial state values to be regulated, each initial state parameter to be regulated in the corresponding initial state parameter combination to be regulated is predicted to obtain a plurality of first predicted control values for each initial state parameter to be regulated; Establishing a time reference line according to the optimal control duration, setting a number of preset time nodes according to a preset time interval, performing time mapping based on the number of preset time nodes and a number of first predicted control values, and obtaining a predicted control change sequence corresponding to the initial state parameter to be controlled according to the mapping result; Calculating the control sub-evaluation value of the corresponding initial state parameter to be controlled according to the predicted control change sequence, and generating a comprehensive control evaluation value according to the control sub-evaluation value of each initial state parameter to be controlled in the same combination of initial state parameters to be controlled; The initial state parameter combination to be regulated and the corresponding energy-saving control strategy with the largest comprehensive regulation evaluation value are set as the preferred state parameter combination to be regulated and the corresponding preferred energy-saving control strategy corresponding to the selected energy-saving evaluation index; Each initial state parameter to be regulated and the corresponding initial value to be regulated in the selected preferred state parameter combination to be regulated of the energy-saving evaluation index are set as a plurality of first state parameters to be regulated and the corresponding first values to be regulated, and a weight coefficient of the first state parameter to be regulated is set according to the regulation sub-evaluation value; Setting the energy-saving control parameters involved in the preferred energy-saving control strategy corresponding to the preferred combination of state parameters to be regulated to a plurality of preferred energy-saving control parameters; The preferred energy-saving control parameter is mapped one-to-one with the first state parameter to be regulated and the corresponding first value to be regulated.

4. The energy-saving optimization method for a thermal power plant boiler according to claim 3, characterized in that: Calculate the control sub-evaluation value corresponding to the initial state parameter to be controlled according to the predicted control change sequence, including: The first preset time node at which the first predicted control value of each initial state parameter to be controlled satisfies the initial control value of the corresponding initial state parameter to be controlled is set as a characteristic time node, and a first predicted control duration is obtained according to the characteristic time node; Generate a first control evaluation value corresponding to the initial state parameter to be controlled according to the first predicted control duration; Calculating the difference between first predicted control values of adjacent preset time nodes in the first predicted control duration of the predicted control change sequence of each initial state parameter to be controlled, and generating a second control evaluation value corresponding to the initial state parameter to be controlled based on the first predicted control value difference; Calculating a first predicted control cost for each initial state parameter to be controlled in the first predicted control duration, and generating a third control evaluation value according to the first predicted control cost; A control sub-evaluation value is generated according to the first control evaluation value, the second control evaluation value and the third control evaluation value of each initial state parameter to be controlled.

5. The energy-saving optimization method for a thermal power plant boiler according to claim 4, characterized in that: Several real-time control value change curves are obtained, including: Setting a test period according to the optimal control duration, and setting a number of test time nodes in the test period based on a weight coefficient of each first state parameter to be regulated; Acquire real-time state data corresponding to the first state parameter to be regulated based on the inspection time node, and obtain the real-time regulation value at each inspection time node; A real-time control value variation curve corresponding to the first state parameter to be regulated is generated according to the real-time control value at a plurality of inspection time nodes corresponding to the current first state parameter to be regulated.

6. The energy-saving optimization method for a thermal power plant boiler according to claim 5, characterized in that: Generate the sub-application coefficient of the corresponding optimal energy-saving control parameter according to each real-time control value change curve, including: Generate a standard control value change curve corresponding to the first state parameter to be controlled according to the predicted control change sequence corresponding to each initial state parameter to be controlled in the preferred combination of state parameters to be controlled, and intercept the standard control value change curve based on the corresponding inspection time node to obtain a standard control value change curve segment; Based on the same time comparison principle, the real-time control value change curve of each first state parameter to be controlled is analyzed for similarity with the corresponding standard control value change curve segment to obtain similarity; Pre-set similarity threshold; If the similarity is less than the similarity threshold, the real-time control value change curve of the corresponding first state parameter to be controlled is extrapolated to obtain a predicted control value change curve segment of the corresponding first state parameter to be controlled in the remaining period of the optimal control time, wherein the predicted control value change curve segment includes the second predicted control value at several monitoring time nodes in the remaining period; The first monitoring time node at which the second predicted control value in the predicted control value change curve segment satisfies the first to-be-controlled value of the corresponding first to-be-controlled state parameter is set as a characteristic monitoring node, and the second predicted control duration is determined according to the characteristic monitoring node; Calculating a plurality of second predicted control value differences and a second predicted control cost in a second predicted control duration of the first state parameter to be controlled; Generate a first sub-application coefficient according to a difference between a second predicted control duration and a first predicted control duration for the same state parameter to be controlled; Generate a predicted degree of fluctuation according to a plurality of second predicted control value differences, and generate a second sub-application coefficient according to a difference between the predicted degree of fluctuation and a predicted degree of fluctuation of a preset degree of fluctuation threshold; generating a third sub-application coefficient according to a predicted control cost difference between a second predicted control cost and a first predicted control cost of the same state parameter to be controlled; Generate a sub-application coefficient of the preferred energy-saving control parameter mapped to the first state parameter to be regulated according to the first sub-application coefficient, the second sub-application coefficient, and the third sub-application coefficient; When the similarity is less than the similarity threshold, the calculation formula of the sub-application coefficient Y1 is: ； Among them, z1 is the first sub-application conversion coefficient, a1 is the weight coefficient of the first sub-application coefficient, is the predicted control time difference, z2 is the second sub-application conversion coefficient, a2 is the weight coefficient of the second sub-application coefficient, is the predicted volatility difference, z3 is the third sub-application conversion coefficient, a3 is the weight coefficient of the third sub-application coefficient, To predict the difference in regulatory costs; If the similarity is greater than the similarity threshold, generating a sub-application coefficient of the preferred energy-saving control parameter mapped to the first state parameter to be regulated according to the similarity; When the similarity is greater than the similarity threshold, the calculation formula of the sub-application coefficient Y2 is: ； Where z4 is the fourth sub-application conversion coefficient, n is the number of test time nodes in the test period, is the difference in the curve value at the i-th test time node, is the difference in the slope of the curve at the i-th test time node, is the difference in curve shape between the i-th inspection time node and the previous inspection time node, x1 is the first similarity conversion coefficient, c1 is the weight coefficient of the curve value difference, x2 is the second similarity conversion coefficient, c2 is the weight coefficient of the curve slope difference, x3 is the third similarity conversion coefficient, c3 is the weight coefficient of the curve shape difference, and d0 is the similarity threshold.

7. The energy-saving optimization method for a thermal power plant boiler according to claim 5, characterized in that: Generate a comprehensive application coefficient for energy-saving control instructions based on several sub-application coefficients, including: Obtaining the sub-application coefficient of the first state parameter to be regulated mapped to the same preferred energy-saving control parameter and the weight coefficient corresponding to the first state parameter to be regulated, and calculating the weighted average to obtain the average of the sub-application coefficients of each preferred energy-saving control parameter; The comprehensive application coefficient of the corresponding energy-saving control instruction is generated according to the average value of the sub-application coefficients of several preferred energy-saving control parameters in the energy-saving control instruction.

8. The energy-saving optimization method for a thermal power plant boiler according to claim 7, characterized in that: Determining whether to modify the energy-saving control instruction based on the comprehensive application coefficient, and if so, selecting a second state parameter to be regulated and determining a second value to be regulated, including: Pre-set comprehensive application coefficient threshold; If the comprehensive application coefficient is greater than the comprehensive application coefficient threshold, the energy-saving control instruction is not corrected; If the comprehensive application coefficient is less than the comprehensive application coefficient threshold, the energy-saving control instruction is modified; Comparing the sub-application coefficients of the first state parameter to be regulated mapped to the plurality of preferred energy-saving control parameters in the energy-saving control instruction with a preset sub-application coefficient threshold, screening out the first state parameter to be regulated whose sub-application coefficient is less than the preset sub-application coefficient threshold and setting it as the second state parameter to be regulated, and generating a second value to be regulated for the second state parameter to be regulated according to the difference in the sub-application coefficients; Based on the energy-saving evaluation index to which the second parameter to be regulated belongs, a corresponding energy-saving control strategy reference library is determined, and the second state parameter to be regulated and the corresponding second value to be regulated are analyzed, and an energy-saving control optimization instruction is generated according to the analysis result.

9. An energy-saving optimization system for a thermal power plant boiler, characterized in that: include: a collection module for collecting a plurality of real-time boiler combustion state parameters at a real-time monitoring time node, determining whether an energy-saving control instruction is triggered based on the plurality of real-time boiler combustion state parameters, and if so, generating an energy-saving control instruction, the energy-saving control instruction including a plurality of preferred energy-saving control parameters, a plurality of first state parameters to be regulated, and corresponding first values to be regulated; An inspection module is used to pre-set an inspection period and several inspection time nodes, obtain real-time state data of several first state parameters to be regulated based on the inspection time nodes, and perform curve fitting to obtain several real-time regulation value change curves; A calculation module, configured to generate a sub-application coefficient corresponding to the optimal energy-saving control parameter according to each real-time control value change curve, and generate a comprehensive application coefficient of the energy-saving control instruction according to a plurality of sub-application coefficients; The optimization module is used to determine whether to modify the energy-saving control instruction based on the comprehensive application coefficient. If so, the second state parameter to be adjusted is screened out and the second value to be adjusted is determined, and the energy-saving control optimization instruction is generated based on the second state parameter to be adjusted and the second value to be adjusted.

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