Anti-balance coal consumption testing method and system

Abstract

The invention relates to the technical field of coal consumption testing, in particular to an anti-balance coal consumption testing method and system. Comprising the steps of setting a coal consumption period and a plurality of operation indexes according to an anti-balance coal consumption model; generating a disturbance evaluation value of each operation index, and setting a monitoring parameter of each operation index according to all the disturbance evaluation values; acquiring a first-level reference value of each operation index in a single coal consumption period, and generating coal consumption in the single coal consumption period according to a preset correction model and all the first-level reference values; corresponding deviation correction strategies are set according to different operation indexes, disturbance of environment parameter fluctuation to all the operation indexes is avoided by dynamically adjusting compensation coefficients of all the operation indexes, corresponding correction coefficients are set according to the confidence degree of collected data of all the operation indexes, multi-stage correction of all the operation indexes is achieved, and the correction accuracy of all the operation indexes is improved. The calculation precision of counter-balance coal consumption is ensured, and the overall operation and maintenance efficiency of a power plant is improved.

Description

Technical Field

[0001] The present application relates to the technical field of coal consumption testing, and in particular to a counter-balance coal consumption testing method and system. Background Art

[0002] Power supply coal consumption is an important economic indicator for thermal power companies. The daily calculation and statistical results of power supply coal consumption not only directly reflect the company's precise management level, but also play an important role in grasping the operating status of the unit, guiding the further optimization of the unit operation, and improving the economic benefits of the power plant.

[0003] At present, each plant adopts the principle of "positive balance assessment and negative balance verification" to calculate the coal consumption of power generation and supply of units. In actual statistics, the negative balance calculation can be specific to each energy distribution and loss, which is convenient for energy consumption diagnosis, but its calculation is complicated, and the results are affected by factors such as pressure / temperature parameters, abnormal operating conditions, and flow measurement values, and the accuracy is low. Summary of the invention

[0004] The purpose of this application is: to solve the above-mentioned technical problems, this application provides a counter-balance coal consumption testing method and system, aiming to improve the calculation accuracy of counter-balance coal consumption and improve the operation and maintenance efficiency of power plants.

[0005] In some embodiments of the present application, multiple operating indicators are generated according to the parameters in the counter-balanced coal consumption model, and accurate monitoring of each operating indicator is achieved by dynamically adjusting the monitoring parameters of each operating indicator, thereby improving the calculation accuracy of the counter-balanced coal consumption and improving the overall operation and maintenance efficiency of the power plant.

[0006] In some embodiments of the present application, corresponding correction strategies are set according to different operating indicators, and the disturbance of each operating indicator due to fluctuations in environmental parameters is avoided by dynamically adjusting the compensation coefficient of each operating indicator. The corresponding correction coefficient is set according to the confidence level of the collected data of each operating indicator, so as to realize multi-level correction of each operating indicator, ensure the calculation accuracy of the counter-balanced coal consumption, and improve the overall operation and maintenance efficiency of the power plant.

[0007] In some embodiments of the present application, a counter-balanced coal consumption test method is provided, comprising: Set coal consumption cycle and multiple operation indicators according to the counter-balance coal consumption model; Generate disturbance evaluation values ​​for each operating indicator, and set monitoring parameters for each operating indicator based on all disturbance evaluation values; Obtain the primary reference value of each operating indicator in a single coal consumption cycle, and generate the coal consumption in a single coal consumption cycle based on the preset correction model and all the primary reference values; Among them, when setting multiple operating indicators, including: Establish the running index sequence A, A=(a1,a2…a i…a n ), where ai is the i-th operating indicator and n is the number of operating indicators.

[0008] In some embodiments of the present application, generating disturbance evaluation values ​​of various operating indicators includes: According to the running index sequence A, set a i Run metrics for goals; Set multiple disturbance indicators of target operating indicators; Generate the volatility evaluation value of each disturbance indicator based on historical parameters; Establish a series of fluctuation evaluation values ​​C, C=(c1, c2…c i …c θ ), where θ is the number of disturbance indicators; ci is the fluctuation evaluation value of the i-th indicator; Generate a disturbance evaluation value of the target operation index according to the fluctuation evaluation value sequence C; Generate disturbance evaluation values ​​of various operating indicators in sequence; Establish the disturbance evaluation value series B=(b1,b2…b i …b n ), where b i is the disturbance evaluation value of the i-th operating indicator.

[0009] In some embodiments of the present application, the disturbance evaluation value of the target operation index includes: b=e1*Q1*[ η i *c i ]+e2*Q2*U; Wherein, b is the disturbance evaluation value of the target operation index; e1 is the preset first weight coefficient; e2 is the preset second weight coefficient; Q1 is the preset first fixed coefficient; Q2 is the preset second fixed coefficient; η i is the influencing factor of the i-th disturbance index; U is the reference value of the influence degree of the target operation index.

[0010] In some embodiments of the present application, when the monitoring parameters of various operating indicators are set according to all disturbance evaluation values, it includes: Set multiple related indicators of target operation indicators; Establish the correlation index series T, T=(t1, t2…t i …t m ), where t i is the i-th associated indicator of the target operation indicator; m is the number of associated indicators of the target operation indicator; Obtain the disturbance evaluation value b of the target operation index; The data collection amount k in a single coal consumption cycle is set according to the disturbance evaluation value b; Preset a first disturbance evaluation value threshold B1 and a second disturbance evaluation value threshold B2; Set the data acquisition amount of each operation index according to the disturbance evaluation value sequence B in turn; If b < B1, set the data acquisition amount k as the preset first data acquisition amount K1, that is, k = K1; If B1 ≤ b < B2, set the data acquisition amount k as the preset second data acquisition amount K2, that is, k = K2; If b ≥ B2, set the data acquisition amount k of the i-th operation index as the preset third data acquisition amount K3, that is, k = K3; and K1 < K2 < K3; Set the monitoring parameters of the target operation index according to the data acquisition amount k and the associated index sequence T; Set the monitoring parameters of each operation index in turn.

[0011] In some embodiments of the present application, when obtaining the first-level reference value of each operation index within a single coal consumption cycle, it includes: Obtain the monitoring data packet of the target operation index within the current coal consumption cycle; Generate the confidence evaluation value of each associated index in the associated index sequence T according to the monitoring data packet; Establish a confidence evaluation value sequence G, G=(g1, g2…g i …g m ), where g i is the confidence evaluation value of t i within the current coal consumption cycle; Judge whether to correct the monitoring data packet according to the confidence evaluation value sequence; Preset a first confidence value threshold G1 and a second confidence value threshold G2, and G1 < G2; If g i < G1, generate a secondary correction instruction for the i-th associated index; If G1 < g i < G2, generate a primary correction instruction for the i-th associated index; If g i > G2, do not generate a correction instruction for the i-th associated index; Generate the real-time monitoring value of each associated index according to the correction result, and generate the first-level reference value of the target operation index; Generate the first-level reference value of each operation index within the current coal consumption cycle in turn.

[0012] In some embodiments of the present application, when establishing the confidence evaluation value sequence G, it includes: Set t i as the target associated index in turn according to the associated index sequence T Obtain all the collected values of the target associated index according to the monitoring data packet; Generate a confidence evaluation value g of the target association index; g=Y*[ (j i -j') 2 ]; Where, Y is the conversion coefficient; j i is the i-th collection value of the target-related indicator; j' is the average value of all collection values ​​of the target-related indicator; k is the data collection amount of the target operation indicator; Generate confidence evaluation values ​​for each associated indicator in turn.

[0013] In some embodiments of the present application, when the correction model is preset, it includes: Establish multiple disturbance scenarios based on all disturbance indicators corresponding to the calculation model of the target operation indicator; Generate compensation coefficients for each disturbance scenario based on historical parameters; Establish a disturbance scenario-compensation coefficient mapping table for target operating indicators; Generate disturbance scenario-compensation coefficient mapping tables for each operating indicator in turn; A correction model is constructed based on the mapping table of all disturbance scenarios and compensation coefficients.

[0014] In some embodiments of the present application, when the coal consumption in a single coal consumption cycle is generated according to the preset correction model and all primary reference values, it includes: Obtain the primary reference values ​​of various operating indicators in the current coal consumption cycle; Establish a first-level reference value series F, F=(f1, f2…f i …f n ), where f i is the primary reference value of the ith operating index in the current coal consumption cycle; Generate compensation coefficients for various operating indicators in the current coal consumption cycle according to the correction model; Establish compensation coefficient series R, R=(r1, r2…r i …r n ), where ri is the compensation coefficient of the ith operating index in the current coal consumption cycle; Generate secondary reference values ​​for each operating indicator within the current coal consumption cycle; h i =r i *β i *f i ; Among them, β i is the correction coefficient set based on the confidence evaluation value series of the ith operating indicator in the current coal consumption cycle; is the secondary reference value of the ith operating indicator in the current coal consumption cycle; The coal consumption in the current coal consumption cycle is generated based on all secondary reference values ​​and the counter-balance coal consumption model.

[0015] In some embodiments of the present application, when establishing the compensation coefficient sequence R, it includes: Obtain feedback data within the current coal consumption cycle; Generate the real-time values ​​of all disturbance indicators corresponding to the calculation model of the target operation indicator according to the feedback data; Select the target disturbance scenario of the target operation index according to the real-time values ​​of all disturbance indexes; Set the compensation coefficient r of the target operation index according to the target disturbance scenario; Set the compensation coefficient of each operating indicator in turn.

[0016] In some embodiments of the present application, a counter-balance coal consumption test system is provided, comprising: The first processing module is used to set the coal consumption cycle and multiple operation indicators according to the anti-balance coal consumption model; The second processing module is used to generate a disturbance evaluation value of each operating indicator and set the monitoring parameters of each operating indicator according to all the disturbance evaluation values; The third processing module is used to obtain the primary reference value of each operating indicator in a single coal consumption cycle, and generate the coal consumption in a single coal consumption cycle according to the preset correction model and all the primary reference values; The first processing module is also used to establish an operation index sequence A, A=(a1, a2…a i …a n ), where ai is the i-th operating indicator; n is the number of operating indicators; The second processing module is also used to set a according to the operation index sequence A in sequence i Run metrics for goals; Set multiple disturbance indicators of target operating indicators; Generate the volatility evaluation value of each disturbance indicator based on historical parameters; Establish a series of fluctuation evaluation values ​​C, C=(c1, c2…c i …c θ ), where θ is the number of disturbance indicators; ci is the fluctuation evaluation value of the i-th indicator; Generate a disturbance evaluation value of the target operation index according to the fluctuation evaluation value sequence C; Generate disturbance evaluation values ​​of various operating indicators in sequence; Establish the disturbance evaluation value series B=(b1,b2…b i …b n ), where b i is the disturbance evaluation value of the i-th operating indicator.

[0017] Compared with the prior art, the counter-balance coal consumption test method and system of the present application embodiment has the following beneficial effects: Multiple operating indicators are generated according to the parameters in the counter-balanced coal consumption model, and accurate monitoring of each operating indicator is achieved by dynamically adjusting the monitoring parameters of each operating indicator, thereby improving the calculation accuracy of the counter-balanced coal consumption and improving the overall operation and maintenance efficiency of the power plant.

[0018] Corresponding correction strategies are set according to different operating indicators. The compensation coefficients of various operating indicators are dynamically adjusted to avoid disturbances to various operating indicators caused by fluctuations in environmental parameters. Corresponding correction coefficients are set according to the confidence level of the collected data of each operating indicator to achieve multi-level correction of each operating indicator, ensure the calculation accuracy of the counter-balanced coal consumption, and improve the overall operation and maintenance efficiency of the power plant. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a flow chart of a counter-balance coal consumption test method in a preferred embodiment of the present application. DETAILED DESCRIPTION

[0020] The specific implementation methods of the present application are further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present application but are not intended to limit the scope of the present application.

[0021] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present 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 should not be understood as a limitation on the present application.

[0022] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0023] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0024] like Figure 1 As shown, a counter-balanced coal consumption test method of a preferred embodiment of the present application includes: S101: setting a coal consumption cycle and multiple operation indicators according to a counter-balance coal consumption model; S102: generating disturbance evaluation values ​​of various operation indicators, and setting monitoring parameters of various operation indicators according to all disturbance evaluation values; S103: obtaining the primary reference value of each operating indicator in a single coal consumption cycle, and generating the coal consumption in the single coal consumption cycle according to a preset correction model and all the primary reference values; Among them, when setting multiple operating indicators, including: Establish the running index sequence A, A=(a1,a2…a i …a n ), where ai is the i-th operating indicator and n is the number of operating indicators.

[0025] Specifically, a plurality of operating indicators are set according to the parameters contained in the calculation formula of the counter-balance coal consumption model, and the operating indicators include but are not limited to parameters such as steam turbine heat consumption rate, pipeline efficiency, boiler efficiency, and plant power consumption rate.

[0026] Specifically, the disturbance evaluation values ​​of various operating indicators are generated, including: According to the running index sequence A, set a i Run metrics for goals; Set multiple disturbance indicators of target operating indicators; Generate the volatility evaluation value of each disturbance indicator based on historical parameters; Establish a series of fluctuation evaluation values ​​C, C=(c1, c2…c i …c θ ), where θ is the number of disturbance indicators; ci is the fluctuation evaluation value of the i-th indicator; Generate a disturbance evaluation value of the target operation index according to the fluctuation evaluation value sequence C; Generate disturbance evaluation values ​​of various operating indicators in sequence; Establish the disturbance evaluation value series B=(b1,b2…b i …b n), where b i is the disturbance evaluation value of the i-th operating indicator.

[0027] Specifically, the disturbance indexes corresponding to different operating indicators are also different, and the disturbance indexes can be set according to historical operating parameters. For example, the heat consumption rate of the steam turbine and the efficiency of the boiler are disturbed by parameters such as temperature and pressure.

[0028] Specifically, the greater the fluctuation evaluation value, the less likely it is that the current disturbance index is in a stable state, which makes the monitoring value of the target operation index more likely to have an error.

[0029] Specifically, the disturbance evaluation value of the target operation index is generated, including: b=e1*Q1*[ η i *c i ]+e2*Q2*U; Wherein, b is the disturbance evaluation value of the target operation index; e1 is the preset first weight coefficient; e2 is the preset second weight coefficient; Q1 is the preset first fixed coefficient; Q2 is the preset second fixed coefficient; η i is the influencing factor of the i-th disturbance index; U is the reference value of the influence degree of the target operation index.

[0030] Specifically, all parameters in the model are normalized by presetting the first fixed coefficient and the second fixed coefficient, so that each parameter is within the same value range.

[0031] Specifically, when an error occurs in the target operating indicator, the greater the impact on the final calculation result of the counter-balanced coal consumption model, the greater the corresponding impact reference value U.

[0032] Specifically, the larger the disturbance evaluation value is, the greater the impact of environmental parameters on the target operating index during the calculation process, and the greater the possibility of calculation errors.

[0033] Specifically, when setting the monitoring parameters of various operating indicators according to the total disturbance evaluation values, it includes: Set multiple related indicators of target operation indicators; Establish the correlation index series T, T=(t1, t2…t i …t m ), where t i is the i-th associated indicator of the target operation indicator; m is the number of associated indicators of the target operation indicator; Obtain the disturbance evaluation value b of the target operation index; The data collection amount k in a single coal consumption cycle is set according to the disturbance evaluation value b; Preset the first disturbance evaluation value threshold B1 and the second disturbance evaluation value threshold B2; Set the data acquisition amount of each operation index in sequence according to the disturbance evaluation value sequence B; If b < B1, set the data acquisition amount k as the preset first data acquisition amount K1, that is, k = K1; If B1 ≤ b < B2, set the data acquisition amount k as the preset second data acquisition amount K2, that is, k = K2; If b ≥ B2, set the data acquisition amount k of the i-th operation index as the preset third data acquisition amount K3, that is, k = K3; and K1 < K2 < K3; Set the monitoring parameters of the target operation index according to the data acquisition amount k and the associated index sequence T; Set the monitoring parameters of each operation index in sequence.

[0034] Specifically, the associated index refers to the parameters in the calculation formula of the target operation index, that is, the data types that need to be monitored; for example, the calculation of the turbine heat rate and the boiler efficiency requires the use of pressure, temperature, and flow rate. The flow rate includes but is not limited to: main steam flow rate, feed water flow rate, superheater desuperheating water flow rate, reheater desuperheating water flow rate, reheated steam flow rate, boiler blowdown flow rate, steam flow rate for soot blowing, and other parameters.

[0035] Specifically, according to the data acquisition amount of the target operation index, set multiple monitoring points of each associated index in sequence, collect multiple groups of data for each associated index at the same time, so as to generate the corresponding monitoring data packet, and calibrate the monitoring data of each associated index in sequence, so as to improve the monitoring accuracy of the target operation index.

[0036] It can be understood that in the above embodiments, multiple operation indexes are generated according to the parameters in the inverse balance coal consumption model, a multi-level test model is constructed, and by dynamically adjusting the monitoring parameters of each operation index, the accurate monitoring of each operation index is realized, so as to improve the calculation accuracy of the inverse balance coal consumption and improve the overall operation and maintenance efficiency of the power plant.

[0037] In the preferred embodiment of the embodiment of the present application, when obtaining the first-level reference value of each operation index within a single coal consumption cycle, it includes: Obtain the monitoring data packet of the target operation index within the current coal consumption cycle; Generate the confidence evaluation value of each associated index in the associated index sequence T according to the monitoring data packet; Establish a confidence evaluation value sequence G, G = (g1, g2…g i …g m ), where g i is the confidence evaluation value of t i within the current coal consumption cycle; Judge whether to correct the monitoring data packet according to the confidence evaluation value sequence; Preset a first confidence value threshold G1 and a second confidence value threshold G2, and G1 < G2; If g i < G1, generate a secondary correction instruction for the i-th associated indicator; If G1 < g i < G2, generate a primary correction instruction for the i-th associated indicator; If g i > G2, do not generate a correction instruction for the i-th associated indicator; Generate real-time monitoring values for each associated indicator according to the correction result, and generate a primary reference value for the target operation indicator; Generate primary reference values for each operation indicator in the current coal consumption cycle in sequence.

[0038] Specifically, when establishing the confidence evaluation value sequence G, it includes: Set t in sequence according to the associated indicator sequence T i as the target associated indicator Obtain all the collected values of the target associated indicator according to the monitoring data packet; Generate the confidence evaluation value g of the target associated indicator; g = Y * (j i - j') 2 ; where Y is the conversion coefficient; j i is the i-th collected value of the target associated indicator; j' is the average value of all the collected values of the target associated indicator; k is the data collection amount of the target operation indicator; Generate the confidence evaluation values of each associated indicator in sequence.

[0039] Specifically, by presetting the conversion coefficient, the confidence evaluation values of each associated indicator are within a preset value range.

[0040] Specifically, the larger the confidence evaluation value, the higher the accuracy of the collected values of the target associated indicator.

[0041] Specifically, the primary correction instruction means that there are some distorted collected values in the current target associated indicator, which need to be剔除 in time, and the primary reference value of the target associated indicator in the current coal consumption cycle is generated according to the average value of the remaining data after剔除.

[0042] Specifically, the secondary correction instruction means that the collected values in the current target associated indicator are completely distorted and need to be collected again to avoid interfering with the accuracy of subsequent coal consumption calculations due to data collection errors.

[0043] Specifically, when no correction instruction is generated, a first-level reference value of the target-related indicator in the current coal consumption cycle is generated based on the average value of all collected values.

[0044] It can be understood that in the above embodiment, the real-time collected values ​​of all related indicators involved in the target operating indicators are preliminarily screened and calibrated, and distorted data are eliminated in time, thereby improving the accuracy of each basic data and avoiding interference with the calculation accuracy of the counter-balance coal consumption model due to data collection errors.

[0045] In a preferred embodiment of the present application, when the correction model is preset, it includes: Establish multiple disturbance scenarios based on all disturbance indicators corresponding to the calculation model of the target operation indicator; Generate compensation coefficients for each disturbance scenario based on historical parameters; Establish a disturbance scenario-compensation coefficient mapping table for target operating indicators; Generate disturbance scenario-compensation coefficient mapping tables for each operating indicator in turn; A correction model is constructed based on the mapping table of all disturbance scenarios and compensation coefficients.

[0046] Specifically, the size of the value interval of each disturbance index in the target operation index is set according to the disturbance evaluation value of the target operation index. The larger the disturbance evaluation value, the smaller the single value interval, so as to ensure the correction accuracy of the compensation coefficient for the operation index. Multiple disturbance scenarios are generated based on the random combination results of different value intervals of each disturbance index.

[0047] Specifically, by analyzing all historical operation data, the compensation coefficients of the target operation indicators under various disturbance scenarios are generated, thereby eliminating the calculation errors caused by environmental fluctuations on various operation indicators and improving the overall calculation accuracy.

[0048] Specifically, when the coal consumption in a single coal consumption cycle is generated according to the preset correction model and all primary reference values, it includes: Obtain the primary reference values ​​of various operating indicators in the current coal consumption cycle; Establish a first-level reference value series F, F=(f1, f2…f i …f n ), where f i is the primary reference value of the ith operating index in the current coal consumption cycle; Generate compensation coefficients for various operating indicators in the current coal consumption cycle according to the correction model; Establish compensation coefficient series R, R=(r1, r2…r i …r n ), where ri is the compensation coefficient of the ith operating index in the current coal consumption cycle; Generate secondary reference values ​​for each operating indicator within the current coal consumption cycle; h i =r i *β i *f i ; Among them, β i is the correction coefficient set based on the confidence evaluation value series of the ith operating indicator in the current coal consumption cycle; is the secondary reference value of the ith operating indicator in the current coal consumption cycle; The coal consumption in the current coal consumption cycle is generated based on all secondary reference values ​​and the counter-balance coal consumption model.

[0049] Specifically, when establishing the compensation coefficient sequence R, it includes: Obtain feedback data within the current coal consumption cycle; Generate the real-time values ​​of all disturbance indicators corresponding to the calculation model of the target operation indicator according to the feedback data; Select the target disturbance scenario of the target operation index according to the real-time values ​​of all disturbance indexes; Set the compensation coefficient r of the target operation index according to the target disturbance scenario; Set the compensation coefficient of each operating indicator in turn.

[0050] Specifically, based on real-time feedback data, the disturbance scenario corresponding to each operating indicator is determined, so that the corresponding compensation coefficient is selected to correct each operating indicator, thereby improving the calculation efficiency and accuracy of the counter-balance coal consumption model.

[0051] It can be understood that in the above embodiment, corresponding correction strategies are set according to different operating indicators, and the disturbance of various operating indicators due to fluctuations in environmental parameters is avoided by dynamically adjusting the compensation coefficient of each operating indicator. The corresponding correction coefficient is set according to the confidence level of the collected data of each operating indicator, so as to realize multi-level correction of each operating indicator, ensure the calculation accuracy of the counter-balanced coal consumption, and improve the overall operation and maintenance efficiency of the power plant.

[0052] Based on another preferred embodiment of a counter-balanced coal consumption test method in any of the above preferred embodiments, this preferred embodiment provides a counter-balanced coal consumption test method, including: The first processing module is used to set the coal consumption cycle and multiple operation indicators according to the anti-balance coal consumption model; The second processing module is used to generate a disturbance evaluation value of each operating indicator and set the monitoring parameters of each operating indicator according to all the disturbance evaluation values; The third processing module is used to obtain the primary reference value of each operating indicator in a single coal consumption cycle, and generate the coal consumption in a single coal consumption cycle according to the preset correction model and all the primary reference values; The first processing module is also used to establish an operation index sequence A, A=(a1, a2…a i …a n ), where ai is the i-th operating indicator; n is the number of operating indicators; The second processing module is also used to set a according to the operation index sequence A in sequence i Run metrics for goals; Set multiple disturbance indicators of target operating indicators; Generate the volatility evaluation value of each disturbance indicator based on historical parameters; Establish a series of fluctuation evaluation values ​​C, C=(c1, c2…c i …c θ ), where θ is the number of disturbance indicators; ci is the fluctuation evaluation value of the i-th indicator; Generate a disturbance evaluation value of the target operation index according to the fluctuation evaluation value sequence C; Generate disturbance evaluation values ​​of various operating indicators in sequence; Establish the disturbance evaluation value series B=(b1,b2…b i …b n ), where b i is the disturbance evaluation value of the i-th operating indicator.

[0053] According to the first concept of the present application, multiple operating indicators are generated according to the parameters in the counter-balanced coal consumption model, and accurate monitoring of each operating indicator is achieved by dynamically adjusting the monitoring parameters of each operating indicator, thereby improving the calculation accuracy of the counter-balanced coal consumption and improving the overall operation and maintenance efficiency of the power plant.

[0054] According to the second concept of the present application, corresponding correction strategies are set according to different operating indicators, and the disturbance of various operating indicators due to fluctuations in environmental parameters is avoided by dynamically adjusting the compensation coefficients of various operating indicators. Corresponding correction coefficients are set according to the confidence level of the collected data of each operating indicator, thereby realizing multi-level correction of each operating indicator, ensuring the calculation accuracy of the counter-balanced coal consumption, and improving the overall operation and maintenance efficiency of the power plant.

[0055] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and substitutions can be made without departing from the technical principles of the present application. These improvements and substitutions should also be regarded as the scope of protection of the present application.

Claims

1. A counter-balance coal consumption test method, characterized in that: Including: Setting a coal consumption period and multiple operation indicators according to the anti - balance coal consumption model; Generating disturbance evaluation values for each operation indicator, and setting monitoring parameters for each operation indicator according to all the disturbance evaluation values; Obtaining first - level reference values of each operation indicator within a single coal consumption period, and generating the coal consumption within a single coal consumption period according to a preset correction model and all the first - level reference values; Among them, when setting multiple operation indicators, it includes: Establish the running index sequence A, A=(a1,a2…a i …a n ), where ai is the i-th operating indicator and n is the number of operating indicators.

2. The counter-balance coal consumption test method according to claim 1, characterized in that: The generating of the disturbance evaluation values for each operation indicator includes: According to the running index sequence A, set a i Run metrics for goals; Setting multiple disturbance indicators for the target operation indicator; Generating fluctuation evaluation values for each disturbance indicator according to historical parameters; Establish a series of fluctuation evaluation values ​​C, C=(c1, c2…c i …c θ ), where θ is the number of disturbance indicators; ci is the fluctuation evaluation value of the i-th indicator; Generating a disturbance evaluation value for the target operation indicator according to the fluctuation evaluation value sequence C; Generating disturbance evaluation values for each operation indicator in sequence; Establish the disturbance evaluation value series B=(b1,b2…b i …b n ), where b i is the disturbance evaluation value of the i-th operating indicator.

3. The counter-balance coal consumption test method according to claim 2, characterized in that: The disturbance evaluation value of the target operation indicator includes: b=e1*Q1*[ η i *c i ]+e2*Q2*U; Wherein, b is the disturbance evaluation value of the target operation index; e1 is the preset first weight coefficient; e2 is the preset second weight coefficient; Q1 is the preset first fixed coefficient; Q2 is the preset second fixed coefficient; η i is the influencing factor of the i-th disturbance index; U is the reference value of the influence degree of the target operation index.

4. The counter-balance coal consumption test method according to claim 3, characterized in that: When setting monitoring parameters for each operation indicator according to all the disturbance evaluation values, it includes: Setting multiple associated indicators for the target operation indicator; Establish the correlation index series T, T=(t1, t2…t i …t m ), where t i is the i-th associated indicator of the target operation indicator; m is the number of associated indicators of the target operation indicator; Obtaining the disturbance evaluation value b of the target operation indicator; Setting the data acquisition amount k within a single coal consumption period according to the disturbance evaluation value b; Presetting a first disturbance evaluation value threshold B1 and a second disturbance evaluation value threshold B2; Setting the data acquisition amount for each operation indicator in sequence according to the disturbance evaluation value sequence B; If b < B1, setting the data acquisition amount k as a preset first data acquisition amount K1, that is, k = K1; If B1 ≤ b < B2, setting the data acquisition amount k as a preset second data acquisition amount K2, that is, k = K2; If b ≥ B2, setting the data acquisition amount k of the i - th operation indicator as a preset third data acquisition amount K3, that is, k = K3; and K1 < K2 < K3; Setting the monitoring parameters of the target operation indicator according to the data acquisition amount k and the associated indicator sequence T; Setting the monitoring parameters of each operation indicator in sequence.

5. The counter-balance coal consumption test method according to claim 4, characterized in that: When obtaining the first - level reference values of each operation indicator within a single coal consumption period, it includes: Obtaining the monitoring data packet of the target operation indicator within the current coal consumption period; Generating confidence evaluation values for each associated indicator in the associated indicator sequence T according to the monitoring data packet; Establish a confidence evaluation value sequence G, G=(g1,g2…g i …g m ), where g i t i Confidence evaluation value within the current coal consumption cycle; Judging whether to correct the monitoring data packet according to the confidence evaluation value sequence; Presetting a first confidence value threshold G1 and a second confidence value threshold G2, and G1 < G2; If g i <G1, generate a secondary correction instruction for the i-th associated index; If G1 < g i < G2, generate a first-level correction instruction for the i-th associated index; If g i >G2, do not generate correction instructions for the i-th associated indicator; Generating real - time monitoring values of each associated indicator according to the correction result, and generating the first - level reference value of the target operation indicator; Generating the first - level reference values of each operation indicator within the current coal consumption period in sequence.

6. The counter-balance coal consumption test method according to claim 5, characterized in that: When establishing the confidence evaluation value sequence G, it includes: According to the correlation index sequence T, set t i Associating indicators with targets Obtaining all the acquisition values of the target associated indicator according to the monitoring data packet; Generating a confidence evaluation value g of the target associated indicator; g=Y*[ (j i -j') 2 ]; Where, Y is the conversion coefficient; j i is the i-th collection value of the target-related indicator; j' is the average value of all collection values ​​of the target-related indicator; k is the data collection amount of the target operation indicator; Generating confidence evaluation values for each associated indicator in sequence.

7. The counter-balance coal consumption test method according to claim 5, characterized in that: When presetting the correction model, it includes: Establishing multiple disturbance scenarios according to all the disturbance indicators corresponding to the calculation model of the target operation indicator; Generating compensation coefficients for each disturbance scenario according to historical parameters; Establishing a disturbance scenario - compensation coefficient mapping table for the target operation indicator; Generating disturbance scenario - compensation coefficient mapping tables for each operation indicator in sequence; Constructing a correction model according to all the disturbance scenario - compensation coefficient mapping tables.

8. The counter-balance coal consumption test method according to claim 7, characterized in that: When generating the coal consumption within a single coal consumption period according to the preset correction model and all the first - level reference values, it includes: Obtain the primary reference values ​​of various operating indicators in the current coal consumption cycle; Establish a first-level reference value series F, F=(f1, f2…f i …f n ), where f i is the primary reference value of the ith operating index in the current coal consumption cycle; Generate compensation coefficients for various operating indicators in the current coal consumption cycle according to the correction model; Establish compensation coefficient series R, R=(r1, r2…r i …r n ), where ri is the compensation coefficient of the ith operating index in the current coal consumption cycle; Generate secondary reference values ​​for each operating indicator within the current coal consumption cycle; h i =r i *b i *f i ? Among them, β i is the correction coefficient set based on the confidence evaluation value series of the ith operating indicator in the current coal consumption cycle; is the secondary reference value of the ith operating indicator in the current coal consumption cycle; The coal consumption in the current coal consumption cycle is generated based on all secondary reference values ​​and the counter-balance coal consumption model.

9. The counter-balance coal consumption test method according to claim 8, characterized in that: When establishing the compensation coefficient sequence R, it includes: Obtain feedback data within the current coal consumption cycle; Generate the real-time values ​​of all disturbance indicators corresponding to the calculation model of the target operation indicator according to the feedback data; Select the target disturbance scenario of the target operation index according to the real-time values ​​of all disturbance indexes; Set the compensation coefficient r of the target operation index according to the target disturbance scenario; Set the compensation coefficient of each operating indicator in turn.

10. A counter-balanced coal consumption test system, using the counter-balanced coal consumption test method according to any one of claims 1 to 9, characterized in that: include: The first processing module is used to set the coal consumption cycle and multiple operation indicators according to the anti-balance coal consumption model; The second processing module is used to generate a disturbance evaluation value of each operating indicator and set the monitoring parameters of each operating indicator according to all the disturbance evaluation values; The third processing module is used to obtain the primary reference value of each operating indicator in a single coal consumption cycle, and generate the coal consumption in a single coal consumption cycle according to the preset correction model and all the primary reference values; The first processing module is also used to establish an operation index sequence A, A=(a1, a2…a i …a n ), where ai is the i-th operating indicator; n is the number of operating indicators; The second processing module is also used to set a according to the operation index sequence A in sequence i Run metrics for goals; Set multiple disturbance indicators of target operating indicators; Generate the volatility evaluation value of each disturbance indicator based on historical parameters; Establish a series of fluctuation evaluation values ​​C, C=(c1, c2…c i …c θ ), where θ is the number of disturbance indicators; ci is the fluctuation evaluation value of the i-th indicator; Generate a disturbance evaluation value of the target operation index according to the fluctuation evaluation value sequence C; Generate disturbance evaluation values ​​of various operating indicators in sequence; Establish the disturbance evaluation value series B=(b1,b2…b i …b n ), where b i is the disturbance evaluation value of the i-th operating indicator.

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