System for automatically optimizing and setting instruction curve of coordination control based on big data

Abstract

The invention belongs to the field of boiler coordinated optimization control, and particularly relates to a system for automatically optimizing and setting a coordinated control instruction curve based on big data, which comprises a real-time optimizing logic unit and a big data statistics storage unit, the real-time optimizing logic unit judges the optimal operation state of a unit according to parameter data deviation, and the big data statistics storage unit stores the optimal operation state of the unit. And when the optimal operation state condition is reached, the big data statistics storage unit counts and records parameter data in the coordination control instruction, counts and stores the average value of the parameter data, and updates and sets a relation curve of a plurality of units in the coordination control logic in real time. The automatic adjustment level of coordination control is improved, and the labor intensity of manual adjustment is reduced.

Description

Technical Field

[0001] The present invention belongs to the field of coordinated control of thermal power units, and in particular relates to a system for automatically optimizing and adjusting a command curve of coordinated control based on big data. Background Art

[0002] The DCS (distributed control system) of coal-fired power generation units usually adopts the feedforward command F(x) curve and PID deviation correction control method, such as Figure 1 shown.

[0003] 1. Total fuel quantity command = the total coal quantity after correction and the fuel quantity corresponding to the unit load feedforward command curve F1(x) * the coal type calorific value correction coefficient (BTU) PID loop corrected fuel quantity.

[0004] 2. Total feed water flow command = total feed water flow and feed water flow corresponding to unit load feed forward command curve F2(x) + mid-point temperature PID loop correction to adjust feed water flow.

[0005] 3. Total air volume command = total air volume and air volume corresponding to unit load feedforward command curve F3(x) + corrected air volume of oxygen control PID loop.

[0006] The above coordinated control has inherent loop correction adjustment delay and large inertia adjustment characteristics in the boiler adjustment process, so the accuracy of the total feedwater flow and unit load feedforward instruction curve, the corrected total coal volume and unit load feedforward instruction curve, and the total air volume and unit load feedforward instruction curve is crucial. It is directly related to whether the unit's water, coal, and air medium supply and demand are accurate at each load; it directly affects the unit's variable load response capability and the stability of the main steam pressure, main steam temperature, and nitrogen oxides, as well as the coordinated control automation adjustment level and the operator's manual parameter adjustment labor, and is closely related to the safety and economy of the unit's operation. Summary of the invention

[0007] In order to solve the problems in the existing boiler regulation technology that the automation regulation level of coordinated control is low, regulation relies more on manpower, and the traditional regulation scheme is usually affected by the number of operating condition tests, seasonal condenser vacuum, combustion of different coal types, and changing characteristics of equipment transformation, and the accuracy of feedforward regulation cannot be guaranteed, the present invention proposes a system for automatically optimizing and adjusting the command curve of coordinated control based on big data, which can ensure the accuracy of feedforward regulation, improve the automation regulation level of coordinated control, and reduce the labor intensity of manual regulation.

[0008] The technical solution of the present invention is as follows:

[0009] A system for automatically optimizing and adjusting the command curve of coordinated control based on big data includes a real-time optimization logic unit and a big data statistical storage unit. The real-time optimization logic unit will determine the optimal operating state of the unit based on the parameter data deviation. When the optimal operating state conditions are reached, the big data statistical storage unit will statistically record the parameter data in the coordinated control instructions, and count and store the average value of the parameter data, and update and set the relationship curves of multiple units in the coordinated control logic in real time.

[0010] Preferably, the parameter data include unit load, corrected total coal quantity, total feed water flow, total air volume, midpoint temperature and boiler oxygen content.

[0011] Preferably, the relationship curves of multiple units include the relationship curve between the corrected total coal volume and unit load, the relationship curve between the total feed water flow and unit load, the relationship curve between the total air volume and unit load, the relationship curve between the midpoint temperature and unit load, and the relationship curve between the boiler oxygen content and unit load.

[0012] Preferably, the real-time optimization logic unit determines the optimal operating state of the unit according to the parameter deviation, and the determination method is as follows:

[0013] Unit load deviation judgment: |Unit real-time load - boiler load instruction| < preset absolute value ABS1;

[0014] Main steam pressure deviation judgment: |main steam pressure command-main steam pressure feedback value|<preset absolute value ABS2;

[0015] Determination of intermediate point superheat and steam temperature deviation: preset minimum temperature L1<main steam temperature<preset maximum temperature H1, and preset minimum temperature L2<intermediate point superheat<preset maximum temperature H2;

[0016] Unit load judgment: |Unit real-time load - X% rated load setting value| < preset absolute value ABS 3, X represents a percentage value of a rated load in the load segment that the unit is allowed to coordinate and control, which is usually taken as a gradient of 5% integer multiples of the rated load;

[0017] When the above conditions are met at the same time, the optimal operating state conditions are met.

[0018] Preferably, it also includes a coal quantity command control loop for adjusting the relationship curve between the total coal quantity and the load after correction, and adopting the calorific value correction coefficient BTU to perform correction and adjustment on the coal quantity loop.

[0019] Preferably, it also includes a water supply flow control loop for regulating the total water supply flow and load relationship curve, and using the intermediate point temperature and load relationship curve to perform PID correction and adjustment.

[0020] Preferably, it also includes a total air volume control loop for regulating the total air volume and load relationship curve, and using the boiler oxygen content and load relationship curve to perform PID correction and adjustment.

[0021] Compared with the prior art, the present invention has the following beneficial effects:

[0022] (1) The present invention makes full use of the statistical analysis capabilities of computer big data to automatically optimize the real-time data or historical operation data of the unit to determine the optimal state, and to count, store and analyze the optimal state instruction data, so as to realize automatic optimization and adjustment of multiple feedforward instruction curves of DCS coordinated control, thereby improving the accuracy of water, coal and wind feedforward control instructions of coal-fired power generation units, so that the unit can accurately respond to load capacity while the main steam pressure and main steam temperature are within the qualified range, thereby improving the level of automated adjustment of coordinated control and reducing the labor intensity of manual adjustment.

[0023] (2) In the present invention, a computer control system is used to monitor the unit operation data. The real-time optimization logic unit will determine the optimal operating state of the unit based on the parameter deviation. When the optimal operating state conditions are reached, the big data statistical storage unit will statistically record the instruction parameter data in the coordinated control instructions, and statistically store the average value of the instruction parameter data, and update and set the multiple combined instruction parameters in the coordinated control logic in real time. Automatic optimization and precise adjustment of water, coal, and wind control instructions are achieved to meet the boiler's precise response load capacity while the main steam pressure and main steam temperature are within the qualified range.

[0024] (3) Through real-time optimization and big data statistics of the unit operation data under the optimal operating state, the average values ​​of the corresponding total coal quantity, total feed water flow, total air volume, midpoint temperature (midpoint superheat), boiler oxygen content and other unit coordinated control curve index parameters are obtained. The relationship curves of the total coal quantity and unit load after correction, the relationship curves of the total feed water flow and unit load, the relationship curves of the total air volume and unit load, the relationship curves of the midpoint temperature (midpoint superheat) and unit load, the relationship curves of the boiler oxygen content and unit load, and other required relationship curves in coordinated control are accurately adjusted. Improve the accuracy of the feedforward adjustment of the total coal quantity, total feedwater flow, and total air volume of the DCS coordinated control system, reduce the large delay and hysteresis of the BTU correction coal quantity, the intermediate point temperature correction feedwater flow, and the oxygen control correction air volume, and accurately solve the problem of how much coal quantity, feedwater quantity, and total air volume should correspond to each load of the coal-fired boiler, so as to improve the boiler load response rate and accuracy, improve the stability of the main steam temperature, main steam pressure, and NOx, reduce the abnormal events of boiler steam temperature, steam pressure, and tube wall overtemperature, and at the same time improve the DCS automation control level and reduce the labor intensity of monitoring operations by centralized control operators. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1It is a schematic diagram of the DCS coordinated control strategy of the unit in the prior art;

[0026] Figure 2 It is a schematic diagram of the coordinated control strategy of the present invention;

[0027] Figure 3 for Figure 2 An enlarged schematic diagram of the reference numeral A;

[0028] Figure 4 for Figure 2 An enlarged schematic diagram of the reference numeral B;

[0029] Figure 5 The curve diagram of the relationship between the corrected coal quantity and the unit load in the embodiment of the present invention;

[0030] Figure 6 is a curve diagram showing the relationship between the total feedwater flow rate and the unit load in an embodiment of the present invention;

[0031] Figure 7 is a curve diagram showing the relationship between the total air volume and the unit load in an embodiment of the present invention;

[0032] Figure 8 is a curve showing the relationship between the intermediate point temperature and the unit load in the embodiment of the present invention;

[0033] Fig. 9 This is a curve diagram showing the relationship between boiler oxygen content and unit load in an embodiment of the present invention. DETAILED DESCRIPTION

[0034] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0035] See also Figure 2-4 A system for automatically optimizing and adjusting the command curve of coordinated control based on big data includes a real-time optimization logic unit and a big data statistical storage unit. The real-time optimization logic unit will determine the optimal operating state of the unit based on the parameter data deviation. When the optimal operating state conditions are reached, the big data statistical storage unit will statistically record the parameter data in the coordinated control command, and count and store the average value of the parameter data, and update and set the relationship curves of multiple units in the coordinated control logic in real time.

[0036] It also includes a coal quantity command control loop, a water supply flow control loop and a total air volume control loop;

[0037] The coal quantity command control loop is used to adjust the relationship curve between the total coal quantity after correction and the unit load, and the calorific value correction coefficient BTU is used to correct and adjust the coal quantity loop;

[0038] The feedwater flow control loop is used to control the relationship curve between the total feedwater flow and the unit load, and the relationship curve between the intermediate point temperature and the unit load is used for PID correction adjustment;

[0039] The total air volume control loop is used to adjust the relationship curve between the total air volume and the unit load, and the relationship curve between the boiler oxygen content and the unit load is used for PID correction and adjustment.

[0040] See also Figure 2-4 In one embodiment of the present invention, the parameter data includes unit load, corrected total coal quantity, total feed water flow, total air volume, midpoint temperature and boiler oxygen quantity.

[0041] See also Figure 2-4 In another embodiment of the present invention, the relationship curves of multiple units include the relationship curve between the corrected total coal volume and unit load, the relationship curve between the total feed water flow and the unit load, the relationship curve between the total air volume and the unit load, the relationship curve between the intermediate point temperature and the unit load, and the relationship curve between the boiler oxygen content and the unit load.

[0042] In another embodiment of the present invention, the real-time optimization logic unit determines the optimal operating state of the unit according to the parameter deviation, and the determination method is as follows:

[0043] Unit load deviation judgment: |Unit real-time load - boiler load instruction| < preset absolute value ABS1;

[0044] Main steam pressure deviation judgment: |main steam pressure command-main steam pressure feedback value|<preset absolute value ABS2;

[0045] Determination of intermediate point superheat and steam temperature deviation: preset minimum temperature L1<main steam temperature<preset maximum temperature H1, and preset minimum temperature L2<intermediate point superheat<preset maximum temperature H2;

[0046] Unit load judgment: |Unit real-time load - X% rated load setting value| < preset absolute value ABS 3, X represents a percentage value of a rated load in the load segment that the unit is allowed to coordinate and control, which is usually taken as a gradient of 5% integer multiples of the rated load;

[0047] If the rated load is 1000MW, the load range allowed to be coordinated is 400MW-1000MW.

[0048] Its usual values ​​are 100, 95, 90, 85, 80, ..., 50, 45, 40.

[0049] When the above conditions are met at the same time, the optimal operating state conditions are met.

[0050] The present invention will be further described below in conjunction with a specific embodiment:

[0051] A 1000MW ultra-supercritical unit adopts this patent to automatically optimize and adjust the control command curve of coordinated control.

[0052] The curves related to the coordinated control loop in the DCS coordinated control system of the unit are as follows:

[0053] 1. Coal quantity command control loop: There is a curve of the relationship between the corrected total coal quantity and the unit load, and the calorific value correction coefficient BTU is used to correct and adjust the coal quantity loop.

[0054] 2. Feedwater flow control loop: There is a relationship curve between total feedwater flow and unit load, and the relationship curve between the intermediate point temperature and unit load is used for PID correction adjustment.

[0055] 3.Total air volume control loop: There is a total air volume and unit load relationship curve, and the boiler oxygen volume and unit load relationship curve is used for PID correction and adjustment.

[0056] The judgment logic setting conditions of the real-time optimization logic unit of the unit are as follows:

[0057] 1. Judgment of unit load deviation: |Unit real-time load - boiler load instruction| < 5 (MW).

[0058] 2. Main steam pressure deviation judgment: |Main steam pressure command-main steam pressure feedback value|<0.05MPa.

[0059] 3. Judgment of midpoint superheat and steam temperature deviation: (597℃<main steam temperature<603℃), and (5℃<midpoint temperature<35℃).

[0060] 4. Unit load judgment: The absolute value of |unit real-time load - X% rated load setting| is less than 5MW, where X is 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, and 100 respectively.

[0061] The following is the experimental data of the actual implementation of this system. The computer big data statistical storage unit collects data of unit loads around 1000MW, 950MW, 900MW...400MW, and 350MW as follows:

[0062]

[0063] The modeling analysis relationship is expressed as follows

[0064] 1. See Figure 5 , the expression of the relationship between the corrected total coal quantity and unit load is:

[0065] F1(x)=0.4214x+23.887, the relationship between the total coal quantity and the unit load after correction is as follows:

[0066] x 1050.00 1000.00 900.00 800.00 700.00 600.00 500.00 400.00 300.00 <![CDATA[F1(x)]]> 466.36 445.29 403.15 361.01 318.87 276.73 234.59 192.45 150.31

[0067] 2. See Figure 6 , the relationship between total feedwater flow and unit load is expressed as:

[0068] F2(x)=2.9804x-121.68, the relationship between total feedwater flow and unit load setting is as follows:

[0069] x 1050.00 1000.00 900.00 800.00 700.00 600.00 500.00 400.00 300.00 <![CDATA[F2(x)]]> 3007.74 2858.72 2560.68 2262.64 1964.60 1666.56 1368.52 1070.48 772.44

[0070] 3. See Figure 7 , the relationship between total air volume and unit load is expressed as: F3(x) = 2.0722x + 859.56, and the setting relationship between total air volume and unit load is as follows:

[0071] x 1050.00 1000.00 900.00 800.00 700.00 600.00 500.00 400.00 300.00 <![CDATA[F3(x)]]> 3035.37 2931.76 2724.54 2517.32 2310.10 2102.88 1895.66 1688.44 1481.22

[0072] 4. See Figure 8 , the relationship curve between the intermediate point temperature and the unit load: F4(x)=0.1162x+296.46, the relationship curve between the intermediate point temperature and the unit load is as follows:

[0073] x 1050.00 1000.00 900.00 800.00 700.00 600.00 500.00 400.00 300.00 <![CDATA[F3(x)]]> 418.47 412.66 401.04 389.42 377.80 366.18 354.56 342.94 331.32

[0074] 5. See Fig. 9 , boiler oxygen content and unit load relationship curve:

[0075] F5(x)=-0.0187x+23.422

[0076] x 1050.00 1000.00 900.00 800.00 700.00 600.00 500.00 400.00 300.00 <![CDATA[F5(x)]]> 0.55 1.01 1.92 2.83 3.74 4.65 5.56 6.47 7.38

[0077] Using the above curve expression, the following F(X) setting values ​​in the coordinated control are calculated as follows:

[0078]

[0079]

[0080] The above setting table data is used to set the curve in the control instruction of the coordinated control of the ultra-supercritical unit 1000MW unit, and the results are as follows:

[0081]

[0082] It can be seen that compared with the traditional adjustment method, the patent big data can accurately adjust the control command curve of coordinated control, which improves the boiler load response rate and accuracy, improves the stability of main steam temperature and main steam pressure, reduces the abnormal over-temperature events of boiler heating surface, improves the DCS automation control level, and reduces the manual correction operation amount of centralized control operators.

[0083] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A system for automatically optimizing and adjusting the command curve of coordinated control based on big data, characterized in that: It includes a real-time optimization logic unit and a big data statistical storage unit. The real-time optimization logic unit will determine the optimal operating state of the unit based on the parameter data deviation. When the optimal operating state conditions are reached, the big data statistical storage unit will statistically record the parameter data in the coordinated control instructions, and statistically store the average value of the parameter data, and update and set the relationship curves of multiple units in the coordinated control logic in real time.

2. The system for automatically optimizing and adjusting the command curve of coordinated control based on big data according to claim 1 is characterized in that: The parameter data include unit load, corrected total coal quantity, total feed water flow, total air volume, intermediate point temperature and boiler oxygen quantity.

3. The system for automatically optimizing and adjusting the command curve of coordinated control based on big data according to claim 1 is characterized in that: The real-time optimization logic unit will determine the optimal operating state of the unit according to the parameter deviation, and the determination method is as follows: Unit load deviation judgment: |Unit real-time load - boiler load instruction| < preset absolute value ABS 1; Main steam pressure deviation judgment: |main steam pressure command-main steam pressure feedback value|<preset absolute value ABS2; Determination of intermediate point superheat and steam temperature deviation: preset minimum temperature L1<main steam temperature<preset maximum temperature H1, and preset minimum temperature L2<intermediate point superheat<preset maximum temperature H2; Unit load judgment: |Unit real-time load - X% rated load setting value| < preset absolute value ABS 3, X represents a percentage value of a rated load in the load segment that the unit is allowed to coordinate and control, which is usually taken as a gradient of 5% integer multiples of the rated load; When the above conditions are met at the same time, the optimal operating state conditions are met.

4. The system for automatically optimizing and adjusting the command curve of coordinated control based on big data according to claim 1 is characterized in that: The relationship curves of the multiple units include the relationship curve between the corrected total coal volume and unit load, the relationship curve between the total feed water flow and unit load, the relationship curve between the total air volume and unit load, the relationship curve between the intermediate point temperature and unit load, and the relationship curve between the boiler oxygen volume and unit load.

5. The system for automatically optimizing and adjusting the command curve of coordinated control based on big data according to claim 4 is characterized in that: It also includes a coal quantity command control loop, which is used to adjust the relationship curve between the corrected total coal quantity and the unit load, and uses the calorific value correction coefficient BTU to perform coal quantity loop correction adjustment.

6. The system for automatically optimizing and adjusting the command curve of coordinated control based on big data according to claim 4 is characterized in that: It also includes a feed water flow control loop for regulating the relationship curve between the total feed water flow and the unit load, and adopts the relationship curve between the intermediate point temperature and the unit load for PID correction and adjustment.

7. The system for automatically optimizing and adjusting the command curve of coordinated control based on big data according to claim 4 is characterized in that: It also includes a total air volume control loop for regulating the relationship curve between the total air volume and the unit load, and uses the relationship curve between the boiler oxygen volume and the unit load to perform PID correction and adjustment.

Images