Dust concentration daily mean value control method based on electric precipitation optimization control system

Abstract

The invention provides a dust concentration daily mean value control method based on an electric precipitation optimization control system. The method comprises the following steps: acquiring meteorological and unit field data through a DCS (Distributed Control System); calculating the current daily average concentration, identifying key high and low load control points on the load curve by applying a bubbling method, and determining a dynamic offset value in combination with the daily average concentration, a manual set value and meteorological data; before a time check point is manually set, the system carries out differential real-time setting according to the interval where the real-time load of the unit is located, and meanwhile, standard exceeding logic is implanted to guarantee instantaneous emission safety. According to the method, through a set value strategy of high load relaxation and low load tightening, on the premise of ensuring that the daily mean value of all-day dust emission concentration meets the standard, the overall operation energy consumption of the electric dust removal system is remarkably reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of energy-saving control of electrostatic precipitators, and particularly to a method for calculating the daily average value of dust concentration based on an optimized control system for electrostatic precipitators. Background Art

[0002] The daily average value of the outlet dust concentration of the unit should be equal to a fixed set value. Especially in summer with high temperatures, the unit load factor is very high. When the high-frequency power supply of some old unit equipment reaches the maximum output, the dust concentration may still exceed the set value; when the load is low, the dust concentration can be controlled to the set value; and after 21:00, the unit load may still be relatively high. Therefore, it is necessary to reduce the set value even at low loads to ensure that the daily average value does not exceed the standard. Therefore, in many cases, the output of the 24-hour high-frequency power supply is fully at the maximum to prevent exceeding the standard.

[0003] When the dust emission concentration remains unchanged, the higher the unit load, the greater the power consumption of the electrostatic precipitator system; the lower the unit load, the lower the power consumption of the electrostatic precipitator system. And the daily unit load curve is different. For example, in summer when the temperature suddenly rises, the average load factor is 90%; if it suddenly rains and causes the temperature to drop, the average load factor may be around 50%. Sometimes the maximum unit load is around 12:00, and sometimes the maximum load is around 21:00. Environmental protection requirements stipulate that the daily average value remains unchanged. Therefore, according to the unit load, the daily average value concentration, and the recent unit load curve, etc., the dust concentration set value is continuously adjusted to minimize the overall energy consumption.

[0004] Currently, most of the optimized control systems for electrostatic precipitators adopt manual control, and a small part adopts open-loop control. The higher the unit load, the greater the secondary current. Currently, most electrostatic precipitator control systems use programming languages such as VB / C# or the statement list of PLC for code development. Each time the strategy is adjusted, the source code needs to be modified, which affects the development speed and system stability.

[0005] Traditional optimized control systems for electrostatic precipitators are implemented through the structured text of PLC or c++ code. Developers need to master a lot of programming knowledge, but there are still problems such as low code reuse rate, poor software portability, poor software reliability, low development efficiency, and large maintenance workload. Summary of the Invention

[0006] The purpose of the present invention is to solve the deficiencies existing in the prior art and provide an optimized control method for the daily average value of dust concentration in an electrostatic precipitator system.

[0007] An optimized control method for the daily average value of dust concentration based on an electrostatic precipitator optimization control system includes: S1: The distributed control system DCS collects meteorological data and on-site data; S2: Calculate the daily average concentration based on the meteorological data, on-site data, and time data in step S1. Use the bubble sort method to obtain the high-load control point PH and the low-load control point PL for the unit load in the on-site data. Obtain the dynamic offset value based on the daily average concentration, the manually set daily average value, and the meteorological data. Obtain the high and low load conditions based on the unit load and the dynamic offset value in the on-site data; S3: Manually set the time check point. Before the manually set time check point, adjust the real-time outlet concentration set value of the dust according to the high and low load conditions and the load curve of the unit load; Set the dust concentration exceeding standard logic; S4: After the manually set time check point, control the real-time outlet concentration set value of the dust according to the daily average control target value, and input the current time for time limit.

[0008] Further, S1 is specifically as follows: The distributed control system DCS obtains meteorological data including temperature, irradiation intensity, and wind speed through the meteorological server; Transmit the meteorological data to the weather forecast acquisition interface machine, the reverse isolation device, and the meteorological interface machine in sequence; The first communication gateway receives the meteorological data output by the meteorological interface machine through the Modbus RTU protocol of the remote terminal unit, and then forwards it to the optimization controller through the Modbus TCP protocol of the Ethernet; The distributed control system DCS collects on-site data, and the on-site data includes unit load, rapping status, flue gas concentration, and secondary current data; And transmit the on-site data to the optimization controller through the Modbus serial card, the second communication gateway, and the control network in sequence.

[0009] Further, S2 is specifically as follows: S21: Input the dust concentration and unit load collected by the distributed control system DCS in real time; Calculate the daily average concentration; Set the low-load control point and the high-load control point according to the unit load; S22: Perform dynamic offset correction based on the input meteorological data and on-site data. Specifically: Obtain the environmental factor offset PHBias2, expressed as: PHBias2 = k1×(average temperature of the current day / average temperature of the previous 3 days) + k2×(average irradiation intensity of the current day / average irradiation intensity of the previous 3 days) + k3×(average wind speed of the current day / average wind speed of the previous 3 days); where k1, k2, and k3 are set weight coefficients; Obtain the fuzzy controller offset PHBias1, expressed as: Input the current hour number and the deviation from the daily average value into the fuzzy controller to obtain the fuzzy controller bias PHBias1. Here, the deviation from the daily average value is the deviation between the daily average concentration and the manually set daily average value; and further process the fuzzy controller through an accumulator to obtain the fuzzy controller bias PHBias1; Among them, both PHBias1 and PHBias2 are dynamic bias values; Obtain high and low load conditions based on the unit load and dynamic bias values in the on-site data; specifically: When the unit load P < PL, it is judged as low load, When the unit load P > PH + PHBias1 + PHBias2, it is judged as high load.

[0010] Furthermore, S3 is specifically: Before the manually set inspection time point, adjust the real-time outlet concentration set value of the dust according to the high and low load conditions and the load curve. Specifically: Under low load conditions, the real-time outlet concentration set value SP = the daily average value set value SPDay - the deviation of the daily average value set value Delta; Under medium load conditions, the real-time outlet concentration set value SP = the daily average value set value SPDay; Under high load conditions, the real-time outlet concentration set value SP = the daily average value set value SPDay + the deviation of the daily average value set value Delta; Set the logic for exceeding the dust concentration standard, specifically: When the real-time concentration of the dust > the real-time concentration set value of the dust or the minute average concentration of the dust > the minute concentration set value of the dust or the hourly average concentration of the dust > the hourly concentration set value SP H, after judging that the dust concentration exceeds the standard, the set values of the dry electric secondary currents of each electric dust removal device are all increased by a specified value.

[0011] Furthermore, S4 is specifically: After the manually set inspection time point, first control the real-time outlet concentration set value according to the daily average control target value SPDayAim, and then perform time limiting, and further achieve upper and lower limit limiting. Specifically, the real-time outlet concentration set value = (24 * the daily average control target value SPDayAim - the cumulative value of the dust concentration on the current day) / (24 - the current hour - the current minute / 60 - the current second / 3600); When the unit load is the highest, the dust concentration statistical value is the dust concentration in the most unfavorable situation; If the dust concentration ZBLND in the most unfavorable situation on the current day > the daily average control target value, then the time limiting allowable signal = 0, otherwise the time limiting allowable signal = 1.

[0012] The present invention has the following technical effects: 1. The present invention distinguishes between a high-load section and a low-load section (raising the set value of dust concentration in the high-load section and lowering the set value of dust concentration in the low-load section), and significantly reduces the overall energy consumption of the electrostatic precipitation system on the premise of ensuring that the outlet dust concentration meets the emission requirements.

[0013] 2. Based on the statistical law of unit load (the time when the unit load > PH accounts for 35%, the time when the unit load < PL accounts for 35%, and the intermediate load accounts for 40%), the present invention dynamically adjusts the judgment interval of the high-load section to effectively adapt to the load fluctuation of the unit.

[0014] 3. The present invention calculates the cumulative value of the daily dust concentration through the daily average value calculation function block, and combines the control of the most unfavorable situation (calculating the ZBLND value) after the artificial setting time checkpoint and the time limit function (such as the maximum value of 1.8 at 22:00) to ensure that the daily average value of the dust concentration meets the standard stably throughout the day. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a network structure diagram of the electrostatic precipitation optimization control system.

[0016] Figure 2 It is a schematic diagram of the daily average value curve of the electrostatic precipitation optimization control system.

[0017] Figure 3 It is a functional block diagram of the daily average value of the electrostatic precipitation optimization system. DETAILED DESCRIPTION OF THE INVENTION

[0018] In order to make the purpose, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with embodiments. The specific embodiments described here are only used to explain the present invention and are not used to limit the invention.

[0019] Referring to Figures 1-3 , a method for controlling the daily average value of dust concentration based on an electrostatic precipitation optimization control system includes: S1: The distributed control system DCS collects meteorological data and on-site data; S2: Based on the meteorological data, on-site data and time data in step S1, calculate the daily average value of concentration. Use the bubble method for the unit load of the on-site data to obtain the high-load control point PH and the low-load control point PL, and obtain the dynamic offset value based on the daily average value of concentration, the manually set value of the daily average value and the meteorological data; obtain the high and low load conditions based on the unit load and the dynamic offset value in the on-site data; S3: Manually set the time checkpoint. Before the manually set time checkpoint, adjust the real-time outlet concentration set value of the dust according to the high and low load conditions and the load curve of the unit load; set the dust concentration exceeding the standard logic; S4: After the artificially set time checkpoint, control the set value of the real-time outlet concentration of dust according to the daily average control target value, and input the current time for time limiting.

[0020] Further, S1 is specifically as follows: The distributed control system DCS obtains meteorological data including temperature, irradiation intensity, and wind speed through a meteorological server; transmits the meteorological data to the weather forecast acquisition interface machine, reverse isolation device, and meteorological interface machine in sequence; the first communication gateway receives the meteorological data output by the meteorological interface machine through the Modbus RTU protocol of the remote terminal unit, and then forwards it to the optimization controller through the Modbus TCP protocol of the Ethernet. The distributed control system DCS collects on-site data, and the on-site data includes unit load, rapping status, flue gas concentration, and secondary current data; and transmits the on-site data to the optimization controller through the Modbus serial card, second communication gateway, and control network in sequence.

[0021] Further, S2 is specifically as follows: S21: Input the dust concentration and unit load collected in real time by the distributed control system DCS; calculate the daily average concentration; set the low-load control point and high-load control point according to the unit load. S22: Perform dynamic offset correction based on the input meteorological data and on-site data. Specifically: Obtain the environmental factor offset PHBias2, expressed as: PHBias2 = k1×(average temperature of the current day / average temperature of the previous 3 days) + k2×(average irradiation intensity of the current day / average irradiation intensity of the previous 3 days) + k3×(average wind speed of the current day / average wind speed of the previous 3 days); where k1, k2, and k3 are set weight coefficients. Obtain the fuzzy controller offset PHBias1, expressed as: Input the current hour number and the daily average deviation into the fuzzy controller to obtain the fuzzy controller offset PHBias1, where the daily average deviation is the deviation between the daily average concentration and the artificially set value of the daily average; and further process the fuzzy controller through an accumulator to obtain the fuzzy controller offset PHBias1. Among them, both PHBias1 and PHBias2 are dynamic offset values. Obtain the high and low load conditions based on the unit load in the on-site data and the dynamic offset value. Specifically: When the unit load P < PL, it is judged as low load. When the unit load P > PH + PHBias1 + PHBias2, it is judged as high load.

[0022] Further, S3 is specifically as follows: Before the artificially set inspection time point, adjust the real-time outlet concentration set value of the dust according to the high and low load conditions and the load curve. Specifically: Under low load conditions, the real-time outlet concentration set value SP = the daily average set value SPDay - the daily average set value offset Delta; Under medium load conditions, the real-time outlet concentration set value SP = the daily average set value SPDay; Under high load conditions, the real-time outlet concentration set value SP = the daily average set value SPDay + the daily average set value offset Delta; Set the dust concentration over-limit logic. Specifically: The real-time concentration of the dust > the real-time concentration set value of the dust or the minute average concentration of the dust > the minute concentration set value of the dust or the hourly average concentration of the dust > the hourly concentration set value SP H. After determining that the dust concentration exceeds the limit, the set values of the dry electric secondary currents of each electric dust removal device are all increased by a specified value.

[0023] Furthermore, S4 is specifically as follows: After the artificially set inspection time point, first control the real-time outlet concentration set value according to the daily average control target value SPDayAim, and then perform time limiting, and further achieve upper and lower limit limiting. Specifically, the real-time outlet concentration set value = (24 * the daily average control target value SPDayAim - the cumulative value of the dust concentration on the current day) / (24 - the current hour - the current minute / 60 - the current second / 3600); When the unit load is the highest, the dust concentration statistical value is the dust concentration in the most unfavorable situation; If the dust concentration ZBLND in the most unfavorable situation on the current day > the daily average control target value, then the time limiting permission signal = 0, otherwise the time limiting permission signal = 1.

[0024] Specifically, in an example, at 0:00:00, PHBias1 = 0, and then PHBias1 is adjusted every 2 hours. If the current daily average concentration is higher than the artificially set daily average value, then increase PHBias1; the larger the current hour number, the larger the increased PHBias1. Specifically, it is adjusted according to the input fuzzy controller. The fuzzy inputs are the current hour number and the daily average deviation.

[0025] Further, in one example, the process of unit load statistics is as follows: The maximum value, minimum value, and average value of the unit load are statistically calculated based on the start time and end time, and the high load control point PH and low load control point PL are statistically calculated. Specifically, the unit load is sorted from small to large by the bubble method, and the number of load points Count is statistically calculated. The Count * 35% -th point from small to large is the high load control point PH, such that the time when the unit load > PH accounts for 35% of the total statistical time. The Count * 35% -th point from large to small is the low load control point PL; the time when the unit load < PL accounts for 35% of the total statistical time, and the time when the unit load > PH and the unit load < PL accounts for 40% of the total statistical time. Before 10 o'clock or when the maximum value - minimum value of the unit load curve on the same day < 10% * the rated load of the unit, the start time and end time of the load statistics are 0:00:00 of the previous 3 days to 0:00:00 of the same day. Otherwise, the start time and end time of the load statistics are 0:00:00 of the same day to the current time of the same day.

[0026] In one example, the process of calculating the daily average concentration is as follows: Statistics are carried out when the unit load > 0, and the unit load less than 0 does not participate in the statistics. The number of outlet dust concentrations and the cumulative value of dust concentrations from 0:00:00 of the same day to the current time are statistically calculated. The daily average concentration = cumulative value of dust concentrations / number. At 0:00:00 of the same day, the number of outlet dust concentrations = 0, and the cumulative value of dust concentrations = 0.

[0027] In one example, the process of time limiting is specifically as follows: Based on the maximum value of the set concentration values limited at different times, such as the maximum value at 12 o'clock = 1.2; the maximum value at 14 o'clock = 1.3; the maximum value at 16 o'clock = 1.4; the maximum value at 18 o'clock = 1.6; the maximum value at 22 o'clock = 1.8, the upper and lower limits of the real - time outlet concentration set value are limited accordingly, such as the upper limit is 3 and the lower limit is 0.5.

Claims

1. A method for controlling the daily average value of dust concentration based on an optimized control system for electrostatic precipitation, characterized in that Including: S1: The distributed control system DCS collects meteorological data and on-site data; S2: Based on the meteorological data, on-site data and time data in step S1, calculate the daily average concentration. Use the bubble sort method to obtain the high-load control point PH and low-load control point PL based on the unit load in the on-site data. Obtain the dynamic offset value based on the daily average concentration, the manually set daily average value and meteorological data; Obtain the high and low load conditions based on the unit load and the dynamic offset value in the on-site data; S3: Manually set the time check point. Before the manually set time check point, adjust the real-time outlet concentration set value of dust according to the high and low load conditions and the load curve of the unit load; Set the logic for dust concentration exceeding the standard; S4: After the manually set time check point, control the real-time outlet concentration set value of dust according to the daily average control target value, and input the current time for time limiting.

2. The method for controlling the daily average dust concentration based on the optimized control system for electrostatic precipitation according to claim 1, characterized in that, Specifically, S1 is as follows: The distributed control system DCS obtains meteorological data including temperature, irradiation intensity and wind speed through the meteorological server; Transmit the meteorological data to the weather forecast acquisition interface machine, reverse isolation device and meteorological interface machine in sequence; The first communication gateway receives the meteorological data output by the meteorological interface machine through the Modbus RTU protocol of the remote terminal unit, and then forwards it to the optimization controller through the ModbusTCP protocol of the Ethernet; The distributed control system DCS collects on-site data. The on-site data includes unit load, rapping status, flue gas concentration and secondary current data; And transmit the on-site data to the optimization controller through the Modbus serial card, the second communication gateway and the control network in sequence.

3. The method for controlling the daily average value of dust concentration based on the optimized control system for electrostatic precipitation according to claim 1, characterized in that Specifically, S2 is as follows: S21: Input the dust concentration and unit load collected in real time by the distributed control system DCS; Calculate the daily average concentration; Set the low-load control point and high-load control point according to the unit load; S22: Perform dynamic offset correction based on the input meteorological data and on-site data. Specifically: Obtain the environmental factor offset PHBias2, expressed as: PHBias2 = k1×(average temperature of the current day / average temperature of the previous 3 days) + k2×(average irradiation intensity of the current day / average irradiation intensity of the previous 3 days) + k3×(average wind speed of the current day / average wind speed of the previous 3 days); where k1, k2, and k3 are set weight coefficients; Obtain the fuzzy controller offset PHBias1, expressed as: Input the current hour number and the daily average deviation into the fuzzy controller to obtain the fuzzy controller offset PHBias1, where the daily average deviation is the deviation between the daily average concentration and the manually set daily average value; And further process the fuzzy controller through the accumulator to obtain the fuzzy controller offset PHBias1; Among them, both PHBias1 and PHBias2 are dynamic offset values; Obtain the high and low load conditions based on the unit load and the dynamic offset value in the on-site data. Specifically: When the unit load P < PL, it is judged as low load, When the unit load P > PH + PHBias1 + PHBias2, it is judged as high load.

4. A method for controlling the daily average value of dust concentration based on an optimized control system for electrostatic precipitation according to claim 1, characterized in that, Specifically, S3 is as follows: Before the manually set check time point, adjust the real-time outlet concentration set value of dust according to the high and low load conditions and the load curve. Specifically: Under low load conditions, the real-time outlet concentration set value SP = daily average set value SPDay - daily average set value offset Delta; Under medium load conditions, the real-time outlet concentration set value SP = daily average set value SPDay; Under high load conditions, the real-time outlet concentration set value SP = daily average set value SPDay + daily average set value offset Delta; Set the logic for dust concentration exceeding the standard, specifically: The real-time concentration of dust > the real-time concentration set value of dust or the minute average concentration of dust > the minute concentration set value of dust or the hourly average concentration of dust > the hourly concentration set value SP H. After determining that the dust concentration exceeds the standard, the set values of the dry electric secondary currents of each electric dust removal device are all increased by a specified value.

5. The method for controlling the daily average value of dust concentration based on the optimized control system for electrostatic precipitation according to claim 1, wherein S4 is specifically: After the manually set inspection time point, first control the real-time outlet concentration set value according to the daily average control target value SPDayAim, and then perform time limiting, and further achieve upper and lower limit limiting. Specifically, the real-time outlet concentration set value = (24 * daily average control target value SPDayAim - the cumulative value of the dust concentration on the current day) / (24 - the current hour - the current minute / 60 - the current second / 3600); When the unit load is the highest, the dust concentration statistical value is the dust concentration in the most unfavorable situation; If the dust concentration ZBLND in the most unfavorable situation on the current day > the daily average control target value, then the time limiting permission signal = 0, otherwise the time limiting permission signal = 1.

Images