Generator set AGC regulation performance evaluation method based on parameter calculation

Abstract

The invention provides a generator set AGC regulation performance evaluation method based on parameter calculation, aims to solve the technical problem that the AGC regulation performance of an existing grid-connected generator set cannot be accurately quantified, and relates to the technical field of power control. According to the method, real-time data is collected and accurately screened by taking an instruction change interval as a period, an effective data table is formed to obtain a calculation basis of K1, K2 and K3, accurate numerical values of K1, K2 and K3 are calculated according to an AGC regulation performance specific quantitative data rating basis, and the accurate numerical values are compared with a power grid grid-connected unit regulation performance parameter detail requirement table; meanwhile, an AGC overall regulation performance grade data model is established; the actual data average value is compared with the AGC overall adjustment performance grade data model, and accurate positioning of an adjustment performance short board is achieved; and weekly or monthly real-time performance indexes are analyzed and pertinent improvement is carried out, so that closed-loop continuous improvement is achieved, and the AGC regulation performance is continuously improved.

Description

Technical Field

[0001] The present invention relates to an AGC regulation method for a generator set, and in particular to an AGC regulation performance evaluation method for a generator set based on parameter calculation, and belongs to the technical field of power control. Background Art

[0002] AGC (Automatic Generation Control) service, namely automatic generation control, refers to the service in which the generator set tracks the power dispatching instructions within the prescribed output adjustment range and adjusts the power generation output in real time at a certain adjustment rate to meet the power system frequency and interconnection line power control requirements. This service is mainly provided by coal-fired power units connected to the grid.

[0003] The future mission of existing large-scale power generating units will shift from power generation to auxiliary services, helping new energy sources to peak and regulate the frequency of electricity.

[0004] In view of this, the quality of auxiliary services provided by generator sets to the grid during grid connection directly determines the economic benefits of unit operation, and the most important auxiliary service is AGC service.

[0005] The existing methods for evaluating the AGC regulation performance of generator sets are as follows: Figure 1 As shown, a small amount of data is manually collected from the generator set at irregular intervals, and the overall AGC regulation performance is estimated based on the results of data calculation and summary, and then a rough evaluation conclusion is drawn after comparison with the power grid assessment data. There are too few variables in the data collection, and no unified data standardization and calculation are performed after collection. Only open-loop processing and qualitative evaluation can be performed on the overall performance indicators. It is impossible to intuitively quantify the AGC regulation performance of the generator set based on the evaluation results, and it is impossible to continuously improve the actual regulation performance of the generator set in a closed loop based on the weekly or monthly evaluation results, and it is even more impossible to meet the increasingly stringent requirements of the National Energy Administration and the power grid for the AGC indicators of grid-connected units. Summary of the invention

[0006] In view of the problems existing in the above-mentioned prior art, the present invention proposes a generator set AGC regulation performance evaluation method based on parameter calculation, which can evaluate the AGC regulation performance of the generator set at any time, solving the problem that the AGC regulation performance of the existing grid-connected generator set cannot be accurately quantified.

[0007] The present invention provides a method for evaluating the AGC regulation performance of a generator set based on parameter calculation, and the technical solution comprises the following steps:

[0008] Step 1: On the engineer station of the generator unit control system, establish a standard cycle and basic unit for data collection to collect real-time data;

[0009] Step 2: Accurately screen the standard data according to the interval changes of the AGC instructions, and summarize all the data in each cycle into a valid data table;

[0010] Step 3, based on each adjustment process data in the effective data table, the absolute difference between the actual output at the time of entering the dead zone and the actual output at the response time, and the time difference between the time of entering the dead zone and the response time are obtained. The ratio of the above two is the basis for calculating the AGC adjustment rate K1;

[0011] Step 4, based on each adjustment process data in the effective data table, calculate the time difference value from the time when the command is sent to the time when the actual output exceeds the adjustment dead zone and no longer reverses, and obtain the AGC response time K3;

[0012] Step 5, based on each adjustment process data in the effective data table, the integral average value data of the output deviation between the moment of entering the dead zone and the moment when the instruction is sent again is counted to obtain the calculation basis of the AGC adjustment accuracy K2;

[0013] Step 6, repeatedly perform the calculations of step 3 to step 5, take 24 hours as the basic unit, form standard quantitative data of AGC response time, AGC regulation rate, and AGC regulation accuracy for N cycles, calculate the accurate values ​​of K1, K2, and K3 according to the specific quantitative data rating basis of AGC regulation performance, and compare them with the detailed requirements table of regulation performance parameters of grid-connected units, and then obtain preliminary basic evaluation results;

[0014] Step 7, collecting the AGC regulation performance standard parameters and key variables of the generator sets from the official data website of the power system, and establishing an AGC overall regulation performance level data model;

[0015] Step 8: Use a comparison algorithm to compare and analyze the average value of the quantitative data with the AGC overall regulation performance level data model, accurately locate the shortcomings of the AGC regulation performance, and find out the specific reasons for the regulation problems;

[0016] Step 9, further analyze the average values ​​of weekly or monthly segmented performance indicators and overall performance indicators, and adjust the unit's online parameters or modify the overall shutdown control logic for segmented performance indicators with poor average values ​​according to the barrel theory in data above level C. After the parameters or logic are modified, continue to collect parameters in step 1, thus forming a closed-loop continuous improvement process to continuously improve the AGC regulation performance.

[0017] Furthermore, in the step 1, the interval between two changes of the AGC instruction is used as the standard period for collecting data, and a collection program is established to collect real-time data of the instruction sending time, target output, actual output, response time, dead zone entering time, and instruction sending time again in 24 hours as a basic unit, and the data scanning period is 1 second.

[0018] Furthermore, in step 2, all the data include the actual output at the moment of entering the dead zone, the actual output at the response moment, the target output at the moment of entering the dead zone, the moment of entering the dead zone, the moment of sending the instruction, the output deviation at the moment of entering the dead zone, the output deviation when the instruction is sent again, the moment when the actual output begins to change beyond the dead zone and no longer reverses, and the response moment.

[0019] Furthermore, in step 3,

[0020] K1 = ABS (actual output at the moment of entering the dead zone - actual output at the moment of response) / (moment of entering the dead zone - moment of response);

[0021] Among them, the dead zone is 0.5% of the rated capacity of the generator set; the dead zone entry time is the time when the load changes for the first time and enters the AGC target output regulation dead zone; the response time is the time when the actual output starts to change with the target output and exceeds the regulation dead zone and does not return; ABS is the absolute value;

[0022] The monthly average regulation accuracy of AGC refers to the average value of the regulation accuracy of the unit in that month.

[0023] Furthermore, in step 4,

[0024] K3 = (the moment when the actual output starts to change beyond the dead zone and does not return) - the moment when the command is sent;

[0025] The command sending time is the exact time value when the AGC command changes for the first time;

[0026] AGC response time pass rate = (number of AGC response time pass times for the unit in that month / total number of AGC adjustments for the unit in that month) × 100%.

[0027] Furthermore, in the step 5,

[0028] K2=[ABS(target output-actual output) / unit rated capacity]×100%

[0029] The target output is the active power target value of this AGC instruction change;

[0030] The actual output is the actual active power value of the generator set;

[0031] ABS is the absolute value;

[0032] Output deviation is the absolute value of the difference between the target output and the actual output;

[0033] The statistics of adjustment accuracy start from the moment of entering the dead zone until the moment the instruction is sent again.

[0034] Furthermore, in step 8, the data levels of the three subdivided performance indicators and one overall performance indicator in all the quantitative data are determined, and the number of data with KP values ​​in the range of 0.01, 0.02, 0.03, 0.1, 0.2, and 0.3 in the D-level data and the E-level data is counted;

[0035] KP=K1×K2×K3.

[0036] The beneficial effects of the present invention are:

[0037] 1. Changing the traditional manual irregular data collection method, adopting an innovative data collection method of periodic automatic collection at intervals of instruction changes has greatly improved the work efficiency of data collection, and also improved the quality and standardization of the collected data.

[0038] 2. The scope of collected data has been changed from the traditional few AGC-related variables to all relevant variables covering the three main regulation performance indicators of AGC. The collected data is more targeted and the data source is more reliable, laying a solid foundation for the subsequent accurate processing and reliable calculation of the data.

[0039] 3. The data calculation and processing results after data collection can only estimate the overall regulation performance of AGC by traditional methods, and cannot be compared with the grid assessment data item by item. It has been improved to accurately calculate all three subdivided regulation performance indicators of AGC and one overall performance indicator, and accurately compare them with the grid sub-item assessment data, solving the technical problem that the AGC regulation performance of existing grid-connected generators cannot be accurately quantified at any time. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 The figure is a flow chart for evaluating the AGC regulation performance in the prior art.

[0041] Figure 2 The figure is a flow chart of the AGC regulation performance evaluation based on parameter calculation according to the present invention. DETAILED DESCRIPTION

[0042] In order to deepen the understanding of the present invention, the present invention will be further described in detail below in conjunction with examples. The examples are only used to explain the present invention and do not constitute a limitation on the protection scope of the present invention.

[0043] Example

[0044] Step 1: On the engineer station of the generator unit control system, take the interval between two changes of the AGC command as the standard cycle for data collection, establish a collection program to collect real-time data of the command sending time, target output, actual output, response time, dead zone time, and command re-sending time in 24 hours as the basic unit, and the data scanning cycle is 1 second. The standard data of 24 hours is used to form the standard data of one week, one month, or even one quarter. The specific amount of data depends on the needs of the evaluation work.

[0045] Step 2: Accurately screen the standard data according to the interval changes of the AGC instructions, and summarize all data such as the actual output at the moment of entering the dead zone, the actual output at the response time, the target output at the moment of entering the dead zone, the moment of entering the dead zone, the moment of sending the instruction, the output deviation at the moment of entering the dead zone, the output deviation when the instruction is sent again, the moment when the actual output begins to change beyond the dead zone and no longer reverses, and the response time into a valid data table.

[0046] Step 3: Based on each adjustment process data in the effective data table, obtain the absolute difference between the actual output at the time of entering the dead zone and the actual output at the response time, and the time difference between the time of entering the dead zone and the response time. The ratio of the above two is the basis for calculating the AGC adjustment rate K1.

[0047] Step 4: Based on each adjustment process data in the effective data table, calculate the time difference from the time the command is sent to the time when the actual output exceeds the adjustment dead zone and no longer reverses, and obtain the AGC response time K3.

[0048] Step 5: Based on each adjustment process data in the effective data table, the integral average data of the output deviation between the moment of entering the dead zone and the moment the command is sent again is counted to obtain the calculation basis of the AGC adjustment accuracy K2.

[0049] Step 6: Repeat the calculations from step 3 to step 5, taking 24 hours as the basic unit, to form standard quantitative data of AGC response time, AGC regulation rate, and AGC regulation accuracy for N cycles, calculate the accurate values ​​of K1, K2, and K3 according to the specific quantitative data rating basis of AGC regulation performance (Table 3), and compare them with the detailed requirements table of regulation performance parameters of grid-connected units (Table 1), to obtain preliminary basic evaluation results.

[0050] Step 7: Collect the standard parameters and key variables of the AGC regulation performance of the generator sets from the official data website of the power system, and establish the AGC overall regulation performance level data model.

[0051] Step 8: Use the comparison algorithm to compare and analyze the average value of the quantitative data with the AGC overall adjustment performance level data model (Table 2), determine the data level of the three sub-performance indicators and one overall performance indicator in all quantitative data, and count the number of data with KP values ​​in the range of 0.01, 0.02, 0.03, 0.1, 0.2, and 0.3 in the D-level data and E-level data, accurately locate the shortcomings of the AGC adjustment performance, and quickly find out the specific causes of the adjustment problems.

[0052] Step 9: Further analyze the average values ​​of the weekly or monthly segmented performance indicators and the overall performance indicators. For data above level C, adjust the unit's online parameters or modify the overall shutdown control logic for the segmented performance indicators with poor average values ​​according to the barrel theory. After the parameters or logic are modified, continue to collect the parameters in step 1, thus forming a closed-loop continuous improvement process to continuously improve the AGC regulation performance.

[0053] The present invention adopts the instruction change interval to periodically and automatically collect all AGC related variables, summarizes and calculates the details of the AGC regulation performance indicators, and can realize data quantification in terms of regulation rate, regulation accuracy, response time and comprehensive performance, which completely reverses the passive situation that the AGC regulation performance of the existing grid-connected generator set can only be roughly estimated. The evaluation process can be carried out in days, weeks or months, and the evaluation results can be directly used for online parameter adjustment or offline logic transformation of the generator set. After the parameter adjustment or logic transformation, the regulation performance evaluation can be carried out again, so as to continuously improve the regulation performance.

[0054] The AGC regulation performance level data model established by the present invention can be directly compared with the collected data in terms of standard parameters and key variables. The operation mode is simple and effective, and the reliable evaluation of the regulation performance and the quantification of all indicators are realized. The AGC regulation performance of the grid-connected generator set is clearly divided into six levels, and the shortcomings and weak links of the subdivided indicators can be quickly found out according to the quantification results for targeted adjustments, thereby realizing continuous improvement of the closed loop.

[0055] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

[0056] Table 1: Detailed requirements for regulation performance parameters of grid-connected units in Northeast China Power Grid

[0057]

[0058] Table 2: AGC overall regulation performance level data model

[0059]

[0060] Table 3: Specific quantitative data rating basis for AGC regulation performance (taking a 600MW unit of a direct-blowing pulverizing system as an example)

[0061]

Claims

1. A method for evaluating the AGC regulation performance of a generator set based on parameter calculation, characterized in that: The following steps are involved: Step 1: On the engineer station of the generator unit control system, establish a standard cycle and basic unit for data collection to collect real-time data; Step 2: Accurately screen the standard data according to the interval changes of the AGC instructions, and summarize all the data in each cycle into a valid data table; Step 3, based on each adjustment process data in the effective data table, the absolute difference between the actual output at the time of entering the dead zone and the actual output at the response time, and the time difference between the time of entering the dead zone and the response time are obtained. The ratio of the above two is the basis for calculating the AGC adjustment rate K1; Step 4, based on each adjustment process data in the effective data table, calculate the time difference value from the time when the command is sent to the time when the actual output exceeds the adjustment dead zone and no longer reverses, and obtain the AGC response time K3; Step 5, based on each adjustment process data in the effective data table, the integral average value data of the output deviation between the moment of entering the dead zone and the moment when the instruction is sent again is counted to obtain the calculation basis of the AGC adjustment accuracy K2; Step 6, repeatedly perform the calculations of step 3 to step 5, take 24 hours as the basic unit, form standard quantitative data of AGC response time, AGC regulation rate, and AGC regulation accuracy for N cycles, calculate the accurate values ​​of K1, K2, and K3 according to the specific quantitative data rating basis of AGC regulation performance, and compare them with the detailed requirements table of regulation performance parameters of grid-connected units, and then obtain preliminary basic evaluation results; Step 7, collecting the AGC regulation performance standard parameters and key variables of the generator sets from the official data website of the power system, and establishing an AGC overall regulation performance level data model; Step 8: Use a comparison algorithm to compare and analyze the average value of the quantitative data with the AGC overall regulation performance level data model, accurately locate the shortcomings of the AGC regulation performance, and find out the specific reasons for the regulation problems; Step 9, further analyze the average values ​​of weekly or monthly segmented performance indicators and overall performance indicators, and adjust the unit's online parameters or modify the overall shutdown control logic for segmented performance indicators with poor average values ​​according to the barrel theory in data above level C. After the parameters or logic are modified, continue to collect parameters in step 1, thus forming a closed-loop continuous improvement process to continuously improve the AGC regulation performance.

2. A method for evaluating the AGC regulation performance of a generator set based on parameter calculation according to claim 1, characterized in that: In the step 1, the interval between two changes of the AGC instruction is used as the standard period for collecting data, and a collection program is established to collect real-time data of the instruction sending time, target output, actual output, response time, dead zone entering time, and instruction sending time again in 24 hours as a basic unit, and the data scanning period is 1 second.

3. A method for evaluating the AGC regulation performance of a generator set based on parameter calculation according to claim 1, characterized in that: In step 2, all the data include the actual output at the moment of entering the dead zone, the actual output at the response moment, the target output at the moment of entering the dead zone, the moment of entering the dead zone, the moment of sending the command, the output deviation at the moment of entering the dead zone, the output deviation at the moment of sending the command again, the moment when the actual output starts to change beyond the dead zone and no longer reverses, and the response moment.

4. The method for evaluating the AGC regulation performance of a generator set based on parameter calculation according to claim 1, characterized in that: In the step 3, K1=ABS (actual output at the moment of entering the dead zone - actual output at the moment of response) / (moment of entering the dead zone - moment of response); Among them, the dead zone is 0.5% of the rated capacity of the generator set; the dead zone entry time is the time when the load changes for the first time and enters the AGC target output regulation dead zone; the response time is the time when the actual output starts to change with the target output and exceeds the regulation dead zone and does not return; ABS is the absolute value; The monthly average regulation accuracy of AGC refers to the average value of the regulation accuracy of the unit in that month.

5. The method for evaluating the AGC regulation performance of a generator set based on parameter calculation according to claim 1, characterized in that: In the step 4, K3 = (the moment when the actual output starts to change beyond the dead zone and does not return) - the moment when the command is sent; The command sending time is the exact time value when the AGC command changes for the first time; AGC response time pass rate = (number of AGC response time passes for the unit that month / total number of AGC adjustments for the unit that month) × 100%.

6. The method for evaluating the AGC regulation performance of a generator set based on parameter calculation according to claim 1, characterized in that: In the step 5, K2=[ABS (target output - actual output) / unit rated capacity]×100% The target output is the active power target value of this AGC instruction change; The actual output is the actual active power value of the generator set; ABS is the absolute value; Output deviation is the absolute value of the difference between the target output and the actual output; The statistics of adjustment accuracy start from the moment of entering the dead zone until the moment the instruction is sent again.

7. A method for evaluating the AGC regulation performance of a generator set based on parameter calculation according to claim 1, characterized in that: In the step 8, the data levels of the three subdivided performance indicators and one overall performance indicator in all the quantitative data are determined, and the number of data with KP values ​​in the range of 0.01, 0.02, 0.03, 0.1, 0.2, and 0.3 in the D-level data and the E-level data is counted; KP= K1×K2×K3.

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