CN107749631B - Unit primary frequency modulation capability pre-estimating method - Google Patents
Unit primary frequency modulation capability pre-estimating method Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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Abstract
The invention discloses a method for estimating the primary frequency modulation capacity of a unit, which comprises the following steps: and taking the unit historical primary frequency modulation analysis result as a sample library, distributing weight coefficients according to a time dimension and a frequency difference dimension, and carrying out comprehensive weighted statistical fusion on the unit primary frequency modulation contribution index historical value to finally obtain a unit primary frequency modulation estimated contribution of the appointed expected frequency difference, thereby realizing the estimation of the unit primary frequency modulation capacity. The method can realize the on-line estimation of the primary frequency modulation output capacity of the unit under the condition of a given frequency difference by using the historical analysis result of the primary frequency modulation of the unit, and make up for the defect that the estimation means of the primary frequency modulation capacity of the unit is lacked in the conventional estimation technology of the primary frequency modulation capacity of the unit; the method can be operated on line, is convenient to calculate, has no special requirement limit, and can provide reference for estimating the primary frequency modulation capacity of the unit.
Description
Technical Field
The invention relates to a unit primary frequency modulation capability pre-estimation method, and belongs to the technical field of power grids.
Background
The self fault of the ultra-high voltage transmission system can cause the power grid to suddenly lose a high-power supply, so that huge impact is generated on the frequency of the power grid, and even the safety of the power grid is threatened. Theoretically, when the power grid frequency changes suddenly, the generator set with the primary frequency modulation function can respond quickly, effectively inhibit the fluctuation range of the power grid frequency, shorten the transition time of fluctuation, and stabilize the power grid frequency in the dynamic process quickly. And in a ten-second-level time period after the fault, only the primary frequency modulation function of the generator set can effectively intervene the power grid frequency from the power supply side. Therefore, in order to enhance the capability of the power grid for resisting high-power disturbance, reduce the steep drop amplitude of the power grid frequency after the high-power supply is lost, improve the frequency quality of the power grid and ensure the safe operation of the power grid, the primary frequency modulation function of the generator set is given full play, the reasonable estimation of the primary frequency modulation capability of the generator set can better evaluate the adjustment capability of the power grid for coping with accidents, coping with insufficient frequency modulation capability is prepared in advance, and the safe and stable operation of the power grid is facilitated to be ensured.
At present, in actual operation, operators pay more and more attention to whether the primary frequency modulation capability of a unit can meet the requirement of adjustment under the condition that a power grid has larger system frequency deviation, and the operators can be helped to know the primary frequency modulation capability of the power grid more clearly by means of estimation of the primary frequency modulation capability of the unit. However, an effective primary frequency modulation capability estimation method is still lacked in the existing unit primary frequency modulation capability evaluation technology, and PMU (synchronous phasor measurement Unit) data has the characteristics of high sampling precision (millisecond level) and strict and accurate time identification, so that new data and technical means are provided for more accurately calculating and estimating the primary frequency modulation capability of the unit under a given expected frequency difference, and the defects of the existing technical method can be overcome.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, provides a unit primary frequency modulation capability estimation method, and can simply, accurately and effectively realize online estimation of the unit primary frequency modulation capability.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows: the method for estimating the primary frequency modulation capacity of the unit comprises the following steps:
and taking the unit historical primary frequency modulation analysis result as a sample library, distributing weight coefficients according to a time dimension and a frequency difference dimension, and carrying out comprehensive weighted statistical fusion on the unit primary frequency modulation contribution index historical value to finally obtain a unit primary frequency modulation estimated contribution of the appointed expected frequency difference, thereby realizing the estimation of the unit primary frequency modulation capacity.
The sample database contains sample data as follows: primary frequency modulation occurrence time, maximum frequency deviation and contribution index of output.
The specific method of assigning the weight coefficients according to the time dimension is as follows:
according to the time of the primary frequency modulation events in the historical time period, clustering and dividing all the primary frequency modulation events of the unit by taking 'month' as a unit;
sorting the months with primary frequency modulation events according to the sequence from near to far from the current time and distributing weighting coefficients, wherein the weighting coefficients are a and a2，a3，…，atAnd the weight coefficient satisfies formula (1):
a+a2+a3+...+at＝1 (1)
wherein t is the number of months in which the FM event occurs.
The specific method for distributing the weight coefficients according to the frequency difference dimension is as follows:
setting an expected frequency difference delta f of primary frequency modulation capacity needing to be estimated, dividing a frequency difference range [ delta f-df, delta f + df ] into k equal frequency difference intervals, and dividing and clustering actual maximum frequency deviations of all primary frequency modulation events in a unit month into corresponding frequency difference intervals;
sequencing and dividing frequency difference intervals with primary frequency modulation events according to the sequence of the distance predicted frequency difference value delta f from near to farWeighting coefficients are assigned, and the weighting coefficients are taken as b and b in sequence2，b3，…，bmAnd the weight coefficient satisfies formula (2):
b+b2+b3+...+bm＝1 (2)
wherein, Δ f is the deviation value between the setting value and 50Hz, df is the width of the selected frequency difference range, and m is the number of frequency difference intervals with frequency modulation events.
The specific method for calculating the primary frequency modulation estimated contribution of the unit comprises the following steps:
calculating the comprehensive contribution index of the frequency difference interval, and performing weighted calculation according to the distribution weight coefficient of the corresponding frequency difference interval to obtain a monthly comprehensive contribution index pre-estimated value;
carrying out weighted calculation on the comprehensive contribution index pre-estimated value of each month according to the distribution weight coefficient of the corresponding time dimension to obtain the contribution index pre-estimated value;
and calculating the primary frequency modulation theoretical output contribution of the unit under the expected frequency difference by combining the output contribution index pre-estimated value to obtain the estimated output contribution of the unit primary frequency modulation.
Integrated contribution index Idxf of frequency difference intervaljIs determined by the contribution index Idx of the primary frequency modulation output falling in the frequency difference interval j in the unitnThe average value is calculated, and the specific calculation is shown in formula (3):
wherein, N is the contribution index number of the primary frequency modulation output in the frequency difference interval j.
The theoretical contribution amount delta P of primary frequency modulation output of the unit under the expected frequency difference is calculated by adopting the following formula
Wherein, PNRated active output of the unit, KcRated rotational speed unequal rate of the unit, delta fsqIs a unit for one timeFrequency modulation dead zone, fNAnd delta f is the expected frequency difference of the rated frequency of the power grid.
The estimated contribution to output of the primary frequency modulation of the unit is calculated by adopting the following formula:
ΔPpre＝Idxpre×ΔP
wherein IdxpreAn estimate is predicted for the contribution index.
Compared with the prior art, the invention has the following beneficial effects:
the capacity of the primary frequency modulation output of the unit under the condition of a given frequency difference can be estimated by utilizing the historical analysis result of the primary frequency modulation of the unit on line, and the defect that the estimation means of the capacity of the primary frequency modulation of the unit is lacked in the existing technology for estimating the capacity of the primary frequency modulation of the unit is overcome; the method can be operated on line, is convenient to calculate, has no special requirement limit, and can provide reference for estimating the primary frequency modulation capacity of the unit.
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FIG. 1 is a flow chart of the present invention.
Detailed Description
The method for estimating the primary frequency modulation capacity of the unit takes the historical primary frequency modulation analysis result of the unit as a sample library, distributes weight coefficients according to time dimension and frequency difference dimension, and comprehensively weights, counts and fuses the historical value of the primary frequency modulation contribution index of the unit according to the weight coefficients, so that estimated contribution of the primary frequency modulation of the unit with specified expected frequency difference is finally obtained, and the estimation of the primary frequency modulation capacity of the unit is realized.
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
As shown in fig. 1, is a flow chart of the present invention, comprising the steps of:
step one, taking the current time as a starting point, and obtaining a unit primary frequency modulation analysis result obtained by calculation based on PMU data in a historical time range as a sample library. The main sample data includes: primary frequency modulation occurrence time, maximum frequency deviation and contribution index of output.
Step (ii) ofAnd secondly, according to the occurrence time of the primary frequency modulation events in the historical time period, carrying out cluster division on all the primary frequency modulation events of the unit by taking 'month' as a unit. Meanwhile, the months with the frequency modulation events are sorted according to the sequence from near to far from the current time and are distributed with weighting coefficients, wherein the weighting coefficients are a and a2，a3，…，atAnd the weight coefficient satisfies formula (1):
a+a2+a3+...+at＝1 (1)
wherein t is the number of months in which the FM event occurs.
Step three, setting the expected frequency difference delta f needing to estimate the primary frequency modulation capability, and setting the frequency difference range [ delta f-df, delta f + df [ ]]Dividing the frequency difference into k equal frequency difference intervals, and dividing and clustering the actual maximum frequency deviation of all primary frequency modulation events in a unit month into corresponding frequency difference intervals. Meanwhile, sorting frequency difference intervals with frequency modulation events according to the order from near to far from the expected frequency difference value delta f and distributing weighting coefficients, wherein the weighting coefficients are b and b in sequence2，b3，…，bmAnd the weight coefficient satisfies formula (2):
b+b2+b3+...+bm＝1 (2)
wherein, Δ f is the deviation value between the setting value and 50Hz, df is the width of the selected frequency difference range, and m is the number of frequency difference intervals with frequency modulation events.
Step four, setting the contribution index Idx of the primary frequency modulation output falling in the frequency difference interval j in the unit month inCalculating the average value by adopting a formula (3) to obtain a comprehensive output contribution index Idxf of the frequency difference interval jjThen according to the distribution weight coefficient b of the frequency difference interval jjAdopting a formula (4) to carry out weighting calculation to obtain a comprehensive contribution index estimated value Idxm of the unit in the single month ii：
Wherein N is the number of contribution indexes of primary frequency modulation output in the frequency difference interval j, bjA weighting factor is assigned to the frequency difference interval j.
Step five, estimating the comprehensive contribution index expected value Idxm of each monthiWeighting factor a according to the time dimensioniThe formula (5) is adopted to carry out weighting calculation to obtain an output contribution index estimated value Idxpre：
Step six, calculating the theoretical output contribution amount delta P of the primary frequency modulation of the unit under the expected frequency difference delta f by adopting a formula (6), and calculating to obtain the estimated output contribution amount delta P of the primary frequency modulation of the unit by utilizing a formula (7)pre：
ΔPpre＝Idxpre×ΔP (7)
Wherein, PNRated active output of the unit, KcRated rotational speed unequal rate of the unit, delta fsqFor the unit primary frequency modulation dead zone (generally taking 0.033Hz), fNThe rated frequency of the power grid (50 Hz is taken).
The method can realize the on-line estimation of the primary frequency modulation output capacity of the unit under the condition of a given frequency difference by using the historical analysis result of the primary frequency modulation of the unit, and make up for the defect that the estimation means of the primary frequency modulation capacity of the unit is lacked in the conventional estimation technology of the primary frequency modulation capacity of the unit; the method can be operated on line, is convenient to calculate, has no special requirement limit, and can provide reference for estimating the primary frequency modulation capacity of the unit.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (6)
1. The method for estimating the primary frequency modulation capacity of the unit is characterized by comprising the following steps of:
taking the unit historical primary frequency modulation analysis result as a sample library, distributing weight coefficients according to time dimension and frequency difference dimension, and carrying out comprehensive weighted statistical fusion on the unit primary frequency modulation contribution index historical value to finally obtain a unit primary frequency modulation estimated contribution of a specified expected frequency difference, thereby realizing estimation of the unit primary frequency modulation capacity;
the specific method of assigning the weight coefficients according to the time dimension is as follows:
according to the time of the primary frequency modulation events in the historical time period, clustering and dividing all the primary frequency modulation events of the unit by taking 'month' as a unit;
sorting the months with primary frequency modulation events according to the sequence from near to far from the current time and distributing weighting coefficients, wherein the weighting coefficients are a and a2，a3，…，atAnd the weight coefficient satisfies formula (1):
a+a2+a3+...+at＝1 (1)
wherein t is the number of months in which the frequency modulation event occurs;
the specific method for distributing the weight coefficients according to the frequency difference dimension is as follows:
setting an expected frequency difference delta f of primary frequency modulation capacity needing to be estimated, dividing a frequency difference range [ delta f-df, delta f + df ] into k equal frequency difference intervals, and dividing and clustering actual maximum frequency deviations of all primary frequency modulation events in a unit month into corresponding frequency difference intervals;
sequencing the frequency difference intervals with the primary frequency modulation events according to the sequence of the distance predicted frequency difference value delta f from near to far and distributing weighting coefficients, wherein the weighting coefficients are b and b in sequence2，b3，…，bmAnd the weight coefficient satisfies formula (2):
b+b2+b3+...+bm＝1 (2)
wherein, Δ f is the deviation value between the setting value and 50Hz, df is the width of the selected frequency difference range, and m is the number of frequency difference intervals with frequency modulation events.
2. The method for estimating primary frequency modulation capability of a unit according to claim 1, wherein the sample database contains sample data including: primary frequency modulation occurrence time, maximum frequency deviation and contribution index of output.
3. The method for estimating the primary frequency modulation capacity of the unit according to claim 1, wherein the specific method for calculating the estimated contribution of the primary frequency modulation of the unit is as follows:
calculating the comprehensive contribution index of the frequency difference interval, and performing weighted calculation according to the distribution weight coefficient of the corresponding frequency difference interval to obtain a monthly comprehensive contribution index pre-estimated value;
carrying out weighted calculation on the comprehensive contribution index pre-estimated value of each month according to the distribution weight coefficient of the corresponding time dimension to obtain the contribution index pre-estimated value;
and calculating the primary frequency modulation theoretical output contribution of the unit under the expected frequency difference by combining the output contribution index pre-estimated value to obtain the estimated output contribution of the unit primary frequency modulation.
4. The method for estimating the primary frequency modulation capacity of a unit as claimed in claim 3, wherein the comprehensive contribution index Idxf of the frequency difference intervaljIs determined by the contribution index Idx of the primary frequency modulation output falling in the frequency difference interval j in the unitnThe average value is calculated, and the specific calculation is shown in formula (3):
wherein, N is the contribution index number of the primary frequency modulation output in the frequency difference interval j.
5. The method for estimating the primary frequency modulation capacity of a unit according to claim 4, wherein the theoretical contribution Δ P of the primary frequency modulation output of the unit under the expected frequency difference is calculated by using the following formula
Wherein, PNRated active output of the unit, KcRated rotational speed unequal rate of the unit, delta fsqIs a unit primary frequency modulation dead zone, fNAnd delta f is the expected frequency difference of the rated frequency of the power grid.
6. The method for estimating the primary frequency modulation capacity of the unit according to claim 5, wherein the estimated contribution of the primary frequency modulation output of the unit is calculated by adopting the following formula:
ΔPpre＝Idxpre×ΔP
wherein IdxpreAn estimate is predicted for the contribution index.
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| CN109378817B (en) * | 2018-10-23 | 2021-09-21 | 国网天津市电力公司电力科学研究院 | Stability evaluation method based on primary frequency modulation |
| CN112383069B (en) * | 2020-11-05 | 2022-06-03 | 国网山东省电力公司电力科学研究院 | Dynamic prediction method for primary frequency modulation compensation capability of generator set |
| CN115508650A (en) * | 2022-10-13 | 2022-12-23 | 西安德纳检验检测有限公司 | New energy station frequency modulation detection method and system based on multipoint synchronous measurement |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP4096470B2 (en) * | 1999-09-10 | 2008-06-04 | 沖電気工業株式会社 | Power supply circuit with battery backup |
| CN102323550A (en) * | 2011-09-09 | 2012-01-18 | 西北电网有限公司 | Primary frequency modulation adjusting performance determination method of generating set |
| CN103346619A (en) * | 2013-07-19 | 2013-10-09 | 国家电网公司 | Online monitoring and performance assessing method for primary frequency modulation of thermal generator set |
| CN104732457A (en) * | 2015-03-27 | 2015-06-24 | 大连理工大学 | Method for evaluating capacity of regional power grid primary frequency modulation based on dynamic ACE |
| CN105808889A (en) * | 2016-04-25 | 2016-07-27 | 中国电力科学研究院 | Frequency deviation factor simulation collocation method |
| CN106300389A (en) * | 2016-08-22 | 2017-01-04 | 国家电网公司 | A kind of integrated evaluating method of generating set primary frequency regulation performance |
-
2017
- 2017-10-25 CN CN201711008302.3A patent/CN107749631B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP4096470B2 (en) * | 1999-09-10 | 2008-06-04 | 沖電気工業株式会社 | Power supply circuit with battery backup |
| CN102323550A (en) * | 2011-09-09 | 2012-01-18 | 西北电网有限公司 | Primary frequency modulation adjusting performance determination method of generating set |
| CN103346619A (en) * | 2013-07-19 | 2013-10-09 | 国家电网公司 | Online monitoring and performance assessing method for primary frequency modulation of thermal generator set |
| CN104732457A (en) * | 2015-03-27 | 2015-06-24 | 大连理工大学 | Method for evaluating capacity of regional power grid primary frequency modulation based on dynamic ACE |
| CN105808889A (en) * | 2016-04-25 | 2016-07-27 | 中国电力科学研究院 | Frequency deviation factor simulation collocation method |
| CN106300389A (en) * | 2016-08-22 | 2017-01-04 | 国家电网公司 | A kind of integrated evaluating method of generating set primary frequency regulation performance |
Non-Patent Citations (2)
| Title |
|---|
| Study and application of real-time frequency deviation adjustment algorithm in establishing a time scale;Yiwei Wu etal.;《2013 Joint European Frequency and Time Forum & International Frequency Control Symposium (EFTF/IFC)》;20131231;第811-814页 * |
| 机组一次调频参数指标在线估计方法;高林 等;《中国电机工程学报》;20120605;第32卷(第16期);第62-69页 * |
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