CN112769147B - Frequency stability early warning method based on power grid perception data - Google Patents
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Abstract
A frequency stability early warning method based on power grid perception data includes the steps of firstly counting the frequency of frequency deviation exceeding of each day of the power grid every year, then carrying out probability distribution function fitting on the frequency deviation exceeding of the frequency according to the counted data, obtaining a confidence range of the frequency deviation exceeding of the probability distribution function obtained through fitting, then observing the frequency deviation exceeding of the current power grid by taking days as a unit, and judging that the power grid has the risk of frequency instability if the frequency deviation exceeding of two consecutive days exceeds of the confidence range, wherein frequency modulation characteristics of a unit in the power grid need to be monitored. The design realizes the early warning of the frequency stability of the system before the system generates large disturbance, and is beneficial to reducing the frequency instability risk of the system.
Description
Technical Field
The invention belongs to the field of safety and stability analysis of power systems, and particularly relates to a frequency stability early warning method based on power grid perception data.
Background
With the rapid development of new energy, it deteriorates the frequency characteristics of the power system from two aspects. On one hand, the output of the new energy is mainly determined by the wind and light conditions, the output has strong randomness and volatility, and the active power balance difficulty of the system is increased by large-scale new energy grid connection. On the other hand, the active power regulation capability of the new energy source unit is relatively poor, the response capability to frequency fluctuation in the system is insufficient, and the frequency regulation capability of the system is further deteriorated. Thus, when the new energy permeability in the system is too high, the risk of instability of the system occurring frequency increases. In 2019, frequency instability accidents caused by the fact that the new energy power generation proportion is too high occur in the United kingdom, and huge losses are brought to vast power consumers and social safety production. Therefore, it is urgently needed to provide an early warning method for system frequency instability so as to conveniently investigate the system operation condition and effectively reduce the risk of system frequency instability.
Aiming at the problem of frequency stability of a power system, "Lichanggang, Zhang Heng xu, Liu Yu Tian, Sun Huadong and Tang Yong. Transient frequency stability assessment (Electrical engineering science and technology report, 2013, 28 (2): 271 and 278) "of the power system considering the low-frequency protection of the unit defines a transient frequency stability margin index based on the critical disturbance power of the low-frequency protection, and deduces a frequency response analysis solution considering the spinning reserve and the low-frequency load shedding so as to rapidly and effectively assess the transient frequency stability of the system and guide the safe and stable operation of the system; "Zhang Yi surpasses, smells it, Wang Xiao Ru, Li jin Li. The prediction of the frequency curve of the power system after disturbance (Chinese Motor engineering report, 2019, 39 (17): 5095-5104) based on the deep belief network provides a method for predicting the frequency curve of the power system after disturbance, which is mainly used for the emergency judgment of the frequency change trend and the frequency stability of the system under the condition of large disturbance, provides a basis for the frequency control of the system, cannot early warn the frequency stability of the system in advance, and provides sufficient time margin for troubleshooting and operation mode adjustment of the system.
Disclosure of Invention
The invention aims to solve the problems in the prior art, and provides a frequency stability early warning method based on power grid perception data, which can perform stability early warning before large disturbance.
In order to achieve the above purpose, the technical scheme of the invention is as follows:
a frequency stability early warning method based on power grid perception data sequentially comprises the following steps:
step A, counting the frequency of out-of-limit frequency deviation occurring every day in one year on a power grid;
b, firstly, carrying out probability distribution function fitting of the out-of-limit frequency deviation according to the data counted in the step A, and then solving a confidence range of the out-of-limit frequency deviation according to the probability distribution function obtained by fitting;
and step C, observing the current out-of-limit frequency deviation number of the power grid by taking days as a unit, and if the out-of-limit frequency deviation number of the power grid for two consecutive days exceeds the maximum value of the confidence range, judging that the power grid has the risk of frequency instability, and monitoring the frequency modulation characteristics of the unit in the power grid.
In the step B, the probability distribution function fitting of the frequency deviation out-of-limit times according to the data counted in the step A sequentially comprises the following steps:
b1, calculating the occurrence probability of different frequency deviation out-of-limit times according to the data counted in the step A;
b2, drawing a frequency deviation out-of-limit frequency probability distribution histogram by taking the frequency deviation out-of-limit frequency as an abscissa and taking the occurrence probability as an ordinate;
b3, fitting the histogram obtained in the step B2 by adopting various typical probability distribution functions respectively to obtain a plurality of probability distribution functions;
and B4, respectively calculating the cumulative errors between the probability distribution functions and the histogram, and selecting the probability distribution function with the minimum cumulative error as the probability distribution function of the frequency deviation out-of-limit times.
In step B1, the probability of occurrence of the out-of-limit times of the different frequency deviations is calculated by the following formula:
in the above formula, f (x) is the probability of x frequency deviation overruns, D (x) is the number of days in the last year in which x frequency deviation overruns occur, and DT is the total number of days in the last year.
In step B, the step of obtaining the confidence range of the out-of-limit frequency deviation according to the probability distribution function obtained by fitting is: and calculating the cumulative probability distribution of the probability distribution function obtained by fitting, and then calculating the confidence range of the out-of-limit times of the frequency deviation of the power grid every day under the set confidence.
The value range of the confidence coefficient m is more than 98% and less than 100%.
In the step A, the step B is carried out,
for the power grid capacity of 300 ten thousand kilowatts or more, the threshold value of the frequency deviation is +/-0.1 Hz;
for the power grid capacity below 300 ten thousand kilowatts, the threshold value of the frequency deviation is +/-0.25 Hz.
Compared with the prior art, the invention has the beneficial effects that:
the invention relates to a frequency stability early warning method based on power grid perception data, which comprises the steps of firstly counting the frequency of frequency deviation exceeding the limit every year on a power grid, then carrying out probability distribution function fitting on the frequency deviation exceeding the limit according to the counted data, solving the confidence range of the frequency deviation exceeding the limit according to the probability distribution function obtained by fitting, then observing the frequency deviation exceeding number of the current power grid by taking days as a unit, if the frequency deviation exceeding number of two continuous days exceeds the maximum value of the confidence range, judging that the power grid has the risk of frequency instability, and monitoring the frequency modulation characteristics of a unit in the power grid, wherein the method can carry out characteristic analysis on the frequency fluctuation sign expressed before the frequency instability of the power grid occurs, can carry out early warning on the frequency stability of a system before the large disturbance occurs, and provides sufficient time for the adjustment and the accident investigation of a system operation mode, thereby effectively reducing the risk of frequency instability of the system. Therefore, the invention realizes the early warning of the frequency stability of the system before the large disturbance occurs, and is beneficial to reducing the frequency instability risk of the system.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is a frequency deviation out-of-limit number probability distribution histogram obtained in example 1.
FIG. 3 shows a plurality of probability distribution functions obtained by the fitting in example 1.
Fig. 4 is a cumulative probability distribution calculated in example 1.
Detailed Description
The present invention will be described in further detail with reference to specific embodiments.
Referring to fig. 1, a frequency stability early warning method based on power grid perception data sequentially includes the following steps:
step A, counting the frequency of out-of-limit frequency deviation occurring every day in one year on a power grid;
b, firstly, carrying out probability distribution function fitting of the out-of-limit frequency deviation according to the data counted in the step A, and then solving a confidence range of the out-of-limit frequency deviation according to the probability distribution function obtained by fitting;
and step C, observing the current out-of-limit frequency deviation number of the power grid by taking days as a unit, and if the out-of-limit frequency deviation number of the power grid for two consecutive days exceeds the maximum value of the confidence range, judging that the power grid has the risk of frequency instability, and monitoring the frequency modulation characteristics of the unit in the power grid.
In the step B, the probability distribution function fitting of the frequency deviation out-of-limit times according to the data counted in the step A sequentially comprises the following steps:
b1, calculating the occurrence probability of different frequency deviation out-of-limit times according to the data counted in the step A;
b2, drawing a frequency deviation out-of-limit frequency probability distribution histogram by taking the frequency deviation out-of-limit frequency as an abscissa and taking the occurrence probability as an ordinate;
b3, fitting the histogram obtained in the step B2 by adopting various typical probability distribution functions respectively to obtain a plurality of probability distribution functions;
and B4, respectively calculating the cumulative errors between the probability distribution functions and the histogram, and selecting the probability distribution function with the minimum cumulative error as the probability distribution function of the frequency deviation out-of-limit times.
In step B1, the probability of occurrence of the out-of-limit times of the different frequency deviations is calculated by the following formula:
in the above formula, f (x) is the probability of x frequency deviation overruns, D (x) is the number of days in the last year in which x frequency deviation overruns occur, and DT is the total number of days in the last year.
In step B, the step of obtaining the confidence range of the out-of-limit frequency deviation according to the probability distribution function obtained by fitting is: and calculating the cumulative probability distribution of the probability distribution function obtained by fitting, and then calculating the confidence range of the out-of-limit times of the frequency deviation of the power grid every day under the set confidence.
The value range of the confidence coefficient m is more than 98% and less than 100%.
In the step A, the step B is carried out,
for the power grid capacity of 300 ten thousand kilowatts or more, the threshold value of the frequency deviation is +/-0.1 Hz;
for the power grid capacity below 300 ten thousand kilowatts, the threshold value of the frequency deviation is +/-0.25 Hz.
The principle of the invention is illustrated as follows:
the traditional frequency instability judging method aims at the condition that after the system generates large disturbance, the frequency has obvious instability symptoms, the frequency instability state of the system is judged in advance, and the frequency instability state of the system can not be predicted when the large disturbance does not occur. Therefore, the invention provides a frequency stability early warning method based on power grid perception data, which can early warn the frequency state of a system through the frequency fluctuation characteristic expressed by small random disturbance of the system, and can win a time window for system operation state repair and fault troubleshooting, thereby effectively reducing the frequency instability accidents of the system.
Example 1:
referring to fig. 1, a frequency stability early warning method based on power grid perception data is sequentially performed according to the following steps for a certain power grid with capacity exceeding 500 ten thousand kilowatts:
1. firstly, the threshold value of the frequency deviation of the power grid is determined to be +/-0.1 Hz according to the capacity of the power grid, then the frequency of the frequency deviation exceeding +/-0.1 Hz every day in the last year of the power grid is counted, and the result is shown in a table 1:
TABLE 1 out-of-limit frequency deviation per day of a year on a grid
2. Calculating the occurrence probability of different frequency deviation out-of-limit times by adopting the following formula:
in the above formula, f (x) is the probability of x times of frequency deviation exceeding, D (x) is the number of days of x times of frequency deviation exceeding in the last year, and DT is the total number of days of the last year;
3. the frequency deviation out-of-limit times are used as an abscissa, the occurrence probability of the frequency deviation out-of-limit times is used as an ordinate, a frequency deviation out-of-limit times probability distribution histogram is drawn, and the result is shown in FIG. 2;
4. fitting the obtained histogram by respectively adopting normal distribution, exponential distribution and generalized extreme value distribution functions to obtain a plurality of probability distribution functions, as shown in fig. 3;
5. calculating the cumulative errors between the functions obtained by normal distribution, exponential distribution and generalized extremum fitting and the histogram to be 0.883, 1.257 and 0.8246 respectively, and selecting the generalized extremum distribution fitting function as the probability distribution function of the frequency deviation out-of-limit times;
6. calculating the cumulative probability distribution of the probability distribution function obtained by fitting (see fig. 4), and then solving the confidence range of the out-of-limit times of the frequency deviation of the power grid under the confidence of 99% for 0-8.332 times each day;
7. and observing the out-of-limit frequency deviation number of the current power grid by taking days as a unit, and if the out-of-limit frequency deviation number of the continuous two days exceeds the maximum value of the confidence range, judging that the power grid has the risk of frequency instability, and monitoring the frequency modulation characteristics of the unit in the power grid.
The time sequence simulation operation of the power grid for 1 year is carried out, the frequency of the power grid with the risk of frequency instability is found to be 7 times, the frequency modulation characteristics of the unit in the power grid are monitored after the risk of frequency instability is judged to exist in the power grid every time, and the frequency instability can be effectively prevented for 2 times.
Claims (5)
1. A frequency stability early warning method based on power grid perception data is characterized by comprising the following steps:
the early warning method sequentially comprises the following steps:
step A, counting the frequency of out-of-limit frequency deviation occurring every day in one year on a power grid;
b, carrying out probability distribution function fitting of the frequency deviation out-of-limit times according to the data counted in the step A, and then solving a confidence range of the frequency deviation out-of-limit times according to the probability distribution function obtained by fitting, wherein the probability distribution function fitting of the frequency deviation out-of-limit times according to the data counted in the step A sequentially comprises the following steps:
b1, calculating the occurrence probability of different frequency deviation out-of-limit times according to the data counted in the step A;
b2, drawing a frequency deviation out-of-limit frequency probability distribution histogram by taking the frequency deviation out-of-limit frequency as an abscissa and taking the occurrence probability as an ordinate;
b3, fitting the histogram obtained in the step B2 by adopting various typical probability distribution functions respectively to obtain a plurality of probability distribution functions;
b4, respectively calculating the cumulative error between each probability distribution function and the histogram, and selecting the probability distribution function with the minimum cumulative error as the probability distribution function of the out-of-limit frequency of the frequency deviation;
and step C, observing the current out-of-limit frequency deviation number of the power grid by taking days as a unit, and if the out-of-limit frequency deviation number of the power grid for two consecutive days exceeds the maximum value of the confidence range, judging that the power grid has the risk of frequency instability, and monitoring the frequency modulation characteristics of the unit in the power grid.
2. The power grid perception data-based frequency stability early warning method according to claim 1, wherein the power grid perception data-based frequency stability early warning method comprises the following steps:
in step B1, the probability of occurrence of the out-of-limit times of the different frequency deviations is calculated by the following formula:
in the above formula, f (x) is the probability of x frequency deviation overruns, D (x) is the number of days in the last year in which x frequency deviation overruns occur, and DT is the total number of days in the last year.
3. The frequency stability early warning method based on power grid perception data as claimed in claim 1 or 2, wherein:
in step B, the step of obtaining the confidence range of the out-of-limit frequency deviation according to the probability distribution function obtained by fitting is: and calculating the cumulative probability distribution of the probability distribution function obtained by fitting, and then calculating the confidence range of the out-of-limit times of the frequency deviation of the power grid every day under the set confidence.
4. The power grid perception data-based frequency stability early warning method according to claim 3, wherein the power grid perception data-based frequency stability early warning method comprises the following steps: the value range of the confidence coefficient m is more than 98% and less than 100%.
5. The frequency stability early warning method based on power grid perception data as claimed in claim 1 or 2, wherein:
in the step A, the step B is carried out,
for the power grid capacity of 300 ten thousand kilowatts or more, the threshold value of the frequency deviation is +/-0.1 Hz;
for the power grid capacity below 300 ten thousand kilowatts, the threshold value of the frequency deviation is +/-0.25 Hz.
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