CN115236285B - Intelligent monitoring and analyzing method, equipment and storage medium for energy power system emission - Google Patents
Intelligent monitoring and analyzing method, equipment and storage medium for energy power system emission Download PDFInfo
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 241
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- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 claims abstract description 159
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- 229910018503 SF6 Inorganic materials 0.000 claims abstract description 72
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Abstract
The invention discloses an intelligent monitoring and analyzing method, equipment and a storage medium for energy power system emission, which are characterized in that the monitoring of carbon emission of switch equipment and the monitoring of carbon emission of line loss are respectively carried out on a power transmission line of a power system, and further the comprehensive carbon emission index of a target power transmission line in the current monitoring period is counted based on the monitoring result, so that the carbon emission monitoring of the power system on the side of a power grid is realized, the carbon emission monitoring of the power system is deepened, the carbon emission monitoring requirement of the whole power system is met, meanwhile, in the process of monitoring the carbon emission of the switch equipment in the power transmission line, the sulfur hexafluoride leakage amount of the switch equipment is monitored, the atmospheric environment of the installation position of the switch equipment is monitored, and the diffusion state of the sulfur hexafluoride is analyzed accordingly, so that the carbon emission coefficient of the switch equipment is comprehensively evaluated based on the sulfur hexafluoride leakage amount and the diffusion state thereof, and the comprehensiveness and the profound property of the monitoring of the carbon emission of the switch equipment are improved.
Description
Technical Field
The invention belongs to the technical field of electric power emission monitoring, in particular to an electric power carbon emission monitoring technology, and particularly relates to an intelligent monitoring and analyzing method, equipment and a storage medium for energy power system emission.
Background
In recent years, with the continuous improvement of national living standard, the demand for electric energy is increasing, and in order to meet the increasing electric energy demand of people, the power grid scale is gradually enlarged, and the power department needs to consume a large amount of coal resources in the process of producing electric energy due to the enlargement of the power grid scale, so that the emission of greenhouse gases is overlarge, and the ecological environment is polluted. In order to protect the ecological environment and achieve the aims of energy conservation and emission reduction, the monitoring of the carbon emission of the power system is particularly important.
However, most of the current carbon emission monitoring of the power system only aims at the carbon emission of the power generation side and the power utilization side, the carbon emission monitoring of the power grid side, namely the power transmission line, is neglected, on one hand, the carbon emission of the power transmission line is that sulfur hexafluoride is easy to leak in the operation process of switch equipment such as a circuit breaker, a current transformer and the like, and the greenhouse effect of sulfur hexafluoride gas is equivalent to tens of thousands of times of carbon dioxide; on the other hand, the line loss of the transmission line is increased, and the longer the transmission line is laid, the more power equipment is used, and the carbon emission is increased to a certain extent.
Therefore, the carbon emission on the power grid side also plays a very important role in the carbon emission of the whole power system, and if the carbon emission monitoring on the power grid side is ignored, the carbon emission monitoring of the power system has blind spots and limitations, so that the carbon emission monitoring requirement of the whole power system is difficult to meet.
Disclosure of Invention
Aiming at the problems, the application provides an intelligent monitoring and analyzing method, equipment and a storage medium for energy power system emission, which are used for solving the technical problem that carbon emission monitoring is omitted from a power grid side in the prior art.
In a first aspect, the invention provides an intelligent monitoring and analyzing method for energy and power system emission, comprising the following steps:
s1, marking an electric power transmission line to be subjected to carbon emission monitoring as a target transmission line, and acquiring basic parameters of the target transmission line, wherein the basic parameters comprise a wire cross section area and a wire material;
s2, counting the number of the switch devices existing on the target power transmission line, positioning the installation position of each switch device, marking each switch device as 1,2 according to a preset sequence, i, n, counting the number of power transmission towers existing on the target power transmission line, dividing the target power transmission line into a plurality of power transmission sections according to the number of the power transmission towers, and marking each power transmission section as 1,2, j, m;
s3, arranging greenhouse gas emission monitoring equipment at the installation position of each switch equipment on a target power transmission line, and arranging a current sensor on each power transmission section;
s4, setting a monitoring period, dividing the monitoring period according to a set time interval to obtain a plurality of monitoring time points, and marking the monitoring time points as 1,2 according to time sequence;
s5: the greenhouse gas emission monitoring equipment collects greenhouse gas emission parameters and atmospheric environment parameters corresponding to the switching equipment at each monitoring time point, and the current sensor collects the flowing current of each power transmission section at each monitoring time point;
s6, evaluating the leakage carbon emission coefficient corresponding to each switch device in each monitoring time point based on the greenhouse gas emission parameter and the atmospheric environment parameter corresponding to each switch device in each monitoring time point;
s7: estimating the line loss carbon emission coefficient corresponding to each power transmission section in each monitoring time point based on the basic parameters of the target power transmission line and the flowing current of each power transmission section in each monitoring time point;
s8, counting the comprehensive carbon emission index of the target power transmission line in the current monitoring period based on the leakage carbon emission coefficient corresponding to each switch device and the line loss carbon emission coefficient corresponding to each power transmission section in each monitoring time point;
s9, analyzing the leakage carbon emission coefficient corresponding to each switch device in each monitoring time point, screening dangerous switch devices of the target power transmission line in the current monitoring period, and simultaneously analyzing the line loss carbon emission coefficient corresponding to each power transmission segment in each monitoring time point, and screening dangerous power transmission segments corresponding to each monitoring time point of the target power transmission line in the current monitoring period;
and S10, carrying out background display on the comprehensive carbon emission index, the dangerous switching equipment number and the dangerous power transmission section number corresponding to each monitoring time point of the target power transmission line in the current monitoring period.
In one implementation of the first aspect of the present invention, the greenhouse gas emission monitoring device includes a sulfur hexafluoride detector, a temperature sensor, a gas flow rate meter, and a barometer.
In one implementation manner of the first aspect of the present invention, the greenhouse gas emission parameter is sulfur hexafluoride leakage, and the atmospheric environment parameter includes temperature, air flow rate and atmospheric pressure.
In one implementation manner of the first aspect of the present invention, the estimating the leakage carbon emission coefficient corresponding to each switching device in each monitoring time point in S6 specifically includes the following estimating steps:
s61: extracting temperature, air flow rate and atmospheric pressure from atmospheric environment parameters corresponding to each switch device in each monitoring time point, and calculating sulfur hexafluoride diffusion environment influence factors corresponding to each switch device in each monitoring time point according to the temperature, the air flow rate and the atmospheric pressure, wherein a calculation formula is as followsη t i is expressed as sulfur hexafluoride diffusion environment influence factor corresponding to the ith switch equipment in the T-th monitoring time point, T t i、V t i、P t i is respectively expressed as the temperature, the air flow rate and the atmospheric pressure corresponding to the ith switch equipment in the ith monitoring time point, T 0 、V 0 、P 0 Respectively expressed as a reference temperature, a reference air flow rate,Referring to the atmospheric pressure, e is expressed as a natural constant, A, B, C is expressed as a corresponding duty ratio coefficient of temperature, air flow rate and atmospheric pressure, respectively;
s62: obtaining the relative molecular mass of sulfur hexafluoride, obtaining the relative molecular mass of air, comparing the relative molecular mass of sulfur hexafluoride with the relative molecular mass of air, and calculating the diffusion rate influence factor corresponding to sulfur hexafluoride, wherein the calculation formula is as followsLambda is expressed as a diffusion rate influencing factor corresponding to sulfur hexafluoride, M is expressed as the relative molecular mass of sulfur hexafluoride, M 0 Expressed as the relative molecular mass of air, f is expressed as a preset constant;
s63: based on the sulfur hexafluoride leakage quantity, the sulfur hexafluoride diffusion environment influence factor and the diffusion rate influence factor corresponding to each switch device in each monitoring time point, the leakage carbon emission coefficient corresponding to each switch device in each monitoring time point is estimated, and the estimation formula is as follows Expressed as a leakage carbon emission coefficient, q, corresponding to the ith switching device at the nth monitoring time point t i is expressed as sulfur hexafluoride leakage quantity, q corresponding to the ith switch equipment in the t monitoring time point 0 Expressed as predefined sulfur hexafluoride alert leakage, a and b are respectively expressed as sulfur hexafluoride diffusion environment influence factors and correction coefficients corresponding to sulfur hexafluoride diffusion rate influence factors, and a+b=1.
In one implementation manner of the first aspect of the present invention, the estimating the line loss carbon emission coefficient corresponding to each power transmission segment in each monitoring time point in S7 specifically includes the following estimating steps:
s71: extracting electric wire materials from basic parameters of a target power transmission line, matching the electric wire materials with electric resistivity corresponding to various electric wire materials stored in a power transmission database, and screening out the electric resistivity corresponding to the electric wire material of the target power transmission line;
s72: extracting the wire sectional area from the basic parameters of the target power transmission line, acquiring the wire length corresponding to each power transmission section, and further importing the wire length corresponding to each power transmission section, the resistivity corresponding to the wire material of the target power transmission line and the wire sectional area corresponding to the target power transmission line into a resistance formulaObtaining the electric wire resistance corresponding to each power transmission section, wherein R j Expressed as the electric wire resistance corresponding to the j-th transmission section, ρ is expressed as the electric wire material corresponding to the target transmission line, L j The length of the electric wire corresponding to the j-th power transmission section is represented, and S is represented as the sectional area of the electric wire corresponding to the target power transmission line;
s73: calculating the electric quantity loss corresponding to each power transmission section in each monitoring time point based on the flowing current and the wire resistance of each power transmission section in each monitoring time point, wherein the calculation formula is P t j=(I t j) 2 R j ,P t j is expressed as the electric quantity loss corresponding to the j-th transmission segment in the t-th monitoring time point, I t j represents the current flowing through the jth power transmission section in the jth monitoring time point;
s74: and comparing the electric quantity loss corresponding to each power transmission section in each monitoring time point with an electric quantity loss range corresponding to preset various line loss carbon emission coefficients, and screening out the line loss carbon emission coefficients corresponding to each power transmission section in each monitoring time point.
In one implementation manner of the first aspect of the present invention, a statistical formula of the comprehensive carbon emission index of the target power transmission line in the current monitoring period is thatPsi is expressed as the comprehensive carbon emission index, χ of the target transmission line in the current monitoring period t j is expressed as a line loss carbon emission coefficient corresponding to the j-th transmission segment in the t-th monitoring time point.
In one implementation manner of the first aspect of the present invention, the specific screening steps corresponding to the dangerous switching device of the target power line in the current monitoring period are as follows:
s91: comparing the leakage carbon emission coefficients corresponding to the switch devices in each monitoring time point, screening out the switch device corresponding to the maximum leakage carbon emission coefficient in each monitoring time point, and taking the switch device as the key switch device corresponding to each monitoring time point;
s92: comparing the key switch devices corresponding to the monitoring time points with each other, judging whether the same key switch devices exist, if so, acquiring the number of the same key switch devices, meanwhile, counting the occurrence frequency of the same key switch devices, and further extracting the same key switch device with the highest occurrence frequency from the same key switch device as a static dangerous switch device of the target power transmission line in the current monitoring period;
s93: comparing the leakage carbon emission coefficients corresponding to the switch devices in each monitoring time point, and screening out the maximum leakage carbon emission coefficient and the minimum leakage carbon emission coefficient of the switch devices in the current monitoring period;
s94: substituting the maximum leakage carbon emission coefficient and the minimum leakage carbon emission coefficient of each switch device in the current monitoring period into a leakage carbon emission coefficient fluctuation degree calculation formulaCalculating the fluctuation degree of the leakage carbon emission coefficient of each switch device in the current monitoring period, wherein omega i Expressed as fluctuation degree of leakage carbon emission coefficient of ith switching device in current monitoring period, +.>The maximum leakage carbon emission coefficient and the minimum leakage carbon emission coefficient of the ith switch equipment in the current monitoring period are respectively expressed;
s95: and screening out the switching equipment with the largest fluctuation degree of the leakage carbon emission coefficient from the fluctuation degree of the leakage carbon emission coefficient of each switching equipment in the current monitoring period as the dynamic dangerous switching equipment of the target power transmission line in the current monitoring period.
In one implementation manner of the first aspect of the present invention, the specific screening manner corresponding to the dangerous power transmission section of the target power transmission line in the current monitoring period is: and comparing and analyzing the line loss carbon emission coefficient corresponding to each power transmission section in each monitoring time point, screening the power transmission section corresponding to the maximum line loss carbon emission coefficient in each monitoring time point, and taking the power transmission section as the dangerous power transmission section corresponding to each monitoring time point.
In a second aspect, the invention provides an intelligent monitoring and analyzing device for energy and power system emission, which comprises a processor, and a memory and a network interface connected with the processor; the network interface is connected with a nonvolatile memory in the server; and the processor retrieves the computer program from the nonvolatile memory through the network interface when in operation, and runs the computer program through the memory to execute the intelligent monitoring and analyzing method for the emission of the energy power system.
In a third aspect, the invention provides an intelligent monitoring and analyzing storage medium for energy and power system emission, wherein the storage medium is burnt with a computer program, and the computer program realizes the intelligent monitoring and analyzing method for energy and power system emission when running in a memory of a server.
By combining all the technical schemes, the invention has the advantages and positive effects that:
(1) According to the invention, the power transmission line of the power system is respectively subjected to the leakage carbon emission monitoring and the line loss carbon emission monitoring of the switch equipment, so that the comprehensive carbon emission index of the target power transmission line in the current monitoring period is counted based on the monitoring result, the carbon emission monitoring of the power system on the power grid side is realized, the blind point that the current carbon emission monitoring of the power system omits the carbon emission monitoring of the power grid side is filled, the carbon emission monitoring of the power system is greatly deepened, the carbon emission monitoring requirement of the whole power system is met to the greatest extent, and powerful guarantee is provided for protecting the ecological environment and realizing the energy conservation and emission reduction targets.
(2) According to the method, in the process of monitoring the carbon emission leakage of the switch equipment on the power transmission line, not only is the sulfur hexafluoride leakage amount of the switch equipment monitored, but also the atmospheric environment of the installation position of the switch equipment is monitored, and further the diffusion state of sulfur hexafluoride is quantitatively analyzed according to the monitored atmospheric environment parameters, so that the carbon emission leakage coefficient of the switch equipment is comprehensively evaluated based on the sulfur hexafluoride leakage amount and the diffusion state of the sulfur hexafluoride.
(3) According to the invention, the monitoring period is set, and the leakage carbon emission coefficient corresponding to each switch device and the line loss carbon emission coefficient corresponding to each power transmission section on the target power transmission line are monitored and analyzed at each monitoring time point, so that the dangerous switch device of the target power transmission line in the current monitoring period and the dangerous power transmission section corresponding to each monitoring time point are screened out, the back-end treatment of the carbon emission monitoring of the power transmission line is realized, the dangerous switch device and the dangerous power transmission section of the target power transmission line in the aspect of carbon emission can be intuitively and timely known by related management staff, a targeted treatment target is provided for subsequent treatment, blind treatment is avoided, and the treatment efficiency is improved.
Drawings
The invention will be further described with reference to the accompanying drawings, in which embodiments do not constitute any limitation of the invention, and other drawings can be obtained by one of ordinary skill in the art without inventive effort from the following drawings.
FIG. 1 is a flow chart of the steps of the method of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Referring to fig. 1, the invention provides an intelligent monitoring and analyzing method for energy and power system emission, which comprises the following steps:
s1, marking an electric power transmission line to be subjected to carbon emission monitoring as a target transmission line, and acquiring basic parameters of the target transmission line, wherein the basic parameters comprise a wire cross section area and a wire material;
s2, counting the number of the switch devices existing on the target power transmission line, positioning the installation position of each switch device, marking each switch device as 1,2 according to a preset sequence, i, n, counting the number of power transmission towers existing on the target power transmission line, dividing the target power transmission line into a plurality of power transmission sections according to the number of the power transmission towers, and marking each power transmission section as 1,2, j, m;
it should be noted that the specific division basis corresponding to dividing the target power transmission line into a plurality of power transmission segments according to the number of power transmission towers is that the power transmission segment between two adjacent power transmission towers is a power transmission segment;
s3, respectively arranging greenhouse gas emission monitoring equipment at the installation position of each switch equipment on a target power transmission line, and simultaneously arranging a current sensor on each power transmission section, wherein the greenhouse gas emission monitoring equipment comprises a sulfur hexafluoride detector, a temperature sensor, a gas flow rate meter and a barometer, wherein the sulfur hexafluoride detector is used for detecting sulfur hexafluoride leakage quantity of each switch equipment, and the temperature sensor, the gas flow rate meter and the barometer are used for respectively detecting temperature, air flow rate and atmospheric pressure of the corresponding installation position of each switch equipment;
s4, setting a monitoring period, dividing the monitoring period according to a set time interval to obtain a plurality of monitoring time points, and marking the monitoring time points as 1,2 according to time sequence;
s5: the greenhouse gas emission monitoring equipment collects greenhouse gas emission parameters and atmospheric environment parameters corresponding to the switching equipment at each monitoring time point, and the current sensor collects the flowing current of each power transmission section at each monitoring time point, wherein the greenhouse gas emission parameters are sulfur hexafluoride leakage quantity, and the atmospheric environment parameters comprise temperature, air flow rate and atmospheric pressure;
s6, evaluating the carbon emission coefficient of leakage corresponding to each switch device in each monitoring time point based on the greenhouse gas emission parameter and the atmospheric environment parameter corresponding to each switch device in each monitoring time point, wherein the evaluation steps are as follows:
s61: extracting temperature, air flow rate and atmospheric pressure from atmospheric environment parameters corresponding to each switch device in each monitoring time point, and calculating sulfur hexafluoride diffusion environment influence factors corresponding to each switch device in each monitoring time point according to the temperature, the air flow rate and the atmospheric pressure, wherein a calculation formula is as followsη t i is expressed as sulfur hexafluoride diffusion environment influence factor corresponding to the ith switch equipment in the T-th monitoring time point, T t i、V t i、P t i is respectively expressed as the temperature, the air flow rate and the atmospheric pressure corresponding to the ith switch equipment in the ith monitoring time point, T 0 、V 0 、P 0 Expressed as a reference temperature, a reference air flow rate, and a reference atmospheric pressure, respectively, e expressed as a natural constant, A, B, C expressed as duty ratios corresponding to the temperature, the air flow rate, and the atmospheric pressure, respectively;
in the sulfur hexafluoride diffusion environment influence factor calculation formula, the higher the temperature, the faster the air flow speed and the lower the atmospheric pressure are, the larger the sulfur hexafluoride diffusion environment influence factor is, which indicates that the stronger the sulfur hexafluoride diffusion force is;
s62: obtaining the relative molecular mass of sulfur hexafluoride, obtaining the relative molecular mass of air, comparing the relative molecular mass of sulfur hexafluoride with the relative molecular mass of air, and calculating the diffusion rate influence factor corresponding to sulfur hexafluoride, wherein the calculation formula is as followsLambda is expressed as a diffusion rate influencing factor corresponding to sulfur hexafluoride, M is expressed as the relative molecular mass of sulfur hexafluoride, M 0 Expressed as the relative molecular mass of air, f is expressed as a preset constant;
in the above formula for calculating the diffusion rate influencing factor, the larger the relative molecular mass of sulfur hexafluoride relative to the relative molecular mass of air, the smaller the diffusion rate influencing factor, indicating that the diffusion rate is slower;
s63: based on the sulfur hexafluoride leakage quantity, the sulfur hexafluoride diffusion environment influence factor and the diffusion rate influence factor corresponding to each switch device in each monitoring time point, the leakage carbon emission coefficient corresponding to each switch device in each monitoring time point is estimated, and the estimation formula is as follows Expressed as a leakage carbon emission coefficient, q, corresponding to the ith switching device at the nth monitoring time point t i is expressed as sulfur hexafluoride leakage quantity, q corresponding to the ith switch equipment in the t monitoring time point 0 Expressed as predefined sulfur hexafluoride alert leakage, a and b are respectively expressed as sulfur hexafluoride diffusion environment influence factors and correction coefficients corresponding to sulfur hexafluoride diffusion rate influence factors, and a+b=1.
It should be noted that, in the estimation formula of the carbon emission coefficient of leakage, the influence of the sulfur hexafluoride leakage amount on the carbon emission coefficient of leakage is positive, and the influence of the sulfur hexafluoride diffusion environment influence factor and the sulfur hexafluoride diffusion rate influence factor on the carbon emission coefficient of leakage is negative, because the larger the sulfur hexafluoride diffusion environment influence factor and the sulfur hexafluoride diffusion rate influence factor are, the more easily the sulfur hexafluoride is diluted and is thus less easily accumulated, the greenhouse effect generated under the condition is smaller than the greenhouse effect generated under the state of accumulation of sulfur hexafluoride, so that the influence on the carbon emission coefficient of leakage is smaller;
according to the embodiment of the invention, in the process of monitoring the carbon emission leakage of the switch equipment on the power transmission line, not only the sulfur hexafluoride leakage amount of the switch equipment is monitored, but also the atmospheric environment of the installation position of the switch equipment is monitored, and the diffusion state of sulfur hexafluoride is quantitatively analyzed according to the monitored atmospheric environment parameters, so that the carbon emission leakage coefficient of the switch equipment is comprehensively evaluated based on the sulfur hexafluoride leakage amount and the diffusion state of the sulfur hexafluoride.
S7: based on basic parameters of a target power transmission line and flowing currents of power transmission sections in each monitoring time point, estimating line loss carbon emission coefficients corresponding to the power transmission sections in each monitoring time point, wherein the specific estimating steps are as follows:
s71: extracting electric wire materials from basic parameters of a target power transmission line, matching the electric wire materials with electric resistivity corresponding to various electric wire materials stored in a power transmission database, and screening out the electric resistivity corresponding to the electric wire material of the target power transmission line;
s72: extracting the wire sectional area from the basic parameters of the target power transmission line, acquiring the wire length corresponding to each power transmission section, and further importing the wire length corresponding to each power transmission section, the resistivity corresponding to the wire material of the target power transmission line and the wire sectional area corresponding to the target power transmission line into a resistance formulaObtaining the electric wire resistance corresponding to each power transmission section, wherein R j Expressed as the electric wire resistance corresponding to the j-th transmission section, ρ is expressed as the electric wire material corresponding to the target transmission line, L j The length of the electric wire corresponding to the j-th power transmission section is represented, S is represented as the sectional area of the electric wire corresponding to the target power transmission line, wherein the longer the electric wire length is, the smaller the sectional area of the electric wire is, and the larger the electric wire resistance is;
s73: based on eachThe electric quantity loss corresponding to each power transmission section in each monitoring time point is calculated by the flowing current and the wire resistance of each power transmission section in each monitoring time point, and the calculation formula is P t j=(I t j) 2 R j ,P t j is expressed as the electric quantity loss corresponding to the j-th transmission segment in the t-th monitoring time point, I t j represents the current flowing through the jth power transmission section in the jth monitoring time point;
s74: and comparing the electric quantity loss corresponding to each power transmission section in each monitoring time point with an electric quantity loss range corresponding to preset various line loss carbon emission coefficients, and screening out the line loss carbon emission coefficients corresponding to each power transmission section in each monitoring time point.
S8, counting the comprehensive carbon emission index of the target power transmission line in the current monitoring period based on the leakage carbon emission coefficient corresponding to each switch device and the line loss carbon emission coefficient corresponding to each power transmission section in each monitoring time point, wherein the counting formula is as followsPsi is expressed as the comprehensive carbon emission index, χ of the target transmission line in the current monitoring period t j represents a line loss carbon emission coefficient corresponding to a j-th transmission section in a t-th monitoring time point;
according to the embodiment of the invention, the power transmission line of the power system is respectively monitored for the leakage carbon emission and the line loss carbon emission of the switch equipment, so that the comprehensive carbon emission index of the target power transmission line in the current monitoring period is counted based on the monitoring result, the carbon emission monitoring of the power system on the power grid side is realized, the blind point that the current carbon emission monitoring of the power system omits the carbon emission monitoring of the power grid side is filled, the carbon emission monitoring of the power system is greatly deepened, the carbon emission monitoring requirement of the whole power system is met to the greatest extent, and a powerful guarantee is provided for protecting the ecological environment and realizing the energy conservation and emission reduction targets.
S9, analyzing the leakage carbon emission coefficient corresponding to each switch device in each monitoring time point, and screening dangerous switch devices of the target power transmission line in the current monitoring period from the leakage carbon emission coefficient, wherein the specific screening steps are as follows:
s91: comparing the leakage carbon emission coefficients corresponding to the switch devices in each monitoring time point, screening out the switch device corresponding to the maximum leakage carbon emission coefficient in each monitoring time point, and taking the switch device as the key switch device corresponding to each monitoring time point;
s92: comparing the key switch devices corresponding to the monitoring time points with each other, judging whether the same key switch devices exist, if so, acquiring the number of the same key switch devices, meanwhile, counting the occurrence frequency of the same key switch devices, and further extracting the same key switch device with the highest occurrence frequency from the same key switch device as a static dangerous switch device of the target power transmission line in the current monitoring period;
s93: comparing the leakage carbon emission coefficients corresponding to the switch devices in each monitoring time point, and screening out the maximum leakage carbon emission coefficient and the minimum leakage carbon emission coefficient of the switch devices in the current monitoring period;
s94: substituting the maximum leakage carbon emission coefficient and the minimum leakage carbon emission coefficient of each switch device in the current monitoring period into a leakage carbon emission coefficient fluctuation degree calculation formulaCalculating the fluctuation degree of the leakage carbon emission coefficient of each switch device in the current monitoring period, wherein omega i Expressed as fluctuation degree of leakage carbon emission coefficient of ith switching device in current monitoring period, +.>The maximum leakage carbon emission coefficient and the minimum leakage carbon emission coefficient of the ith switch equipment in the current monitoring period are respectively expressed;
s95: screening out the switching equipment with the largest fluctuation degree of the leakage carbon emission coefficient from the fluctuation degree of the leakage carbon emission coefficient of each switching equipment in the current monitoring period as the dynamic dangerous switching equipment of the target power transmission line in the current monitoring period;
in a specific embodiment, in the process of screening dangerous switching equipment, the static dangerous switching equipment and the dynamic dangerous switching equipment of the target power transmission line in the current monitoring period are comprehensively screened out by considering the difference between static leakage carbon emission and dynamic leakage carbon emission, so that the screening mode of the dangerous switching equipment is perfected, and the method has the characteristic of strong practicability;
s9, analyzing the line loss carbon emission coefficient corresponding to each power transmission section in each monitoring time point, and screening out dangerous power transmission sections corresponding to each monitoring time point of the target power transmission line in the current monitoring period, wherein the specific screening mode is as follows: comparing and analyzing the line loss carbon emission coefficient corresponding to each power transmission section in each monitoring time point, screening the power transmission section corresponding to the maximum line loss carbon emission coefficient in each monitoring time point from the line loss carbon emission coefficient, and taking the power transmission section as a dangerous power transmission section corresponding to each monitoring time point;
and S10, carrying out background display on the comprehensive carbon emission index, the dangerous switching equipment number and the dangerous power transmission section number corresponding to each monitoring time point of the target power transmission line in the current monitoring period.
According to the embodiment of the invention, the monitoring period is set, the leakage carbon emission coefficient corresponding to each switch device and the line loss carbon emission coefficient corresponding to each power transmission section on the target power transmission line are monitored and analyzed at each monitoring time point, so that the dangerous switch device of the target power transmission line in the current monitoring period and the dangerous power transmission section corresponding to each monitoring time point are screened out, the back-end treatment of the carbon emission monitoring of the power transmission line is realized, related management staff can intuitively and timely know the dangerous switch device and the dangerous power transmission section of the target power transmission line in the aspect of carbon emission, a targeted treatment target is provided for subsequent treatment, blind treatment is avoided, and the treatment efficiency is improved.
Example 2
The invention provides intelligent monitoring and analyzing equipment for energy power system emission, which comprises a processor, and a memory and a network interface which are connected with the processor; the network interface is connected with a nonvolatile memory in the server; and the processor retrieves the computer program from the nonvolatile memory through the network interface when in operation, and runs the computer program through the memory to execute the intelligent monitoring and analyzing method for the emission of the energy power system.
Example 3
The invention provides an intelligent monitoring and analyzing storage medium for energy power system emission, which is burnt with a computer program, and the computer program realizes the intelligent monitoring and analyzing method for energy power system emission when running in a memory of a server.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art can be made to the described embodiments without departing from the scope of the invention or from the scope of the invention as defined in the accompanying claims.
Claims (5)
1. The intelligent monitoring and analyzing method for the emission of the energy power system is characterized by comprising the following steps of:
s1, marking an electric power transmission line to be subjected to carbon emission monitoring as a target transmission line, and acquiring basic parameters of the target transmission line, wherein the basic parameters comprise a wire cross section area and a wire material;
s2, counting the number of the switch devices existing on the target power transmission line, positioning the installation position of each switch device, marking each switch device as 1,2 according to a preset sequence, i, n, counting the number of power transmission towers existing on the target power transmission line, dividing the target power transmission line into a plurality of power transmission sections according to the number of the power transmission towers, and marking each power transmission section as 1,2, j, m;
s3, arranging greenhouse gas emission monitoring equipment at the installation position of each switch equipment on a target power transmission line, and arranging a current sensor on each power transmission section;
s4, setting a monitoring period, dividing the monitoring period according to a set time interval to obtain a plurality of monitoring time points, and marking the monitoring time points as 1,2 according to time sequence;
s5: the greenhouse gas emission monitoring equipment collects greenhouse gas emission parameters and atmospheric environment parameters corresponding to the switching equipment at each monitoring time point, and the current sensor collects the flowing current of each power transmission section at each monitoring time point;
s6, evaluating the leakage carbon emission coefficient corresponding to each switch device in each monitoring time point based on the greenhouse gas emission parameter and the atmospheric environment parameter corresponding to each switch device in each monitoring time point;
s7: estimating the line loss carbon emission coefficient corresponding to each power transmission section in each monitoring time point based on the basic parameters of the target power transmission line and the flowing current of each power transmission section in each monitoring time point;
s8, counting the comprehensive carbon emission index of the target power transmission line in the current monitoring period based on the leakage carbon emission coefficient corresponding to each switch device and the line loss carbon emission coefficient corresponding to each power transmission section in each monitoring time point;
s9, analyzing the leakage carbon emission coefficient corresponding to each switch device in each monitoring time point, screening dangerous switch devices of the target power transmission line in the current monitoring period, and simultaneously analyzing the line loss carbon emission coefficient corresponding to each power transmission segment in each monitoring time point, and screening dangerous power transmission segments corresponding to each monitoring time point of the target power transmission line in the current monitoring period;
s10, carrying out background display on the comprehensive carbon emission index, the dangerous switching equipment number and the dangerous power transmission section number corresponding to each monitoring time point of the target power transmission line in the current monitoring period;
the step S6 of evaluating the leakage carbon emission coefficient corresponding to each switch device in each monitoring time point specifically comprises the following evaluation steps:
s61: extracting temperature, air flow rate and atmospheric pressure from atmospheric environment parameters corresponding to each switch device in each monitoring time point, and calculating sulfur hexafluoride diffusion environment influence factors corresponding to each switch device in each monitoring time point according to the temperature, the air flow rate and the atmospheric pressure, wherein a calculation formula is as followsη t i is expressed as sulfur hexafluoride diffusion environment influence factor corresponding to the ith switch equipment in the T-th monitoring time point, T t i、V t i、P t i is respectively expressed as the temperature, the air flow rate and the atmospheric pressure corresponding to the ith switch equipment in the ith monitoring time point, T 0 、V 0 、P 0 Expressed as a reference temperature, a reference air flow rate, and a reference atmospheric pressure, respectively, e expressed as a natural constant, A, B, C expressed as duty ratios corresponding to the temperature, the air flow rate, and the atmospheric pressure, respectively;
s62: obtaining the relative molecular mass of sulfur hexafluoride, obtaining the relative molecular mass of air, comparing the relative molecular mass of sulfur hexafluoride with the relative molecular mass of air, calculating the diffusion rate influence factor corresponding to sulfur hexafluoride, and adopting a calculation formula ofLambda is expressed as a diffusion rate influencing factor corresponding to sulfur hexafluoride, M is expressed as the relative molecular mass of sulfur hexafluoride, M 0 Expressed as the relative molecular mass of air, f is expressed as a preset constant;
s63: based on the sulfur hexafluoride leakage quantity, the sulfur hexafluoride diffusion environment influence factor and the diffusion rate influence factor corresponding to each switch device in each monitoring time point, the carbon emission coefficient of leakage corresponding to each switch device in each monitoring time point is estimated, and an estimation formula is as follows Expressed as a leakage carbon emission coefficient, q, corresponding to the ith switching device at the nth monitoring time point t i is expressed as sulfur hexafluoride leakage quantity, q corresponding to the ith switch equipment in the t monitoring time point 0 The sulfur hexafluoride warning leakage quantity is expressed as predefined sulfur hexafluoride diffusion environment influence factors, correction coefficients corresponding to the sulfur hexafluoride diffusion rate influence factors are expressed as sulfur hexafluoride diffusion environment influence factors, and a+b=1;
the step S7 of evaluating the carbon emission coefficient of the line loss corresponding to each power transmission section in each monitoring time point specifically comprises the following evaluation steps:
s71: extracting electric wire materials from basic parameters of a target power transmission line, matching the electric wire materials with resistivity corresponding to various electric wire materials stored in a power transmission database, and screening out the resistivity corresponding to the electric wire materials of the target power transmission line;
s72: extracting the wire sectional area from the basic parameters of the target power transmission line, acquiring the wire length corresponding to each power transmission section, and further importing the wire length corresponding to each power transmission section, the resistivity corresponding to the wire material of the target power transmission line and the wire sectional area corresponding to the target power transmission line into a resistance formulaObtaining the electric wire resistance corresponding to each power transmission section, wherein R j Expressed as the electric wire resistance corresponding to the j-th transmission section, ρ is expressed as the electric wire material corresponding to the target transmission line, L j The length of the electric wire corresponding to the j-th power transmission section is represented, and S is represented as the sectional area of the electric wire corresponding to the target power transmission line;
s73: calculating the electric quantity loss corresponding to each power transmission section in each monitoring time point based on the flowing current and the wire resistance of each power transmission section in each monitoring time point, wherein a calculation formula is P t j=(I t j) 2 R j ,P t j is expressed as the electric quantity loss corresponding to the j-th transmission segment in the t-th monitoring time point, I t j represents the current flowing through the jth power transmission section in the jth monitoring time point;
s74: comparing the electric quantity loss corresponding to each power transmission section in each monitoring time point with the electric quantity loss range corresponding to the preset various line loss carbon emission coefficients, and screening out the line loss carbon emission coefficients corresponding to each power transmission section in each monitoring time point;
the statistical formula of the comprehensive carbon emission index of the target power transmission line in the current monitoring period is thatPsi is expressed as the comprehensive carbon emission index, χ of the target transmission line in the current monitoring period t j is represented as the tth monitorMeasuring a line loss carbon emission coefficient corresponding to a j-th transmission section in a time point;
the specific screening steps corresponding to the dangerous switching equipment of the screened target power transmission line in the current monitoring period are as follows:
s91: comparing the leakage carbon emission coefficients corresponding to the switch devices in each monitoring time point, screening out the switch device corresponding to the largest leakage carbon emission coefficient in each monitoring time point, and taking the switch device corresponding to the largest leakage carbon emission coefficient in each monitoring time point as the key switch device corresponding to each monitoring time point;
s92: comparing the key switch devices corresponding to the monitoring time points with each other, judging whether the same key switch devices exist, if so, acquiring the number of the same key switch devices, meanwhile, counting the occurrence frequency of the same key switch devices, and further extracting the same key switch device with the highest occurrence frequency from the same key switch device as a static dangerous switch device of the target power transmission line in the current monitoring period;
s93: comparing the leakage carbon emission coefficients corresponding to the switch devices in each monitoring time point, and screening out the maximum leakage carbon emission coefficient and the minimum leakage carbon emission coefficient of the switch devices in the current monitoring period;
s94: substituting the maximum leakage carbon emission coefficient and the minimum leakage carbon emission coefficient of each switch device in the current monitoring period into a leakage carbon emission coefficient fluctuation degree calculation formulaCalculating the fluctuation degree of the leakage carbon emission coefficient of each switch device in the current monitoring period, wherein omega i Expressed as fluctuation degree of leakage carbon emission coefficient of ith switching device in current monitoring period, +.>The maximum leakage carbon emission coefficient and the minimum leakage carbon emission coefficient of the ith switch equipment in the current monitoring period are respectively expressed;
s95: screening out the switching equipment with the largest fluctuation degree of the leakage carbon emission coefficient from the fluctuation degree of the leakage carbon emission coefficient of each switching equipment in the current monitoring period as the dynamic dangerous switching equipment of the target power transmission line in the current monitoring period;
the specific screening method for screening out the dangerous power transmission section of the target power transmission line in the current monitoring period comprises the following steps: and comparing and analyzing the line loss carbon emission coefficient corresponding to each power transmission section in each monitoring time point, screening the power transmission section corresponding to the maximum line loss carbon emission coefficient in each monitoring time point, and taking the power transmission section corresponding to the maximum line loss carbon emission coefficient in each monitoring time point as the dangerous power transmission section corresponding to each monitoring time point.
2. The intelligent monitoring and analyzing method for energy and power system emission according to claim 1, wherein the method comprises the following steps: the greenhouse gas emission monitoring device comprises a sulfur hexafluoride detector, a temperature sensor, a gas flow rate meter and a barometer.
3. The intelligent monitoring and analyzing method for energy and power system emission according to claim 1, wherein the method comprises the following steps: the greenhouse gas emission parameter is sulfur hexafluoride leakage, and the atmospheric environment parameters include temperature, air flow rate and atmospheric pressure.
4. The intelligent monitoring and analyzing equipment for the emission of the energy power system is characterized by comprising a processor, and a memory and a network interface which are connected with the processor; the network interface is connected with a nonvolatile memory in the server; the processor, when running, retrieving a computer program from the non-volatile memory via the network interface and running the computer program via the memory to perform the method of any of the preceding claims 1-3.
5. An intelligent monitoring and analyzing storage medium for energy and power system emission, which is characterized in that: the storage medium having a computer program recorded thereon, the computer program implementing the method of any of the preceding claims 1-3 when run in the memory of a server.
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Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103218690A (en) * | 2013-04-23 | 2013-07-24 | 清华大学 | Method for measuring carbon emission quantities during power consumption by active power distribution network users and based on carbon emission flow |
CN107367435A (en) * | 2016-05-13 | 2017-11-21 | 国家电网公司 | Carbon emission amount accounting method containing sulfur hexafluoride electrical equipment in network system |
CN110416914A (en) * | 2019-07-10 | 2019-11-05 | 河池学院 | A kind of high voltage transmission line intelligent monitoring system and monitoring method |
CN112865295A (en) * | 2019-11-27 | 2021-05-28 | 杭州绿安智能电网技术有限公司 | Power transmission line operation monitoring system for smart power grid |
CN114611966A (en) * | 2022-03-18 | 2022-06-10 | 武汉胜天地消防工程有限公司 | Intelligent quantitative evaluation method for power transmission and transformation operation safety of smart power grid power system |
CN114626570A (en) * | 2021-12-07 | 2022-06-14 | 国网天津市电力公司 | Power carbon emission trajectory analysis method and device |
Family Cites Families (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US9563215B2 (en) * | 2012-07-14 | 2017-02-07 | Causam Energy, Inc. | Method and apparatus for actively managing electric power supply for an electric power grid |
WO2019193583A2 (en) * | 2018-04-05 | 2019-10-10 | Russell Blades | Methods, systems, apparatuses and devices for facilitating provisioning of audit data related to energy consumption, water consumption, water quality, greenhouse gas emissions, and air emissions using blockchain |
-
2022
- 2022-07-27 CN CN202210888222.6A patent/CN115236285B/en active Active
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103218690A (en) * | 2013-04-23 | 2013-07-24 | 清华大学 | Method for measuring carbon emission quantities during power consumption by active power distribution network users and based on carbon emission flow |
CN107367435A (en) * | 2016-05-13 | 2017-11-21 | 国家电网公司 | Carbon emission amount accounting method containing sulfur hexafluoride electrical equipment in network system |
CN110416914A (en) * | 2019-07-10 | 2019-11-05 | 河池学院 | A kind of high voltage transmission line intelligent monitoring system and monitoring method |
CN112865295A (en) * | 2019-11-27 | 2021-05-28 | 杭州绿安智能电网技术有限公司 | Power transmission line operation monitoring system for smart power grid |
CN114626570A (en) * | 2021-12-07 | 2022-06-14 | 国网天津市电力公司 | Power carbon emission trajectory analysis method and device |
CN114611966A (en) * | 2022-03-18 | 2022-06-10 | 武汉胜天地消防工程有限公司 | Intelligent quantitative evaluation method for power transmission and transformation operation safety of smart power grid power system |
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