CN117554746A - Power distribution network fault diagnosis system based on digital twin - Google Patents
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Abstract
The invention discloses a digital twin-based power distribution network fault diagnosis system which comprises a model building module, a data acquisition module, a fault parameter analysis module, a fault diagnosis evaluation module and a fault early warning module.
Description
Technical Field
The invention belongs to the technical field of power transmission fault diagnosis of a power distribution network, and particularly relates to a power distribution network fault diagnosis system based on digital twin.
Background
The distribution network is an important component in the power system, and is used for transmitting power to terminal appliances and terminal equipment, transmitting and distributing the power transmitted to the distribution network to each electric equipment through cables, wires and transformer equipment, and is widely applied to household power, industrial power, commercial power, urban basic application power and agricultural power, and is an indispensable part of the current social power development.
However, when the method is actually used, more defects still exist, such as that the traditional power distribution network fault detection method is mostly operated and maintained in a manual regular inspection mode, the efficiency is low, the flexibility is lacking in the process, the detection precision is relatively low, some potential faults can not be found in time, so that potential safety hazards are caused for the operation and the user power consumption of the power distribution network, meanwhile, the traditional power distribution network fault detection method lacks the support of automatic and intelligent technical means, the real-time monitoring and the fault early warning can not be realized, and the manual processing and the inspection are relied on, so that the operation and the maintenance work of the power distribution network are not convenient and efficient.
Disclosure of Invention
The invention aims to solve the technical problems that: the utility model provides a distribution network fault diagnosis system based on digital twin, in order to solve traditional distribution network fault detection method lack the support of automation and intelligent technical means, can't realize real-time supervision and fault early warning, rely on manual processing to troubleshoot for the operation of distribution network and maintenance work are not convenient enough and high-efficient scheduling problem.
The technical scheme of the invention is as follows:
a digital twinning-based power distribution network fault diagnosis system, comprising:
and a model building module: and constructing a digital twin model of the power distribution network by using a digital twin technology, and simulating the actual running condition of the power distribution network through the digital twin model of the power distribution network.
Description: the digital twin technology can simulate the attribute, parameter and running state of a physical entity, and through experiments and tests on the power distribution network in a virtual environment, the cost and risk of the experiments in a real environment are reduced, and the cost is saved.
Further, the method for building the digital twin model of the power distribution network comprises the following steps:
the method comprises the steps of carrying out detailed mapping and data collection on a real power distribution network, including all details of lines, equipment and connection points of the power distribution network, then modeling the power distribution network by using a digital twin technology, and digitizing all details;
data acquisition and processing: acquiring operation data of all devices in the power distribution network, including states, operation conditions and environmental parameters of the devices, and then processing and analyzing the data to extract data affecting the operation of the power distribution network;
constructing a digital twin model: constructing a data model of the power distribution network according to the equipment information of the power distribution network, and combining the extracted power distribution network operation data with the data model to obtain a digital twin model of the power distribution network;
model verification and correction: and comparing the model with an actual power distribution network, verifying the accuracy and feasibility of the model, and correcting and optimizing the inaccurate place of the digital twin model.
And a data acquisition module: based on the actual running condition of the distribution network simulated by the digital twin model of the distribution network, the power running data of the distribution network are collected, wherein the power running data comprise the state, running condition and environmental parameters of equipment, and specifically comprise voltage and current of the distribution network equipment and a running change value, voltage and current resistance of a distribution network line and a running change value, a power set value, a current set value, a temperature set value and a time set value.
The fault parameter acquisition module is used for: the fault parameter acquisition module is used for acquiring a fault parameter value of the power distribution network from the operation data of the power distribution network, and comprises: the system comprises a stability index acquisition unit, an environment influence index acquisition unit and a power loss index acquisition unit, wherein the stability index acquisition unit is used for calculating to obtain a stability evaluation index, the environment influence index is used for calculating to obtain an environment influence index, and the power loss index acquisition unit is used for calculating to obtain an abnormal loss performance index.
And a fault parameter analysis module: based on the information obtained by the fault parameter obtaining module, the stability evaluation index, the environment influence index and the abnormal loss performance index of the power distribution network are obtained through analysis.
The fault parameter analysis module comprises: the system comprises a stability index analysis unit, an environment influence analysis unit and a power loss analysis unit, wherein the stability index analysis unit is used for calculating to obtain a stability evaluation index, the environment influence analysis unit is used for calculating to obtain an environment influence index, and the power loss index analysis unit is used for calculating to obtain an abnormal loss performance index.
Fault diagnosis and evaluation module: based on the stability evaluation index, the environment influence index and the abnormal loss performance index which are obtained by the analysis of the fault analysis module, the quality evaluation coefficient of the power distribution network is obtained, and is compared with a preset quality evaluation coefficient, and corresponding processing is carried out.
And the fault early warning module is used for: the monitoring nodes used for screening the power distribution network in the abnormal working state are sent to a power distribution network supervision center, and the digital model is used for extracting abnormal state characteristics and carrying out corresponding early warning processing.
Preferably, the specific acquisition mode of the fault parameter value of the power distribution network by the fault parameter acquisition module is as follows:
stability index acquisition unit: the method comprises the steps that a power sensor is arranged in a power distribution network, and stability parameters of a control end of the power distribution network and stability parameters of a user operation terminal are collected; the control end stability parameters of the power distribution network comprise: the fault times, the fault duration, the fault control precision and the fault response speed are respectively marked as nl, hl, jl, sl; the user operation terminal stability parameters include: fault frequency, harmonic current and energy consumption indexes are respectively marked as pl, xl and nh;
an environmental impact index acquisition unit: the method is used for collecting environmental influence factors of power distribution network operation, wherein the environmental influence factors comprise: ambient humidity, ambient air pressure, ambient temperature, wind speed, respectively labeled gx, gy, gw, fv;
a power loss index acquisition unit: a electric power loss data for setting up power sensor, gather distribution network monitoring node, electric power loss data includes: resistance loss, inductance loss, current loss, respectively marked as: dp, dz, el.
Preferably, the method for calculating the stability parameter of the user operation terminal comprises the following steps:
the failure frequency refers to the number of times of failure in the running process of the power distribution network in unit time, and the calculation formula is as follows:
pl＝nl*hc
where pl represents the failure frequency, nl represents the number of failures, hc represents the total time of operation; the harmonic current is a non-sinusoidal characteristic current which is superimposed on a main power supply and is introduced by equipment or a system, and the calculation formula is as follows:
xl＝l1*(k 1 *wt+k 2 *2wt+k 3 *3wt+...+k n *nwt)
where xl represents the harmonic current, l1 represents the magnitude of the fundamental current, k 1 、k 2 、k 3 、k n Coefficients representing the respective harmonic currents, w representing the fundamental frequency, t representing time, and n representing the harmonic times; the energy consumption index refers to the proportion of the power loss of each link in the power supply amount during the power transmission and distribution process of the power grid, and the calculation formula is as follows:
wherein nh represents an energy consumption index, zd represents a power supply quantity, zh represents a sales quantity, and y represents a time set value.
Preferably, the method for calculating the stability evaluation index comprises the following steps:
substituting the power distribution network fault times, fault duration, control precision, response speed, fault frequency and harmonic current into a formula:
wherein beta represents a stability evaluation index of the power distribution network, nl represents the number of faults of the power distribution network, hl represents the duration of the faults, jl represents the control accuracy of the faults, sl represents the response speed of the faults, pl represents the frequency of the faults, xl represents the harmonic current, mu 1 、μ 2 The fault detection method is respectively expressed as other influencing factors of the power distribution network faults;
and (3) the environmental influence factors of the power distribution network: the ambient humidity, ambient air pressure and ambient temperature are substituted into the formula:
wherein λ represents an environmental impact index, σ 1 Other influencing factors of the fault environment are represented, gx represents ambient humidity, gy represents ambient air pressure, gw represents ambient temperature, and e represents a natural constant.
Based on the power loss data of the power distribution network monitoring node, the power loss data comprises: the method comprises the steps of obtaining abnormal loss performance indexes by resistance loss, inductance loss and current loss, wherein the resistance loss is generated when current passes through a cable, and is related to the sectional area of a conductor material of the cable, the length of the cable and the current, and the calculation formula is as follows:
wherein dp represents resistance loss, I represents circuit output current, R represents line resistance, m represents conductor material sectional area, and q represents cable length; the inductance loss refers to the loss caused by self inductance and mutual inductance effect caused by a magnetic field generated when current passes through the cable, and the calculation formula is as follows:
dz＝I∧2RL
where dz represents the inductance loss and L represents the line inductance value; the current loss refers to energy loss generated when current flows through the resistor, and the calculation formula is as follows: el=l×r×z, where el represents current loss, l represents a current set value, R represents line resistance, and z represents a transmission distance;
the resistance loss, the inductance loss and the current loss obtained by the joint analysis are used for obtaining an abnormal loss performance index, and the abnormal loss performance index is calculated according to the formula:
wherein the method comprises the steps ofThe abnormal loss performance index is represented by dp, the resistive loss, dz, the inductive loss, el, the current loss, s, the loss rate evaluation factor, and hz, the loss time evaluation factor.
Preferably, the quality evaluation coefficient is calculated by the following steps:
where θ represents a quality evaluation coefficient of the power distribution network, λ represents an environmental impact index, β represents a stability evaluation index,representing the loss performance index.
Preferably, the specific evaluation mode of the fault diagnosis evaluation module is as follows:
and acquiring a quality evaluation coefficient of each monitoring node of the power distribution network, extracting abnormal state characteristics by using a digital twin model, comparing the abnormal state characteristics with a preset quality evaluation coefficient, and if the quality evaluation coefficient is larger than the preset quality evaluation coefficient, indicating that the monitoring nodes of the power distribution network are abnormal, otherwise, indicating that the monitoring nodes of the power distribution network are normal in operation and have no faults.
Preferably, the fault early warning module specifically comprises:
the method is used for screening each monitoring node of the power distribution network in an abnormal working state, counting the data of each monitoring node of the power distribution network in the abnormal working state, sending the data to a power distribution network supervision center, extracting abnormal state characteristics by utilizing a digital twin model, quickly acquiring fault information and occurrence positions, sending early warning to management staff, and correspondingly processing according to the received typical fault types to realize effective fault removal.
The invention has the beneficial effects that:
according to the invention, the actual running condition of the power distribution network is simulated by establishing a digital twin model, the fault parameter values of monitoring nodes of the power distribution network are obtained by utilizing a digital twin technology, the stability evaluation index, the environment influence index and the abnormal loss performance index of each monitoring node of the power distribution network are further obtained, the quality evaluation coefficient is obtained by analysis and is compared with the preset quality evaluation coefficient, the monitoring nodes of the power distribution network in an abnormal working state are screened and sent to a power distribution network supervision center, the abnormal state characteristic extraction is carried out by utilizing the digital twin model, the corresponding early warning processing is carried out, the reliability and the stability of the power distribution network are improved, the more advanced and intelligent fault diagnosis technology is adopted, the real-time monitoring and the fault early warning of the power distribution network are realized, and the precision and the efficiency of fault detection are improved.
Drawings
Fig. 1 is a block diagram of the overall structure of a system module according to the present invention.
Fig. 2 is a schematic diagram of a fault parameter acquisition module according to the present invention.
Detailed Description
Example 1
The invention provides a digital twin-based power distribution network fault diagnosis system as shown in fig. 1, which comprises a model building module, a data acquisition module, a fault parameter analysis module, a fault diagnosis evaluation module and a fault early warning module.
The model building module builds a digital twin model of the power distribution network by utilizing a digital twin technology, simulates actual running conditions of the power distribution network, and builds a full life cycle model of a power distribution network line and equipment in a digital modeling mode;
the data acquisition module simulates actual running conditions of the power distribution network based on the digital twin model of the power distribution network, acquires power running data of the power distribution network, and the power distribution network running data comprise: power set point, current set point, temperature set point, time set point;
the fault parameter acquisition module filters and calibrates the data based on the power operation data acquired by the data acquisition module, removes impurities and redundant information in the data, and acquires a fault parameter value of the power distribution network;
the power distribution network fault parameter values include: a stability index acquisition unit, an environmental impact index acquisition unit, and a power loss index acquisition unit;
the fault parameter acquisition module is based on the fault parameter acquisition module, a stability evaluation index is calculated through a stability index acquisition unit, an environment influence index is calculated through an environment influence index acquisition unit, and an abnormal loss performance index is calculated through an electric power loss index acquisition unit;
the fault parameter analysis module calculates a quality evaluation coefficient based on the stability evaluation index, the environment influence index and the abnormal loss performance index acquired by the fault parameter acquisition module;
the fault diagnosis evaluation module is used for acquiring a quality evaluation coefficient of the power distribution network, comparing the quality evaluation coefficient with a preset quality evaluation coefficient and carrying out corresponding processing;
the fault early warning module is used for screening monitoring nodes of the power distribution network in abnormal working states, sending the monitoring nodes to a power distribution network supervision center, extracting abnormal state characteristics by using a digital model, and carrying out corresponding early warning processing.
In the embodiment of the present invention, it should be explained that the specific building manner of the model building module is:
based on the digital twin concept, the digital model is utilized to simulate the real-time operation of the power distribution network, and the digital twin model of the power distribution network is constructed to establish the full life cycle model of the power distribution network line and equipment data in a digital modeling mode.
In the embodiment of the present invention, it should be explained that the specific acquisition mode of the data acquisition module is:
the method is used for simulating the actual operation condition of the distribution network by the digital twin model of the distribution network, collecting the power operation data of the distribution network, wherein the power operation data of the distribution network comprises the following steps: the power set point, the current set point, the temperature set point, and the time set point are respectively marked as follows: g. l, d, y.
Referring to fig. 2, in the embodiment of the present invention, it should be explained that the specific method for obtaining the fault parameter value of the power distribution network by the fault parameter obtaining module is as follows:
stability index acquisition unit: the method comprises the steps of setting a power sensor, and collecting stability parameters of a control end of a power distribution network and stability parameters of a user operation terminal;
the control end stability parameters of the power distribution network comprise: the fault times, the fault duration, the fault control precision and the fault response speed are respectively marked as nl, hl, jl, sl;
the stability parameters of the user operation terminal include: fault frequency, harmonic current and energy consumption indexes are respectively marked as pl, xl and nh;
an environmental impact index acquisition unit: the method is used for collecting environmental influence factors of power distribution network operation, wherein the environmental influence factors comprise: the ambient humidity, the ambient air pressure and the ambient temperature are respectively marked as gx, gy and gw;
a power loss index acquisition unit: a electric power loss data for setting up power sensor, gather distribution network monitoring node, electric power loss data includes: resistance loss, inductance loss, current loss, respectively marked as: dp, dz, el.
In the embodiment of the present invention, it should be explained that the method for calculating the stability parameter of the user operation terminal is as follows:
the failure frequency refers to the number of times of common failure in the running process of the power distribution network in unit time, and the calculation formula is as follows: pl=nl×hc, where pl represents the failure frequency and nl representsThe number of faults, hc, represents the total time of operation; the harmonic current is a non-sinusoidal characteristic current which is superimposed on a main power supply and is introduced by equipment or a system, and the calculation formula is as follows: xl=l1 (k 1 *wt+k 2 *2wt+k 3 *3wt+...+k n * nwt), where xl denotes the harmonic current, l1 denotes the magnitude of the fundamental current, k 1 、k 2 、k 3 、k n Coefficients representing the respective harmonic currents, w representing the fundamental frequency, t representing time, and n representing the harmonic times; the energy consumption index refers to the proportion of the power loss of each link in the power supply amount during the power transmission and distribution process of the power grid, and the calculation formula is as follows:wherein nh represents an energy consumption index, zd represents a power supply quantity, zh represents a sales quantity, and y represents a time set value.
In the embodiment of the present invention, it should be explained that the method for calculating the stability evaluation index is as follows:
substituting the power distribution network fault times, fault duration, control precision, response speed, fault frequency and harmonic current into a formula:
wherein beta represents a stability evaluation index of the power distribution network, nl represents the number of faults of the power distribution network, hl represents the duration of the faults, jl represents the control accuracy of the faults, sl represents the response speed of the faults, pl represents the frequency of the faults, xl represents the harmonic current, mu 1 、μ 2 The fault detection method is respectively expressed as other influencing factors of the power distribution network faults;
and (3) the environmental influence factors of the power distribution network: the ambient humidity, ambient air pressure and ambient temperature are substituted into the formula:
wherein λ represents an environmental impact index, σ 1 Other influencing factors of the fault environment are represented, gx represents ambient humidity, gy represents ambient air pressure, gw represents ambient temperature, and e represents a natural constant.
Based on the power loss data of the power distribution network monitoring node, the power loss data comprises: the method comprises the steps of obtaining abnormal loss performance indexes by resistance loss, inductance loss and current loss, wherein the resistance loss is generated when current passes through a cable, and is related to the sectional area of a conductor material of the cable, the length of the cable and the current, and the calculation formula is as follows:
wherein dp represents resistance loss, I represents circuit output current, R represents line resistance, m represents conductor material sectional area, and q represents cable length; the inductance loss refers to the loss caused by self inductance and mutual inductance effect caused by a magnetic field generated when current passes through the cable, and the calculation formula is as follows: dz=iΛ2rl, where dz represents the inductance loss and L represents the line inductance value; the current loss refers to energy loss generated when current flows through the resistor, and the calculation formula is as follows: el=l×r×z, where el represents current loss. l represents a current set point, R represents a line resistance, and z represents a transmission distance;
the resistance loss, the inductance loss and the current loss obtained by the joint analysis are used for obtaining an abnormal loss performance index, and the abnormal loss performance index is calculated according to the formula:
wherein the method comprises the steps ofThe abnormal loss performance index is represented by dp, the resistive loss, dz, the inductive loss, el, the current loss, s, the loss rate evaluation factor, and hz, the loss time evaluation factor.
In the embodiment of the present invention, it should be explained that the calculation method of the quality evaluation coefficient is as follows:
where θ represents a quality evaluation coefficient of the power distribution network, λ represents an environmental impact index, β represents a stability evaluation index,representing the loss performance index.
In the embodiment of the present invention, it should be explained that the specific evaluation mode of the fault diagnosis evaluation module is as follows:
and acquiring a quality evaluation coefficient of each monitoring node of the power distribution network, extracting abnormal state characteristics by using a digital twin model, comparing the abnormal state characteristics with a preset quality evaluation coefficient, and if the quality evaluation coefficient is larger than the preset quality evaluation coefficient, indicating that the monitoring nodes of the power distribution network are abnormal, otherwise, indicating that the monitoring nodes of the power distribution network are normal in operation and have no faults.
The fault early warning module comprises the following specific modes:
the method is used for screening each monitoring node of the power distribution network in an abnormal working state, counting the data of each monitoring node of the power distribution network in the abnormal working state, sending the data to a power distribution network supervision center, extracting abnormal state characteristics by utilizing a digital twin model, quickly acquiring fault information and occurrence positions, sending early warning to management staff, and correspondingly processing according to the received typical fault types to realize effective fault removal.
Claims (8)
1. The utility model provides a distribution network fault diagnosis system based on digit twin which characterized in that: the system comprises:
and a model building module: constructing a digital twin model of the power distribution network by utilizing a digital twin technology, and simulating the actual running condition of the power distribution network through the digital twin model of the power distribution network;
and a data acquisition module: based on the actual running condition of the distribution network simulated by the digital twin model of the distribution network, collecting the power running data of the distribution network, wherein the power running data of the distribution network comprises: power set point, current set point, temperature set point, time set point;
simulating the actual running condition of the power distribution network based on the digital twin model of the power distribution network, and collecting power running data of the power distribution network;
and a data screening module: filtering and calibrating the data based on the power operation data acquired by the data acquisition module, removing impurities and redundant information in the data, and acquiring fault parameter values of the power distribution network;
the fault parameter acquisition module is used for: calculating to obtain a stability evaluation index through a stability index obtaining unit, calculating to obtain an environment influence index through an environment influence index obtaining unit, and calculating to obtain an abnormal loss performance index through an electric power loss index obtaining unit;
and a fault parameter analysis module: calculating a quality evaluation coefficient based on the stability evaluation index, the environment influence index and the abnormal loss performance index acquired by the fault parameter acquisition module;
fault diagnosis and evaluation module: the quality evaluation coefficient is used for acquiring the quality evaluation coefficient of the power distribution network, comparing the quality evaluation coefficient with a preset quality evaluation coefficient and carrying out corresponding processing;
and the fault early warning module is used for: the monitoring nodes used for screening the power distribution network in the abnormal working state are sent to a power distribution network supervision center, and the digital model is used for extracting abnormal state characteristics and carrying out corresponding early warning processing.
2. A digital twin based power distribution network fault diagnostic system according to claim 1, wherein: the method for building the digital twin model of the power distribution network comprises the following steps:
the method comprises the steps of carrying out detailed mapping and data collection on a real power distribution network, including all details of lines, equipment and connection points of the power distribution network, then modeling the power distribution network by using a digital twin technology, and digitizing all details;
data acquisition and processing: acquiring operation data of all devices in the power distribution network, including states, operation conditions and environmental parameters of the devices, and then processing and analyzing the data to extract data affecting the operation of the power distribution network;
constructing a digital twin model: constructing a data model of the power distribution network according to the equipment information of the power distribution network, and combining the extracted power distribution network operation data with the data model to obtain a digital twin model of the power distribution network;
model verification and correction: and comparing the model with an actual power distribution network, verifying the accuracy and feasibility of the model, and correcting and optimizing the inaccurate place of the digital twin model.
3. A digital twin based power distribution network fault diagnostic system according to claim 1, wherein: the fault parameter acquisition module comprises: a stability index acquisition unit, an environmental impact index acquisition unit, and a power loss index acquisition unit;
the stability index acquisition unit: acquiring control end stability parameters and user operation terminal stability parameters of the power distribution network through an electric force sensor; the control end stability parameters of the power distribution network comprise: the number of faults, the duration of the faults, the fault control precision and the fault response speed; the stability parameters of the user operation terminal include: fault frequency, harmonic current, and energy consumption index;
the environmental impact index acquisition unit: the method is used for collecting environmental influence factors of power distribution network operation, wherein the environmental influence factors comprise: ambient humidity, ambient air pressure, and ambient temperature;
the power loss index acquisition unit: a electric power loss data for setting up power sensor, gather distribution network monitoring node, electric power loss data includes: resistance loss, inductance loss, and current loss.
4. A digital twin based power distribution network fault diagnostic system according to claim 3, wherein: the method for acquiring the stability index comprises the following steps:
the stability parameter calculation method of the user operation terminal comprises the following steps: the failure frequency refers to the number of times of common failures occurring in the running process of the power distribution network in unit time, and is calculatedThe formula is: pl=nl×hc, where pl represents the failure frequency, nl represents the number of failures, hc represents the total time of operation, harmonic current means that harmonic current is superimposed on the main power supply, and a non-sinusoidal characteristic current is introduced by the device, and the calculation formula is as follows: xl=l1 (k 1 *wt+k 2 *2wt+k 3 *3wt+...+k n * nwt) where xl denotes a harmonic current, l1 denotes the magnitude of a fundamental current, k 1 、k 2 、k 3 、k n The coefficient of each harmonic current is represented, w represents fundamental frequency, t represents time, n represents harmonic frequency, the energy consumption index refers to the proportion of the power loss of each link in the power network in the process of delivering and distributing the power, and the calculation formula is as follows:
wherein nh represents an energy consumption index, zd represents a power supply quantity, zh represents a sales quantity, and y represents a time set value.
5. A digital twin based power distribution network fault diagnostic system according to claim 1, wherein: the calculation method of the stability evaluation index comprises the following steps: substituting the power distribution network fault times, fault duration, control precision, response speed, fault frequency and harmonic current into a formula:
wherein beta represents a stability evaluation index of the power distribution network, nl represents the number of faults of the power distribution network, hl represents the duration of the faults, jl represents the control accuracy of the faults, sl represents the response speed of the faults, pl represents the frequency of the faults, xl represents the harmonic current, mu 1 、μ 2 The fault detection method is respectively expressed as other influencing factors of the power distribution network faults;
and (3) the environmental influence factors of the power distribution network: the ambient humidity, ambient air pressure and ambient temperature are substituted into the formula:
wherein λ represents an environmental impact index, σ 1 Other influencing factors of the fault environment are represented, gx represents ambient humidity, gy represents ambient air pressure, gw represents ambient temperature, and e represents a natural constant;
based on the power loss data of the power distribution network monitoring node, the power loss data comprises: resistance loss, inductance loss and current loss, wherein the resistance loss refers to resistance loss generated when current passes through a cable, and is related to the sectional area of a conductor material of the cable, the length of the cable and the current, and the calculation formula is as follows:
wherein dp represents resistance loss, I represents circuit output current, R represents line resistance, m represents conductor material sectional area, q represents cable length, inductance loss refers to loss caused by self inductance and mutual inductance effect caused by magnetic field generated when current passes through the cable, and the calculation formula is:
dz＝I∧2RL
wherein dz represents inductance loss, L represents line inductance value, current loss refers to energy loss generated when current flows through a resistor, and a calculation formula is as follows:
el＝l*R*z
where el represents current loss, l represents a current set point, R represents line resistance, and z represents a transmission distance;
the resistance loss, the inductance loss and the current loss obtained by the joint analysis are used for obtaining an abnormal loss performance index, and the abnormal loss performance index is calculated according to the formula:
wherein the method comprises the steps ofThe abnormal loss performance index is represented by dp, the resistive loss, dz, the inductive loss, el, the current loss, s, the loss rate evaluation factor, and hz, the loss time evaluation factor.
6. A digital twin based power distribution network fault diagnostic system according to claim 1, wherein: the calculation mode of the quality evaluation coefficient is as follows:
where θ represents a quality evaluation coefficient of the power distribution network, λ represents an environmental impact index, β represents a stability evaluation index,representing the loss performance index.
7. A digital twin based power distribution network fault diagnostic system according to claim 1, wherein: the specific evaluation mode of the fault diagnosis evaluation module is as follows:
and acquiring a quality evaluation coefficient of each monitoring node of the power distribution network, extracting abnormal state characteristics by using a digital twin model, comparing the abnormal state characteristics with a preset quality evaluation coefficient, and if the quality evaluation coefficient is larger than the preset quality evaluation coefficient, indicating that the monitoring nodes of the power distribution network are abnormal, otherwise, indicating that the monitoring nodes of the power distribution network are normal in operation and have no faults.
8. A digital twin based power distribution network fault diagnostic system according to claim 1, wherein: the fault early warning module comprises the following specific modes:
the method is used for screening each monitoring node of the power distribution network in an abnormal working state, counting the data of each monitoring node of the power distribution network in the abnormal working state, sending the data to a power distribution network supervision center, extracting abnormal state characteristics by utilizing a digital twin model, quickly acquiring fault information and occurrence positions, sending early warning to management staff, and correspondingly processing according to the received typical fault types to realize effective fault removal.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117933576A (en) * | 2024-03-21 | 2024-04-26 | 网思科技集团有限公司 | Power distribution network operation and maintenance method, system and medium based on digital twin |
| CN118094060A (en) * | 2024-04-23 | 2024-05-28 | 江苏沃能电气科技有限公司 | Digital twinning-based remote health diagnosis method for power bus |
| CN118263852A (en) * | 2024-03-27 | 2024-06-28 | 华中科技大学 | Fault pre-judging method and system based on digital twin |
| CN118395362A (en) * | 2024-06-28 | 2024-07-26 | 上海凌至物联网有限公司 | Digital twinning-based transformer bushing internal fault diagnosis method |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117933576A (en) * | 2024-03-21 | 2024-04-26 | 网思科技集团有限公司 | Power distribution network operation and maintenance method, system and medium based on digital twin |
| CN117933576B (en) * | 2024-03-21 | 2024-05-28 | 网思科技集团有限公司 | Power distribution network operation and maintenance method, system and medium based on digital twin |
| CN118263852A (en) * | 2024-03-27 | 2024-06-28 | 华中科技大学 | Fault pre-judging method and system based on digital twin |
| CN118094060A (en) * | 2024-04-23 | 2024-05-28 | 江苏沃能电气科技有限公司 | Digital twinning-based remote health diagnosis method for power bus |
| CN118395362A (en) * | 2024-06-28 | 2024-07-26 | 上海凌至物联网有限公司 | Digital twinning-based transformer bushing internal fault diagnosis method |
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