Transformer status assessment method and fire warning method under high penetration of new energy

Abstract

The present invention discloses a transformer state assessment method under high penetration of new energy, including constructing a state assessment index system for oil-immersed transformers under high penetration of new energy; calculating weight coefficients and membership functions in the state assessment index system; and performing fuzzy comprehensive evaluation on the state of the oil-immersed transformer under high penetration of new energy. The present invention also discloses a fire warning method including the transformer state assessment method under high penetration of new energy. The transformer state assessment method and fire warning method under high penetration of new energy provided by the present invention establish a sending-end power grid safety risk assessment system considering the background of high penetration of new energy, use the entropy method to combine subjective scoring and objective data, and use the improved triangular trapezoidal distribution to determine the membership function to construct a fuzzy evaluation matrix; therefore, the present invention has high reliability, good accuracy, and is objective and scientific.

Description

Technical Field

[0001] The present invention belongs to the field of electrical automation, and specifically relates to a transformer state assessment method and a fire warning method under high penetration of new energy. Background Art

[0002] With the development of economy and technology and the improvement of people's living standards, electricity has become an indispensable secondary energy source in people's production and life, bringing endless convenience to people's production and life. Therefore, ensuring the stable and reliable supply of electricity has become one of the most important tasks of the power system.

[0003] Oil-immersed transformers are an important part of the power system, so it is particularly important to evaluate the status of oil-immersed transformers. As environmental issues become increasingly prominent, more and more new energy power generation systems are being integrated into the power grid, which brings new challenges to the safe and stable operation of the power grid and new variables to the status evaluation of oil-immersed transformers.

[0004] The current state assessment method for oil-immersed transformers is still based on the assessment method in the traditional power grid environment; although this method is scientific to a certain extent, it is no longer applicable to the state assessment of oil-immersed transformers in the power grid system under the background of high penetration of new energy. Moreover, the existing assessment method does not consider the changes in the power grid under the background of high penetration of new energy, nor does it consider the state of the new energy power generation system. Summary of the invention

[0005] One of the purposes of the present invention is to provide a transformer status assessment method under high penetration rate of new energy with high reliability, good accuracy and objectivity and science.

[0006] A second object of the present invention is to provide a fire warning method including the transformer status assessment method under the high penetration rate of new energy.

[0007] The transformer status assessment method under the high penetration rate of new energy provided by the present invention comprises the following steps:

[0008] S1. Construct a status assessment index system for oil-immersed transformers under high penetration of new energy;

[0009] S2. Calculate the weight coefficient and membership function in the state assessment index system;

[0010] S3. Based on the data obtained in step S1 and step S2, a fuzzy comprehensive evaluation is performed on the state of the oil-immersed transformer under the high penetration rate of new energy.

[0011] The step S1 of constructing a state assessment index system for oil-immersed transformers under high penetration of new energy specifically includes the following steps:

[0012] The status assessment index system of oil-immersed transformers under high penetration of new energy sources includes grid security risk index, wind and solar power abandonment risk index, test index and operation index, a total of 4 secondary indicators;

[0013] The grid security risk indicators include traditional power structure data, grid topology data, dispatching and operation data, transmission and transformation equipment reliability data, and safety and stability control technology data, a total of 5 third-level indicators;

[0014] The risk indicators for wind and solar power abandonment include new energy access point data, new energy penetration rate data, new energy dispatch management data, new energy real-time control technology data, new energy power generation forecast data and new energy equipment reliability data, a total of 6 third-level indicators;

[0015] The test indicators include dissolved gas data in oil, core grounding current data, DC resistance unbalance coefficient data, core insulation resistance data and dielectric loss value data, a total of 5 third-level indicators;

[0016] The operating indicators include transformer load rate data, cooling device status data, protection action data, oil temperature data, sealing and leakage data, and abnormal noise data, a total of 6 third-level indicators.

[0017] The calculation described in step S2 to obtain the weight coefficient and membership function in the state assessment index system specifically includes the following steps:

[0018] A. Calculate the weight coefficient:

[0019] B. Construct the evaluation matrix U' as where u i ' j is the value of the jth factor in the i-th state quantity;

[0020] C. Standardize the elements in the constructed evaluation matrix U':

[0021] For positive indicators, the standardized calculation formula is:

[0022] For negative indicators, the standardized calculation formula is: Among them, u ij is the index after standardization, min{u' j} is the minimum value of the elements in the jth column of the evaluation matrix U', max{u' j} is the maximum value of the elements in the jth column of the evaluation matrix U';

[0023] D. Calculate the weight of the i-th factor in the j-th index under the j-th comprehensive state X ij for m is the number of expert evaluations;

[0024] E. Calculate the information entropy E of the jth indicator j for where k is the proportionality factor and

[0025] G. Calculate the improved entropy value E' of the jth index j for

[0026] H. Calculate the entropy redundancy d of the jth indicator j is d j =1-E' j ;

[0027] I. Finally, the weight coefficient w of the i-th indicator considering the high penetration rate of new energy is calculated i for Among them U 22 is the value of new energy penetration rate;

[0028] J. Calculate the membership function:

[0029] Based on the triangular trapezoidal distribution, determine the degree of membership:

[0030]

[0031]

[0032]

[0033] Among them, r(v1) is the membership function belonging to “serious”; r(v5) is the membership function belonging to “good”; v is the membership frequency of a single indicator after normalization; r(v i ) is the membership function of the middle three evaluation levels; v i-1 is the left neighbor value of the evaluation level; v i is the right critical value of the evaluation level; v i+1 is the right critical value of the next level of this evaluation level;

[0034] In the method of the present invention, there are five evaluation levels in total. Under normal circumstances, there should be five membership functions. This method improves this and shortens it to three. At the same time, the middle calculation formula is used to calculate the membership values ​​of the three levels of "normal", "caution" and "abnormal". When calculating different levels, v i-1 、v i 、v i+1 Corresponding to different values;

[0035] From the fuzzy relationship matrix, the single factor evaluation matrix R of the i-th scheme is calculated i for where r' mn Where m represents the number of indicators, n represents the evaluation level (the present invention has 5 levels) r' mn That is, it is expressed as the membership degree of the nth level of the mth indicator;

[0036] Among them, the fuzzy relationship matrix is ​​composed of the membership degree of each of the above indicators at different levels. For example, the first indicator is , m indicators constitute the fuzzy relationship matrix.

[0037] Step S3, based on the data obtained in step S1 and step S2, performs a fuzzy comprehensive evaluation on the state of the oil-immersed transformer under the high penetration rate of new energy, specifically comprising the following steps:

[0038] a. Construct the secondary index factor evaluation model for oil-immersed transformer condition assessment as follows:

[0039] B i =W*R i

[0040] Among them B i is the fuzzy comprehensive evaluation result vector of the secondary indicators, and B i =[b i1 ,b i2 ,...,b im ], b ik is the membership degree of each level of the secondary indicator, (This formula is just B i =W*R i Another way to write ), a j is the weight value between the three-level indicators, r ik is the index membership degree; W is the comprehensive index weight set, and W=[w1,w2,...,w i ,...],w i is the weight coefficient of the i-th indicator under the high penetration rate of new energy; R i is the single factor evaluation matrix of the i-th solution;

[0041] b. According to the secondary indicator factor evaluation model of oil-immersed transformer condition evaluation, the first-level factor comprehensive evaluation matrix B of oil-immersed transformer condition evaluation is calculated as B Among them B I is the fuzzy comprehensive evaluation result vector of the first-level index, A I is the weight value of the secondary index, R I is the secondary fuzzy relationship matrix composed of the secondary index evaluation result vector, ο is the matrix multiplication symbol;

[0042] c. Based on the obtained comprehensive evaluation matrix of the first-level factors of oil-immersed transformer status assessment, the maximum membership principle is adopted to obtain the status assessment results of the oil-immersed power transformer considering the high penetration rate of new energy; the status assessment results include "good", "normal", "caution", "abnormal" and "serious".

[0043] The transformer status assessment method under high penetration of new energy sources also includes the following steps:

[0044] S4. Predict the remaining life of the transformer.

[0045] The prediction of the remaining life of the transformer described in step S4 specifically includes the following steps:

[0046] (1) The DP failure probability standard of insulating paper fiber is defined as:

[0047] If DP ≥ 450, the failure probability is 0;

[0048] If 250≤DP<450, the failure probability is

[0049] If DP < 250, the failure probability is 1;

[0050] Wherein, DP is the degree of polymerization;

[0051] (2) Using the average DP value, estimate the remaining life of the transformer based on the following formula:

[0052]

[0053] where n l is the average DP value after the service period; n0 is the starting value of the average DP value; U 22 is the value of new energy penetration rate; r is the average DP decline rate; L is the service life.

[0054] The present invention also provides a fire warning method including the transformer state assessment method under high penetration rate of new energy, which specifically includes the following steps:

[0055] A. Using the transformer status assessment method under high penetration rate of new energy, the target oil-immersed transformer is assessed;

[0056] B. According to the status evaluation results obtained in step A, make a judgment:

[0057] If the status assessment result is "good", "normal" or "caution", the target oil-immersed transformer is continuously monitored and the status assessment is performed; the algorithm ends;

[0058] If the status assessment result is "abnormal", proceed to the next step;

[0059] C. Provide fire warning for the target oil-immersed transformer.

[0060] The fire warning for the target oil-immersed transformer described in step C specifically includes the following steps:

[0061] C1. Construct an oil-immersed transformer fire warning device;

[0062] C2. Use the constructed fire warning device for oil-immersed transformers to provide fire warning for the target oil-immersed transformers.

[0063] The oil-immersed transformer fire warning device specifically includes a temperature sensor module, a flame sensor module, a smoke sensor module, a fire extinguishing module, an audible and visual alarm module, a slave communication module, a slave control module, a host control module, a touch screen module and a host communication module; the temperature sensor module, the flame sensor module, the smoke sensor module, the fire extinguishing module, the audible and visual alarm module and the slave communication module are all connected to the slave control module; the touch screen module and the host communication module are both connected to the host control module; the slave control module is connected to the host control module; the temperature sensor module is used to measure the real-time temperature information of the target oil-immersed transformer and upload the measurement data to the slave control module; the flame sensor module is used to measure the real-time flame information of the target oil-immersed transformer and upload the measurement data to the slave control module; the smoke sensor module is used to measure the real-time smoke information of the target oil-immersed transformer and upload the measurement data to the slave control module The measurement data is uploaded to the slave control module; the fire extinguishing module is used to receive the control signal sent by the slave control module, start and perform fire extinguishing operations on the target oil-immersed transformer in a timely manner; the sound and light alarm module is used to receive the control signal sent by the slave control module, and perform sound and light alarm in a timely manner; the slave communication module and the host communication module are paired communication modules, which are used for data interaction and communication between the host control module and the slave control module; the slave control module is used to receive data information uploaded by the temperature sensor module, the flame sensor module and the smoke sensor module, send control instructions to the fire extinguishing module and the sound and light alarm module, and communicate with the host control module through the slave communication module; the host control module is used to communicate with the slave control module through the host communication module, and to interact with the touch screen module for data; the touch screen module is used for the oil-immersed transformer fire early warning device to interact with the outside for data.

[0064] The fire extinguishing module is a fine water mist spraying device.

[0065] The slave communication module and the host communication module are paired LoRa communication modules.

[0066] The fire warning for the target oil-immersed transformer specifically includes the following steps:

[0067] a. Obtain temperature information, smoke information and flame parameter information of the target oil-immersed transformer in real time;

[0068] b. Filter the information obtained in step a to obtain determination data information;

[0069] c. According to the determination data information obtained in step b, make the following determination:

[0070] If the temperature is greater than 50°C or the temperature rise rate is greater than 5°C / min or the absolute value of the smoke exceeds 1V or the smoke rise rate exceeds 0.1V / s, the target oil-immersed transformer is judged to be in a warning state;

[0071] If the target oil-immersed transformer is in the early warning state and the flame rising rate is greater than 5V / s, it is determined that the target oil-immersed transformer is in the alarm state;

[0072] If the target oil-immersed transformer is not in the warning state and the flame rising rate is greater than 5V / s, it is judged as a false alarm state;

[0073] d. If the target oil-immersed transformer is in alarm state and there is no external operation within the set time, the fire extinguishing module will be automatically turned on after the set time to extinguish the target oil-immersed transformer;

[0074] If the target oil-immersed transformer is in an alarm state and receives an operation from an external person within the set time, the subsequent actions are performed according to the received operation;

[0075] If the condition assessment result is "critical", it is recommended to replace the transformer as soon as possible.

[0076] The transformer status assessment method and fire warning method under high penetration rate of new energy provided by the present invention establish a sending-end power grid safety risk assessment system considering the background of high penetration rate of new energy, use the entropy method to combine subjective scoring and objective data, and use the improved triangular trapezoidal distribution to determine the membership function to construct a fuzzy evaluation matrix; therefore, the present invention has high reliability, good accuracy, and is objective and scientific. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 It is a schematic diagram of the method flow of the state assessment method of the present invention.

[0078] Figure 2 The figure is a schematic diagram of the method flow of the fire early warning method of the present invention.

[0079] Figure 3 This is a functional module diagram of the oil-immersed transformer fire warning device of the fire warning method of the present invention. DETAILED DESCRIPTION

[0080] like Figure 1 The method flow chart of the state assessment method of the present invention is shown as follows: The transformer state assessment method under the high penetration rate of new energy provided by the present invention comprises the following steps:

[0081] S1. Construct a status assessment index system for oil-immersed transformers under high penetration of new energy; specifically, the following steps are included:

[0082] The status assessment index system of oil-immersed transformers under high penetration of new energy sources includes grid security risk index, wind and solar power abandonment risk index, test index and operation index, a total of 4 secondary indicators;

[0083] The grid security risk indicators include traditional power structure data, grid topology data, dispatching and operation data, transmission and transformation equipment reliability data, and safety and stability control technology data, a total of 5 third-level indicators;

[0084] The risk indicators for wind and solar power abandonment include new energy access point data, new energy penetration rate data, new energy dispatch management data, new energy real-time control technology data, new energy power generation forecast data and new energy equipment reliability data, a total of 6 third-level indicators;

[0085] The test indicators include dissolved gas data in oil, core grounding current data, DC resistance unbalance coefficient data, core insulation resistance data and dielectric loss value data, a total of 5 third-level indicators;

[0086] The operation indicators include transformer load rate data, cooling device status data, protection action data, oil temperature data, sealing and leakage data, and abnormal noise data, a total of 6 third-level indicators;

[0087] S2. Calculate the weight coefficient and membership function in the status assessment index system; specifically include the following steps:

[0088] A. Calculate the weight coefficient:

[0089] B. Construct the evaluation matrix U' as where u' ij is the value of the jth factor in the i-th state quantity;

[0090] C. Standardize the elements in the constructed evaluation matrix U':

[0091] For positive indicators, the standardized calculation formula is:

[0092] For negative indicators, the standardized calculation formula is: In the formula, u ij is the index after standardization, min{u' j} is the minimum value of the elements in the jth column of the evaluation matrix U', max{u'j} is the maximum value of the elements in the jth column of the evaluation matrix U';

[0093] D. Calculate the weight of the i-th factor in the j-th index under the j-th comprehensive state X ij for m is the number of expert evaluations;

[0094] E. Calculate the information entropy E of the jth indicator j for where k is the proportionality factor and

[0095] F. Calculate the improved entropy value E' of the jth indicator j for

[0096] G. Calculate the entropy redundancy d of the jth indicator j is d j =1-E' j ;

[0097] H. Finally, the weight coefficient w of the i-th indicator considering the high penetration rate of new energy is calculated i for Among them U 22 is the value of new energy penetration rate;

[0098] I. Calculate the membership function:

[0099] Based on the triangular trapezoidal distribution, determine the degree of membership:

[0100]

[0101]

[0102]

[0103] Among them, r(v1) is the membership function belonging to “serious”; r(v5) is the membership function belonging to “good”; v is the membership frequency of a single indicator after normalization; r(v i ) is the membership function of the middle three evaluation levels; v i-1 is the left neighbor value of the evaluation level; v i is the right critical value of the evaluation level; v i+1 is the right critical value of the next level of this evaluation level;

[0104] In the method of the present invention, there are five evaluation levels in total. Under normal circumstances, there should be five membership functions. This method improves this and shortens it to three. At the same time, the middle calculation formula is used to calculate the membership values ​​of the three levels of "normal", "caution" and "abnormal". When calculating different levels, v i-1、v i 、v i+1 Corresponding to different values;

[0105] From the fuzzy relationship matrix, the single factor evaluation matrix R of the i-th scheme is calculated i for where r' mn Where m represents the number of indicators, n represents the evaluation level (the present invention has 5 levels) r' mn That is, it is expressed as the membership degree of the nth level of the mth indicator;

[0106] Among them, the fuzzy relationship matrix is ​​composed of the membership degree of each of the above indicators at different levels. For example, the first indicator is , m indicators constitute the fuzzy relationship matrix;

[0107] S3. Based on the data obtained in step S1 and step S2, a fuzzy comprehensive evaluation is performed on the state of the oil-immersed transformer under high penetration of new energy; specifically comprising the following steps:

[0108] a. Construct the secondary index factor evaluation model for oil-immersed transformer condition assessment as follows:

[0109] B i =W*R i

[0110] Where B i is the fuzzy comprehensive evaluation result vector of the secondary indicators, and B i =[b i1 ,b i2 ,...,b im ], b ik is the membership degree of each level of the secondary indicator, (This formula is just B i =W*R i Another way to write ), a j is the weight value between the three-level indicators, r ik is the index membership degree; W is the comprehensive index weight set, and W=[w1,w2,...,w i ,...],w i is the weight coefficient of the i-th indicator under the high penetration rate of new energy; R i is the single factor evaluation matrix of the i-th solution;

[0111] b. According to the secondary indicator factor evaluation model of oil-immersed transformer condition evaluation, the first-level factor comprehensive evaluation matrix B of oil-immersed transformer condition evaluation is calculated as B Among them B I is the fuzzy comprehensive evaluation result vector of the first-level index, A Iis the weight value of the secondary index, R I is the secondary fuzzy relationship matrix composed of the secondary index evaluation result vector, ο is the matrix multiplication symbol;

[0112] c. Based on the obtained comprehensive evaluation matrix of the first-level factors of the oil-immersed transformer status assessment, the maximum membership principle is used to obtain the status assessment results of the oil-immersed power transformer under the environment of high penetration of new energy; the status assessment results include "good", "normal", "caution", "abnormal" and "serious";

[0113] S4. Predict the remaining life of the transformer; specifically, the steps include:

[0114] (1) The DP failure probability standard of insulating paper fiber is defined as:

[0115] If DP ≥ 450, the failure probability is 0;

[0116] If 250≤DP<450, the failure probability is

[0117] If DP < 250, the failure probability is 1;

[0118] Wherein, DP is the degree of polymerization;

[0119] (2) Using the average DP value, estimate the remaining life of the transformer based on the following formula:

[0120]

[0121] Where n l is the average DP value after the service period; n0 is the starting value of the average DP value; U 22 is the value of new energy penetration rate; r is the average DP decline rate; L is the service life.

[0122] like Figure 2 The method flow chart of the fire warning method of the present invention is shown as follows: the fire warning method provided by the present invention, which includes the transformer state assessment method under the high penetration rate of new energy, specifically includes the following steps:

[0123] A. Using the transformer status assessment method under high penetration rate of new energy, the target oil-immersed transformer is assessed;

[0124] B. According to the status evaluation results obtained in step A, make a judgment:

[0125] If the status assessment result is "good", "normal" or "caution", the target oil-immersed transformer is continuously monitored and the status assessment is performed; the algorithm ends;

[0126] If the status assessment result is "abnormal", proceed to the next step;

[0127] C. Carry out fire warning for the target oil-immersed transformer; specifically include the following steps:

[0128] C1. Construct an oil-immersed transformer fire warning device;

[0129] C2. Using the constructed fire warning device for oil-immersed transformers, a fire warning is performed on the target oil-immersed transformer; specifically comprising the following steps:

[0130] a. Obtain temperature information, smoke information and flame parameter information of the target oil-immersed transformer in real time;

[0131] b. Filter the information obtained in step a to obtain determination data information;

[0132] c. According to the determination data information obtained in step b, make the following determination:

[0133] If the temperature is greater than 50°C or the temperature rise rate is greater than 5°C / min or the absolute value of the smoke exceeds 1V or the smoke rise rate exceeds 0.1V / s, the target oil-immersed transformer is judged to be in a warning state;

[0134] If the target oil-immersed transformer is in the early warning state and the flame rising rate is greater than 5V / s, it is determined that the target oil-immersed transformer is in the alarm state;

[0135] If the target oil-immersed transformer is not in the warning state and the flame rising rate is greater than 5V / s, it is judged as a false alarm state;

[0136] d. If the target oil-immersed transformer is in alarm state and there is no external operation within the set time, the fire extinguishing module will be automatically turned on after the set time to extinguish the target oil-immersed transformer;

[0137] If the target oil-immersed transformer is in an alarm state and receives an operation from an external person within the set time, subsequent actions are performed according to the received operation.

[0138] During specific implementation, the oil-immersed transformer fire warning device includes a temperature sensor module, a flame sensor module, a smoke sensor module, a fire extinguishing module, an audible and visual alarm module, a slave communication module, a slave control module, a host control module, a touch screen module and a host communication module; the temperature sensor module, the flame sensor module, the smoke sensor module, the fire extinguishing module, the audible and visual alarm module and the slave communication module are all connected to the slave control module; the touch screen module and the host communication module are both connected to the host control module; the slave control module is connected to the host control module; the temperature sensor module is used to measure the real-time temperature information of the target oil-immersed transformer and upload the measurement data to the slave control module; the flame sensor module is used to measure the real-time flame information of the target oil-immersed transformer and upload the measurement data to the slave control module; the smoke sensor module is used to measure the real-time smoke information of the target oil-immersed transformer and upload the measurement data to the slave control module Data is uploaded to the slave control module; the fire extinguishing module is used to receive the control signal sent by the slave control module, start and perform fire extinguishing operations on the target oil-immersed transformer in a timely manner; the sound and light alarm module is used to receive the control signal sent by the slave control module, and perform sound and light alarm in a timely manner; the slave communication module and the host communication module are paired communication modules, which are used for data interaction and communication between the host control module and the slave control module; the slave control module is used to receive data information uploaded by the temperature sensor module, the flame sensor module and the smoke sensor module, and send control instructions to the fire extinguishing module and the sound and light alarm module, and communicate with the host control module through the slave communication module; the host control module is used to communicate with the slave control module through the host communication module, and to interact with the touch screen module for data; the touch screen module is used for the oil-immersed transformer fire early warning device to interact with the outside world; the specific structure is as follows Figure 3 shown.

[0139] In specific implementation, the fire extinguishing module is a fine water mist spray device; the slave communication module and the host communication module are paired LoRa communication modules.

Claims

1. A transformer status assessment method under high penetration of new energy sources, comprising the following steps: S1. Construct a status assessment index system for oil-immersed transformers under high penetration of new energy; specifically, the following steps are included: The status assessment index system of oil-immersed transformers under high penetration of new energy sources includes grid security risk index, wind and solar power abandonment risk index, test index and operation index, a total of 4 secondary indicators; The grid security risk indicators include traditional power structure data, grid topology data, dispatching and operation data, transmission and transformation equipment reliability data, and safety and stability control technology data, a total of 5 third-level indicators; The risk indicators for wind and solar power abandonment include new energy access point data, new energy penetration rate data, new energy dispatch management data, new energy real-time control technology data, new energy power generation forecast data and new energy equipment reliability data, a total of 6 third-level indicators; The test indicators include dissolved gas data in oil, core grounding current data, DC resistance unbalance coefficient data, core insulation resistance data and dielectric loss value data, a total of 5 third-level indicators; The operation indicators include transformer load rate data, cooling device status data, protection action data, oil temperature data, sealing and leakage data, and abnormal noise data, a total of 6 third-level indicators; S2. Calculate the weight coefficient and membership function in the status assessment index system; specifically include the following steps: A. Calculate the weight coefficient: B. Construct the evaluation matrix U' as where u i ' j is the value of the jth factor in the i-th state quantity; C. Standardize the elements in the constructed evaluation matrix U': For positive indicators, the standardized calculation formula is: For negative indicators, the standardized calculation formula is: in, u ij is the index after standardization, min{u' j } is the minimum value of the elements in the jth column of the evaluation matrix U', max{u' j } is the maximum value of the elements in the jth column of the evaluation matrix U'; D. Calculate the weight of the i-th factor in the j-th index under the j-th comprehensive state X ij for m is the number of expert evaluations; E. Calculate the information entropy E of the jth indicator j for where k is the proportionality factor and G. Calculate the improved entropy value E' of the jth index j for H. Calculate the entropy redundancy d of the jth indicator j is d j =1-E' j ; I. Finally, the weight coefficient w of the i-th indicator considering the high penetration rate of new energy is calculated i for Among them U 22 is the value of new energy penetration rate; J. Calculate the membership function: Based on the triangular trapezoidal distribution, determine the degree of membership: where r(v 1 ) is the membership function of "serious"; r(v 5 ) is the membership function of "good"; v is the membership frequency of a single indicator after normalization; r(v i ) is the membership function of the middle three evaluation levels; v i-1 is the left boundary value of the evaluation level; v i is the right critical value of the evaluation level; v i+1 is the right critical value of the next level of this evaluation level; From the fuzzy relationship matrix, the single factor evaluation matrix R of the i-th scheme is calculated i for where r m ' n The m in the formula represents the number of indicators, n represents the evaluation level, and r represents the m ' n Indicates the degree of membership of the nth level of the mth indicator; S3. Based on the data obtained in step S1 and step S2, a fuzzy comprehensive evaluation is performed on the state of the oil-immersed transformer under high penetration of new energy; specifically comprising the following steps: a. Construct the secondary index factor evaluation model for oil-immersed transformer condition assessment as follows: B i =W*R i Among them B i is the fuzzy comprehensive evaluation result vector of the secondary indicators, and B i =[b i1 ,b i2 ,...,b im ], b ik is the membership degree of each level of the secondary indicator, a j is the weight value between the three-level indicators, r ik is the index membership size; W is the comprehensive index weight set, and W = [w 1 ,w 2 ,...,w i ,...],w i is the weight coefficient of the i-th indicator under the high penetration rate of new energy; R i is the single factor evaluation matrix of the i-th solution; b. According to the secondary indicator factor evaluation model of oil-immersed transformer condition evaluation, the first-level factor comprehensive evaluation matrix B of oil-immersed transformer condition evaluation is calculated as follows: Among them B I is the fuzzy comprehensive evaluation result vector of the first-level index, A I is the weight value of the secondary index, R I is the secondary fuzzy relationship matrix composed of the secondary index evaluation result vector, is the matrix multiplication symbol; c. Based on the obtained comprehensive evaluation matrix of the first-level factors of oil-immersed transformer status assessment, the maximum membership principle is adopted to obtain the status assessment results of the oil-immersed power transformer considering the high penetration rate of new energy; the status assessment results include "good", "normal", "caution", "abnormal" and "serious".

2. The transformer status assessment method under high penetration rate of new energy according to claim 1, Features The transformer status assessment method under high penetration of new energy sources also includes the following steps: S4. Predict the remaining life of the transformer.

3. The transformer status assessment method under high penetration of new energy according to claim 2, Features The prediction of the remaining life of the transformer described in step S4 specifically includes the following steps: (1) The DP failure probability standard of insulating paper fiber is defined as: If DP ≥ 450, the failure probability is 0; If 250≤DP<450, the failure probability is If DP < 250, the failure probability is 1; Wherein, DP is the degree of polymerization; (2) Using the average DP value, estimate the remaining life of the transformer based on the following formula: Where n l is the average DP value after the service period; n 0 is the starting value of the average DP value; U 22 is the value of new energy penetration rate; r is the average DP decline rate; L is the service life.

4. A fire warning method comprising the transformer status assessment method under high penetration rate of new energy as claimed in any one of claims 1 to 3, specifically comprising the following steps: A. Using the transformer status assessment method under high penetration rate of new energy, the target oil-immersed transformer is assessed; B. According to the status evaluation results obtained in step A, make a judgment: If the status assessment result is "good", "normal" or "caution", the target oil-immersed transformer is continuously monitored and the status assessment is performed; the algorithm ends; If the status assessment result is "abnormal", proceed to the next step; C. Provide fire warning for the target oil-immersed transformer.

5. The fire warning method according to claim 4, Features The fire warning for the target oil-immersed transformer described in step C specifically includes the following steps: C1. Construct an oil-immersed transformer fire warning device; C2. Use the constructed fire warning device for oil-immersed transformers to provide fire warning for the target oil-immersed transformers.

6. The fire warning method according to claim 5, Features The oil-immersed transformer fire warning device specifically includes a temperature sensor module, a flame sensor module, a smoke sensor module, a fire extinguishing module, an audible and visual alarm module, a slave communication module, a slave control module, a host control module, a touch screen module and a host communication module; the temperature sensor module, the flame sensor module, the smoke sensor module, the fire extinguishing module, the audible and visual alarm module and the slave communication module are all connected to the slave control module; the touch screen module and the host communication module are all connected to the host control module; the slave control module is connected to the host control module; the temperature sensor module is used to measure the real-time temperature information of the target oil-immersed transformer and upload the measurement data to the slave control module; the flame sensor module is used to measure the real-time flame information of the target oil-immersed transformer and upload the measurement data to the slave control module Upload to the slave control module; the smoke sensor module is used to measure the real-time smoke information of the target oil-immersed transformer and upload the measured data to the slave control module; the fire extinguishing module is used to receive the control signal sent by the slave control module, start and extinguish the target oil-immersed transformer in a timely manner; the sound and light alarm module is used to receive the control signal sent by the slave control module and make sound and light alarms in a timely manner; the slave communication module and the host communication module are paired communication modules, which are used for data interaction and communication between the host control module and the slave control module; the slave control module is used to receive the data information uploaded by the temperature sensor module, the flame sensor module and the smoke sensor module, send control instructions to the fire extinguishing module and the sound and light alarm module, and communicate with the host control module through the slave communication module; The host control module is used to communicate with the slave control module through the host communication module, and to exchange data with the touch screen module; the touch screen module is used for the oil-immersed transformer fire warning device to exchange data with the outside; the fire extinguishing module is a fine water mist spray device; the slave communication module and the host communication module are paired LoRa communication modules.

7. The fire warning method according to claim 6, Features The fire warning for the target oil-immersed transformer specifically includes the following steps: a. Obtain temperature information, smoke information and flame parameter information of the target oil-immersed transformer in real time; b. Filter the information obtained in step a to obtain determination data information; c. According to the determination data information obtained in step b, make the following determination: If the temperature is greater than 50°C or the temperature rise rate is greater than 5°C / min or the absolute value of the smoke exceeds 1V or the smoke rise rate exceeds 0.1V / s, the target oil-immersed transformer is judged to be in a warning state; If the target oil-immersed transformer is in the early warning state and the flame rising rate is greater than 5V / s, it is determined that the target oil-immersed transformer is in the alarm state; If the target oil-immersed transformer is not in the warning state and the flame rising rate is greater than 5V / s, it is judged as a false alarm state; d. If the target oil-immersed transformer is in an alarm state and there is no external operation within the set time, the fire extinguishing module will be automatically turned on after the set time to extinguish the target oil-immersed transformer; If the target oil-immersed transformer is in an alarm state and receives an operation from an external person within the set time, the subsequent actions are performed according to the received operation; If the condition assessment result is "critical", it is recommended to replace the transformer as soon as possible.

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