A remote monitoring system and method based on distribution transformer

Abstract

The present invention provides a remote monitoring system and method based on a distribution transformer, which remotely monitors and analyzes the temperature data of the distribution transformer within a complete working cycle, determines the heat change state information of the environment in which the transformer is located, and judges whether the transformer is overheated; remotely monitors the heat dissipation device corresponding to the transformer to obtain its operating state data, and judges whether the heat dissipation device is in a heat dissipation operating state matching the working state of the transformer and adjusts the operating parameters of the heat dissipation device to improve the heat dissipation efficiency of the heat dissipation device; thermal infrared visual monitoring and analysis are performed on the space where the transformer is located to judge whether the transformer is in an effective heat dissipation state, and based on the real-time operating load of the heat dissipation device, transformer working failure prediction and early warning are performed, the working heat dissipation of the transformer is monitored from multiple dimensions, the transformer is effectively adjusted for heat dissipation, and the possible overheating failure of the transformer is predicted in a timely and accurate manner.

Description

Technical Field

[0001] The present invention relates to the field of power distribution equipment monitoring, and in particular to a remote monitoring system and method based on a distribution transformer. Background Art

[0002] As a key component of the power grid, distribution transformers play an important role in the stable and low-loss transmission of electric energy. Distribution transformers have a high operating power and generate a large amount of heat during operation. To dissipate the heat from the distribution transformer in a timely manner, the distribution transformer is placed in a mineral oil environment and equipped with a cooling fan for active heat dissipation. To ensure timely and effective heat dissipation of the distribution transformer, the operating temperature of the distribution transformer is monitored, and based on the operating temperature monitoring data of the distribution transformer, it is determined whether the distribution transformer is in an overheating state. However, existing technologies only determine whether the distribution transformer is overheating by monitoring the single parameter of operating temperature. They are unable to accurately identify the heat dissipation quality of the distribution transformer, thereby reducing the accuracy of the judgment of the operating reliability of the distribution transformer. Summary of the Invention

[0003] The object of the present invention is to provide a remote monitoring system and method based on a distribution transformer, which remotely monitors and analyzes the temperature data of the distribution transformer within a complete working cycle, determines the heat change status information of the transformer environment, thereby judging whether the transformer is overheating, and directly monitors the working temperature of the transformer to achieve timely and accurate identification of the transformer overheating state; it also remotely monitors the heat dissipation device corresponding to the transformer to obtain its operating status data, thereby judging whether the heat dissipation device is in a heat dissipation operating state matching the working state of the transformer and adjusting the operating parameters of the heat dissipation device to improve the heat dissipation efficiency of the heat dissipation device; it also performs thermal infrared visual monitoring and analysis of the space where the transformer is located to judge whether the transformer is in an effective heat dissipation state, and based on the real-time operating load of the heat dissipation device, performs transformer working failure prediction and early warning, monitors the working heat dissipation of the transformer from multiple dimensions, effectively adjusts the heat dissipation of the transformer, and timely and accurately predicts possible overheating failure of the transformer.

[0004] The present invention is achieved through the following technical solutions:

[0005] A remote monitoring system based on a distribution transformer, comprising:

[0006] A remote temperature monitoring module is used to remotely monitor the temperature of the distribution transformer and obtain the temperature data of the distribution transformer within a complete working cycle;

[0007] A transformer overheating identification module is used to analyze the temperature data to determine the heat change status information of the environment in which the distribution transformer is located; based on the heat change status information, determine whether the distribution transformer is in an overheating state;

[0008] a heat dissipation device operation monitoring module, configured to remotely monitor the heat dissipation device corresponding to the distribution transformer when the distribution transformer is in an overheated state, and obtain operation status data of the heat dissipation device;

[0009] a heat dissipation device operation adjustment module, configured to analyze the operation status data, determine whether the heat dissipation device is in a heat dissipation operation state that matches the operating state of the distribution transformer, and adjust the operation parameters of the heat dissipation device accordingly;

[0010] A remote thermal infrared monitoring and identification module is used to perform remote thermal infrared visual monitoring of the space where the distribution transformer is located, obtain dynamic heat transfer data of the space, and determine whether the distribution transformer is in an effective heat dissipation state based on the dynamic heat transfer data;

[0011] The transformer failure prediction and early warning module is used to perform working failure prediction and early warning operations on the distribution transformer based on the real-time operating load of the heat dissipation device when the distribution transformer is not in an effective heat dissipation state.

[0012] Optionally, the remote temperature monitoring module is used to remotely monitor the temperature of the distribution transformer to obtain temperature data of the distribution transformer within a complete working cycle, including:

[0013] Remotely monitor the dynamic temperature of several components under the distribution transformer to obtain the operating temperature data of all components within a complete working cycle;

[0014] The transformer overheating identification module is used to analyze the temperature data to determine the heat change state information of the environment in which the distribution transformer is located; based on the heat change state information, determine whether the distribution transformer is in an overheating state, including:

[0015] Based on the distribution position information of all devices in the distribution transformer, the operating temperature data of all devices are integrated to obtain the overall operating temperature field change information of the distribution transformer;

[0016] Perform a time evolution analysis on the operating temperature field change information to determine heat accumulation rate information of the environment in which the distribution transformer is located; based on the heat accumulation rate information, determine whether the heat accumulation amount within a spatial range with a preset radius from the distribution transformer exceeds a preset accumulation threshold amount; if so, determine that the distribution transformer is in an overheated state; if not, determine that the distribution transformer is not in an overheated state.

[0017] Optionally, the heat dissipation device operation monitoring module is configured to remotely monitor the heat dissipation device corresponding to the distribution transformer when the distribution transformer is in an overheating state, and obtain operation status data of the heat dissipation device, including:

[0018] When the distribution transformer is in an overheated state, remotely and dynamically monitor the heat dissipation device corresponding to the distribution transformer to obtain rotation speed data of the heat dissipation blades of the heat dissipation device within a complete working cycle;

[0019] The heat dissipation device operation adjustment module is used to analyze the operation status data to determine whether the heat dissipation device is in a heat dissipation operation state that matches the operating state of the distribution transformer, thereby adjusting the operation parameters of the heat dissipation device, including:

[0020] Perform fitting analysis on the rotational speed data to obtain heat dissipation information of the heat dissipation device within a complete working cycle; compare the heat dissipation information with the heat accumulation information of the distribution transformer in time domain changes to determine whether the occurrence time of the heat dissipation peak of the heat dissipation device overlaps with the occurrence time of the heat accumulation peak of the distribution transformer; if so, determine that the heat dissipation device is in a heat dissipation operation state that matches the working state of the distribution transformer; if not, determine that the heat dissipation device is not in a heat dissipation operation state that matches the working state of the distribution transformer, and adjust the rotational speed change frequency of the heat dissipation blades of the heat dissipation device.

[0021] Optionally, the remote thermal infrared monitoring and identification module is used to perform remote thermal infrared visual monitoring of the space where the distribution transformer is located, obtain dynamic heat transfer data of the space, and determine whether the distribution transformer is in an effective heat dissipation state based on the dynamic heat transfer data, including:

[0022] Performing remote thermal infrared visual monitoring of the space where the distribution transformer is located to obtain a thermal infrared dynamic image of the space; performing heat diffusion identification on the thermal infrared dynamic image to obtain heat diffusion speed and diffusion direction data of the space; analyzing the heat diffusion speed and diffusion direction data to determine whether the distribution transformer is in an effective heat dissipation state;

[0023] The transformer failure prediction and warning module is used to perform working failure prediction and warning operations on the distribution transformer based on the real-time operating load of the heat dissipation device when the distribution transformer is not in an effective heat dissipation state, including:

[0024] When the distribution transformer is not in an effective heat dissipation state, the real-time operating load of the heat dissipation device is used to determine whether the heat dissipation device is in an extreme working state; if it is in an extreme working state, the time information of the overheating failure event of the distribution transformer is predicted based on the heat diffusion speed and diffusion direction data, and an early warning message containing the time information is sent to the remote monitoring platform.

[0025] Optionally, analyzing the heat diffusion speed and diffusion direction data to determine whether the distribution transformer is in an effective heat dissipation state includes:

[0026] Step S1: Assume that there are k obstacles around the distribution transformer, where the surface area of ​​the i-th obstacle is S i , i is the obstacle number, which is an integer greater than or equal to 1 and less than or equal to k, and the straight-line distance from the geometric center of the i-th obstacle to the distribution transformer is D i , then the influence coefficient of the obstacles around the distribution transformer on its heat dissipation is:

[0027]

[0028] In the above formula (1), W is the influence coefficient of the obstacles around the distribution transformer on its heat dissipation, T i is the reflectivity of the ith obstacle, a is an adjustment parameter whose value is greater than 0, and e is a natural constant;

[0029] In step S2, assuming that the airflow resistance coefficient of the environment in which the distribution transformer is located is C, v(t) is the wind speed at time t, v is the reference wind speed, and θ(t) is the angle between the wind direction and the heat diffusion direction at time t, the influence function of the airflow on the heat dissipation of the distribution transformer is:

[0030]

[0031] In the above formula (2), f(t) is the influence function of airflow on the heat dissipation of the distribution transformer, and b is the velocity index;

[0032] Step S3, determining the heat dissipation efficiency of the distribution transformer based on the calculation results of the above steps S1 and S2,

[0033]

[0034] In the above formula (3), H is the heat dissipation efficiency of the distribution transformer, wp(t) is the heat diffusion rate at time t, t0 is the start time of the monitoring period, and t1 is the end time of the monitoring period;

[0035] When H is greater than or equal to the preset efficiency threshold, it is determined that the distribution transformer is in an effective heat dissipation state; when H is less than the preset efficiency threshold, it is determined that the distribution transformer is not in an effective heat dissipation state.

[0036] A remote monitoring method based on a distribution transformer, comprising:

[0037] Remotely monitor the temperature of the distribution transformer to obtain temperature data of the distribution transformer during a complete working cycle; analyze the temperature data to determine heat change status information of the environment in which the distribution transformer is located; and determine whether the distribution transformer is in an overheating state based on the heat change status information;

[0038] When the distribution transformer is in an overheated state, remotely monitor the heat dissipation device corresponding to the distribution transformer to obtain operating status data of the heat dissipation device; analyze the operating status data to determine whether the heat dissipation device is in a heat dissipation operating state that matches the operating state of the distribution transformer, and adjust the operating parameters of the heat dissipation device accordingly;

[0039] Conduct remote thermal infrared visual monitoring of the space where the distribution transformer is located to obtain dynamic data on heat transfer in the space. Based on the dynamic data on heat transfer, determine whether the distribution transformer is in an effective heat dissipation state. When the distribution transformer is not in an effective heat dissipation state, perform work failure prediction and early warning operations on the distribution transformer based on the real-time operating load of the heat dissipation equipment.

[0040] Optionally, remote temperature monitoring is performed on the distribution transformer to obtain temperature data of the distribution transformer during a complete working cycle; the temperature data is analyzed to determine heat change status information of the environment in which the distribution transformer is located; and based on the heat change status information, determining whether the distribution transformer is in an overheating state includes:

[0041] Remote temperature dynamic monitoring of several components under the distribution transformer is performed to obtain the operating temperature data of all components within a complete working cycle; based on the distribution location information of all components in the distribution transformer, the operating temperature data of all components are integrated to obtain the overall operating temperature field change information of the distribution transformer;

[0042] Perform a time evolution analysis on the operating temperature field change information to determine heat accumulation rate information of the environment in which the distribution transformer is located; based on the heat accumulation rate information, determine whether the heat accumulation amount within a spatial range with a preset radius from the distribution transformer exceeds a preset accumulation threshold amount; if so, determine that the distribution transformer is in an overheated state; if not, determine that the distribution transformer is not in an overheated state.

[0043] Optionally, when the distribution transformer is in an overheated state, remotely monitoring a heat dissipation device corresponding to the distribution transformer to obtain operating status data of the heat dissipation device; analyzing the operating status data to determine whether the heat dissipation device is in a heat dissipation operating state that matches the operating state of the distribution transformer, and adjusting operating parameters of the heat dissipation device accordingly, includes:

[0044] When the distribution transformer is in an overheated state, remotely and dynamically monitor the heat dissipation device corresponding to the distribution transformer to obtain rotation speed data of the heat dissipation blades of the heat dissipation device within a complete working cycle;

[0045] Perform fitting analysis on the rotational speed data to obtain heat dissipation information of the heat dissipation device within a complete working cycle; compare the heat dissipation information with the heat accumulation information of the distribution transformer in time domain changes to determine whether the occurrence time of the heat dissipation peak of the heat dissipation device overlaps with the occurrence time of the heat accumulation peak of the distribution transformer; if so, determine that the heat dissipation device is in a heat dissipation operation state that matches the working state of the distribution transformer; if not, determine that the heat dissipation device is not in a heat dissipation operation state that matches the working state of the distribution transformer, and adjust the rotational speed change frequency of the heat dissipation blades of the heat dissipation device.

[0046] Optionally, remote thermal infrared visual monitoring is performed on the space where the distribution transformer is located to obtain dynamic heat transfer data of the space. Based on the dynamic heat transfer data, it is determined whether the distribution transformer is in an effective heat dissipation state; when the distribution transformer is not in an effective heat dissipation state, based on the real-time operating load of the heat dissipation device, a working failure prediction and early warning operation is performed on the distribution transformer, including:

[0047] Performing remote thermal infrared visual monitoring of the space where the distribution transformer is located to obtain a thermal infrared dynamic image of the space; performing heat diffusion identification on the thermal infrared dynamic image to obtain heat diffusion speed and diffusion direction data of the space; analyzing the heat diffusion speed and diffusion direction data to determine whether the distribution transformer is in an effective heat dissipation state;

[0048] When the distribution transformer is not in an effective heat dissipation state, the real-time operating load of the heat dissipation device is used to determine whether the heat dissipation device is in an extreme working state; if it is in an extreme working state, the time information of the overheating failure event of the distribution transformer is predicted based on the heat diffusion speed and diffusion direction data, and an early warning message containing the time information is sent to the remote monitoring platform.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] The present application provides a remote monitoring system and method based on a distribution transformer, which remotely monitors and analyzes the temperature data of the distribution transformer within a complete working cycle, determines the heat change status information of the transformer environment, and thereby determines whether the transformer is overheating, performs direct working temperature monitoring on the transformer, and realizes timely and accurate identification of the transformer overheating state; it also remotely monitors the heat dissipation device corresponding to the transformer to obtain its operating status data, thereby determining whether the heat dissipation device is in a heat dissipation operating state that matches the working state of the transformer and adjusting the operating parameters of the heat dissipation device to improve the heat dissipation efficiency of the heat dissipation device; it also performs thermal infrared visual monitoring and analysis of the space where the transformer is located to determine whether the transformer is in an effective heat dissipation state, and based on the real-time operating load of the heat dissipation device, performs transformer working failure prediction and early warning, monitors the working heat dissipation of the transformer from multiple dimensions, performs effective heat dissipation adjustment on the transformer, and timely and accurately predicts possible overheating failure of the transformer. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work. Among them:

[0052] Figure 1 This is a structural diagram of a remote monitoring system based on distribution transformers provided by the present invention.

[0053] Figure 2 A flow chart of a remote monitoring method based on a distribution transformer provided by the present invention. DETAILED DESCRIPTION

[0054] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are described in detail below in conjunction with the accompanying drawings. It will be understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for ease of description, only some, rather than all, structures related to the present application are shown in the accompanying drawings. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0055] As used herein, the terms "comprise," "comprising," and "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or apparatus.

[0056] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0057] See also Figure 1 As shown, an embodiment of the present application provides a remote monitoring system based on a distribution transformer. The remote monitoring system based on a distribution transformer includes:

[0058] Remote temperature monitoring module, used to remotely monitor the temperature of the distribution transformer and obtain the temperature data of the distribution transformer within a complete working cycle;

[0059] The transformer overheating identification module is used to analyze the temperature data to determine the heat change status information of the environment in which the distribution transformer is located; based on the heat change status information, determine whether the distribution transformer is in an overheating state;

[0060] The heat dissipation device operation monitoring module is used to remotely monitor the heat dissipation device corresponding to the distribution transformer when the distribution transformer is in an overheated state, and obtain the operation status data of the heat dissipation device;

[0061] a heat dissipation device operation adjustment module, configured to analyze the operation status data, determine whether the heat dissipation device is in a heat dissipation operation state that matches the operating state of the distribution transformer, and thereby adjust the operation parameters of the heat dissipation device;

[0062] The remote thermal infrared monitoring and identification module is used to perform remote thermal infrared visual monitoring of the space where the distribution transformer is located, obtain dynamic data on heat transfer in the space, and determine whether the distribution transformer is in an effective heat dissipation state based on the dynamic data on heat transfer;

[0063] The transformer failure prediction and early warning module is used to perform working failure prediction and early warning operations on the distribution transformer based on the real-time operating load of the heat dissipation device when the distribution transformer is not in an effective heat dissipation state.

[0064] The beneficial effects of the above embodiments are as follows: the remote monitoring system based on the distribution transformer remotely monitors and analyzes the temperature data of the distribution transformer within a complete working cycle, determines the heat change status information of the environment in which the transformer is located, thereby judging whether the transformer is overheating, and directly monitoring the working temperature of the transformer to achieve timely and accurate identification of the transformer overheating state; it also remotely monitors the heat dissipation device corresponding to the transformer to obtain its operating status data, thereby judging whether the heat dissipation device is in a heat dissipation operating state matching the working state of the transformer and adjusting the operating parameters of the heat dissipation device to improve the heat dissipation efficiency of the heat dissipation device; it also performs thermal infrared visual monitoring and analysis of the space where the transformer is located to judge whether the transformer is in an effective heat dissipation state, and based on the real-time operating load of the heat dissipation device, performs transformer working failure prediction and early warning, monitors the working heat dissipation of the transformer from multiple dimensions, makes effective heat dissipation adjustments to the transformer, and timely and accurately predicts possible overheating failure of the transformer.

[0065] In another embodiment, the remote temperature monitoring module is used to remotely monitor the temperature of the distribution transformer to obtain temperature data of the distribution transformer within a complete working cycle, including:

[0066] Remotely monitor the dynamic temperature of several components under the distribution transformer to obtain the operating temperature data of all components within a complete working cycle;

[0067] The transformer overheating identification module is used to analyze the temperature data to determine the heat change state information of the environment in which the distribution transformer is located; based on the heat change state information, determine whether the distribution transformer is in an overheating state, including:

[0068] Based on the distribution location information of all devices in the distribution transformer, the operating temperature data of all devices are integrated to obtain the overall operating temperature field change information of the distribution transformer;

[0069] A time evolution analysis is performed on the operating temperature field change information to determine the heat accumulation rate information of the environment in which the distribution transformer is located; based on the heat accumulation rate information, a determination is made as to whether the heat accumulation amount within a spatial range with a preset radius from the distribution transformer exceeds a preset accumulation threshold amount; if so, the distribution transformer is determined to be in an overheated state; if not, the distribution transformer is determined to be not in an overheated state.

[0070] The beneficial effects of the above embodiments are as follows: the distribution transformer is an integrated device with a complex structure, which contains multiple electronic devices inside. The corresponding operating temperature of each electronic device during the operation of the distribution transformer is also different. In order to accurately determine the overall operating temperature of the distribution transformer, remote temperature dynamic monitoring is performed on several electronic devices under the distribution transformer to obtain the operating temperature data of all electronic devices in a complete working cycle. Combined with the distribution position information of all electronic devices inside the distribution transformer, the operating temperature data of all electronic devices are integrated, thereby effectively fitting the overall operating temperature of the distribution transformer, determining the overall operating temperature field change information of the distribution transformer, and providing an accurate basis for subsequent judgment of whether the distribution transformer is overheating. In addition, a time evolution analysis is performed on the working temperature field change information to determine the heat accumulation rate information of the environment in which the distribution transformer is located, that is, the working temperature field change information is converted into the corresponding working heat generation time domain to obtain the heat accumulation rate information of the environment in which the distribution transformer is located (that is, the cumulative increase in heat in the environment per unit time). The heat accumulation rate information is then compared with the threshold value of the three-dimensional heat accumulation amount to determine whether the distribution transformer is in an overheating state, thereby facilitating the effective prediction of abnormal working conditions of the distribution transformer.

[0071] In another embodiment, the heat dissipation device operation monitoring module is used to remotely monitor the heat dissipation device corresponding to the distribution transformer when the distribution transformer is in an overheating state, and obtain the operation status data of the heat dissipation device, including:

[0072] When the distribution transformer is in an overheated state, remote dynamic monitoring is performed on the heat dissipation device corresponding to the distribution transformer to obtain the rotation speed data of the heat dissipation blades of the heat dissipation device within a complete working cycle;

[0073] The heat dissipation device operation adjustment module is used to analyze the operation status data to determine whether the heat dissipation device is in a heat dissipation operation state that matches the operating state of the distribution transformer, and thereby adjust the operation parameters of the heat dissipation device, including:

[0074] A fitting analysis is performed on the rotational speed data to obtain information on the amount of heat dissipated by the heat dissipation device within a complete working cycle; the heat dissipation information is compared with the heat accumulation information of the distribution transformer in time domain changes to determine whether the time when the peak value of the heat dissipation of the heat dissipation device occurs overlaps with the time when the peak value of the heat accumulation of the distribution transformer occurs; if so, it is determined that the heat dissipation device is in a heat dissipation operating state that matches the working state of the distribution transformer; if not, it is determined that the heat dissipation device is not in a heat dissipation operating state that matches the working state of the distribution transformer, and the rotational speed change frequency of the heat dissipation blades of the heat dissipation device is adjusted.

[0075] The beneficial effect of the above embodiment is that when the distribution transformer is in an overheating state, it indicates that the heat dissipation device corresponding to the distribution transformer fails to dissipate the heat generated by the operation of the distribution transformer in a timely manner. Therefore, the heat dissipation device corresponding to the distribution transformer is remotely and dynamically monitored to obtain the rotation speed data of the heat dissipation blades of the heat dissipation device in a complete working cycle. In this way, the rotation speed changes of the heat dissipation blades of the heat dissipation device in a complete working cycle can be comprehensively monitored. In addition, a fitting analysis is performed on the rotation speed data to obtain information on the heat dissipation of the heat dissipation device within a complete working cycle. Generally speaking, the greater the rotation speed of the heat dissipation blades, the greater the heat dissipation of the heat dissipation device. The heat dissipation information and the heat accumulation information of the distribution transformer are then compared in time domain changes to determine whether the occurrence time of the heat dissipation peak of the heat dissipation device overlaps with the occurrence time of the heat accumulation peak of the distribution transformer, that is, to determine that when the heat accumulation value of the distribution transformer reaches a maximum value, the heat dissipation blades inside the heat dissipation device are in the highest rotation speed state, thereby determining whether the heat dissipation device is in a heat dissipation operation state that matches the working state of the distribution transformer. When the heat dissipation device is not in a heat dissipation operation state that matches the working state of the distribution transformer, the rotation speed change frequency of the heat dissipation blades of the heat dissipation device is adjusted so that the heat dissipation blades of the heat dissipation device can quickly and timely dissipate the heat generated by the distribution transformer during operation.

[0076] In another embodiment, the remote thermal infrared monitoring and identification module is used to perform remote thermal infrared visual monitoring of the space where the distribution transformer is located, obtain dynamic heat transfer data of the space, and determine whether the distribution transformer is in an effective heat dissipation state based on the dynamic heat transfer data, including:

[0077] Conduct remote thermal infrared visual monitoring of the space where the distribution transformer is located to obtain a thermal infrared dynamic image of the space; perform heat diffusion identification on the thermal infrared dynamic image to obtain data on the heat diffusion rate and direction of the space; analyze the heat diffusion rate and direction data to determine whether the distribution transformer is in an effective heat dissipation state;

[0078] The transformer failure prediction and warning module is used to perform working failure prediction and warning operations on the distribution transformer based on the real-time operating load of the heat dissipation device when the distribution transformer is not in an effective heat dissipation state, including:

[0079] When the distribution transformer is not in an effective heat dissipation state, the real-time operating load of the heat dissipation device is used to determine whether the heat dissipation device is in an extreme working state; if it is in an extreme working state, the time information of the overheating failure event of the distribution transformer is predicted based on the heat diffusion speed and diffusion direction data, and an early warning message containing the time information is sent to the remote monitoring platform.

[0080] The beneficial effects of the above embodiment include: in order to comprehensively identify the diffusion and transmission of heat generated by the distribution transformer in the space where the distribution transformer is located, remote thermal infrared visual monitoring and analysis of the space where the distribution transformer is located is performed to obtain data on the heat diffusion rate and diffusion direction of the space. This allows accurate judgment of whether the distribution transformer is in an effective heat dissipation state, thereby identifying whether the distribution transformer is at risk of overheating and failure. Furthermore, when the distribution transformer is not in an effective heat dissipation state, the real-time operating load of the heat dissipation device is used to determine whether the heat dissipation device is in an extreme operating state. If it is in an extreme operating state, the time information corresponding to the time when the accumulated heat value in the space where the distribution transformer is located reaches the critical value corresponding to the distribution transformer switching to an overheating failure state is predicted based on the heat diffusion rate and diffusion direction data, and an early warning message containing this time information is sent to the remote monitoring platform, thereby enabling predictive operating state control of the distribution transformer and ensuring its continued stable operation.

[0081] In another embodiment, analyzing the heat diffusion speed and diffusion direction data to determine whether the distribution transformer is in an effective heat dissipation state includes:

[0082] Step S1: Assume that there are k obstacles around the distribution transformer, where the surface area of ​​the i-th obstacle is S i , i is the obstacle number, which is an integer greater than or equal to 1 and less than or equal to k. The straight-line distance from the geometric center of the i-th obstacle to the distribution transformer is D i , then the influence coefficient of the obstacles around the distribution transformer on its heat dissipation is:

[0083]

[0084] In the above formula (1), W is the influence coefficient of the obstacles around the distribution transformer on its heat dissipation, R iis the reflectivity of the i-th obstacle, a is an adjustment parameter whose value is greater than 0 and can be adjusted according to actual conditions, and e is a natural constant. By accurately quantifying and considering the conditions and emissivity of obstacles around the distribution transformer, the impact of obstacles on the heat diffusion process is accurately quantified and considered, providing a basis for subsequent judgment of whether the distribution transformer is in an effective heat dissipation state.

[0085] In step S2, assume that the airflow resistance coefficient of the environment in which the distribution transformer is located is C, v(t) is the wind speed at time t, v is the reference wind speed, and θ(t) is the angle between the wind direction and the heat diffusion direction at time t. Then, the influence function of the airflow on the heat dissipation of the distribution transformer is:

[0086]

[0087] In the above formula (2), f(t) is the influence function of airflow on the heat dissipation of the distribution transformer, and b is the velocity index; the influence of airflow on the heat dissipation of the distribution transformer is accurately reflected by factors such as airflow velocity and airflow angle;

[0088] Step S3, based on the calculation results of the above steps S1 and S2, determine the heat dissipation efficiency of the distribution transformer.

[0089]

[0090] In the above formula (3), H is the heat dissipation efficiency of the distribution transformer, wp(t) is the heat diffusion rate at time t, t0 is the start time of the monitoring period, and t1 is the end time of the monitoring period;

[0091] When H is greater than or equal to the preset efficiency threshold, it is determined that the distribution transformer is in an effective heat dissipation state; when H is less than the preset efficiency threshold, it is determined that the distribution transformer is not in an effective heat dissipation state.

[0092] The beneficial effects of the above embodiments are as follows: since the environment in which the distribution transformer is located may include a variety of factors that affect heat dissipation, such as airflow, obstacles, and the heat capacity of surrounding objects, these factors will affect the heat propagation path and speed. At the same time, heat may be transmitted through various means such as conduction, convection, and radiation. This increases the difficulty of determining whether the distribution transformer is in an effective heat dissipation state. However, if it is not possible to accurately determine whether the distribution transformer is in an effective heat dissipation state, the distribution transformer may be damaged or a major safety accident may occur. Accurately determining whether the distribution transformer is in an effective heat dissipation state based on the conditions of obstacles and airflow around the distribution transformer can avoid damage to the distribution transformer or the occurrence of major safety accidents.

[0093] See also Figure 2As shown, an embodiment of the present application provides a remote monitoring method based on a distribution transformer. The remote monitoring method based on a distribution transformer includes:

[0094] Remotely monitor the temperature of the distribution transformer to obtain temperature data of the distribution transformer during a complete working cycle; analyze the temperature data to determine the thermal change status information of the distribution transformer's environment; and determine whether the distribution transformer is in an overheating state based on the thermal change status information;

[0095] When the distribution transformer is in an overheated state, remotely monitor the heat dissipation device corresponding to the distribution transformer to obtain operating status data of the heat dissipation device; analyze the operating status data to determine whether the heat dissipation device is in a heat dissipation operating state that matches the operating state of the distribution transformer, and adjust the operating parameters of the heat dissipation device accordingly;

[0096] Conduct remote thermal infrared visual monitoring of the space where the distribution transformer is located to obtain dynamic data on heat transfer in the space. Based on the dynamic data, determine whether the distribution transformer is in an effective heat dissipation state. When the distribution transformer is not in an effective heat dissipation state, perform work failure prediction and early warning operations on the distribution transformer based on the real-time operating load of the heat dissipation equipment.

[0097] The beneficial effects of the above embodiments are as follows: the remote monitoring method based on the distribution transformer remotely monitors and analyzes the temperature data of the distribution transformer within a complete working cycle, determines the heat change status information of the environment in which the transformer is located, thereby judging whether the transformer is overheating, and directly monitoring the working temperature of the transformer to achieve timely and accurate identification of the transformer overheating state; it also remotely monitors the heat dissipation device corresponding to the transformer to obtain its operating status data, thereby judging whether the heat dissipation device is in a heat dissipation operating state matching the working state of the transformer and adjusting the operating parameters of the heat dissipation device to improve the heat dissipation efficiency of the heat dissipation device; it also performs thermal infrared visual monitoring and analysis of the space where the transformer is located to judge whether the transformer is in an effective heat dissipation state, and based on the real-time operating load of the heat dissipation device, performs transformer working failure prediction and early warning, monitors the working heat dissipation of the transformer from multiple dimensions, makes effective heat dissipation adjustments to the transformer, and timely and accurately predicts possible overheating failure of the transformer.

[0098] In another embodiment, remote temperature monitoring is performed on a distribution transformer to obtain temperature data of the distribution transformer during a complete working cycle; the temperature data is analyzed to determine thermal change status information of an environment in which the distribution transformer is located; and based on the thermal change status information, determining whether the distribution transformer is in an overheating state includes:

[0099] Remotely monitor the dynamic temperature of several components under the distribution transformer to obtain the operating temperature data of all components within a complete working cycle; based on the distribution location information of all components on the distribution transformer, integrate the operating temperature data of all components to obtain the overall operating temperature field change information of the distribution transformer;

[0100] A time evolution analysis is performed on the operating temperature field change information to determine the heat accumulation rate information of the environment in which the distribution transformer is located; based on the heat accumulation rate information, a determination is made as to whether the heat accumulation amount within a spatial range with a preset radius from the distribution transformer exceeds a preset accumulation threshold amount; if so, the distribution transformer is determined to be in an overheated state; if not, the distribution transformer is determined to be not in an overheated state.

[0101] The beneficial effects of the above embodiments are as follows: the distribution transformer is an integrated device with a complex structure, which contains multiple electronic devices inside. The corresponding operating temperature of each electronic device during the operation of the distribution transformer is also different. In order to accurately determine the overall operating temperature of the distribution transformer, remote temperature dynamic monitoring is performed on several electronic devices under the distribution transformer to obtain the operating temperature data of all electronic devices in a complete working cycle. Combined with the distribution position information of all electronic devices inside the distribution transformer, the operating temperature data of all electronic devices are integrated, thereby effectively fitting the overall operating temperature of the distribution transformer, determining the overall operating temperature field change information of the distribution transformer, and providing an accurate basis for subsequent judgment of whether the distribution transformer is overheating. In addition, a time evolution analysis is performed on the working temperature field change information to determine the heat accumulation rate information of the environment in which the distribution transformer is located, that is, the working temperature field change information is converted into the corresponding working heat generation time domain to obtain the heat accumulation rate information of the environment in which the distribution transformer is located (that is, the cumulative increase in heat in the environment per unit time). The heat accumulation rate information is then compared with the threshold value of the three-dimensional heat accumulation amount to determine whether the distribution transformer is in an overheating state, thereby facilitating the effective prediction of abnormal working conditions of the distribution transformer.

[0102] In another embodiment, when the distribution transformer is in an overheating state, remote monitoring is performed on a heat dissipation device corresponding to the distribution transformer to obtain operating status data of the heat dissipation device; the operating status data is analyzed to determine whether the heat dissipation device is in a heat dissipation operating state that matches the operating state of the distribution transformer, and the operating parameters of the heat dissipation device are adjusted accordingly, including:

[0103] When the distribution transformer is in an overheated state, remote dynamic monitoring is performed on the heat dissipation device corresponding to the distribution transformer to obtain the rotation speed data of the heat dissipation blades of the heat dissipation device within a complete working cycle;

[0104] A fitting analysis is performed on the rotational speed data to obtain information on the amount of heat dissipated by the heat dissipation device within a complete working cycle; the heat dissipation information is compared with the heat accumulation information of the distribution transformer in time domain changes to determine whether the time when the peak value of the heat dissipation of the heat dissipation device occurs overlaps with the time when the peak value of the heat accumulation of the distribution transformer occurs; if so, it is determined that the heat dissipation device is in a heat dissipation operating state that matches the working state of the distribution transformer; if not, it is determined that the heat dissipation device is not in a heat dissipation operating state that matches the working state of the distribution transformer, and the rotational speed change frequency of the heat dissipation blades of the heat dissipation device is adjusted.

[0105] The beneficial effect of the above embodiment is that when the distribution transformer is in an overheating state, it indicates that the heat dissipation device corresponding to the distribution transformer fails to dissipate the heat generated by the operation of the distribution transformer in a timely manner. Therefore, the heat dissipation device corresponding to the distribution transformer is remotely and dynamically monitored to obtain the rotation speed data of the heat dissipation blades of the heat dissipation device in a complete working cycle. In this way, the rotation speed changes of the heat dissipation blades of the heat dissipation device in a complete working cycle can be comprehensively monitored. In addition, a fitting analysis is performed on the rotation speed data to obtain information on the heat dissipation of the heat dissipation device within a complete working cycle. Generally speaking, the greater the rotation speed of the heat dissipation blades, the greater the heat dissipation of the heat dissipation device. The heat dissipation information and the heat accumulation information of the distribution transformer are then compared in time domain changes to determine whether the occurrence time of the heat dissipation peak of the heat dissipation device overlaps with the occurrence time of the heat accumulation peak of the distribution transformer, that is, to determine that when the heat accumulation value of the distribution transformer reaches a maximum value, the heat dissipation blades inside the heat dissipation device are in the highest rotation speed state, thereby determining whether the heat dissipation device is in a heat dissipation operation state that matches the working state of the distribution transformer. When the heat dissipation device is not in a heat dissipation operation state that matches the working state of the distribution transformer, the rotation speed change frequency of the heat dissipation blades of the heat dissipation device is adjusted so that the heat dissipation blades of the heat dissipation device can quickly and timely dissipate the heat generated by the distribution transformer during operation.

[0106] In another embodiment, remote thermal infrared visual monitoring is performed on the space where the distribution transformer is located to obtain dynamic heat transfer data of the space. Based on the dynamic heat transfer data, it is determined whether the distribution transformer is in an effective heat dissipation state. When the distribution transformer is not in an effective heat dissipation state, based on the real-time operating load of the heat dissipation device, a working failure prediction and early warning operation is performed on the distribution transformer, including:

[0107] Conduct remote thermal infrared visual monitoring of the space where the distribution transformer is located to obtain a thermal infrared dynamic image of the space; perform heat diffusion identification on the thermal infrared dynamic image to obtain data on the heat diffusion rate and direction of the space; analyze the heat diffusion rate and direction data to determine whether the distribution transformer is in an effective heat dissipation state;

[0108] When the distribution transformer is not in an effective heat dissipation state, the real-time operating load of the heat dissipation device is used to determine whether the heat dissipation device is in an extreme working state; if it is in an extreme working state, the time information of the overheating failure event of the distribution transformer is predicted based on the heat diffusion speed and diffusion direction data, and an early warning message containing the time information is sent to the remote monitoring platform.

[0109] The beneficial effects of the above embodiment include: in order to comprehensively identify the diffusion and transmission of heat generated by the distribution transformer in the space where the distribution transformer is located, remote thermal infrared visual monitoring and analysis of the space where the distribution transformer is located is performed to obtain data on the heat diffusion rate and diffusion direction of the space. This allows accurate judgment of whether the distribution transformer is in an effective heat dissipation state, thereby identifying whether the distribution transformer is at risk of overheating and failure. Furthermore, when the distribution transformer is not in an effective heat dissipation state, the real-time operating load of the heat dissipation device is used to determine whether the heat dissipation device is in an extreme operating state. If it is in an extreme operating state, the time information corresponding to the time when the accumulated heat value in the space where the distribution transformer is located reaches the critical value corresponding to the distribution transformer switching to an overheating failure state is predicted based on the heat diffusion rate and diffusion direction data, and an early warning message containing this time information is sent to the remote monitoring platform, thereby enabling predictive operating state control of the distribution transformer and ensuring its continued stable operation.

[0110] In general, the remote monitoring system and method based on the distribution transformer remotely monitors and analyzes the temperature data of the distribution transformer within a complete working cycle, determines the heat change status information of the transformer environment, and judges whether the transformer is overheating, performs direct working temperature monitoring on the transformer, and realizes timely and accurate identification of the transformer overheating state; it also remotely monitors the heat dissipation equipment corresponding to the transformer to obtain its operating status data, and judges whether the heat dissipation equipment is in a heat dissipation operating state that matches the working state of the transformer and adjusts the operating parameters of the heat dissipation equipment to improve the heat dissipation efficiency of the heat dissipation equipment; it also performs thermal infrared visual monitoring and analysis of the space where the transformer is located to judge whether the transformer is in an effective heat dissipation state, and based on the real-time operating load of the heat dissipation equipment, predicts and warns the transformer's working failure, monitors the working heat dissipation of the transformer from multiple dimensions, makes effective heat dissipation adjustments to the transformer, and predicts the possible overheating failure of the transformer in a timely and accurate manner.

[0111] The above is only a specific embodiment of the present invention, and any other improvements made based on the concept of the present invention are considered to be within the scope of protection of the present invention.

Claims

1. A remote monitoring system based on distribution transformer, characterized in that: include: A remote temperature monitoring module is used to remotely monitor the temperature of the distribution transformer and obtain the temperature data of the distribution transformer within a complete working cycle; A transformer overheating identification module is used to analyze the temperature data to determine the heat change state information of the environment in which the distribution transformer is located; based on the heat change state information, determine whether the distribution transformer is in an overheating state; A heat dissipation device operation monitoring module is used to remotely monitor the heat dissipation device corresponding to the distribution transformer when the distribution transformer is in an overheated state, and obtain the operation status data of the heat dissipation device; a heat dissipation device operation adjustment module, used to analyze the operation status data, determine whether the heat dissipation device is in a heat dissipation operation state that matches the working state of the distribution transformer, and thereby adjust the operation parameters of the heat dissipation device; A remote thermal infrared monitoring and identification module is used to perform remote thermal infrared visual monitoring of the space where the distribution transformer is located, obtain dynamic data of heat transfer in the space, and determine whether the distribution transformer is in an effective heat dissipation state based on the dynamic data of heat transfer; A transformer failure prediction and early warning module, used to perform working failure prediction and early warning operations on the distribution transformer based on the real-time operating load of the heat dissipation device when the distribution transformer is not in an effective heat dissipation state; The remote thermal infrared monitoring and identification module is used to perform remote thermal infrared visual monitoring of the space where the distribution transformer is located, obtain dynamic data of heat transfer in the space, and determine whether the distribution transformer is in an effective heat dissipation state based on the dynamic data of heat transfer, including: Performing remote thermal infrared visual monitoring on the space where the distribution transformer is located to obtain a thermal infrared dynamic image of the space; performing heat diffusion recognition on the thermal infrared dynamic image to obtain heat diffusion speed and diffusion direction data of the space; analyzing the heat diffusion speed and diffusion direction data to determine whether the distribution transformer is in an effective heat dissipation state; The transformer failure prediction and early warning module is used to perform working failure prediction and early warning operations on the distribution transformer based on the real-time operating load of the heat dissipation device when the distribution transformer is not in an effective heat dissipation state, including: When the distribution transformer is not in an effective heat dissipation state, whether the heat dissipation device is in an extreme working state is determined based on the real-time operating load of the heat dissipation device; if it is in an extreme working state, the time information of the overheating failure event of the distribution transformer is predicted based on the heat diffusion speed and diffusion direction data, and an early warning message containing the time information is sent to a remote monitoring platform; the heat diffusion speed and diffusion direction data are analyzed to determine whether the distribution transformer is in an effective heat dissipation state, including: Step S1: Assume that there are k obstacles around the distribution transformer, where the surface area of ​​the i-th obstacle is S i , i is the obstacle number, which is an integer greater than or equal to 1 and less than or equal to k, and the straight-line distance from the geometric center of the i-th obstacle to the distribution transformer is D i , then the influence coefficient of obstacles around the distribution transformer on its heat dissipation is: In the above formula (1), w is the influence coefficient of the obstacles around the distribution transformer on its heat dissipation, R i is the reflectivity of the ith obstacle, a is an adjustment parameter, its value is greater than 0, and e is a natural constant; Step S2, assuming that the airflow resistance coefficient of the environment in which the distribution transformer is located is C, v(t) is the wind speed at time t, v is the reference wind speed, θ(t) is the angle between the wind direction and the heat diffusion direction at time t, then the influence function of the airflow on the heat dissipation of the distribution transformer is: In the above formula (2), f(t) is the influence function of airflow on the heat dissipation of the distribution transformer, and b is the velocity index; Step S3, determining the heat dissipation efficiency of the distribution transformer according to the calculation results of the above steps S1 and S2, In the above formula (3), H is the heat dissipation efficiency of the distribution transformer, wp(t) is the heat diffusion rate at time t, t0 is the start time of the monitoring time period, and t1 is the end time of the monitoring time period; When H is greater than or equal to a preset efficiency threshold, it is determined that the distribution transformer is in an effective heat dissipation state; when H is less than the preset efficiency threshold, it is determined that the distribution transformer is not in an effective heat dissipation state.

2. The remote monitoring system based on distribution transformer according to claim 1, characterized in that: The remote temperature monitoring module is used to remotely monitor the temperature of the distribution transformer to obtain the temperature data of the distribution transformer in a complete working cycle, including: Remotely monitor the temperature of several components under the distribution transformer to obtain the operating temperature data of all components within a complete working cycle; The transformer overheating identification module is used to analyze the temperature data to determine the heat change state information of the environment in which the distribution transformer is located; based on the heat change state information, determine whether the distribution transformer is in an overheating state, including: Based on the distribution position information of all devices in the distribution transformer, the operating temperature data of all devices are integrated to obtain the overall operating temperature field change information of the distribution transformer; Perform a time evolution analysis on the working temperature field change information to determine the heat accumulation rate information of the environment in which the distribution transformer is located; based on the heat accumulation rate information, determine whether the heat accumulation amount within a spatial range of a preset radius from the distribution transformer exceeds a preset accumulation threshold amount; if so, determine that the distribution transformer is in an overheated state; if not, determine that the distribution transformer is not in an overheated state.

3. The remote monitoring system based on distribution transformer according to claim 1, characterized in that: The heat dissipation device operation monitoring module is used to remotely monitor the heat dissipation device corresponding to the distribution transformer when the distribution transformer is in an overheated state, and obtain the operation status data of the heat dissipation device, including: When the distribution transformer is in an overheated state, remotely monitor the cooling device corresponding to the distribution transformer to obtain the rotation speed data of the cooling blades of the cooling device in a complete working cycle; The heat dissipation device operation adjustment module is used to analyze the operation status data to determine whether the heat dissipation device is in a heat dissipation operation state that matches the working state of the distribution transformer, thereby adjusting the operation parameters of the heat dissipation device, including: The rotation speed data is fitted and analyzed to obtain the heat dissipation information of the heat dissipation device in a complete working cycle; the heat dissipation information and the heat accumulation information of the distribution transformer are compared in time domain to determine whether the occurrence time of the heat dissipation peak of the heat dissipation device overlaps with the occurrence time of the heat accumulation peak of the distribution transformer; if so, it is determined that the heat dissipation device is in a heat dissipation operation state that matches the working state of the distribution transformer; if not, it is determined that the heat dissipation device is not in a heat dissipation operation state that matches the working state of the distribution transformer, and the rotation speed change frequency of the heat dissipation blades of the heat dissipation device is adjusted.

4. A remote monitoring method based on distribution transformer, characterized in that: include: Perform remote temperature monitoring on the distribution transformer to obtain temperature data of the distribution transformer within a complete working cycle; Analyze the temperature data to determine the heat change state information of the environment in which the distribution transformer is located; based on the heat change state information, determine whether the distribution transformer is in an overheating state; When the distribution transformer is in an overheated state, remotely monitor the heat dissipation device corresponding to the distribution transformer to obtain operation status data of the heat dissipation device; Analyzing the operating state data to determine whether the heat dissipation device is in a heat dissipation operating state that matches the operating state of the distribution transformer, thereby adjusting the operating parameters of the heat dissipation device; Performing remote thermal infrared visual monitoring of the space where the distribution transformer is located to obtain dynamic data of heat transfer in the space, and judging whether the distribution transformer is in an effective heat dissipation state based on the dynamic data of heat transfer; When the distribution transformer is not in an effective heat dissipation state, based on the real-time operating load of the heat dissipation device, a working failure prediction and early warning operation is performed on the distribution transformer; Performing remote thermal infrared visual monitoring of the space where the distribution transformer is located to obtain dynamic data of heat transfer in the space, and judging whether the distribution transformer is in an effective heat dissipation state based on the dynamic data of heat transfer; When the distribution transformer is not in an effective heat dissipation state, based on the real-time operating load of the heat dissipation device, a working failure prediction and early warning operation is performed on the distribution transformer, including: Performing remote thermal infrared visual monitoring on the space where the distribution transformer is located to obtain a thermal infrared dynamic image of the space; performing heat diffusion recognition on the thermal infrared dynamic image to obtain heat diffusion speed and diffusion direction data of the space; analyzing the heat diffusion speed and diffusion direction data to determine whether the distribution transformer is in an effective heat dissipation state; When the distribution transformer is not in an effective heat dissipation state, whether the heat dissipation device is in an extreme working state is determined based on the real-time operating load of the heat dissipation device; if it is in an extreme working state, the time information of the overheating failure event of the distribution transformer is predicted based on the heat diffusion speed and diffusion direction data, and an early warning message containing the time information is sent to a remote monitoring platform; the heat diffusion speed and diffusion direction data are analyzed to determine whether the distribution transformer is in an effective heat dissipation state, including: Step S1: Assume that there are k obstacles around the distribution transformer, where the surface area of ​​the i-th obstacle is S i , i is the obstacle number, which is an integer greater than or equal to 1 and less than or equal to k, and the straight-line distance from the geometric center of the i-th obstacle to the distribution transformer is D i , then the influence coefficient of obstacles around the distribution transformer on its heat dissipation is: In the above formula (1), w is the influence coefficient of the obstacles around the distribution transformer on its heat dissipation, R i is the reflectivity of the ith obstacle, a is an adjustment parameter, its value is greater than 0, and e is a natural constant; Step S2, assuming that the airflow resistance coefficient of the environment in which the distribution transformer is located is C, v(t) is the wind speed at time t, v is the reference wind speed, θ(t) is the angle between the wind direction and the heat diffusion direction at time t, then the influence function of the airflow on the heat dissipation of the distribution transformer is: In the above formula (2), f(t) is the influence function of airflow on the heat dissipation of the distribution transformer, and b is the velocity index; Step S3, determining the heat dissipation efficiency of the distribution transformer according to the calculation results of the above steps S1 and S2, In the above formula (3), H is the heat dissipation efficiency of the distribution transformer, wp(t) is the heat diffusion rate at time t, t0 is the start time of the monitoring time period, and t1 is the end time of the monitoring time period; When H is greater than or equal to a preset efficiency threshold, it is determined that the distribution transformer is in an effective heat dissipation state; when H is less than the preset efficiency threshold, it is determined that the distribution transformer is not in an effective heat dissipation state.

5. The remote monitoring method based on distribution transformer according to claim 4, characterized in that: Remotely monitor the temperature of the distribution transformer to obtain temperature data of the distribution transformer in a complete working cycle; analyze the temperature data to determine the heat change state information of the environment in which the distribution transformer is located; Based on the heat change state information, determining whether the distribution transformer is in an overheated state includes: Perform remote temperature dynamic monitoring on several devices under the distribution transformer to obtain the operating temperature data of all devices in a complete working cycle; based on the distribution location information of all devices in the distribution transformer, integrate the operating temperature data of all devices to obtain the overall operating temperature field change information of the distribution transformer; Perform a time evolution analysis on the working temperature field change information to determine the heat accumulation rate information of the environment in which the distribution transformer is located; based on the heat accumulation rate information, determine whether the heat accumulation amount within a spatial range of a preset radius from the distribution transformer exceeds a preset accumulation threshold amount; if so, determine that the distribution transformer is in an overheated state; if not, determine that the distribution transformer is not in an overheated state.

6. The remote monitoring method based on distribution transformer according to claim 5, characterized in that: When the distribution transformer is in an overheated state, remotely monitor the heat dissipation device corresponding to the distribution transformer to obtain the operation status data of the heat dissipation device; analyze the operation status data to determine whether the heat dissipation device is in a heat dissipation operation state matching the working state of the distribution transformer, so as to adjust the operation parameters of the heat dissipation device, including: When the distribution transformer is in an overheated state, remotely monitor the cooling device corresponding to the distribution transformer to obtain the rotation speed data of the cooling blades of the cooling device in a complete working cycle; The rotation speed data is fitted and analyzed to obtain the heat dissipation information of the heat dissipation device in a complete working cycle; the heat dissipation information and the heat accumulation information of the distribution transformer are compared in time domain to determine whether the occurrence time of the heat dissipation peak of the heat dissipation device overlaps with the occurrence time of the heat accumulation peak of the distribution transformer; if so, it is determined that the heat dissipation device is in a heat dissipation operation state that matches the working state of the distribution transformer; if not, it is determined that the heat dissipation device is not in a heat dissipation operation state that matches the working state of the distribution transformer, and the rotation speed change frequency of the heat dissipation blades of the heat dissipation device is adjusted.

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