Intelligent American transformer and combined transformer substation

Abstract

The invention belongs to the technical field of transformers, and particularly relates to an intelligent American transformer and a combined substation, the transformer comprises a transformer body, a data acquisition device and an intelligent component, the intelligent component comprises a plurality of monitoring units, and the monitoring units are used for obtaining predicted operation data according to historical operation data, historical environment data and related data and sending the predicted operation data to the transformer body. Calculating a monitoring index according to the predicted operation data and the related data, and calculating the size of an estimated monitoring memory according to the monitoring index; the intelligent American transformer selects one of the microprocessors of the plurality of monitoring units as a main processor; and the main processor is configured to deploy the memory of each monitoring unit according to the pre-estimated monitoring memory size corresponding to each monitoring unit so as to optimize the memory utilization rate of each monitoring unit. According to the invention, the memory of each monitoring unit can be deployed, the memory utilization rate of each monitoring unit is optimized, and safe and reliable operation of the American transformer is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of transformers, and in particular to an intelligent American-style transformer and a combined substation. Background Art

[0002] American transformers are suitable for commercial centers, industrial parks, residential areas, streets, airports, docks, subways, densely populated areas in Maocheng, and deep into the load center, for ring network and two-way power supply. They can be installed once to achieve power transmission. They have the characteristics of full insulation, full sealing structure, maintenance-free, easy installation, etc. American transformers often have multiple monitoring units for monitoring different types of data signals. The monitoring units are equipped with independent microprocessors to analyze the collected data signals, and then determine whether the transformer is faulty, and feedback to the monitoring terminal or dispatching center.

[0003] In the prior art, for transformers and / or box-type substations, the memory of multiple monitoring units is often used separately without additional allocation, which can easily lead to the inability to effectively analyze the relevant data of the transformer body due to insufficient memory in the monitoring unit, resulting in monitoring errors and omissions, or the inability to effectively utilize the monitoring unit memory due to excessive remaining monitoring memory, resulting in low memory utilization. Some transformers and / or box-type substations may simply allocate monitoring memory units, but do not take into account the specific memory size that may be used by different monitoring units, nor do they combine the corresponding operating fault index of the transformer body. The intelligence level of memory allocation of the monitoring unit is low, and the memory utilization efficiency is also low. Summary of the invention

[0004] In order to solve the problems existing in the prior art, the present invention provides an intelligent American transformer, which can obtain predicted operation data based on the historical operation data and historical environmental data of the target object collected by the monitoring unit, and calculate the monitoring index based on the predicted operation data and related data, and then calculate the corresponding estimated monitoring memory size, and finally allocate the memory of each monitoring unit according to the estimated monitoring memory size corresponding to each monitoring unit to optimize the memory utilization of each monitoring unit. The specific technical solution of the intelligent American transformer is as follows:

[0005] An intelligent American transformer comprises a transformer body, a plurality of data acquisition devices installed on the transformer body, and an intelligent component connected to the data acquisition device, wherein the intelligent component comprises a plurality of monitoring units, and the plurality of data acquisition units correspond one to one to the plurality of monitoring units, the data acquisition device is used to collect relevant data of the transformer body and feed it back to the corresponding monitoring unit; the monitoring unit is used to obtain corresponding historical operation data and historical environmental data, obtain predicted operation data according to the historical operation data, historical environmental data and related data, calculate a monitoring index according to the predicted operation data and the related data, and calculate an estimated monitoring memory size according to the monitoring index.

[0006] The intelligent American transformer selects one of the microprocessors of the multiple monitoring units as the main processor;

[0007] The main processor is configured to allocate the memory of each monitoring unit according to the estimated monitoring memory size corresponding to each monitoring unit, so as to optimize the memory utilization of each monitoring unit.

[0008] Preferably, the monitoring unit first calculates the operation fault occurrence index based on the real-time operation data, the predicted operation data and the real-time environmental data, then calculates the monitoring index based on the operation fault index, and finally calculates the estimated monitoring memory size based on the monitoring index and the preset basic monitoring memory.

[0009] Preferably, the intelligent component is also used to compare and analyze the real-time operating data with the corresponding preset data, and remotely transmit the comparison and analysis results to the dispatching center through the communication module, implement fault alarm, and point out the cause and fault point of the fault, so that the dispatching center can monitor and maintain the operating status of the transformer body and the switch of the load terminal to ensure stable operation of the power grid.

[0010] Preferably, the plurality of monitoring units include an oil chromatography and micro-water monitoring unit, a partial discharge monitoring unit, a core grounding current monitoring unit, an acoustic fingerprint monitoring unit, a transformer bushing insulation monitoring unit and an on-load tap changer monitoring unit.

[0011] Preferably, the oil chromatography and trace water monitoring unit, the partial discharge monitoring unit, the core grounding current monitoring unit, the acoustic fingerprint monitoring unit, the transformer bushing insulation monitoring unit and the on-load tap changer monitoring unit all include a microprocessor and a memory.

[0012] Preferably, the intelligent component also includes a universal circuit breaker, an intelligent capacitor, an intelligent molded case circuit breaker and an intelligent watt-hour meter located on the low-voltage side.

[0013] Preferably, the universal circuit breaker, intelligent capacitor, intelligent molded case circuit breaker and intelligent watt-hour meter are all connected to an RS485 bus.

[0014] Preferably, the dispatch center includes a communication terminal and a background monitor, the intelligent component is connected to the communication terminal and the background monitor via a GPRS / GSM wireless communication link, and the background monitor is also connected to an RS485 bus.

[0015] The present invention also provides a combined substation, which includes the intelligent American transformer.

[0016] Preferably, the combined substation further includes a capacitor chamber, a high voltage chamber and a low voltage chamber.

[0017] The present invention provides an intelligent American-style transformer and a combined substation, which have the following beneficial effects:

[0018] 1. It can obtain predicted operation data based on the historical operation data and historical environmental data collected by the monitoring unit, calculate the monitoring index based on the predicted operation data and related data, and then calculate the corresponding estimated monitoring memory size. Finally, according to the estimated monitoring memory size corresponding to each monitoring unit, the memory of each monitoring unit is allocated to optimize the memory utilization of each monitoring unit and ensure the safe and reliable operation of the American transformer.

[0019] 2. By selecting one of the microprocessors of multiple monitoring units as the main processor, the main processor is configured to allocate the memory of each monitoring unit according to the estimated monitoring memory size corresponding to each monitoring unit to optimize the memory utilization of each monitoring unit, which provides a new idea for optimizing the allocation of each monitoring unit of the American transformer to better realize the intelligent monitoring of the American transformer.

[0020] 3. By optimizing the memory utilization of each monitoring unit, the operation of the combined substation can be better monitored, and fault monitoring errors caused by insufficient memory in the transformer monitoring unit can be avoided, which can improve the working reliability of American transformers and combined substations. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The present invention can be further understood from the following description in conjunction with the accompanying drawings. The components in the figures are not necessarily drawn to scale, but the emphasis is placed on illustrating the principles of the embodiments. In different views, the same reference numerals designate corresponding parts.

[0022] Figure 1 It is a schematic diagram of the overall structure of the intelligent American transformer of the present invention;

[0023] Figure 2 A schematic diagram of the structural relationship between the intelligent components and the dispatch center of the present invention;

[0024] Figure 3 A top view of the combined substation of the present invention;

[0025] Figure 4 It is a front view of the combined substation of the present invention;

[0026] Figure 5 It is a right side view of the combined substation of the present invention.

[0027] In the figure: 1. Transformer; 2. Capacitor room; 3. High-voltage room; 4. Low-voltage room. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with its embodiments. It should be understood that the specific implementation methods described herein are only used to explain the present invention and do not limit the protection scope of the present invention.

[0029] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only and do not represent the only implementation method.

[0030] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0031] The “first” and “second” mentioned in the present invention do not represent specific quantities and orders, but are merely used to distinguish names.

[0032] Embodiment 1:

[0033] See also Figure 1 , an intelligent American transformer, comprising a transformer body, a plurality of data acquisition devices installed on the transformer body, and an intelligent component connected to the data acquisition device, wherein the intelligent component comprises a plurality of monitoring units, and the plurality of data acquisition units correspond one to one with the plurality of monitoring units, and the data acquisition device is used to collect relevant data of the transformer body and feed it back to the corresponding monitoring unit. Different data acquisition devices are installed at different positions of the transformer body, and are configured to collect different types of relevant data of the transformer body, such as noise, vibration, temperature and humidity, current and voltage, partial discharge, and bushing insulation performance.

[0034] The monitoring unit is used to obtain corresponding historical operation data and historical environment data, obtain predicted operation data based on the historical operation data, historical environment data and related data, calculate a monitoring index based on the predicted operation data and related data, and calculate an estimated monitoring memory size based on the monitoring index.

[0035] Specifically, another method for obtaining predicted operation data based on historical operation data, historical environmental data and related data is to construct a neural network model for obtaining predicted operation data, train the neural network model through historical operation data and historical environmental data, and obtain predicted operation data by inputting the obtained real-time operation data and real-time environmental data of the transformer body into the trained neural network model. It should be noted that when multiple data acquisition devices respectively collect real-time operation data and real-time environmental data of different types of transformer bodies, the monitoring unit obtains corresponding types of predicted operation data based on historical operation data, historical environmental data and related data.

[0036] In this embodiment, corresponding types of predicted operation data are obtained through historical operation data, historical environmental data and related data, and the influence of environmental data on the operation state of the transformer body is taken into consideration, so that more accurate predicted operation data can be obtained.

[0037] The smart American transformer selects one of the microprocessors from the microprocessors of multiple monitoring units as the main processor. Specifically, one of the multiple monitoring units can be randomly selected as the main processor. Preferably, the difference between the actual memory and the estimated memory is calculated first, and then the priorities of the microprocessors of the multiple monitoring units are obtained according to the size of the difference. The larger the difference between the actual memory and the estimated memory, the higher the priority of the corresponding microprocessor. Finally, the microprocessor with the highest priority is used as the main processor.

[0038] The larger the difference between the actual memory and the estimated memory, the larger the free memory of the microprocessor. In this way, by using the microprocessor with the highest priority as the main processor, the memory utilization efficiency of the microprocessors of the multiple monitoring units can be further optimized.

[0039] The main processor is configured to allocate the memory of each monitoring unit according to the estimated monitoring memory size corresponding to each monitoring unit, so as to optimize the memory utilization of each monitoring unit.

[0040] The intelligent American transformer described in the present invention obtains predicted operation data based on the historical operation data and historical environmental data of the target object collected by the monitoring unit, calculates the monitoring index based on the predicted operation data and related data, and then calculates the corresponding estimated monitoring memory size. Finally, according to the estimated monitoring memory size corresponding to each monitoring unit, the memory of each monitoring unit is allocated, which can optimize the memory utilization of each monitoring unit and ensure the safe and reliable operation of the American transformer.

[0041] In addition, by selecting one of the microprocessors of multiple monitoring units as the main processor, the main processor is configured to allocate the memory of each monitoring unit according to the estimated monitoring memory size corresponding to each monitoring unit to optimize the memory utilization of each monitoring unit, which provides a new idea for optimizing the allocation of each monitoring unit of the American transformer to better realize the intelligent monitoring of the American transformer.

[0042] Embodiment 2:

[0043] See also Figure 1 , an intelligent American transformer, including a transformer body, a plurality of data acquisition devices installed on the transformer body, and an intelligent component connected to the data acquisition device, wherein the intelligent component includes a plurality of monitoring units, and the plurality of data acquisition units correspond one to one with the plurality of monitoring units, and the data acquisition device is used to collect relevant data of the transformer body and feed it back to the corresponding monitoring unit. Different data acquisition devices are installed at different positions of the transformer body, and are configured to collect different types of relevant data of the transformer body, such as noise, vibration, temperature and humidity, current and voltage, partial discharge, and bushing insulation performance data information. Specifically, the plurality of data acquisition devices can be different types of sensors and / or monitoring equipment.

[0044] The monitoring unit is used to obtain corresponding historical operation data and historical environment data, obtain predicted operation data based on the historical operation data, historical environment data and related data, calculate a monitoring index based on the predicted operation data and related data, and calculate an estimated monitoring memory size based on the monitoring index.

[0045] Specifically, another method for obtaining predicted operation data based on historical operation data, historical environmental data and related data is to construct a neural network model for obtaining predicted operation data, train the neural network model through historical operation data and historical environmental data, and obtain predicted operation data by inputting the obtained real-time operation data and real-time environmental data of the transformer body into the trained neural network model. It should be noted that when multiple data acquisition devices respectively collect real-time operation data of different types of transformer bodies, the monitoring unit obtains corresponding types of predicted operation data based on historical operation data, historical environmental data and related data.

[0046] In this embodiment, corresponding types of predicted operation data are obtained through historical operation data, historical environmental data and related data, and the influence of environmental data on the operation state of the transformer body is taken into consideration, so that more accurate predicted operation data can be obtained.

[0047] The intelligent American transformer selects one of the microprocessors from the microprocessors of multiple monitoring units as the main processor. Specifically, one of the multiple monitoring units can be randomly selected as the main processor. Preferably, the difference between the actual memory and the estimated memory is calculated first, and then the priorities of the microprocessors of the multiple monitoring units are obtained according to the size of the difference. The larger the difference between the actual memory and the estimated memory, the higher the priority of the corresponding microprocessor. Finally, the microprocessor with the highest priority is used as the main processor. The larger the difference between the actual memory and the estimated memory, the larger the free memory of the microprocessor. In this way, by using the microprocessor with the highest priority as the main processor, the memory utilization efficiency of the microprocessors of multiple monitoring units can be further optimized.

[0048] The main processor is configured to allocate the memory of each monitoring unit according to the estimated monitoring memory size corresponding to each monitoring unit, so as to optimize the memory utilization of each monitoring unit.

[0049] The intelligent American transformer described in the present invention obtains predicted operation data based on the historical operation data and historical environmental data of the target object collected by the monitoring unit, calculates the monitoring index based on the predicted operation data and related data, and then calculates the corresponding estimated monitoring memory size. Finally, according to the estimated monitoring memory size corresponding to each monitoring unit, the memory of each monitoring unit is allocated, which can optimize the memory utilization of each monitoring unit, improve the intelligence level of transformer operation status monitoring, and ensure the safe and reliable operation of the American transformer.

[0050] Here, the real-time target object refers to the type of data collected, such as temperature and humidity, vibration value, voiceprint value, partial discharge parameters, etc.

[0051] In addition, by selecting one of the microprocessors of multiple monitoring units as the main processor, the main processor is configured to allocate the memory of each monitoring unit according to the estimated monitoring memory size corresponding to each monitoring unit to optimize the memory utilization of each monitoring unit, which provides a new idea for optimizing the allocation of each monitoring unit of the American transformer to better realize the intelligent monitoring of the American transformer.

[0052] Preferably, the monitoring unit first calculates the operation fault occurrence index based on the real-time operation data, the predicted operation data and the real-time environmental data, then calculates the monitoring index based on the operation fault index, and finally calculates the estimated monitoring memory size based on the monitoring index and the preset basic monitoring memory.

[0053] Generally speaking, the operational failure index is proportional to the monitoring index, and the estimated monitoring memory size is proportional to the monitoring index.

[0054] In the prior art, for transformers and / or box-type substations, the memory of multiple monitoring units is often used separately without additional allocation, which can easily lead to the inability to effectively analyze the relevant data of the transformer body due to insufficient memory in the monitoring unit, resulting in monitoring errors and omissions, or the inability to effectively utilize the monitoring unit memory due to excessive remaining monitoring memory, resulting in low memory utilization. Some transformers and / or box-type substations may simply allocate monitoring memory units, but do not take into account the specific memory size that may be used by different monitoring units, nor do they combine the corresponding operating fault index of the transformer body. The intelligent degree of memory allocation of the monitoring unit is low.

[0055] Compared with the prior art, the present application calculates the monitoring index through the operation fault index, and finally calculates the estimated monitoring memory size according to the monitoring index and the preset basic monitoring memory. It combines the corresponding operation fault index of the transformer body, and can more specifically calculate the memory size that may be used by the monitoring unit, thereby improving the intelligence level of the memory allocation of the monitoring unit, and can better avoid the problems of monitoring errors and low memory utilization.

[0056] The intelligent component is also used to compare and analyze the real-time operating data with the corresponding preset data, and remotely transmit the comparison and analysis results to the dispatching center through the communication module, implement fault alarm, and point out the cause and fault point of the fault, so that the dispatching center can monitor and maintain the operating status of the transformer body and the switch of the load terminal to ensure the stable operation of the power grid.

[0057] Specifically, the intelligent components include a transformer monitoring main control unit, a comprehensive measurement unit, an oil chromatography and micro-water monitoring unit, a partial discharge monitoring unit, a core grounding current monitoring unit, an acoustic fingerprint monitoring unit, a transformer bushing insulation monitoring unit and an on-load tap changer monitoring unit.

[0058] The transformer monitoring main control unit, integrated measurement unit, oil chromatography and micro-water monitoring unit, partial discharge monitoring unit, core grounding current monitoring unit, acoustic fingerprint monitoring unit, transformer bushing insulation monitoring unit and on-load tap changer monitoring unit all adopt monitoring units with the same structure. The monitoring unit includes a microprocessor, a synchronous dynamic random access memory, a memory, a serial port drive circuit and an Ethernet control. The microprocessor communicates bidirectionally with the synchronous dynamic random access memory, the microprocessor communicates bidirectionally with the memory, the microprocessor communicates bidirectionally with the serial port drive circuit, the microprocessor communicates bidirectionally with the Ethernet controller, and the Ethernet controller is used to realize bidirectional communication with the communication module.

[0059] As the specific installation positions of the transformer monitoring main control unit, integrated measurement unit, oil chromatography and micro-water monitoring unit, partial discharge monitoring unit, core grounding current monitoring unit, acoustic fingerprint monitoring unit, transformer bushing insulation monitoring unit and on-load tap changer monitoring unit and the data acquisition device on the transformer body belong to conventional technical means in this field and will not be elaborated here.

[0060] Since the American transformer integrates multiple data acquisition devices and multiple monitoring units, it does not need to be combined with other detection equipment. The transformer operation data can be independently detected through the data acquisition device and the monitoring unit.

[0061] By setting up multiple different types of data acquisition devices to obtain multiple different types of measurement parameters, the operating status of the transformer can be monitored in real time, unnecessary power outage tests and maintenance can be reduced, the maintenance workload can be reduced, the maintenance cost can be reduced, the targeted maintenance can be improved, the automation of online monitoring information processing can be realized, the reliability of the power system can be significantly improved, and the workload of personnel can be greatly reduced.

[0062] Also, see Figure 2 The intelligent component also includes a universal circuit breaker, an intelligent capacitor, an intelligent molded case circuit breaker and an intelligent watt-hour meter located on the low-voltage side. The intelligent component, the universal circuit breaker, the intelligent capacitor, the intelligent molded case circuit breaker and the intelligent watt-hour meter are all connected to the RS485 bus. The dispatch center includes a communication terminal and a background monitor, and the intelligent component is connected to the communication terminal and the background monitor through a GPRS / GSM wireless communication link, and the background monitor is also connected to the RS485 bus.

[0063] By implementing communication networking through RS485 bus technology, the staff can monitor the operating status of the product in different locations in real time through the background monitor. In addition, since the intelligent components are connected to the communication terminal and the background monitor through the GPRS / GSM wireless communication link, the real-time alarm function of the American box transformer can be realized through the GPRS / GSM technology, ensuring the safe operation of the product in an unattended state, realizing the automation of online monitoring information processing, significantly improving the reliability of the power system, and greatly reducing the workload of personnel.

[0064] See also Figure 3-5 This embodiment also provides a combined substation, which includes the smart American transformer 1. Specifically, the combined substation also includes a capacitor room 2, a high-voltage room 3, and a low-voltage room 4. A low-voltage switch is installed in the low-voltage room. Since the specific installation layout of the capacitor room, the high-voltage room, the low-voltage room and the transformer belongs to conventional technical means, it will not be repeated here.

[0065] Embodiment three:

[0066] It should be understood that this embodiment at least includes all the technical features of the above embodiments, and on the basis of the above embodiments, further specifically describes the American transformer and combined substation described in this application.

[0067] The specific method for obtaining predicted operation data based on historical operation data, historical environmental data and related data includes: constructing a prediction neural network model, training the prediction neural network model through historical operation data and historical environmental data, and using the trained prediction neural network model to obtain predicted operation data based on real-time operation data and real-time environmental data. The predicted operation data includes but is not limited to the operating current, voltage, vibration sound pattern, partial discharge and bushing insulation performance parameters of the transformer body in the future preset time period, as well as the environmental parameters around the transformer body in the future preset time period.

[0068] The specific method for calculating the monitoring index based on the predicted operation data and related data includes the following steps:

[0069] The first step is to calculate the predicted failure probability of the target monitoring object within a preset time period in the future based on the predicted operation data.

[0070] Specifically, the fault data set of the target monitoring object can be obtained first, and the predicted fault probability can be calculated based on the similarity between the predicted operation data and the fault data set.

[0071] The second step is to calculate the real-time failure probability of the target monitoring object based on relevant data (i.e., real-time operation data and real-time environmental data).

[0072] Specifically, the fault data set of the target monitoring object can be obtained first, and the real-time fault probability can be calculated based on the similarity between the calculated relevant data and the fault data set.

[0073] The third step is to calculate the predicted failure probability P of the target monitoring object. p , real-time failure probability P r The monitoring index is calculated based on the fault occurrence time Ft and number n in the past preset time period, the minimum time interval Ft between two consecutive faults, the design service life Lc of the transformer body, and the operation time Rt of the transformer body.

[0074] Specifically, the monitoring index Among them, Ft i Indicates the time when the i-th fault occurred within the past preset time period.

[0075] By formula It can be seen that the monitoring index is proportional to the predicted failure probability, the real-time failure probability, the ratio of the failure time and the minimum interval time, the design service life, and the difference between the design service life and the time put into operation. The higher the preset failure probability and the real-time failure probability, the higher the monitoring index is relatively; at the same time, the longer the monitoring object is in operation, the higher its monitoring index is relatively. The longer the failure time is, the more serious the failure is to a certain extent. The smaller the time interval between two consecutive failures is, the higher the frequency of failures of the target monitoring object is. By calculating the ratio of the failure time and the minimum interval time, the degree of failure or the comprehensive health of the target monitoring object in the past preset time period can be obtained.

[0076] It should be noted that the fault occurrence time Ft of the target monitoring object in the past preset time period refers to the time when the data monitored by the monitoring unit exceeds the preset threshold, and the number of fault occurrences n of the target monitoring object in the past preset time period refers to the number of times the data monitored by the monitoring unit exceeds the preset threshold. That is, when the data monitored by the monitoring unit exceeds the preset threshold, it is determined that a fault has occurred.

[0077] The predicted failure probability P of the comprehensive target monitoring object p , real-time failure probability P r , the fault occurrence time Ft and number n in the past preset time period, the minimum time interval Ft between two consecutive faults, the design service life Lc of the transformer body, and the operation time Rt of the transformer body are used to calculate the monitoring index. This can more comprehensively consider the impact of various different factors on the memory size of the monitoring unit, so that the monitoring index is more in line with the actual situation of the monitoring unit.

[0078] The fourth step is to calculate the estimated monitoring memory size based on the monitoring index. Specifically, based on the monitoring index and the preset basic monitoring memory PMR', calculate the estimated monitoring memory size PMR = α*Mi + PMR'. Among them, α is the memory allocation ratio value corresponding to the monitoring index, which can be set by the technical staff and will not be repeated here. The preset basic monitoring memory can be set according to the average value of the memory actually used by the monitoring unit in the past preset time period.

[0079] After calculating the estimated monitoring memory size of each monitoring unit, the main processor allocates the memory of each monitoring unit to optimize the memory utilization of each monitoring unit, so that the working memory required by each monitoring unit is more reasonable. Specifically, for a monitoring unit whose actual memory is smaller than the corresponding estimated monitoring memory, other monitoring units whose actual memory is larger than the corresponding estimated monitoring memory can be used to perform data analysis.

[0080] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0081] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. An intelligent American transformer, comprising a transformer body, a plurality of data acquisition devices mounted on the transformer body, and an intelligent component connected to the data acquisition device, wherein the intelligent component comprises a plurality of monitoring units, wherein the plurality of data acquisition units correspond one to one with the plurality of monitoring units, and the data acquisition device is used to collect relevant data of the transformer body and feed it back to the corresponding monitoring unit, characterized in that: The monitoring unit is used to obtain corresponding historical operation data and historical environment data, obtain predicted operation data according to the historical operation data, historical environment data and related data, calculate a monitoring index according to the predicted operation data and related data, and calculate an estimated monitoring memory size according to the monitoring index; The intelligent American transformer selects one of the microprocessors of the multiple monitoring units as the main processor; The main processor is configured to allocate the memory of each monitoring unit according to the estimated monitoring memory size corresponding to each monitoring unit to optimize the memory utilization of each monitoring unit; The relevant data include real-time operation data and real-time environment data.

2. The intelligent American transformer according to claim 1, characterized in that: The monitoring unit first calculates an operation fault occurrence index based on real-time operation data, predicted operation data and real-time environmental data, then calculates a monitoring index based on the operation fault index, and finally calculates an estimated monitoring memory size based on the monitoring index and a preset basic monitoring memory.

3. The intelligent American transformer according to claim 2, characterized in that: The intelligent component is also used to compare and analyze the real-time operating data with the corresponding preset data, and remotely transmit the comparison and analysis results to the dispatching center through the communication module, implement fault alarm, and point out the cause and fault point of the fault, so that the dispatching center can monitor and maintain the operating status of the transformer body and the switch of the load terminal to ensure the stable operation of the power grid.

4. The intelligent American transformer according to claim 3, characterized in that: The multiple monitoring units include an oil chromatography and micro-water monitoring unit, a partial discharge monitoring unit, a core grounding current monitoring unit, an acoustic fingerprint monitoring unit, a transformer bushing insulation monitoring unit and an on-load tap changer monitoring unit.

5. The intelligent American transformer according to claim 4, characterized in that: The oil chromatography and micro-water monitoring unit, the partial discharge monitoring unit, the core grounding current monitoring unit, the acoustic fingerprint monitoring unit, the transformer bushing insulation monitoring unit and the on-load tap changer monitoring unit all include a microprocessor and a memory.

6. The intelligent American transformer according to claim 5, characterized in that: The intelligent components also include a universal circuit breaker, an intelligent capacitor, an intelligent molded case circuit breaker and an intelligent watt-hour meter located on the low-voltage side.

7. The intelligent American transformer according to claim 6, characterized in that: The universal circuit breaker, intelligent capacitor, intelligent molded case circuit breaker and intelligent watt-hour meter are all connected to the RS485 bus.

8. The intelligent American transformer according to claim 7, characterized in that: The dispatch center includes a communication terminal and a background monitor. The intelligent component is connected to the communication terminal and the background monitor via a GPRS / GSM wireless communication link. The background monitor is also connected to an RS485 bus.

9. A combined substation, characterized in that: It comprises the intelligent American transformer as described in any one of claims 1-8.

10. A combined substation according to claim 9, characterized in that: The combined substation also includes a capacitor room, a high voltage room and a low voltage room.

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