New energy box transformer substation environment intelligent monitoring system

Abstract

The invention relates to the technical field of environment monitoring, and discloses a new energy box transformer substation environment intelligent monitoring system which comprises a main control board, a power board, a function board and a display board. The main control board is composed of a main chip, an acquisition circuit and a plurality of sensors, the sensors are used for carrying out data acquisition on environment temperature, environment humidity, smoke, condensation temperature, oil temperature and winding temperature, and when any one of the acquired data exceeds a set threshold value, an alarm instruction corresponding to the threshold value exceeding item needs to be sent to the function board. The new energy box transformer substation temperature and humidity monitoring system monitors the temperature and humidity of a new energy box transformer substation, and also monitors the oil surface temperature, the winding temperature, the condensation temperature and the smoke concentration, and once monitored values reach threshold values set by the host, the host starts corresponding functions or sends an alarm signal to an operator on duty, so that the operator on duty can monitor the temperature and humidity of the new energy box transformer substation. And the items exceeding the threshold value are processed at the first time, so that electrical accidents are avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring, and in particular to an intelligent monitoring system for an environmental protection system of a new energy box transformer. Background Art

[0002] At present, my country's new energy projects are developing rapidly, and wind power generation and photovoltaic power generation can be seen everywhere in life. Traditional new energy box transformers (box-type substations) lack all-round monitoring and protection, and are prone to failures due to unattended operation, thus causing electrical accidents.

[0003] The working environment of new energy box transformers is quite special. Most of them are located in unmanned barren mountains and plains, and in harsh environments with large temperature changes during the day. In addition, existing new energy box transformers are equipped with temperature sensors and humidity sensors. The sensors collect temperature and humidity values ​​and send them to the host. The host can set thresholds and start corresponding functions when the temperature or humidity reaches the threshold. This mode can only start the corresponding functions based on the ambient temperature and ambient humidity, and cannot provide all-round monitoring and protection for new energy box transformers.

[0004] The existing patent discloses the equipment foundation of a power box-type substation with artificial intelligence (publication number CN115882600A), including a concrete-cast foundation body and an operation inspection system, wherein the operation inspection system includes a foundation body space monitoring point layout module, an inspection equipment setting module, a cable laying body attribute acquisition module, a foundation body cable operation status image acquisition module, a foundation body operation environment monitoring module, a safety database, a cable operation risk assessment module and an early warning display terminal. In the technology disclosed in this patent, the environmental monitoring module cannot monitor and protect the box-type substation in an all-round way according to specific safety indicators, which is easy to cause electrical accidents due to failures caused by unattended operation. In addition, in the technology disclosed in this patent, it is impossible to analyze and judge the status of the environmental monitoring module itself, which is easy to cause erroneous execution instructions due to failures of the environmental monitoring module itself. Summary of the invention

[0005] The main technical problem solved by the present invention is to provide a new energy box-type transformer environment intelligent monitoring system, which solves the problems in the above-mentioned background technology.

[0006] To solve the above technical problems, according to one aspect of the present invention, more specifically, a new energy box-type transformer environment intelligent monitoring system includes a main control board, a power board, a function board and a display board; The main control board is composed of a main chip, a collection circuit and a plurality of sensors. The sensors are used to collect data on ambient temperature, ambient humidity, smoke, condensation temperature, oil temperature and winding temperature. When any of the collected data exceeds a set threshold, an alarm instruction corresponding to the threshold value item is sent to the function board; The power board is used to convert the AC220V voltage connected to the device into 12V, 5V, and 3.3V voltages, and input different voltages to the function board, main control board, and display board respectively according to the circuit trend; The function board is composed of relay switches and circuits with different functions to form different function modules, and starts or stops the corresponding functions according to the alarm command sent by the main control board; The display panel is composed of a liquid crystal display screen, buttons and LED lights. The liquid crystal display screen displays the collected values ​​on the screen, and the alarm threshold parameters can be set by pressing buttons.

[0007] Furthermore, the main control board includes: an ambient temperature sensor, an ambient humidity sensor, a smoke sensor, a condensation temperature sensor, an oil temperature sensor and a winding temperature sensor.

[0008] Furthermore, the functional board includes: a temperature functional module, a humidity functional module, a smoke functional module, a condensation functional module, an oil temperature functional module and a winding functional module.

[0009] Furthermore, the main chip in the main control board is connected to the data analysis end signal through a switch; the data analysis end is used to collect sensor parameters in the main control board and environmental parameters of the meteorological center through the switch to determine whether it is necessary to send an alarm of sensor damage to the engineer end.

[0010] Furthermore, the data analysis end determines the index coefficient of the external sensor failure based on the average difference between the temperature parameter of the ambient temperature sensor and the temperature of the big data meteorological center, the average difference between the humidity parameter of the ambient humidity sensor and the humidity parameter of the big data meteorological center, and the average difference between the smoke concentration parameter of the smoke sensor and the haze concentration parameter of the big data meteorological center, which are: In the formula, The index coefficient indicating that the external sensor is faulty, Represents the average temperature difference between the temperature parameter of the ambient temperature sensor and the temperature of the big data meteorological center. It represents the average difference between the humidity parameter of the ambient humidity sensor and the humidity parameter of the big data meteorological center. It represents the average difference between the smoke concentration parameter of the smoke sensor and the haze concentration parameter of the big data meteorological center.

[0011] Furthermore, when When , it means that one or more of the ambient temperature sensor, ambient humidity sensor or smoke sensor has a risk of failure; when , it means that one or more of the ambient temperature sensor, ambient humidity sensor or smoke sensor has no fault risk.

[0012] Furthermore, the data analysis end determines the index coefficient of the internal sensor failure based on the average temperature difference between the oil temperature sensor and the winding temperature sensor, the average temperature difference between the condensation temperature sensor and the big data meteorological center, and the heat accumulation ratio of the transformer equipment in the box-type substation under the standard environment, which are: In the formula, The index coefficient indicating that the internal sensor is faulty, Indicates the average temperature difference between the oil temperature sensor and the winding temperature sensor, It represents the average temperature difference between the condensation temperature sensor and the big data meteorological center. Indicates the temperature parameter of the oil temperature sensor, Represents the temperature parameter of the big data meteorological center, Indicates the temperature change of the transformer equipment in the box-type substation; and: In the formula, Indicates the actual working power of the transformer equipment in the box-type substation. Indicates the continuous working time. Indicates the efficiency of transferring winding heat to the sealing oil. Indicates the total mass of sealing oil, Indicates the specific heat capacity of sealing oil.

[0013] Furthermore, when When , it means that one or more of the condensation temperature sensor, oil temperature sensor or winding temperature sensor has a risk of failure; when , it means that one or more of the condensation temperature sensor, oil temperature sensor or winding temperature sensor is at risk of failure. Beneficial Effects

[0014] 1. In addition to monitoring the temperature and humidity of the new energy box transformer, the present invention also monitors the oil surface temperature, winding temperature, condensation temperature and smoke concentration. Once the monitored value reaches the threshold set by the host, the host starts the corresponding function or sends an alarm signal to the on-duty personnel, and handles the over-threshold items as soon as possible to avoid electrical accidents.

[0015] 2. The present invention can simply and efficiently determine whether an external sensor is faulty through the average temperature difference between the ambient temperature sensor and the big data meteorological center, the average humidity parameter difference between the ambient humidity sensor and the big data meteorological center, and the average smoke concentration parameter difference between the smoke sensor and the haze concentration parameter of the big data meteorological center, so that engineers can be dispatched to repair the external sensor.

[0016] 3. The present invention determines whether the internal sensor is faulty through the average temperature difference between the oil temperature sensor and the winding temperature sensor, the average temperature difference between the condensation temperature sensor and the big data meteorological center, and the heat accumulation ratio of the transformer equipment in the box-type substation under a standard environment, so that engineers can be dispatched for repair. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a flow chart for monitoring a box-type substation in the present invention; Figure 2 A flow chart of monitoring the sensor in the present invention; Figure 3 is the control variable in the present invention Schematic diagram of the model of w, s and u. DETAILED DESCRIPTION

[0018] In order to make the technical solution of the present invention clearer, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments. Example

[0019] like Figure 1 - As shown in Figure 2, according to one aspect of the present invention, there is provided a new energy box transformer environment intelligent monitoring system, including a main control board, a power board, a function board and a display board; the main control board is composed of a main chip, an acquisition circuit and a plurality of sensors, the sensors are used to collect data on ambient temperature, ambient humidity, smoke, condensation temperature, oil temperature and winding temperature, and when any of the collected data exceeds the set threshold, an alarm instruction corresponding to the threshold value item shall be sent to the function board; the power board is used to convert the AC220V voltage connected to the device into 12V, 5V, and 3.3V voltages, and input different voltages to the function board, the main control board and the display board according to the circuit trend; the function board is composed of different functional modules composed of relay switches and circuits with different functions, and starts or stops the corresponding functions according to the alarm command sent from the main control board; the display board is composed of a liquid crystal display, buttons and LED lights, the LCD screen displays the collected values ​​on the screen, and the alarm threshold parameters can be set by buttons. The oil level temperature, winding temperature, condensation temperature and smoke concentration are monitored. Once the monitored value reaches the threshold set by the host, the host will start the corresponding function or send an alarm signal to the on-duty personnel, and deal with the exceeding threshold items as soon as possible to avoid electrical accidents.

[0020] In this embodiment, the main control board includes: an ambient temperature sensor, an ambient humidity sensor, a smoke sensor, a condensation temperature sensor, an oil temperature sensor, and a winding temperature sensor. The ambient temperature sensor, the ambient humidity sensor, and the smoke sensor are used to detect the external ambient temperature and humidity of the box-type substation and the smoke concentration inside the box-type substation. The condensation temperature sensor, the oil temperature sensor, and the winding temperature sensor are used to detect the condensation temperature of the equipment surface of the box-type substation, the temperature of the sealing oil, and the temperature of the winding equipment.

[0021] In this embodiment, the function board includes: a temperature function module, a humidity function module, a smoke function module, a condensation function module, an oil temperature function module and a winding function module; the temperature function module receives an instruction that the ambient temperature parameter is lower than or higher than a threshold value, and increases or decreases the air conditioning temperature of the box-type substation according to the instruction; the humidity function module receives an instruction that the ambient humidity parameter is higher than the threshold value, and increases or decreases the air conditioning dehumidification power of the box-type substation according to the instruction; the smoke function module receives an instruction that the smoke concentration parameter is higher than the threshold value, and disconnects the main power supply of the box-type substation according to the instruction; the condensation function module receives an instruction that the condensation temperature parameter of the box-type substation body is lower than the threshold value, and increases the air conditioning dehumidification power and heating power of the box-type substation according to the instruction; the oil temperature function module receives an instruction that the sealing oil temperature parameter is higher than the threshold value, and reduces the air conditioning temperature of the box-type substation and the working power of the box-type substation according to the instruction; the winding function module receives an instruction that the winding coil temperature parameter is higher than the threshold value, and reduces the air conditioning temperature of the box-type substation and the working power of the box-type substation according to the instruction. Example

[0022] like Figure 3 As shown, the main chip in the main control board is connected to the data analysis end signal through the switch; the data analysis end is used to collect the sensor parameters in the main control board and the environmental parameters of the meteorological center through the switch to determine whether it is necessary to send an alarm of sensor damage to the engineer end.

[0023] The data analysis end determines the index coefficient of external sensor failure based on the average difference between the temperature parameters of the ambient temperature sensor and the temperature of the big data meteorological center, the average difference between the humidity parameters of the ambient humidity sensor and the humidity parameters of the big data meteorological center, and the average difference between the smoke concentration parameters of the smoke sensor and the haze concentration parameters of the big data meteorological center. The following are the index coefficients: In the formula, The index coefficient indicating that the external sensor is faulty, Represents the average temperature difference between the temperature parameter of the ambient temperature sensor and the temperature of the big data meteorological center. It represents the average difference between the humidity parameter of the ambient humidity sensor and the humidity parameter of the big data meteorological center. It represents the average difference between the smoke concentration parameter of the smoke sensor and the haze concentration parameter of the big data meteorological center.

[0024] when When , it means that one or more of the ambient temperature sensor, ambient humidity sensor or smoke sensor is at risk of failure, and an engineer needs to be dispatched for repair; when , it means that one or more of the ambient temperature sensor, ambient humidity sensor or smoke sensor has no fault risk.

[0025] Among them, data monitoring is performed on data sample X. The average difference between the temperature parameter of the ambient temperature sensor and the temperature of the big data meteorological center is taken (Unit: °C, average temperature difference = | average temperature monitored by the ambient temperature sensor within 3 hours - average temperature monitored by the big data meteorological center within 3 hours |, when the average temperature difference is 0, take ).

[0026] The average difference between the humidity parameters of the environmental humidity sensor and the humidity parameters of the big data meteorological center is taken (Average difference in humidity parameters = |average humidity monitored by the ambient humidity sensor within 3 hours - average humidity monitored by the big data meteorological center within 3 hours|).

[0027] The average difference between the smoke concentration parameter of the smoke sensor and the haze concentration parameter of the big data meteorological center is taken as (Unit: μg / m³, average difference of haze concentration parameters = | average haze concentration monitored by the smoke sensor within 3 hours - average haze concentration monitored by the big data meteorological center within 3 hours |, when the average difference of concentration is 0, take ). Then we have:

[0028] From the above calculation, we can know that the index coefficient of the external sensor failure after data monitoring of data sample X is , at this time, one or more of the ambient temperature sensor, ambient humidity sensor or smoke sensor has a risk of failure. And comparing multiple sets of implementation data, there are: Table 1 Monitoring parameters and status of external sensors for some implementation data

[0029] It can be seen from the data in Table 1 above that when the sample data tends to infinity, the index coefficient will have an obvious dividing line depending on whether the external sensor is faulty, and this dividing line is 80%.

[0030] Then when When , it means that one or more of the ambient temperature sensor, ambient humidity sensor or smoke sensor has a risk of failure; when , it means that one or more of the ambient temperature sensor, ambient humidity sensor or smoke sensor has no fault risk. Example

[0031] The data analysis end determines the index coefficient of internal sensor failure based on the average temperature difference between the oil temperature sensor and the winding temperature sensor, the average temperature difference between the condensation temperature sensor and the big data meteorological center, and the heat accumulation ratio of the transformer equipment in the box-type substation under standard conditions. The index coefficients are: In the formula, The index coefficient indicating that the internal sensor is faulty, Indicates the average temperature difference between the oil temperature sensor and the winding temperature sensor, It represents the average temperature difference between the condensation temperature sensor and the big data meteorological center. Indicates the temperature parameter of the oil temperature sensor, Represents the temperature parameter of the big data meteorological center, Indicates the temperature change of the transformer equipment in the box-type substation; and: In the formula, Indicates the actual working power of the transformer equipment in the box-type substation. Indicates the continuous working time. Indicates the efficiency of transferring winding heat to the sealing oil. Indicates the total mass of sealing oil, Indicates the specific heat capacity of sealing oil.

[0032] when When , it means that one or more of the condensation temperature sensor, oil temperature sensor or winding temperature sensor has a risk of failure, and an engineer needs to be dispatched for repair; when , it means that one or more of the condensation temperature sensor, oil temperature sensor or winding temperature sensor is at risk of failure.

[0033] Among them, data sample Y is monitored. The average temperature difference between the oil temperature sensor and the winding temperature sensor is (Unit: °C, average temperature difference = |average temperature monitored by the oil temperature sensor within 40 minutes - average temperature monitored by the winding temperature sensor within 40 minutes|).

[0034] The average temperature difference between the condensation temperature sensor and the big data meteorological center is taken (Unit: °C, average temperature difference = |average temperature monitored by the condensation temperature sensor within 1 hour - average temperature monitored by the big data meteorological center within 1 hour|).

[0035] The temperature parameter of the oil temperature sensor is (℃), the temperature parameter of the Big Data Meteorological Center is (℃), the temperature change of the transformer equipment in the box-type substation is (Unit: °C, when the temperature change is 0, take ), then we have: From the above calculation, we can know that after monitoring the data sample Y, the index coefficient of the internal sensor failure is , then it means that one or more of the condensation temperature sensor, oil temperature sensor or winding temperature sensor has a risk of failure. And comparing multiple sets of data, there are: Table 2 Monitoring parameters and status of internal sensors of some implementation data

[0036] It can be seen from the data in Table 2 above that when the sample data tends to infinity, the index coefficient will have an obvious dividing line depending on whether the internal sensor has a fault, and this dividing line is 65%.

[0037] Then when When , it means that one or more of the condensation temperature sensor, oil temperature sensor or winding temperature sensor has a risk of failure; when , it means that one or more of the condensation temperature sensor, oil temperature sensor or winding temperature sensor is at risk of failure.

[0038] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. 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, which 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. A new energy box-type transformer environment intelligent monitoring system, characterized in that: It includes a main control board, a power board, a function board and a display board; the main control board is composed of a main chip, an acquisition circuit and multiple sensors. The sensors are used to collect data on ambient temperature, ambient humidity, smoke, condensation temperature, oil temperature and winding temperature. When any of the collected data exceeds the set threshold, an alarm instruction corresponding to the threshold value item needs to be sent to the function board; the power board is used to convert the AC220V voltage connected to the device into 12V, 5V, and 3.3V voltages, and input different voltages into the function board, the main control board and the display board according to the circuit trend; the function board is composed of different functional modules composed of relay switches and circuits with different functions, and the corresponding functions are started or stopped according to the alarm command sent by the main control board; the display board is composed of a liquid crystal display, buttons and LED lights. The LCD screen displays the collected values ​​on the screen, and the alarm threshold parameters can be set by pressing buttons.

2. The intelligent monitoring system for the new energy transformer environment according to claim 1 is characterized by: The main control board includes: an ambient temperature sensor, an ambient humidity sensor, a smoke sensor, a condensation temperature sensor, an oil temperature sensor and a winding temperature sensor.

3. The intelligent monitoring system for the new energy transformer environment according to claim 1 is characterized by: The functional board includes: a temperature functional module, a humidity functional module, a smoke functional module, a condensation functional module, an oil temperature functional module and a winding functional module.

4. The intelligent monitoring system for the new energy transformer environment according to claim 1 is characterized by: The main chip in the main control board is connected to the data analysis end signal through a switch; the data analysis end is used to collect sensor parameters in the main control board and environmental parameters of the meteorological center through the switch to determine whether it is necessary to send an alarm of sensor damage to the engineer end.

5. The intelligent monitoring system for the new energy transformer environment according to claim 4 is characterized in that: The data analysis end determines the index coefficient of the external sensor failure based on the average difference between the temperature parameter of the ambient temperature sensor and the temperature of the big data meteorological center, the average difference between the humidity parameter of the ambient humidity sensor and the humidity parameter of the big data meteorological center, and the average difference between the smoke concentration parameter of the smoke sensor and the haze concentration parameter of the big data meteorological center, which are: In the formula, The index coefficient indicating that the external sensor is faulty, Represents the average temperature difference between the temperature parameter of the ambient temperature sensor and the temperature of the big data meteorological center. It represents the average difference between the humidity parameter of the ambient humidity sensor and the humidity parameter of the big data meteorological center. It represents the average difference between the smoke concentration parameter of the smoke sensor and the haze concentration parameter of the big data meteorological center.

6. The intelligent monitoring system for the new energy transformer environment according to claim 5 is characterized by: when When , it means that one or more of the ambient temperature sensor, ambient humidity sensor or smoke sensor has a risk of failure; when , it means that one or more of the ambient temperature sensor, ambient humidity sensor or smoke sensor has no fault risk.

7. The intelligent monitoring system for the new energy transformer environment according to claim 4 is characterized by: The data analysis end determines the index coefficient of the internal sensor failure based on the average temperature difference between the oil temperature sensor and the winding temperature sensor, the average temperature difference between the condensation temperature sensor and the big data meteorological center, and the heat accumulation ratio of the transformer equipment in the box-type substation under the standard environment, which are: In the formula, The index coefficient indicating that the internal sensor is faulty, Indicates the average temperature difference between the oil temperature sensor and the winding temperature sensor, It represents the average temperature difference between the condensation temperature sensor and the big data meteorological center. Indicates the temperature parameter of the oil temperature sensor, Represents the temperature parameter of the big data meteorological center, Indicates the temperature change of the transformer equipment in the box-type substation; and: In the formula, Indicates the actual working power of the transformer equipment in the box-type substation. Indicates the continuous working time. Indicates the efficiency of transferring winding heat to the sealing oil. Indicates the total mass of sealing oil, Indicates the specific heat capacity of sealing oil.

8. The intelligent monitoring system for the new energy transformer environment according to claim 7 is characterized by: when When , it means that one or more of the condensation temperature sensor, oil temperature sensor or winding temperature sensor has a risk of failure; when , it means that one or more of the condensation temperature sensor, oil temperature sensor or winding temperature sensor is at risk of failure.

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