CN-122022051-A - Intelligent environment control method and system for box-type substation

CN122022051ACN 122022051 ACN122022051 ACN 122022051ACN-122022051-A

Abstract

The application relates to an intelligent environment control method and system for a box-type substation. The method comprises the steps of obtaining box-type transformer substation internal environment data, box-type transformer substation external environment data and equipment state data of a box-type transformer substation in a current analysis period, quantifying condensation risks of the box-type transformer substation based on the box-type transformer substation internal environment data to obtain a current condensation difference value sequence, obtaining a condensation difference value prediction sequence based on the current condensation difference value sequence and a preset historical condensation difference value sequence set, obtaining comprehensive environment risk evaluation data of the box-type transformer substation based on the current condensation difference value sequence, the box-type transformer substation external environment data, the condensation difference value prediction sequence and a preset risk classification rule, and generating a control action instruction based on the comprehensive environment risk evaluation data, the equipment state data, the box-type transformer substation internal environment data, the box-type transformer substation external environment data, the preset physical safety interlocking rule and the preset energy efficiency optimization strategy model. By adopting the method, the accuracy of the internal environment control of the transformer substation can be improved.

Inventors

CAO HONGLIANG
DING ZHAO
ZHANG QIANG
WANG HU
CUI LONG

Assignees

河南焜创科技有限公司

Dates

Publication Date: 20260512
Application Date: 20260204

Claims (9)

1. An intelligent environmental control method for a box-type substation, which is characterized by comprising the following steps: Acquiring internal environment data, external environment data and equipment state data of the box-type substation in the current analysis period; Based on the internal environment data of the box transformer substation, quantifying the condensation risk of the box transformer substation to obtain a current condensation difference sequence; Predicting the change of the current condensation difference sequence based on the current condensation difference sequence and a preset historical condensation difference sequence set to obtain a condensation difference prediction sequence; Based on the current condensation difference value sequence, the external environment data of the box transformer substation, the condensation difference value prediction sequence and a preset risk classification rule, quantifying the risk condition existing in the box-type substation, and obtaining comprehensive environment risk evaluation data of the box-type substation; and generating a control action instruction of the box-type substation based on the comprehensive environment risk evaluation data, the equipment state data, the internal environment data of the box-type substation, the external environment data of the box-type substation, a preset physical safety interlocking rule and a preset energy efficiency optimization strategy model, wherein the control action instruction is used for indicating and adjusting the environment state in the box-type substation.
2. The method of claim 1, wherein the box-section internal environment data comprises a set of internal air temperature, internal air relative humidity, and equipment surface temperature, and wherein the set of internal air temperature, internal air relative humidity, and equipment surface temperature are each time stamped with a sampling time stamp, and wherein quantifying the risk of condensation of the box-section substation based on the box-section internal environment data, resulting in a current sequence of condensation differences, comprises: Calculating a dew point temperature value of each sampling time stamp based on the internal air temperature and the internal air relative humidity; Identifying, for each of the sampling time stamps, a lowest temperature within the box-type substation based on the equipment surface temperature set, obtaining a coldest equipment surface temperature value of the sampling time stamp; for each sampling time stamp, calculating a current condensation difference value of the sampling time stamp based on the surface temperature value and the dew point temperature value of the coldest equipment, wherein the expression of the current condensation difference value is as follows: Wherein, the Is the time stamp of any one of the samples, Is a sampling time stamp Is used for the current condensation difference value of (a), Is a sampling time stamp Is used for the cooling equipment surface temperature value, Is a sampling time stamp Dew point temperature value of (2); And obtaining the current condensation difference value sequence based on the current condensation difference value of each sampling time stamp.
3. The method of claim 2, wherein said calculating a dew point temperature value for each of said sampling time stamps based on said internal air temperature and said internal air relative humidity comprises: For each sampling time stamp, calculating a saturated temperature related parameter of the sampling time stamp based on the internal air temperature, the internal air relative humidity, a preset water vapor saturated pressure change coefficient and a preset temperature offset constant, wherein the saturated temperature related parameter has the expression: Wherein, the Is the time stamp of any one of the samples, Is a sampling time stamp Is used for the saturation temperature related parameter of the fuel cell, Is a sampling time stamp Is used for controlling the relative humidity of the internal air of the air conditioner, Is a sampling time stamp Is used for controlling the temperature of the air in the air conditioner, Is the change coefficient of the saturation pressure of water vapor, Is a temperature offset constant; for each sampling time stamp, calculating the dew point temperature value of the sampling time stamp based on the saturated temperature related parameter, the water vapor saturated pressure change coefficient and the temperature offset constant, wherein the expression of the dew point temperature value is as follows: Wherein, the Is the time stamp of any one of the samples, Is a sampling time stamp Is set at the temperature of the dew point of the water, Is a sampling time stamp Is used for the saturation temperature related parameter of the fuel cell, Is the change coefficient of the saturation pressure of water vapor, Is a temperature offset constant.
4. The method according to claim 2, wherein predicting the change of the current condensation difference sequence based on the current condensation difference sequence and a preset historical condensation difference sequence set, to obtain a condensation difference prediction sequence, comprises: inputting the current condensation difference value sequence into a preset condensation risk prediction model to obtain the condensation difference value prediction sequence; The condensation risk prediction model is obtained through training by the following method: the historical condensation difference value sequence set comprises the current condensation difference value sequence and future change label data corresponding to the current condensation difference value sequence in a historical analysis period; taking the current condensation difference value sequence in the historical analysis period as an input characteristic, taking the corresponding future change label data as a prediction target, and dividing the historical condensation difference value sequence set into a model training set and a model verification set according to a preset proportion; Constructing an initial condensation risk prediction model, wherein the initial condensation risk prediction model is constructed based on a long-term and short-term memory network algorithm; Based on the model training set, inputting the input features into the initial condensation risk prediction model to obtain a prediction output corresponding to the input features, and updating the initial condensation risk prediction model towards a direction of minimizing the difference between the prediction output and the prediction target to obtain a preliminary condensation risk prediction model; And verifying the preliminary condensation risk prediction model by using the model verification set until the preliminary condensation risk prediction model meets the preset precision requirement, so as to obtain the condensation risk prediction model.
5. The method according to claim 4, wherein the quantifying risk conditions existing in the box-type substation based on the current condensation difference value sequence, the box-type substation external environment data, the condensation difference value prediction sequence and a preset risk classification rule to obtain comprehensive environment risk evaluation data of the box-type substation includes: extracting a minimum value from the condensation difference prediction sequence to obtain a future condensation difference minimum value; the method comprises the steps of acquiring a historical box-section external environment data set, calculating a level dynamic adjustment factor based on the box-section external environment data and the historical box-section external environment data set, wherein the historical box-section external environment data set comprises the box-section external environment data in a historical analysis period; adjusting a preset basic risk threshold by using the level dynamic adjustment factor to obtain a dynamic risk threshold; Extracting the current condensation difference value corresponding to the latest sampling time stamp from the current condensation difference value sequence to be used as the latest current condensation difference value, and comparing the latest current condensation difference value with the dynamic risk threshold value to obtain a first comparison result; comparing the minimum value of the future condensation difference value with the dynamic risk threshold value to obtain a second comparison result; Determining an environmental risk level of the box-type substation based on the first comparison result, the second comparison result and the risk classification rule; and obtaining the comprehensive environmental risk evaluation data based on the environmental risk grade, the minimum value of the future condensation difference value and the latest current condensation difference value.
6. The method of claim 5, wherein the generating the control action command of the box-type substation based on the comprehensive environmental risk assessment data, the equipment status data, the box-section internal environment data, the box-section external environment data, a preset physical safety interlock rule, and a preset energy efficiency optimization policy model comprises: Constructing a decision state vector based on the comprehensive environmental risk evaluation data, the equipment state data, the inside environment data of the box transformer substation and the outside environment data of the box transformer substation; inputting the decision state vector into the energy efficiency optimization strategy model to obtain an initial control action vector; And correcting the initial control action vector based on the physical safety interlocking rule to obtain the control action instruction.
7. An intelligent environmental control system for a box-type substation, the system comprising: The data acquisition module is used for acquiring the internal environment data, the external environment data and the equipment state data of the box-type transformer substation in the current analysis period; The condensation difference value calculation module is used for quantifying the condensation risk of the box-type transformer substation based on the internal environment data of the box-type transformer substation to obtain a current condensation difference value sequence; The condensation change prediction module is used for predicting the change of the current condensation difference value sequence based on the current condensation difference value sequence and a preset historical condensation difference value sequence set to obtain a condensation difference value prediction sequence; The comprehensive risk determining module is used for quantifying the risk condition of the box-type substation based on the current condensation difference value sequence, the external environment data of the box-type substation, the condensation difference value prediction sequence and a preset risk classification rule to obtain comprehensive environment risk evaluation data of the box-type substation; The adjusting instruction generating module is used for generating a control action instruction of the box-type substation based on the comprehensive environment risk evaluation data, the equipment state data, the internal environment data of the box-type substation, the external environment data of the box-type substation, a preset physical safety interlocking rule and a preset energy efficiency optimizing strategy model, wherein the control action instruction is used for indicating and adjusting the environment state in the box-type substation.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.

Description

Intelligent environment control method and system for box-type substation Technical Field The invention belongs to the field of intelligent power grid maintenance, and particularly relates to an intelligent environment control method and system for a box-type substation. Background With the development of smart grid maintenance technology, a box-type transformer substation is used as a key node of a power system, and safe and stable operation of internal electrical equipment is of great importance. In order to solve the problems of condensation, rust, local overheating and the like caused by humidity and temperature difference in the box transformer substation, an environment control technology based on a fixed threshold value is provided, and the technology realizes automatic control by installing a temperature and humidity sensor in the box transformer substation and setting a fixed action threshold value, so that a traditional box transformer substation environment control mode widely applied at present is formed. In conventional methods, the process typically relies on direct monitoring of the temperature and relative humidity of the air inside the tank. The control system presets one or more fixed humidity thresholds (e.g., relative humidity above 80%) and temperature thresholds. When the real-time data collected by the sensor exceeds a set humidity threshold, the system automatically triggers the heater or the dehumidifier to start for heating or dehumidifying, and when the temperature exceeds a set limit, the fan is started for ventilation and heat dissipation. The whole process is a simple trigger-response logic based on the comparison of the current time monitoring value and the static threshold value, and the judging conditions of the execution action and the equipment start-stop are always unchanged after installation and debugging. However, the conventional control method at present has the prominent problems of control lag and low energy efficiency. Because the method is completely judged by depending on the working condition at the current moment, the change trend of the condensation risk cannot be prejudged, and the intervention can be started only when the condensation is about to occur or occurs, the method is essentially a 'post-remediation', the protection effect is passive and potential safety hazards exist. Meanwhile, the fixed threshold cannot adapt to complex and changeable external climate and internal heat load dynamic changes, unnecessary frequent start-stop or long-time operation of high-power-consumption equipment is easy to cause insufficient accuracy and timeliness of internal environment control of the transformer substation. Disclosure of Invention Based on the above, it is necessary to provide an intelligent environmental control method and system for a box-type substation, which can improve accuracy and timeliness of internal environmental control of the substation. In a first aspect, the present application provides an intelligent environmental control method for a box-type substation, including: acquiring box-type transformer substation internal environment data, box-type transformer substation external environment data and equipment state data of a box-type transformer substation in a current analysis period; Based on the internal environment data of the box transformer substation, quantifying the condensation risk of the box transformer substation, and obtaining a current condensation difference value sequence; Based on the current condensation difference sequence and a preset historical condensation difference sequence set, predicting the change of the current condensation difference sequence to obtain a condensation difference prediction sequence; Based on the current condensation difference value sequence, the external environment data of the box transformer substation, the condensation difference value prediction sequence and a preset risk classification rule, quantifying the risk condition of the box-type substation to obtain comprehensive environment risk evaluation data of the box-type substation; Based on comprehensive environment risk evaluation data, equipment state data, internal environment data of the box transformer substation, external environment data of the box transformer substation, preset physical safety interlocking rules and a preset energy efficiency optimization strategy model, generating a control action instruction of the box transformer substation, wherein the control action instruction is used for indicating and adjusting the environment state in the box transformer substation. Further, case becomes internal environment data and includes inside air temperature, inside air relative humidity and equipment surface temperature collection, and inside air temperature, inside air relative humidity and equipment surface temperature collection all have sampling timestamp, based on case becomes internal environment data, the condensation risk of quanti