Scheduling method and device of drainage equipment, storage medium and program product

Abstract

The invention discloses a drainage equipment scheduling method and device, a storage medium and a program product. The method comprises the steps of obtaining environment data of an area where a transformer substation is located; performing fusion processing on the environment data to obtain a fusion feature vector which is used for representing the environment change condition of the region; on the basis of the fusion feature vector, water level information corresponding to the area at at least one future moment is obtained through prediction, and the water level information is used for representing the water volume of accumulated water in the area; on the basis of the water level information, scheduling information of at least one drainage device in the area is determined, and the scheduling information is used for representing that the drainage device is in an open state or a closed state; and scheduling the at least one drainage device according to the scheduling information so as to discharge the accumulated water from the area by using the scheduled drainage device. The technical problem that the anti-waterlogging efficiency of the transformer substation is poor is solved.

Description

Technical Field

[0001] The present invention relates to the field of electric power systems, and in particular to a method, a device, a storage medium and a program product for dispatching drainage equipment. Background Art

[0002] At present, with the global climate change, extreme weather events, such as rainstorms, typhoons, and floods, are becoming more frequent, posing severe challenges to power facilities. As the core hub of the power system, the safe operation of substations is directly related to the stability of urban power supply and the normal progress of social and economic activities. However, under extreme meteorological conditions, substations face serious threats of waterlogging. Waterlogging may cause equipment short circuits, power outages, or even equipment damage, seriously affecting the stability and reliability of the power supply system.

[0003] In the related art, drainage equipment usually responds passively, that is, the opening and closing of the drainage equipment is controlled by preset rules, which leads to the technical problem of poor flood prevention efficiency of substations.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present invention provide a method, device, storage medium and program product for scheduling drainage equipment to at least solve the technical problem of poor flood prevention efficiency of substations.

[0006] According to one aspect of an embodiment of the present invention, a method for scheduling drainage equipment is provided, and the method may include: acquiring environmental data of an area where a substation is located; fusing the environmental data to obtain a fused feature vector, wherein the fused feature vector is used to characterize environmental changes in the area; based on the fused feature vector, predicting water level information corresponding to the area at at least one future moment, wherein the water level information is used to characterize the amount of accumulated water in the area; based on the water level information, determining scheduling information of at least one drainage equipment in the area, wherein the scheduling information is used to characterize whether the drainage equipment is in an open state or a closed state; and scheduling at least one drainage equipment according to the scheduling information, so as to use the scheduled drainage equipment to drain the accumulated water from the area.

[0007] Optionally, the environmental data is fused to obtain a fused feature vector, including: calling an edge computing device to convert the environmental data to obtain a real-time data stream; using a time attenuation factor to perform data fusion on the real-time data stream to obtain a fused feature vector.

[0008] Optionally, based on the fused feature vector, water level information corresponding to the area at at least one future moment is predicted, including: inputting the fused feature vector into a water level prediction model to predict the water level information, wherein the water level prediction model is trained based on a loss function containing a nonlinear regularization term.

[0009] Optionally, based on the water level information, determining the scheduling information of at least one drainage device in the area includes: determining the load status of the drainage device and the operating status of the drainage device; and determining the scheduling information based on the load status, operating status and water level information.

[0010] Optionally, based on the load status, operating status and water level information, the scheduling information is determined, including: based on the load status, constructing a load balancing target, wherein the load balancing target is used to determine the load to be allocated for at least one drainage device; based on the operating status, constructing an energy consumption balancing target, wherein the energy consumption balancing target is used to determine the energy consumption allowed to be consumed by at least one drainage device; based on the water level information, constructing a constraint condition, wherein the constraint condition is used to represent the critical value of the water level of accumulated water in the area; integrating the load balancing target, the energy consumption balancing target and the constraint condition to obtain an integrated result; and determining the scheduling information based on the integrated result.

[0011] Optionally, after scheduling at least one drainage device according to the scheduling information to drain the accumulated water from the area using the scheduled drainage device, the method further includes: obtaining feedback information, wherein the feedback information is used to represent the feedback result of the drainage of the accumulated water; in response to the feedback information being used to characterize that the amount of accumulated water in the area meets a water amount threshold, increasing the number of scheduled drainage devices.

[0012] Optionally, the method may also include: in response to water level information exceeding a water volume threshold, or the presence of abnormally operating electrical equipment in the area, determining an emergency response strategy based on the water level information, wherein the emergency response strategy is used to represent rules for preventing electrical equipment from being damaged by water; and determining operating data of electrical equipment that is operating normally in the area according to the emergency response strategy.

[0013] According to another aspect of an embodiment of the present invention, a scheduling device for drainage equipment is also provided, and the device may include: an acquisition unit, used to acquire environmental data of the area where the substation is located; a processing unit, used to fuse the environmental data to obtain a fused feature vector, wherein the fused feature vector is used to characterize the environmental changes in the area; a prediction unit, used to predict the water level information corresponding to the area at at least one future moment based on the fused feature vector, wherein the water level information is used to characterize the amount of accumulated water in the area; a determination unit, used to determine the scheduling information of at least one drainage equipment in the area based on the water level information, wherein the scheduling information is used to characterize whether the drainage equipment is in an open state or a closed state; a scheduling unit, used to schedule at least one drainage equipment according to the scheduling information, so as to use the scheduled drainage equipment to drain the accumulated water from the area.

[0014] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is also provided, which includes a stored program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute the scheduling method for drainage equipment of an embodiment of the present invention.

[0015] According to another aspect of an embodiment of the present invention, a processor is further provided, the processor being used to run a program, wherein when the program is run by the processor, the scheduling method for drainage equipment of an embodiment of the present invention is executed.

[0016] According to another aspect of an embodiment of the present invention, a program product is further provided. The program product includes computer instructions, wherein the computer instructions, when executed by a processor, implement the scheduling method of the drainage equipment according to an embodiment of the present invention.

[0017] In an embodiment of the present invention, environmental data of the area where the substation is located is obtained; the environmental data is fused to obtain a fused feature vector, wherein the fused feature vector is used to characterize the environmental changes in the area; based on the fused feature vector, the water level information corresponding to the area at at least one future moment is predicted, wherein the water level information is used to characterize the amount of water accumulated in the area; based on the water level information, the scheduling information of at least one drainage device in the area is determined, wherein the scheduling information is used to characterize whether the drainage device is in an open state or a closed state; according to the scheduling information, at least one drainage device is scheduled to drain the accumulated water from the area using the scheduled drainage device. That is, in an embodiment of the present invention, environmental data (for example, real-time environmental data) of the area where the substation is located is obtained, the environmental data is fused to obtain a fused feature vector, the fused feature vector is predicted to obtain the water level information corresponding to the area at at least one future moment, based on the water level information, the scheduling information of the drainage device in the area is determined, and the drainage device is scheduled according to the scheduling information to achieve the purpose of draining the accumulated water in the area, thereby achieving the technical effect of improving the flood control efficiency of the substation and solving the technical problem of poor flood control efficiency of the substation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0019] Figure 1 is a flow chart of a method for scheduling drainage equipment according to an embodiment of the present invention;

[0020] Figure 2 is a schematic diagram of a scheduling device for drainage equipment according to an embodiment of the present invention;

[0021] Figure 3 is a structural block diagram of a computer terminal according to an embodiment of the present invention;

[0022] Figure 4 It is a block diagram of an electronic device of a method for scheduling drainage equipment according to an embodiment of the present application. DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0024] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0025] According to an embodiment of the present invention, an embodiment of a scheduling method for a drainage device is provided, and the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and, although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0026] In this embodiment, a method for scheduling drainage equipment is proposed. The method obtains environmental data of the area where the substation is located (for example, real-time environmental data), fuses the environmental data to obtain a fused feature vector, and predicts the fused feature vector to obtain water level information corresponding to the area at at least one future moment. Based on the water level information, scheduling information of the drainage equipment in the area is determined, and the drainage equipment is scheduled according to the scheduling information to achieve the purpose of draining the accumulated water in the area, thereby achieving the technical effect of improving the flood control efficiency of the substation and solving the technical problem of poor flood control efficiency of the substation.

[0027] Figure 1 is a flow chart of a method for scheduling drainage equipment according to an embodiment of the present invention. Figure 1 As shown, the method may include the following steps:

[0028] Step S102, obtaining environmental data of the area where the substation is located.

[0029] In the technical solution provided in step S102 of the present invention, the environmental data may be real-time environmental data, which may be used to determine the water level, rainfall intensity, rainfall rate, etc. of the area. It should be noted that this is only an example, and the type of environmental data is not specifically limited. The area may be an area where a substation is deployed.

[0030] In this embodiment, water level sensors can be deployed in low-lying areas, drainage outlets, and surrounding areas of the substation where water is likely to accumulate. The water level sensors can be used to monitor the height of water in the above areas in real time to provide continuous data on water level changes. The water level sensors can be ultrasonic water level sensors that can be used for non-contact water depth measurement. By using the sensors to monitor water level data in environmental data, failures caused by sensor submersion can be effectively avoided.

[0031] Optionally, the water level sensor can be installed at a certain height (eg, 10-20 cm) above the ground to ensure that the water level sensor will not be impacted by the water flow.

[0032] For example, the ultrasonic water level sensor is set to collect data and update it once every minute, with the measurement unit in millimeters (mm). By using the ultrasonic water level sensor, the water level height (W s (t)), for example, the sensor reads the current water height W s (10:00) is 45 mm.

[0033] In this embodiment, multiple rainfall sensors can be deployed around the substation. The rainfall sensors can be used to monitor the local rainfall intensity and rainfall rate in real time to obtain environmental data. For example, rainfall sensors can be installed on the roof, ground and near the drainage pipes in different areas of the substation to capture the rainfall differences in each area. The collection frequency of the rainfall sensor can be updated once per minute, and the collection unit can be millimeter per minute (mm / min), so that the current rainfall amount R can be obtained. s (t), for example, at 10:00, the rainfall sensor reads the rainfall intensity R s (10:00) is 5mm / min.

[0034] In this embodiment, a drainage load sensor can also be deployed. The drainage load sensor can be used to monitor the water flow and load of the drainage pipe. Based on the water flow and load, it can be determined that the pipe master is in a normal working state. For example, the installation position of the drainage load sensor can be the inlet, outlet and key nodes of the drainage pipe. The drainage load sensor can be used to monitor the drainage status at different locations.

[0035] Optionally, the collection frequency of the drainage load sensor can be updated every 20 seconds, and the unit of the obtained environmental data can be liters per minute (L / min), which can output the real-time load (Q s (t)).

[0036] Optionally, to avoid clogging and wear problems, the flow sensor can be electromagnetic or ultrasonic. For example, at 10:00, the flow sensor reads the current flow rate Q of the drainage device. s (10:00) is 140L / min.

[0037] In this embodiment, equipment status sensors can also be installed on key equipment in the above-mentioned area (for example, transformers, distribution cabinets and other equipment). Using the equipment status sensors, key parameters such as temperature, current, vibration and so on of the above-mentioned key equipment can be monitored in real time to ensure that the above-mentioned key equipment can operate safely under waterlogging conditions.

[0038] Optionally, the device status sensor may collect device temperature, current load, and device vibration frequency to determine whether the health status of the above key devices is within a normal range.

[0039] For example, the collection frequency of the device status sensor can be updated every 10 seconds, and the units of the collected environmental data are respectively Celsius (℃), ampere (A), and hertz (Hz). The above device status sensor can output the device status parameter vector E s (t), for example, the output data of the device status sensor can be at 10:00, and the device status parameter is E s (10:00) = [75°C, 120A, 5Hz].

[0040] It should be noted that the above-mentioned methods and devices for obtaining environmental data are only for illustration, and the sizes of the above-mentioned numbers are also only for illustration. The type of environmental data and the method for obtaining environmental data can be selected and changed according to actual conditions, and no specific restrictions are made here.

[0041] In this embodiment, various sensors may be used to collect environmental data. Considering that the sensors collecting environmental data may be disturbed in extreme weather conditions such as heavy rain and storms, a regular automatic calibration mechanism may be used to ensure the accuracy of the environmental data.

[0042] Optionally, the water level sensor can automatically perform a benchmark calibration. In the absence of rainfall and water accumulation, the system realigns the sensor measurement to zero water level and records the offset value to avoid drift caused by long-term use. If the water level sensor reading is not zero but there is no water accumulation, the water level sensor reading deviation can be compensated back to zero.

[0043] Optionally, the rain sensor can be self-calibrated using a rain gauge, which periodically checks for erroneous readings in the absence of rainfall. If abnormal readings occur, compensation can be made automatically.

[0044] In this embodiment, the state sensor of the key equipment can automatically reset the reference point every month to ensure the long-term accuracy of data such as temperature and current. There is no specific restriction on the calibration method here, and a suitable calibration method for the sensor can be selected according to the actual situation to complete the calibration of the sensor.

[0045] Step S104, performing fusion processing on the environmental data to obtain a fused feature vector, wherein the fused feature vector is used to characterize the environmental change of the region.

[0046] In the technical solution provided in the above step S104 of the present invention, the above fused feature vector can be used to characterize the environmental changes in the region, can be used to characterize and integrate real-time environmental data from different sensors, and can be used to capture and express the comprehensive state and trend of multimodal data in the regional environment. For example, the above fused feature vector can include the characteristics of environmental data such as water level, rainfall intensity, drainage system load and water accumulation monitored by machine vision. Therefore, it can characterize the current environmental state of the substation, including the degree of water accumulation, rainfall intensity, operating state of the drainage system, etc. It should be noted that this is only an example, and there is no specific limitation on the content contained in the fused feature vector.

[0047] Optionally, the process of fusing the environmental data to obtain a fused feature vector is to convert the raw data from different sensors into a comprehensive vector, which can more comprehensively and accurately reflect the current state and change trend of the environment in which the substation is located.

[0048] For example, real-time environmental data of the substation is collected. The environmental data may include water level, rainfall intensity, drainage system load and water accumulation monitored by machine vision. The real-time environmental data can be combined into a real-time data stream. Furthermore, a time attenuation factor can be introduced into the real-time data stream for data fusion to obtain a fused feature vector.

[0049] Optionally, the environmental data may be multi-source real-time data, and may include environmental data corresponding to multiple moments, such as temperature data, rainfall intensity data, etc. After obtaining the environmental data, the environmental data from multiple moments and multiple sources may be combined to obtain a unified vector (i.e., a fused feature vector) that can reflect the environmental status of the substation.

[0050] For example, environmental data can be collected from multiple sensors, including data such as water level, rainfall intensity, drainage system load, and water accumulation monitored by machine vision, and the above data can be formed into a real-time data stream. The environmental data over a period of time can be arranged in chronological order to form a time series data matrix in order to capture the trend of data changes over time. Furthermore, using the time attenuation factor and modal weight, the data in the time series data matrix can be weighted and summed to obtain a fused feature vector, which contains comprehensive information of multi-source environmental data after time weighting and modal weighting, and can provide input for subsequent water level prediction and decision-making. It should be noted that this is only an example, and there is no specific limitation on the method of obtaining the fused feature vector. As long as it is based on environmental data, the method of determining the fused feature vector should be within the scope of protection of this application.

[0051] Step S106, based on the fused feature vector, predicting the water level information corresponding to the region at at least one future moment, wherein the water level information is used to characterize the amount of water accumulated in the region.

[0052] In the technical solution provided in the above step S106 of the present invention, the above water level information can be used to characterize the amount of water accumulated in the area, and can include multiple water volumes corresponding to at least one future moment, and can be used to determine the amount of water accumulated in the area.

[0053] Optionally, after obtaining the fused feature vector, the fused feature vector may be processed by a neural network model or by using a pre-set algorithm to obtain water level information of the region at at least one future moment.

[0054] Optionally, in the flood prevention scenario of the substation, the data of various sensors have different effects on the future changes in water levels. Therefore, this embodiment designs an adaptive weighted fusion mechanism to dynamically adjust the weights of different modal data. This mechanism can fuse the data of recent water level, rainfall, drainage load and equipment status into a unified feature vector (that is, a fused feature vector), and input the feature vector into the water level prediction model to predict the water level information of the region at at least one future moment.

[0055] Step S108, based on the water level information, determining the scheduling information of at least one drainage device in the area, wherein the scheduling information is used to indicate whether the drainage device is in an open state or a closed state.

[0056] In the technical solution provided in step S108 of the present invention, the drainage equipment may be a drainage system in the area, which may be used to drain the accumulated water in the area to other areas, and may include drainage pipes and drainage pumps. The scheduling information may be used to determine the scheduling status of at least one drainage equipment. For example, the scheduling information may be to turn on drainage equipment 1 and drainage equipment 2, and turn off drainage equipment 3. It should be noted that this is only an example, and the type of drainage equipment and the content of the scheduling information are not specifically limited.

[0057] Optionally, the predicted water level information at least at a future time (i.e., the future water level result The water level in Western Sydney can be used to provide a basis for the dynamic scheduling of the drainage system to ensure that the drainage system can respond to water level changes in a timely manner and prevent waterlogging in the area.

[0058] Step S110, scheduling at least one drainage device according to the scheduling information, so as to drain the accumulated water from the area by using the scheduled drainage device.

[0059] In the technical solution provided in the above step S110 of the present invention, the working state of at least one drainage device can be controlled according to the scheduling information, for example, the open state or the closed state, so as to use the scheduled drainage device to drain the accumulated water from the area.

[0060] At present, with the global climate change, extreme weather events, such as rainstorms, typhoons, and floods, are becoming more frequent, posing severe challenges to infrastructure, especially power facilities. As the core hub of the power system, the safe operation of substations is directly related to the stability of urban power supply and the normal progress of social and economic activities. However, under extreme meteorological conditions, substations face serious threats of waterlogging. Waterlogging may cause equipment short circuits, power outages, and even equipment damage, seriously affecting the stability and reliability of the power supply system. In recent years, although a variety of technical means have been developed for substation waterlogging prevention, such as elevated substation design and optimization of drainage systems, there are still many problems that cannot be effectively solved.

[0061] In the relevant technologies, substation flood prevention technology mainly focuses on the construction and optimization of drainage systems, protection of substation equipment, and water level monitoring and early warning. However, these traditional methods have shown a series of shortcomings in dealing with waterlogging caused by extreme weather. For example, the existing drainage system usually responds passively, that is, the opening and closing of the drainage pump is controlled by preset rules, which lacks sufficient flexibility and adaptability. When the amount of heavy rain exceeds expectations or the drainage load in a local area is too large, the drainage system is prone to overload, resulting in the rapid spread of local waterlogging and the inability to be removed in time. In addition, the scheduling and management of the drainage system are relatively independent and lack cross-regional coordination, resulting in some drainage equipment being overloaded, while other equipment may be idle. This imbalance in resource allocation further exacerbates the problem of low drainage efficiency. In addition, although the existing water level monitoring and early warning system can monitor water level changes in real time through sensors, its early warning means are still single, and usually only alarms are issued after the water level reaches a certain threshold, which makes it difficult to provide effective foresight. Although the existing equipment protection measures, such as equipment overhead or physical isolation, can prevent the equipment from direct contact with water, most of these protection measures rely on static designs and cannot dynamically respond to rapid changes in water levels. In addition, in extreme weather, fixed elevated or isolated facilities alone cannot provide comprehensive equipment protection. When the water level exceeds the expected height, the equipment still faces the risk of being submerged.

[0062] In response to these problems, the current substation flood prevention technology lacks an intelligent and automated comprehensive solution. In particular, when dealing with complex meteorological changes and changing hydrological environments, the existing system has poor adaptability and cannot dynamically adjust drainage strategies or equipment protection measures according to real-time conditions. This not only reduces the system's emergency response efficiency, but also greatly increases the safety risks of substation operation. Therefore, how to build an intelligent and dynamically adjustable substation flood prevention system under extreme weather conditions has become a technical problem that needs to be solved urgently.

[0063] In this embodiment, in order to solve the above problems, a substation flood prevention decision-making and automatic control method for extreme meteorological environments is proposed. The method realizes dynamic scheduling and coordination of the drainage system through self-organizing network technology; at the same time, through the combination of water level prediction model and machine vision, it provides accurate early warning and protection strategies, forming a complete solution that can automatically and intelligently deal with flooding, significantly improving the protection capability of the substation under extreme weather conditions, thereby achieving the technical effect of improving the flood prevention efficiency of the substation, and solving the technical problem of poor flood prevention efficiency of the substation.

[0064] Through the above-mentioned steps S102 and S110 of the present invention, environmental data of the area where the substation is located is obtained; the environmental data is fused to obtain a fused feature vector, wherein the fused feature vector is used to characterize the environmental changes in the area; based on the fused feature vector, the water level information corresponding to the area at at least one future moment is predicted, wherein the water level information is used to characterize the amount of water accumulated in the area; based on the water level information, the scheduling information of at least one drainage device in the area is determined, wherein the scheduling information is used to characterize whether the drainage device is in an open state or a closed state; according to the scheduling information, at least one drainage device is scheduled to drain the accumulated water from the area using the scheduled drainage device. That is to say, in an embodiment of the present invention, environmental data of the area where the substation is located (for example, real-time environmental data) is obtained, and the environmental data is fused to obtain a fused feature vector. The fused feature vector is predicted to obtain the water level information corresponding to the area at at least one future moment. Based on the water level information, the scheduling information of the drainage equipment in the area is determined, and the drainage equipment is scheduled according to the scheduling information to achieve the purpose of draining the accumulated water in the area, thereby achieving the technical effect of improving the flood control efficiency of the substation and solving the technical problem of poor flood control efficiency of the substation.

[0065] The above method of this embodiment is further introduced below.

[0066] As an optional implementation, step S104, fusing the environmental data to obtain a fused feature vector, includes: calling the edge computing device to convert the environmental data to obtain a real-time data stream; using the time attenuation factor to perform data fusion on the real-time data stream to obtain a fused feature vector.

[0067] In this embodiment, the edge computing device can be called to convert the environmental data to obtain a real-time data stream, and the time decay factor can be used to fuse the real-time data stream to obtain a fused feature vector. The real-time data stream can be a data stream obtained by arranging the environmental data in chronological order, which can be a time series data matrix that can be used to capture the trend of environmental data changing over time. The time decay factor can be used to ensure the weight distribution of the real-time data stream in time, that is, the closer the data is to the current time, the greater the weight, and as time goes by, the weight of the data gradually decreases.

[0068] In this embodiment, the environmental data collected by all sensors can be sent to the edge computing device through a low-power wireless transmission network (for example, LoRa, Zigbee or 5G network), and the environmental data can be processed by the edge computing device, thereby ensuring low-latency transmission of the environmental data and the overall real-time performance of the system.

[0069] Optionally, the reason for choosing edge computing is that when extreme weather (such as heavy rain, strong winds, etc.) may cause communication network interruption, the environmental data can be locally calculated through edge computing devices to ensure continuous processing of critical data.

[0070] Optionally, the edge computing device collects and stores environmental data collected by various sensors in real time, and converts the environmental data to generate real-time data streams:

[0071] S(t)=[W s (t),R s (t),Q s (t),E s (t)]

[0072] The above t can be used to represent the time step, that is, it can be used to represent the acquisition moment and can be updated once every minute.

[0073] For example, assuming that the collected data corresponding to each time step t (i.e., environmental data) can include four types of information: water level, rainfall, drainage load, and equipment status. The environmental data corresponding to each moment can form a multidimensional vector (i.e., real-time data stream):

[0074] S(t)=[W s (t),R s (t),Q s (t),E s (t)]

[0075] Among them, W s (t) can be used to characterize the water level. s (t) can be used to characterize rainfall. s (t), can be used to characterize the drainage load. s (t) can be used to characterize the equipment status of drainage equipment.

[0076] Optionally, the above vectors can be used to represent the status of the environment and equipment inside and outside the substation at the current moment, and can provide input for subsequent processing steps. For example, at a certain moment t = 10:00, the real-time data stream corresponding to the collected environmental data can be:

[0077]

[0078] The above environmental data can be transmitted to edge computing devices in real time as input to support subsequent prediction and decision-making processes.

[0079] Furthermore, in order to ensure the reliability and continuity of environmental data collection, this embodiment also designs redundant sensors and data backup mechanisms. Each sensor has at least one set of redundant equipment. For example, two water level sensors are installed in the same area to ensure that when the main sensor fails, the redundant sensor can take over the task and avoid data loss. Environmental data can be uploaded to a local storage device in real time and synchronized to a remote server via 5G or other high-speed networks. Even if the edge computing device fails, the environmental data can be restored through remote backup.

[0080] Optionally, in order to adapt to the complex influencing factors of waterlogging in the substation scenario, a fusion mechanism with a time decay factor is also designed. Through the above time decay factor, it can be ensured that the recent data has a higher weight on the future water level prediction, and the influence of the long-term data gradually decreases. The time decay factor can be used to fuse the real-time data stream to obtain a fused feature vector (X(t)). The calculation formula of the fused feature vector can be:

[0081]

[0082] Among them, α, β, γ, and δ can be used to characterize the weight coefficients of each mode, which can represent the impact of water level, rainfall, drainage load, and equipment status on the prediction. i It can be used to characterize the time attenuation factor and can be used to dynamically adjust the impact of different time steps. Its formula can be:

[0083] λ i =e -θ·i

[0084] Among them, θ can be used to control the time decay rate to ensure that the weight of recent data is higher and the weight of distant data gradually decreases. At the current moment, λ0=1, and the weight of the most recent time step is large.

[0085] Through the above mechanism, the system can more accurately capture the temporal dependencies of multimodal data and reduce the interference of long-term data on short-term forecasts, especially in extreme weather or sudden rainfall. This mechanism ensures the system's sensitivity to recent environmental changes.

[0086] In this embodiment, the data stream of the past n time steps (ie, moments) can also be used to form a multimodal data matrix D(t), which can be used to capture the trend of historical data:

[0087]

[0088] Optionally, the multimodal data matrix can be used to represent the water level, rainfall, drainage load and equipment status of the past n time steps. Through the multimodal data matrix, the interaction between multimodal data (that is, environmental data) and the impact of different environmental data on future water level changes can be reflected.

[0089] As an optional implementation, step S106, based on the fused feature vector, predicts the water level information corresponding to the area at at least one future moment, including: inputting the fused feature vector into a water level prediction model to predict the water level information, wherein the water level prediction model is trained based on a loss function containing a nonlinear regularization term.

[0090] In this embodiment, a water level prediction model is obtained by pre-training based on a loss function including a nonlinear regularization term, and after obtaining a fused feature vector, the fused feature vector can be input into the water level prediction model to predict water level information. The water level prediction model can be a regularized time series recursive model.

[0091] Optionally, in order to adapt to the complex drainage load fluctuations and the nonlinear impact of extreme weather on the water level, this embodiment proposes a regularized time series recursive model (RTM), which not only takes into account the dependencies of the time series, but also introduces regularization terms to cope with the nonlinear load of the drainage system. Furthermore, the water level prediction model can adopt the structure of a recursive neural network (RNN) to capture the long-term dependencies between historical time steps through a recursive mechanism. Among them, the hidden state update formula of the above recursive neural network can be:

[0092] h t =f(W h ·X(t)+U h ·h t-1 +b h )

[0093] Among them, h t Can be used to represent the hidden state at the current moment. h and U h They can be used to represent the weight matrix of the input feature and the hidden state at the previous moment. h Can be used to represent a bias term. f can be used to represent an activation function (e.g., tanh or ReLU).

[0094] Optionally, the fused feature vector X(t) is input into the water level prediction model, and the recursive neural network generates a hidden state h for predicting the future water level by recursively processing the feature vector X(t). t .

[0095] Optionally, the hidden state is used to update the hidden layer, and the fused feature vector can be processed using the hidden layer to obtain a prediction result. The above hidden state can be used to characterize the update rule.

[0096] In this embodiment, a hidden state may be designed and used to update parameters. The parameters may be output as prediction results. The hidden state may be used to set the update rule of the network.

[0097] Optionally, in order to ensure the stability of the system when dealing with drainage load fluctuations, a nonlinear regularization term can be introduced to constrain the impact of extreme changes in drainage system load on water level prediction. This regularization term can be used to reduce the possibility of the system overfitting to abnormal drainage loads or emergencies. The regularized loss function can be defined as:

[0098]

[0099] in, It can be used to represent the loss function and can be used to minimize the prediction error. s (t+i) can be used to represent the real water level, Can be used to represent the predicted water level. Regularization term To control the drainage load Q s (t) and reduce the system's dependence on extreme loads. r It can be used to represent the regularization coefficient, which can be used to adjust the weight of the regularization term to ensure that the model does not over-respond when faced with extreme drainage loads.

[0100] Optionally, the above-mentioned nonlinear regularization term is based on the fluctuation characteristics of the drainage load, which can effectively improve the robustness of the water level prediction model in dealing with extreme weather and drainage load anomalies, thereby effectively preventing water level prediction distortion caused by over-response to drainage anomalies.

[0101] Optionally, in order to ensure the continued accuracy of the model in actual use, the model will perform parameter updates at each time step, which can be achieved by adjusting the regularization coefficient λ in real time r and time decay parameter θ, so that the water level prediction model can adapt to environmental changes and real-time feedback of sensor data. For example, at the current time t = 10:00, the model predicts the water level change in the next hour by fusion of multimodal data of the past n time steps, and outputs These predictions will be used as the basis for drainage scheduling decisions.

[0102] In this embodiment, efficient fusion of multimodal data and accurate water level prediction are achieved through the time-attenuated weighted mechanism and the regularized time series recursive model. Especially in the substation waterlogging protection scenario, it is necessary to deal with complex nonlinear fluctuations in rainfall, drainage load and equipment status. This design provides an effective solution to these challenges: the adaptive weighted fusion of multimodal data ensures that the temporal correlation of different sensor data is fully utilized. The time decay factor increases the system's sensitivity to recent data changes and adapts to sudden rainfall and equipment load changes. The introduction of nonlinear regularization terms improves the stability of the system in the face of abnormal fluctuations in drainage load and prevents overfitting to local extreme data, thereby achieving the technical effect of improving the substation's waterlogging prevention efficiency and solving the technical problem of poor waterlogging prevention efficiency in the substation.

[0103] As an optional implementation, step S108, based on the water level information, determines the scheduling information of at least one drainage device in the area, including: determining the load status of the drainage device and the operating status of the drainage device; determining the scheduling information based on the load status, operating status and water level information.

[0104] In this embodiment, the load state of each drainage device in the area and the operating state of the drainage device can be determined. s (t)) can be used to determine the drainage state of the drainage equipment, and can be used to characterize the working efficiency of the drainage equipment. For example, it can be used to characterize the amount of water discharged by the drainage equipment per unit time, or it can be used to characterize the amount of water discharged by the drainage equipment within time step t. It can be the drainage volume, drainage flow rate, drainage power and other states of the drainage equipment. The above-mentioned operating state can be used to characterize the working state of the drainage equipment, and can include multiple physical quantities such as the temperature, vibration, load current and the like of the drainage equipment. It should be noted that this is only for example, and there is no specific limitation on the type of load state and the content of the operating state.

[0105] Furthermore, the load state and the operating state of the drainage equipment are determined, and based on the load state and the operating state, the scheduling information of the plurality of drainage equipments can be determined.

[0106] Optionally, based on the water level prediction results (i.e., water level information), the dynamic scheduling of drainage equipment can be optimized to ensure maximum drainage efficiency in the area. At the same time, an equipment protection strategy can be set to automatically trigger equipment protection when water level prediction or real-time monitoring shows that the equipment is threatened.

[0107] For example, in order to achieve reasonable scheduling, the load state Q of the drainage system can be calculated first. s (t) and the operating status of each drainage equipment E s(t). The drainage system may include multiple drainage devices. The load status and operation status can be obtained through sensors, and the calculation method can be standardized through formulas. Drainage load Q s (t) is the amount of water discharged by the drainage system in time step t, which can be calculated based on the flow rate and cross-sectional area of ​​the drainage pipe. Assume that the drainage flow rate of the i-th drainage device is v i (t), the cross-sectional area of ​​the pipe is A i , then the drainage load of the drainage equipment Can be:

[0108]

[0109] Among them, v i (t) can be used to represent the flow rate of the i-th drainage device at time t, in meters per second (m / s). i It can be used to express the cross-sectional area of ​​the drainage pipe in square meters (m 2 ). By real-time monitoring of the flow rate v of the device i (t) and the pipe size A i , the current drainage load of the drainage equipment can be obtained.

[0110] Furthermore, the operating state of the drainage equipment E s (t) reflects the working status of the drainage equipment, which may include multiple physical quantities such as the temperature, vibration, load current, etc. The above working status can be obtained in real time through the equipment status sensor to ensure the healthy operation of the drainage equipment. The state vector of the i-th device can be:

[0111]

[0112] Among them, T i (t) can be used to represent the operating temperature of the ith device in degrees Celsius (℃). i (t) can be used to indicate the current load of the device in amperes (A). i (t) can be used to indicate the vibration frequency of the drainage equipment in Hertz (Hz). By comprehensively analyzing the above operating conditions, the load of the equipment can be adjusted in real time to avoid equipment failure due to overload or overheating.

[0113] As an optional implementation, scheduling information is determined based on load status, operating status and water level information, including: based on the load status, constructing a load balancing target, wherein the load balancing target is used to determine the amount of load to be allocated for at least one drainage device; based on the operating status, constructing an energy consumption balancing target, wherein the energy consumption balancing target is used to determine the amount of energy allowed to be consumed by at least one drainage device; based on the water level information, constructing constraints, wherein the constraints are used to represent the critical value of the water level of accumulated water in the area; integrating the load balancing target, energy consumption balancing target and constraints to obtain an integrated result; and determining scheduling information based on the integrated result.

[0114] In this embodiment, a load balancing target can be constructed based on the load state. An energy consumption balancing target can be constructed based on the operation state. Constraints can be constructed based on the water level information. Further, the load balancing target, the energy consumption balancing target and the constraints can be integrated to obtain an integrated result, and scheduling information can be obtained by analyzing the integrated result. The above integrated result can be the final optimization target.

[0115] Optionally, the above load balancing target can be used to limit the amount of load to be allocated for at least one drainage device. The load balancing target ensures uniform load distribution and avoids overloading of individual drainage devices by minimizing the square value of the relative load of each device. The above energy consumption balancing target can be used to determine the amount of energy consumption allowed to be consumed by at least one drainage device. The energy consumption balancing target can ensure that the drainage tasks of the equipment are reasonably scheduled while minimizing the energy consumption of multiple drainage devices. The above constraints are used to represent the critical value of the water level of accumulated water in the area. Through the above constraints, the drainage system can ensure that the water level of accumulated water in the area is always within a safe range when scheduling drainage equipment, thereby avoiding the occurrence of waterlogging.

[0116] Optionally, the core goal of intelligent drainage scheduling is to achieve efficient scheduling of drainage equipment through a multi-objective optimization model to ensure that system energy consumption is minimized, equipment load is balanced, and water levels do not exceed critical values ​​in extreme weather. Therefore, in order to ensure that drainage equipment is not overloaded and to share the load when multiple drainage equipment work in parallel, the scheduling model first needs to achieve load balancing between drainage equipment. is the current load of the i-th drainage device, As its maximum load capacity, the load balancing target can be expressed by the following formula:

[0117]

[0118] Wherein, N can be used to represent the number of drainage equipment. It can be the current drainage load of device i. It can be the maximum drainage capacity of the equipment. Determining the maximum drainage capacity can prevent the load of a single device from exceeding its physical limit.

[0119] Optionally, the energy consumption of the drainage device increases with the increase of drainage flow, but in practical applications, the relationship between flow and energy consumption is nonlinear. Let the energy consumption of the i-th drainage device be It can be expressed by the following nonlinear formula:

[0120]

[0121] Among them, a i It can be the energy consumption coefficient of the equipment and can be used to reflect the energy efficiency characteristics of the equipment. i s (t) can be the current load of the equipment in liters per minute (L / min). Further construct the energy consumption balance target, the optimization goal is to minimize the total energy consumption of all equipment:

[0122]

[0123] Optionally, based on the water level prediction results It is also necessary to ensure that the water level at time T in the future will not exceed the safety critical value W crit , therefore, constraints can be constructed based on water level information:

[0124]

[0125] in, It can be used to represent the predicted water level at the future time step T. crit It can be used to indicate the critical safe water level set by the substation.

[0126] Furthermore, the above multiple optimization objectives and constraints can be integrated to form an overall optimization problem of intelligent drainage scheduling, that is, the load balance objective, energy consumption balance objective and constraints can be integrated to obtain the final optimization objective function (integration result):

[0127]

[0128] in, It can be used to represent the energy consumption of the equipment and can be used to minimize the energy consumption of the system. w It can be used to represent the weight coefficient of the water level constraint, which can be used to control the importance of the water level constraint. It can be used to represent the water level forecast value at least at a future time to ensure that it does not exceed W crit The goal of this optimization model is to achieve efficient scheduling of the intelligent drainage system by balancing equipment loads and minimizing energy consumption while meeting the constraints of water level safety.

[0129] Optionally, the scheduling information may be determined by parsing the integration condition.

[0130] As an optional implementation, in step S110, after scheduling at least one drainage device according to the scheduling information so as to use the scheduled drainage device to drain the accumulated water from the area, the method further includes: obtaining feedback information, wherein the feedback information is used to determine the discharge of the accumulated water; in response to the feedback information being used to characterize that the amount of accumulated water in the area meets a water amount threshold, increasing the number of scheduled drainage devices.

[0131] In this embodiment, after scheduling at least one drainage system according to the scheduling information, feedback information can be obtained, and the feedback information can be used to characterize the removal of accumulated water in the area, and can be text information, digital information, etc., and the type of feedback information is not specifically limited here. Further, based on the feedback information, it can be determined whether the amount of accumulated water in the area meets the water volume threshold. If the amount of accumulated water in the area meets the water volume threshold, the scheduling information can be adjusted, such as increasing the scheduling number of drainage equipment, or the scheduling power, so as to improve the drainage efficiency of accumulated water.

[0132] Since the drainage system usually consists of multiple drainage devices working in coordination, and the drainage devices are linked to each other, a feedback control mechanism is designed in this embodiment to adjust the working state of the drainage devices in real time. s (t) and drainage status, the load of the drainage equipment can be dynamically adjusted, and the start and stop status of the drainage equipment can be adjusted according to the real-time water level. The control strategy can be:

[0133] If the current water level W s (t) Approaching the critical water level W crit , more drainage equipment can be started to increase the overall drainage load of the drainage system to ensure that the water level does not continue to rise.

[0134] If the future water level forecast If it is still within the safe range, the current operation status of the drainage equipment will be maintained to avoid unnecessary energy consumption caused by excessive scheduling.

[0135] In this embodiment, the closed-loop control mechanism can also be used to feed back the current drainage equipment status and water level status to the optimization model at each time step, forming a continuous scheduling-feedback-adjustment closed-loop control chain, which can include: predicting the future water level: according to the prediction results Predict future water level changes. Optimize scheduling: Based on current load Q s (t), equipment status E s (t) and water level prediction The system runs a multi-objective optimization model to generate a drainage scheduling plan. Feedback adjustment: According to the current water level and drainage status, the load and start-stop status of the equipment are adjusted in real time to ensure that the system can minimize energy consumption under the premise of safe operation. Update equipment status: Feedback the current equipment status to the optimization system to update the optimization target and scheduling strategy for the next time step.

[0136] In this embodiment, when water level prediction or real-time monitoring shows that the device may be threatened, device protection can be automatically triggered, for example, device protection instructions (lifting or isolating) and feedback on the current protection status of the device can be triggered.

[0137] Optionally, dynamically schedule equipment lifting or isolation devices according to water level and equipment status, and ensure that each equipment is protected according to priority, so as to achieve the goal of drainage scheduling results and water level prediction. Combined with the status data of drainage equipment E s (t), can realize the purpose of automatic protection of equipment in substation.

[0138] Optionally, determining the execution of the equipment protection strategy based on the predicted water level and the current equipment state may include: when the water level prediction exceeds a critical value, determining whether to raise the equipment or enable an isolation device. When the state of the drainage equipment (e.g., equipment temperature, current, etc.) exceeds a critical value, determining whether to enable protection.

[0139] Optionally, based on the predicted water level The following formula can be used to determine whether equipment lifting or isolation needs to be enabled:

[0140]

[0141] in, It can be used to represent the predicted water level value at at least one future moment, in millimeters (mm); W crit It can be used to indicate the critical water level, that is, when the water level exceeds this value, the equipment protection needs to be activated. The unit is millimeter (mm); E s (t) can be used to represent the device state vector at the current moment, which may include data such as temperature, current load, vibration, etc.; E crit It can be used to indicate the critical value of device status, that is, the protective action required when the device status exceeds this value.

[0142] Optionally, for equipment that supports automatic lifting (such as a transformer), its lifting height ΔH can be calculated. Assuming that the current height of the equipment is H(t), it needs to be lifted to a safe height H safe above:

[0143]

[0144] Where ΔH represents the height to be lifted, in millimeters (mm); H(t) represents the current physical height of the device, in millimeters (mm); Indicates the future predicted water level in millimeters (mm); H safe Indicates the safe height of the equipment in millimeters (mm), indicating the lowest height to which the equipment should be lifted.

[0145] For example, read the predicted water level information Based on the water level information, the safe height detection can be performed, that is, the safe height H of the electrical equipment in the area can be safe Compare and calculate whether the equipment needs to be raised. The equipment lifting system can be started to increase the height difference (ΔH). For equipment that cannot be lifted (for example, a distribution cabinet), when the predicted water level information is about to exceed the height H of the electrical equipment, device When the water is in direct contact with the electrical equipment, the isolation device can be activated to prevent water from directly contacting the electrical equipment. The judgment logic for activating the isolation device can be:

[0146]

[0147] in, It can be used to indicate the future predicted water level in millimeters (mm); H device Can be used to indicate the physical height of the device in millimeters (mm).

[0148] In this embodiment, for electrical equipment that cannot be raised or lowered in the area, a height detection can be performed on the electrical equipment to read the physical height H of the equipment location. device . Further, according to Perform a water level forecast comparison to determine if the water level will exceed the equipment height. The isolation device can be activated to isolate the accumulated water from the electrical equipment.

[0149] In this embodiment, when there are multiple electrical devices in the area that need to be protected at the same time, the lifting and isolation equipment can be reasonably scheduled according to the importance and status of the electrical equipment and the urgency of the water level change. To this end, a priority scheduling model can be introduced, through which key equipment can be protected first.

[0150] Optionally, the priority P i (t) According to the importance of the equipment β i , predict water level The difference from the critical water level and the severity of the equipment status are calculated:

[0151]

[0152] Among them, P i (t) can be used to represent the protection priority of the i-th device at time t; β i It can be used to indicate the importance coefficient of the equipment, which can be used to indicate the importance of the equipment in the substation system; It can be used to represent the water level prediction at at least one future moment, in millimeters (mm); W crit Can be used to indicate the critical value of water level in millimeters (mm); e It can be used to indicate the weight of the impact of device status on priority; E s (t) can be used to indicate the state of the device at the current moment and can be used to determine physical quantities such as temperature and current load; E crit Can be used to indicate critical values ​​of device status.

[0153] Optionally, when multiple devices need protection at the same time, the protection sequence and time minimization can also be considered. Set the lifting or isolation time of the device to T i , the scheduling target can be:

[0154]

[0155] Among them, T i It can be used to indicate the protection time of the ith device in seconds (s); N can be used to indicate the total number of devices that need protection; P i (t) can be used to indicate the protection priority of the i-th device.

[0156] For example, according to P i (t) Calculate the priority of each device. The higher the priority, the higher the priority of the device. Sort by priority to ensure that the total protection time is minimized. According to the sorting results, the lifting or isolation operations of the equipment can be performed one by one. In the process of executing equipment protection, the system should monitor the protection execution status and the protection progress of the equipment in real time to form a closed-loop feedback control to ensure that the protection measures are executed as planned.

[0157] In this embodiment, the status data E of the device can be obtained in real time. s (t) and the current water level W s(t) Check the working status of the protective equipment; according to the actual equipment status and water level changes, the protection plan can be dynamically adjusted. For example, if a certain equipment is raised or lowered slowly and the water level rises quickly, the isolation device can be started in advance; when the equipment is raised or isolated, its protection status is fed back, which may include: whether the equipment is successfully lifted to the specified height or whether the isolation device is fully enabled; based on the feedback data, the system's protection strategy is updated, and the protection measures of the unexecuted equipment can be adjusted.

[0158] Optionally, in order to improve the response speed and accuracy of equipment protection, it is also proposed to dynamically adjust the protection strategy according to real-time data to have adaptive protection optimization capabilities for the equipment in the area. For example, when the water level changes rapidly, the equipment in poor condition can be processed first. Protection priority P i (t) can be dynamically adjusted according to the real-time water level and equipment status, and the formula can be:

[0159]

[0160] Among them, P i (t) can be used to indicate the priority at the current moment; P i (t-1) can be used to indicate the priority at the previous moment; η can be used to indicate the dynamic adjustment coefficient, which can control the impact of water level changes on the priority; Can be used to express future water level predictions in millimeters (mm); W s (t) can be used to indicate the current actual water level in millimeters (mm); W crit Can be used to indicate water level critical value in millimeters (mm).

[0161] In this embodiment, through the above-mentioned detailed protection decision-making and automated execution scheme, the lifting or isolation measures of equipment in the substation can be dynamically adjusted based on water level prediction and equipment status data. Priority scheduling ensures that key equipment is protected first, and closed-loop feedback control ensures the reliability of protection execution. The adaptive optimization mechanism enables the system to respond flexibly to complex weather and drainage conditions to ensure equipment safety. It should be noted that the above-mentioned protection decision-making scheme can be selected and changed according to actual conditions, and there is no specific restriction on the method of the protection decision-making scheme here.

[0162] As an optional implementation, the method may also include: in response to water level information exceeding a water volume threshold, or the presence of abnormally operating electrical equipment in the area, determining an emergency response strategy based on the water level information, wherein the emergency response strategy is used to represent rules for preventing electrical equipment from being damaged by water; and determining operating data of electrical equipment that is operating normally in the area according to the emergency response strategy.

[0163] In this embodiment, an equipment protection strategy (that is, an emergency response strategy) can be preset. When the predicted water level information exceeds a critical value or when the real-time monitoring displays that the device is threatened, an emergency response strategy can be automatically triggered) to perform equipment protection. Among them, the above-mentioned operating data can be used to characterize the operating status of the electrical equipment, for example, it can be data such as the height, position, waterproof performance, voltage, current, etc. of the electrical equipment. It should be noted that this is only for example, and there is no specific limitation on the type of operating data.

[0164] Optionally, when the water level information of the water level forecast exceeds the critical value, it can be further determined whether to raise the equipment or enable the isolation device; or when the operating status of the equipment exceeds the critical value, it can be determined whether to enable waterproof protection. If the water level information exceeds the water volume threshold, or there is abnormally operating electrical equipment in the area, the corresponding emergency response strategy can be determined based on the water level information and the operating data of the electrical equipment. According to the emergency response strategy, the operating data of the electrical equipment can be further adjusted to ensure the normal operation of the electrical equipment. For example, for electrical equipment that supports automatic lifting in the substation, the height of the electrical equipment can be controlled to prevent water from entering the electrical equipment.

[0165] Optionally, if the water level information in the area exceeds the water volume threshold, and / or there are abnormally operating electrical equipment in the area, the operating status of the electrical equipment can be obtained, and based on the water level and the operating status, an emergency response strategy that matches the water level information and the operating status can be determined. Furthermore, the operating status of the electrical equipment that is operating normally in the area can be controlled according to the above emergency response strategy. Among them, the above operating status may include a normal operating status and an abnormal operating status. The operating status of the electrical equipment can be changed by changing the operating data such as the power and current of the electrical equipment. It should be noted that this is only an example, and there is no specific limitation on the way of changing the operating status. The above electrical equipment may include operating equipment and protective equipment in the area.

[0166] Optionally, multi-level emergency response measures are designed. When the drainage or protection system fails, corresponding emergency response measures are initiated according to the real-time water level and the operating status of the electrical equipment to ensure the stable operation of other equipment and avoid ineffective responses.

[0167] For example, when the system is initialized, the current equipment protection status and overall system health status are checked first to decide whether to start the multi-level emergency response mechanism. If the water level exceeds the safety threshold or some equipment fails (that is, there are abnormally operating electrical equipment), the emergency state can be automatically entered, which can be judged by the following formula:

[0168] if W s (t)≥W crit E s(t)≥E crit :initiate emergency response

[0169] Among them, W s (t) can be used to indicate the current water level in millimeters (mm); W crit It can be used to indicate the safety critical value of water level, in millimeters (mm); E s (t) can be used to represent the device state vector, which can be used to represent the device temperature, current load and other states; E crit Can be used to indicate safety thresholds of device status.

[0170] In this embodiment, a multi-level emergency response mechanism is also designed, which responds step by step according to the severity of the water level exceeding the threshold and the operating status of the equipment, wherein the above emergency response can be divided into three levels, each level corresponding to different response measures. It should be noted that the types of emergency responses and corresponding emergency response strategies here are only examples and can be changed according to actual conditions, and no specific restrictions are made here.

[0171] For example, the above emergency response may include a first-level emergency response (also called a primary response): when the water level approaches the critical value but has not yet exceeded W crit , or the device status is close to E crit , the system can enter the primary response stage and execute the following emergency response strategies: start equipment warning, which can issue an early warning to the equipment, indicating that it is about to reach a critical state; detect the operating status of the protective equipment to ensure the normal operation of the lifting and isolation devices; further optimize the scheduling of drainage equipment to ensure that the drainage capacity is maximized. Among them, the objective function of drainage optimization can be:

[0172]

[0173] in, It can be used to represent the drainage volume of the i-th drainage device in liters per minute (L / min); N can be used to represent the total number of drainage devices. At this time, the drainage system can give priority to ensuring the normal operation of all drainage devices and maximizing the drainage capacity to avoid further rise in water level.

[0174] For example, the above emergency response may include a secondary emergency response (also called an intermediate response): when the water level exceeds a critical value W crit, but when the equipment is still operating normally, you can enter the intermediate emergency response to implement more stringent measures. The emergency response strategy corresponding to the secondary emergency response may include the following steps: enable backup drainage equipment, that is, dispatch backup drainage equipment or temporary drainage system to enhance drainage capacity; accelerate the execution of unfinished equipment lifting or isolation measures to ensure that all equipment protection is in place; you can start backup sensors and data acquisition devices to ensure that accurate environmental data can still be obtained when the main sensor fails.

[0175] Optionally, redundant acquisition can be formulated as:

[0176] D redundant (t) = α·D primary (t)+β·D backup (t)

[0177] Among them, D redundant (t) can be used to represent the results of redundant data integration; D primary (t) can be used to represent the data collected by the main sensor; D backup (t) can be used to represent the data collected by the backup sensor; α can be used to represent the weight coefficient of the main sensor, which is usually close to 1; β can be used to represent the weight coefficient of the backup sensor, which is usually close to 0 but increases when the main sensor fails.

[0178] For example, the above emergency response may include three levels of emergency response (also known as advanced response): when the water level far exceeds the critical value, or the equipment status exceeds the safety threshold, the system enters the third level of emergency response, which is the highest level of emergency measures, which can be used to ensure that the core functions of the electrical system in the area can still be maintained. Among them, the emergency response strategy corresponding to the third level of emergency response may include: starting the emergency power supply to ensure that the key equipment of the substation continues to operate through an independent emergency power supply; starting forced equipment protection, that is, taking forced protection measures for equipment that has not yet completed protection, including forced lifting or immediate activation of isolation devices; emergency data backup and communication, that is, data redundancy backup and emergency communication mechanisms can be started to ensure the transmission and storage of real-time data. The core of the emergency communication mechanism can be:

[0179] C emergency (t)=f(D(t),E s (t),W s (t))

[0180] Among them, C emergency (t) can be used to represent emergency communication output, including equipment status and environmental data; D(t) can be used for real-time data of data acquisition devices; E s (t) can be used for the current state of the device; W s(t) can be used for the current water level; D(t) can be used to characterize the above multimodal data matrix.

[0181] In this embodiment, in order to improve the reliability of the system and its ability to cope with emergencies, the system introduces redundancy design and fault tolerance mechanisms to ensure that the system can continue to operate when certain components fail or data is unreliable. When key equipment in the area (e.g., drainage pumps, data acquisition sensors) fails, the system can automatically enable redundant equipment to ensure the continuity of core functions. The judgment conditions for the activation of redundant equipment can be:

[0182]

[0183] in, It can be used to indicate the current displacement of the i-th device in liters per minute (L / min); Can be used to indicate the minimum drainage capacity of the ith device in liters per minute (L / min).

[0184] Optionally, when some data sensors fail, the redundant data can be dynamically adjusted through the data fusion algorithm to ensure data accuracy. The redundant data fusion model can be:

[0185] D f (t) = α·D primary (t)+β·D backup (t)

[0186] Among them, D f (t) can be expressed as the final fault-tolerant data output; D primary (t) can be expressed as the main sensor data; D backup (t) can be expressed as the backup sensor data; α can be expressed as the weight coefficient of the main sensor; β can be expressed as the weight coefficient of the backup sensor, and the weight coefficient can be dynamically adjusted according to the health status of the sensor.

[0187] In this embodiment, during the emergency response process, feedback can be continuously received and the emergency strategy can be dynamically adjusted to ensure stable operation of the system and avoid ineffective responses.

[0188] Optionally, feedback control can be achieved by the following steps:

[0189] Real-time data monitoring: The system continuously monitors the water level W s (t) and device status E s (t);

[0190] Strategy adjustment: Dynamically adjust emergency response strategies based on real-time feedback, such as lowering the weight of backup equipment or increasing emergency resources;

[0191] Optimized execution: Each emergency operation is optimized and adjusted to ensure the efficient operation of the system under extreme conditions.

[0192] The multi-level emergency response and redundancy design mechanism ensures that the system can continue to operate in the worst case through hierarchical response and redundant design. Whether it is water level exceeding the standard, equipment failure, or partial failure of data collection, the system can respond quickly and take effective measures to ensure system stability and security. Redundant data collection, equipment fault tolerance and emergency communication mechanism ensure that the system can always respond effectively at critical moments.

[0193] In this embodiment, real-time environmental data of the substation is collected, and the environmental data includes water level, rainfall intensity, drainage system load and water accumulation monitored by machine vision, and the real-time environmental data is combined into a real-time data stream. The real-time data stream of the past n time steps is used to form a multimodal data matrix, and a time decay factor is introduced into the real-time data stream for data fusion to obtain a fused feature vector. Then, a regularized time series recursive model is constructed, and the fused feature vector is input to predict the water level; the dynamic scheduling of the drainage system is optimized according to the predicted results of the water level to ensure the maximum drainage efficiency, and the equipment protection strategy is set at the same time. When the water level prediction or real-time monitoring shows that the equipment is threatened, the equipment protection is automatically triggered; multi-level emergency response measures are designed. When the drainage or protection system fails, the corresponding emergency response measures are started according to the real-time water level and the status of the equipment to ensure the stable operation of other equipment and avoid invalid responses;

[0194] Optionally, through self-organizing network technology, the system (which can be used for substation flood prevention decision-making and automatic control systems in extreme weather environments) can dynamically adjust the working status of drainage equipment according to real-time water level monitoring data, and automatically coordinate the drainage equipment in each area to work together. When the water level in a local area rises rapidly or the drainage equipment is overloaded, the system can intelligently dispatch drainage equipment in other areas to support and avoid local drainage problems or equipment overload. This innovation solves the problem of passive response of the existing drainage system, making drainage scheduling more flexible and efficient, and improving the overall drainage capacity.

[0195] Optionally, a water level prediction model based on machine learning (e.g., LSTM) is introduced to accurately predict future water level changes by combining real-time meteorological data and historical hydrological data, and real-time monitoring of water accumulation in the substation area is performed through machine vision technology. Compared with the traditional water level monitoring system, this system can predict the risk of waterlogging in advance and start drainage equipment before the water level exceeds the preset safety line, reducing the lag of responding only after the water level reaches the critical point.

[0196] Optionally, intelligent automatic lifting and isolation protection devices are designed for key equipment in the substation, such as transformers and control cabinets. When water level forecasts or real-time monitoring finds the risk of flooding, the system can automatically lift the equipment to a safe height or activate isolation devices to prevent the equipment from directly contacting the accumulated water. This dynamic equipment protection mechanism overcomes the limitations of the static design of traditional equipment protection methods, ensuring that the equipment can be protected in a timely and effective manner when the water level changes extremely.

[0197] In an embodiment of the present invention, environmental data of the area where the substation is located (for example, real-time environmental data) is obtained, and the environmental data is fused to obtain a fused feature vector. The fused feature vector is predicted to obtain water level information corresponding to the area at at least one future moment. Based on the water level information, the scheduling information of the drainage equipment in the area is determined, and the drainage equipment is scheduled according to the scheduling information to achieve the purpose of draining the accumulated water in the area, thereby achieving the technical effect of improving the flood control efficiency of the substation and solving the technical problem of poor flood control efficiency of the substation.

[0198] According to an embodiment of the present invention, a scheduling device for drainage equipment is also provided. It should be noted that the scheduling device for drainage equipment of this embodiment can be used to execute the scheduling method for drainage equipment of embodiment 1 of the present invention.

[0199] Figure 2 Schematic diagram of a scheduling device for drainage equipment according to an embodiment of the present invention. Figure 2 As shown, the scheduling device 20 of the drainage equipment may include: an acquisition unit 202 , a processing unit 204 , a prediction unit 206 , a determination unit 208 and a scheduling unit 210 .

[0200] The acquisition unit 202 is used to acquire environmental data of the area where the substation is located.

[0201] The processing unit 204 is used to perform fusion processing on the environmental data to obtain a fused feature vector, wherein the fused feature vector is used to characterize the environmental change of the region.

[0202] The prediction unit 206 is used to predict the water level information corresponding to the region at at least one future time based on the fused feature vector, wherein the water level information is used to characterize the amount of water accumulated in the region.

[0203] The determination unit 208 is used to determine the scheduling information of at least one drainage device in the area based on the water level information, wherein the scheduling information is used to indicate whether the drainage device is in an open state or a closed state.

[0204] The scheduling unit 210 is used to schedule at least one drainage device according to the scheduling information, so as to use the scheduled drainage device to drain the accumulated water from the area.

[0205] The scheduling device for drainage equipment of this embodiment obtains environmental data of the area where the substation is located through an acquisition unit; fuses the environmental data through a processing unit to obtain a fused feature vector, wherein the fused feature vector is used to characterize environmental changes in the area; predicts water level information corresponding to the area at at least one future moment based on the fused feature vector through a prediction unit, wherein the water level information is used to characterize the amount of accumulated water in the area; determines scheduling information of at least one drainage equipment in the area based on the water level information through a determination unit, wherein the scheduling information is used to characterize whether the drainage equipment is in an open state or a closed state; and schedules at least one drainage equipment according to the scheduling information through a scheduling unit, so as to use the scheduled drainage equipment to discharge accumulated water from the area, thereby achieving the technical effect of improving the flood control efficiency of the substation and solving the technical problem of poor flood control efficiency of the substation.

[0206] The embodiment of the present invention can provide a computer terminal, which can be any computer terminal device in a computer terminal group. Optionally, in this embodiment, the computer terminal can also be replaced by a terminal device such as a mobile terminal.

[0207] Optionally, in this embodiment, the computer terminal may be located in at least one network device among a plurality of network devices of the computer network.

[0208] In this embodiment, the above-mentioned computer terminal can execute the program code of the following steps in the scheduling method of drainage equipment: obtaining environmental data of the area where the substation is located; fusing the environmental data to obtain a fused feature vector, wherein the fused feature vector is used to characterize the environmental changes in the area; based on the fused feature vector, predicting the water level information corresponding to the area at at least one future moment, wherein the water level information is used to characterize the amount of water accumulated in the area; based on the water level information, determining the scheduling information of at least one drainage equipment in the area, wherein the scheduling information is used to characterize whether the drainage equipment is in an open state or a closed state; according to the scheduling information, scheduling at least one drainage equipment to use the scheduled drainage equipment to drain the accumulated water from the area.

[0209] Optionally, Figure 3 is a structural block diagram of a computer terminal according to an embodiment of the present invention. Figure 3 As shown, the computer terminal 308 may include: one or more (only one is shown in the figure) processors 302 , a memory 304 and a transmission device 306 .

[0210] The memory can be used to store software programs and modules, such as program instructions / modules corresponding to the method and device for scheduling drainage equipment in the embodiment of the present invention. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, the scheduling method of the drainage equipment described above is realized. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the computer terminal 308 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0211] The processor can call the information and application programs stored in the memory through the transmission device to execute the following steps: obtain the environmental data of the area where the substation is located; fuse the environmental data to obtain a fused feature vector, wherein the fused feature vector is used to characterize the environmental changes in the area; based on the fused feature vector, predict the water level information corresponding to the area at at least one future moment, wherein the water level information is used to characterize the amount of water accumulated in the area; based on the water level information, determine the scheduling information of at least one drainage device in the area, wherein the scheduling information is used to characterize whether the drainage device is in an open state or a closed state; according to the scheduling information, schedule at least one drainage device to use the scheduled drainage device to drain the accumulated water from the area.

[0212] It can be understood by those skilled in the art that Figure 3 The structure shown is for illustration only, and the computer terminal 308 may also be a smart phone (such as an Android phone, an iOS phone, etc.), a tablet computer, a PDA, a mobile Internet device (Mobile Internet Devices, referred to as MID), a PAD, or other terminal devices. Figure 3 The structure of the computer terminal 308 is not limited. For example, the computer terminal 308 may also include Figure 3 More or fewer components (such as network interfaces, display devices, etc.) shown in, or having Figure 3 Different configurations shown.

[0213] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing the hardware related to the terminal device through a program, and the program can be stored in a computer-readable storage medium, and the storage medium may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc.

[0214] According to an embodiment of the present invention, a computer-readable storage medium is further provided. The computer-readable storage medium includes a stored program, wherein the program executes the scheduling method of the drainage equipment in Example 1.

[0215] Optionally, in this embodiment, the computer-readable storage medium may be located in any one of the computer terminals in a computer terminal group in a computer network, or in any one of the mobile terminals in a mobile terminal group.

[0216] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for executing the following steps: obtaining environmental data of the area where the substation is located; fusing the environmental data to obtain a fused feature vector, wherein the fused feature vector is used to characterize environmental changes in the area; based on the fused feature vector, predicting water level information corresponding to the area at at least one future moment, wherein the water level information is used to characterize the amount of accumulated water in the area; based on the water level information, determining scheduling information of at least one drainage device in the area, wherein the scheduling information is used to characterize whether the drainage device is in an open state or a closed state; and scheduling at least one drainage device according to the scheduling information to use the scheduled drainage device to drain the accumulated water from the area.

[0217] Optionally, the computer-readable storage medium may also execute program codes of the following steps: calling the edge computing device to convert the environmental data to obtain a real-time data stream; using the time attenuation factor to perform data fusion on the real-time data stream to obtain a fused feature vector.

[0218] Optionally, the computer-readable storage medium may also execute program code of the following steps: inputting the fused feature vector into a water level prediction model to predict water level information, wherein the water level prediction model is trained based on a loss function including a nonlinear regularization term.

[0219] Optionally, the computer-readable storage medium may also execute program codes of the following steps: determining a load state of the drainage equipment and an operating state of the drainage equipment; and determining scheduling information based on the load state, operating state and water level information.

[0220] Optionally, the computer-readable storage medium can also execute the program code of the following steps: constructing a load balancing target based on the load status, wherein the load balancing target is used to determine the load to be allocated for at least one drainage device; constructing an energy consumption balancing target based on the operating status, wherein the energy consumption balancing target is used to determine the energy consumption allowed to be consumed by at least one drainage device; constructing constraint conditions based on water level information, wherein the constraint conditions are used to represent the critical water level value of water accumulation in the area; integrating the load balancing target, energy consumption balancing target and constraint conditions to obtain an integrated result; and determining the scheduling information based on the integrated result.

[0221] Optionally, the computer-readable storage medium may also execute program codes for the following steps: obtaining feedback information, wherein the feedback information is used to represent feedback results on the discharge of accumulated water; and increasing the number of drainage equipment dispatched in response to the feedback information being used to characterize that the amount of accumulated water in the area meets a water amount threshold.

[0222] Optionally, the computer-readable storage medium may also execute program code for the following steps: in response to water level information exceeding a water volume threshold, or the presence of abnormally operating electrical equipment in the area, determining an emergency response strategy based on the water level information, wherein the emergency response strategy is used to represent rules for preventing electrical equipment from being damaged by water; and determining operating data for electrical equipment that is operating normally in the area according to the emergency response strategy.

[0223] In this embodiment, environmental data of the area where the substation is located (for example, real-time environmental data) is obtained, and the environmental data is fused to obtain a fused feature vector. The fused feature vector is predicted to obtain the water level information corresponding to the area at at least one future moment. Based on the water level information, the scheduling information of the drainage equipment in the area is determined, and the drainage equipment is scheduled according to the scheduling information to achieve the purpose of draining the accumulated water in the area, thereby achieving the technical effect of improving the flood prevention efficiency of the substation and solving the technical problem of poor flood prevention efficiency of the substation.

[0224] According to an embodiment of the present invention, a processor is further provided, and the processor is used to run a program, wherein when the program is run by the processor, the scheduling method of the drainage equipment in Embodiment 1 is executed.

[0225] Optionally, in this embodiment, the computer terminal may be located in at least one network device among a plurality of network devices of the computer network.

[0226] In this embodiment, the above-mentioned computer terminal can execute the program code of the following steps in the scheduling method of drainage equipment: obtaining environmental data of the area where the substation is located; fusing the environmental data to obtain a fused feature vector, wherein the fused feature vector is used to characterize the environmental changes in the area; based on the fused feature vector, predicting the water level information corresponding to the area at at least one future moment, wherein the water level information is used to characterize the amount of water accumulated in the area; based on the water level information, determining the scheduling information of at least one drainage equipment in the area, wherein the scheduling information is used to characterize whether the drainage equipment is in an open state or a closed state; according to the scheduling information, scheduling at least one drainage equipment to use the scheduled drainage equipment to drain the accumulated water from the area.

[0227] Among them, the memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the scheduling method and device of the drainage equipment in the embodiment of the present invention. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, realizing the scheduling method of the drainage equipment mentioned above. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the computer terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0228] The processor can call the information and application programs stored in the memory through the transmission device to execute the following steps: obtain the environmental data of the area where the substation is located; fuse the environmental data to obtain a fused feature vector, wherein the fused feature vector is used to characterize the environmental changes in the area; based on the fused feature vector, predict the water level information corresponding to the area at at least one future moment, wherein the water level information is used to characterize the amount of water accumulated in the area; based on the water level information, determine the scheduling information of at least one drainage device in the area, wherein the scheduling information is used to characterize whether the drainage device is in an open state or a closed state; according to the scheduling information, schedule at least one drainage device to use the scheduled drainage device to drain the accumulated water from the area.

[0229] Optionally, in this embodiment, the processor is configured to store program code for executing the following steps: obtaining environmental data of the area where the substation is located; fusing the environmental data to obtain a fused feature vector, wherein the fused feature vector is used to characterize environmental changes in the area; based on the fused feature vector, predicting water level information corresponding to the area at at least one future moment, wherein the water level information is used to characterize the amount of accumulated water in the area; based on the water level information, determining scheduling information of at least one drainage device in the area, wherein the scheduling information is used to characterize whether the drainage device is in an open state or a closed state; and scheduling at least one drainage device according to the scheduling information to use the scheduled drainage device to drain the accumulated water from the area.

[0230] Optionally, the processor may also execute the following program code: call the edge computing device to convert the environmental data to obtain a real-time data stream; use the time attenuation factor to fuse the real-time data stream to obtain a fused feature vector.

[0231] Optionally, the processor may also execute the program code of the following steps: inputting the fused feature vector into a water level prediction model to predict water level information, wherein the water level prediction model is trained based on a loss function including a nonlinear regularization term.

[0232] Optionally, the processor may also execute program codes of the following steps: determining the load status of the drainage equipment and the operating status of the drainage equipment; and determining scheduling information based on the load status, operating status and water level information.

[0233] Optionally, the processor may also execute the program code of the following steps: constructing a load balancing target based on the load status, wherein the load balancing target is used to determine the amount of load to be allocated for at least one drainage device; constructing an energy consumption balancing target based on the operating status, wherein the energy consumption balancing target is used to determine the amount of energy consumption allowed to be consumed by at least one drainage device; constructing constraint conditions based on water level information, wherein the constraint conditions are used to represent the critical value of the water level of accumulated water in the area; integrating the load balancing target, energy consumption balancing target and constraint conditions to obtain an integrated result; and determining the scheduling information based on the integrated result.

[0234] Optionally, the processor may also execute program code for the following steps: obtaining feedback information, wherein the feedback information is used to determine the discharge of accumulated water; and increasing the number of drainage devices to be scheduled in response to the feedback information being used to characterize that the amount of accumulated water in the area meets a water amount threshold.

[0235] Optionally, the processor may also execute program code for the following steps: in response to water level information exceeding a water volume threshold, or the presence of abnormally operating electrical equipment in the area, determining an emergency response strategy based on the water level information, wherein the emergency response strategy is used to represent rules for preventing electrical equipment from being damaged by water; and determining operating data for electrical equipment that is operating normally in the area in accordance with the emergency response strategy.

[0236] By adopting the embodiment of the present invention, environmental data (for example, real-time environmental data) of the area where the substation is located is obtained, and the environmental data is fused to obtain a fused feature vector. The fused feature vector is predicted to obtain the water level information corresponding to the area at at least one future moment. Based on the water level information, the scheduling information of the drainage equipment in the area is determined, and the drainage equipment is scheduled according to the scheduling information to achieve the purpose of draining the accumulated water in the area, thereby achieving the technical effect of improving the flood prevention efficiency of the substation and solving the technical problem of poor flood prevention efficiency of the substation.

[0237] According to an embodiment of the present invention, a computer program product is further provided. The computer program product includes computer instructions, wherein the computer instructions implement the scheduling method of the drainage equipment in Example 1 when executed by a processor.

[0238] An embodiment of the present application may provide an electronic device, which may include a memory and a processor.

[0239] Figure 4It is a block diagram of an electronic device for a method for scheduling drainage equipment according to an embodiment of the present application. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or required herein.

[0240] like Figure 4 As shown, the device 400 includes a computing unit 401, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 402 or a computer program loaded from a storage unit 408 to a random access memory (RAM) 403. In RAM 403, various programs and data required for the operation of the device 400 can also be stored. The computing unit 401, ROM 402, and RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0241] A number of components in the device 400 are connected to the I / O interface 405, including: an input unit 406, such as a keyboard, a mouse, etc.; an output unit 404, such as various types of displays, speakers, etc.; a storage unit 408, such as a disk, an optical disk, etc.; and a communication unit 409, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 409 allows the device 400 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0242] The computing unit 401 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as a verification method for data. For example, in some embodiments, the verification method for data may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 400 via the ROM 402 and / or the communication unit 409. When the computer program is loaded into RAM 403 and executed by the computing unit 401, one or more steps of the data verification method described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to perform the data verification method in any other appropriate manner (e.g., by means of firmware).

[0243] According to an embodiment of the present application, a scheduling method for drainage equipment is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0244] Various embodiments of the systems and techniques described above herein may be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on a chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor that may be a dedicated or general purpose programmable processor that may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0245] The program code for implementing the method of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0246] In the context of the present application, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0247] To provide interaction with a user, the systems and techniques described herein may be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or an LCD (liquid crystal display, monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a path ball) through which the user can provide input to the computer. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0248] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a Local Area Network (LAN), a Wide Area Network (WAN), and the Internet.

[0249] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0250] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0251] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0252] In the several embodiments provided by the present invention, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic, for example, the division of units can be a logical function division, and there can be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0253] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed over multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0254] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0255] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0256] The above are only preferred embodiments of the present invention. It should be pointed out that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for dispatching drainage equipment, characterized in that: include: Obtain environmental data of the area where the substation is located; Performing fusion processing on the environmental data to obtain a fusion feature vector, wherein the fusion feature vector is used to characterize the environmental change of the area; Based on the fused feature vector, predicting the water level information corresponding to the area at at least one future moment, wherein the water level information is used to characterize the amount of water accumulated in the area; Based on the water level information, determining the scheduling information of at least one drainage device in the area, wherein the scheduling information is used to indicate whether the drainage device is in an open state or a closed state; At least one of the drainage devices is scheduled according to the scheduling information, so as to drain the accumulated water from the area by using the scheduled drainage device.

2. The method according to claim 1, characterized in that The step of fusing the environmental data to obtain a fused feature vector includes: Invoke the edge computing device to convert the environmental data to obtain a real-time data stream; The real-time data stream is subjected to data fusion using a time decay factor to obtain the fused feature vector.

3. The method according to claim 1, characterized in that The predicting, based on the fused feature vector, of the water level information corresponding to the area at at least one future moment includes: The fused feature vector is input into a water level prediction model to predict the water level information, wherein the water level prediction model is trained based on a loss function including a nonlinear regularization term.

4. The method according to claim 1, characterized in that: The determining, based on the water level information, the scheduling information of at least one drainage device in the area includes: determining a load state of the drainage device and an operating state of the drainage device; The scheduling information is determined based on the load status, the operating status and the water level information.

5. The method according to claim 4, characterized in that The determining the scheduling information based on the load state, the operating state and the water level information includes: Based on the load state, construct a load balancing target, wherein the load balancing target is used to determine the load to be allocated for at least one of the drainage devices; Based on the operating state, construct an energy consumption balance target, wherein the energy consumption balance target is used to determine the energy consumption amount allowed to be consumed by at least one of the drainage devices; Based on the water level information, construct a constraint condition, wherein the constraint condition is used to represent a critical value of the water level of the accumulated water in the area; Integrate the load balancing target, energy consumption balancing target and constraint conditions to obtain an integrated result; Based on the integration result, the scheduling information is determined.

6. The method according to claim 1, characterized in that After scheduling at least one of the drainage devices according to the scheduling information so as to use the scheduled drainage device to drain the accumulated water from the area, the method further includes: Acquiring feedback information, wherein the feedback information is used to indicate a feedback result on the discharge of the accumulated water; In response to the feedback information being used to indicate that the amount of accumulated water in the area meets a water amount threshold, the dispatching quantity of the drainage equipment is increased.

7. The method according to any one of claims 1 to 6, characterized in that: The method further comprises: In response to the water level information exceeding a water volume threshold, or the presence of abnormally operating electrical equipment in the area, determining an emergency response strategy based on the water level information, wherein the emergency response strategy is used to represent a rule for preventing the electrical equipment from being flooded; According to the emergency response strategy, operating data of electrical equipment operating normally in the area is determined.

8. A dispatching device for drainage equipment, characterized in that: include: An acquisition unit, used for acquiring environmental data of the area where the substation is located; A processing unit, used for fusing the environmental data to obtain a fused feature vector, wherein the fused feature vector is used to characterize the environmental change of the area; A prediction unit, configured to predict water level information corresponding to the area at at least one future moment based on the fused feature vector, wherein the water level information is used to characterize the amount of accumulated water in the area; A determination unit, configured to determine, based on the water level information, scheduling information of at least one drainage device in the area, wherein the scheduling information is used to indicate whether the drainage device is in an open state or a closed state; A scheduling unit is used to schedule at least one of the drainage devices according to the scheduling information, so as to use the scheduled drainage device to drain the accumulated water from the area.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that The method comprises computer instructions, which, when executed by a processor, implement the method according to any one of claims 1 to 7.

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