Intelligent scheduling method and device for electrolytic cell

Abstract

The invention discloses an intelligent scheduling method and device for electrolytic cells, and relates to the technical field of intelligent scheduling, and the method comprises the steps: obtaining distribution equipment connected with a plurality of electrolytic cells; constructing an electrolytic bath topology network; according to the start-stop identification assembly, an identified electrolytic bath set in the multiple electrolytic baths is determined, and the identified electrolytic baths are electrolytic baths required by bath stop; on the basis of the electrolytic cell topology network, identifying a connection sub-network of each identified electrolytic cell and each distributed device in the identified electrolytic cell set; performing influence evaluation on the connection sub-network of each identified electrolytic cell and each distributed device, and outputting a connection influence index; based on the connection influence indexes, a start-stop scheduling scheme is generated, and start-stop scheduling of the multiple electrolytic cells is executed according to the start-stop scheduling scheme. The technical problems that in the prior art, starting and stopping scheduling of the electrolytic cell is not accurate enough, and the resource distribution efficiency is low are solved, and the technical effects of accurate judgment of the running state of the electrolytic cell and resource scheduling optimization are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent scheduling, and in particular to an electrolytic cell intelligent scheduling method and device. Background Art

[0002] With the rapid growth of industrial production and energy demand, electrolytic cells, as important industrial equipment, have been widely used in the fields of chemical industry, electrolytic aluminum and electroplating. However, with the continuous expansion of production scale and the complexity of process flow, the scheduling and management of electrolytic cell operation are also facing increasingly severe challenges. Traditional electrolytic cell start-stop scheduling methods usually rely on fixed rules, and there are problems such as insufficient scheduling accuracy, low resource allocation efficiency and poor operation stability, which are difficult to meet the needs of modern industry for efficient, accurate and stable operation. Summary of the invention

[0003] The present application provides an electrolytic cell intelligent scheduling method and device, which are used to solve the technical problems in the prior art of inaccurate start and stop scheduling of electrolytic cells and low resource allocation efficiency.

[0004] In view of the above problems, the present application provides an electrolytic cell intelligent scheduling method and device.

[0005] In a first aspect of the present application, a method for intelligent scheduling of an electrolytic cell is provided, the method comprising: Obtain distribution equipment connected to a plurality of electrolytic cells; construct an electrolytic cell topology network based on the connection relationship between the distribution equipment and the plurality of electrolytic cells; determine a set of identified electrolytic cells in the plurality of electrolytic cells based on a start-stop identification component, and identify the electrolytic cells as electrolytic cells with a stop requirement; based on the electrolytic cell topology network, identify the connection subnetworks between each identified electrolytic cell in the set of identified electrolytic cells and each distribution equipment; perform an impact assessment on the connection subnetworks between each identified electrolytic cell and each distribution equipment, and output a connection impact index; generate a start-stop scheduling plan based on the connection impact index, and execute the start-stop scheduling of the plurality of electrolytic cells according to the start-stop scheduling plan.

[0006] The second aspect of the present application provides an electrolytic cell intelligent scheduling device, the device comprising: An equipment acquisition module, wherein the equipment acquisition module acquires distributed equipment connected to a plurality of electrolytic cells; an electrolytic cell topology network construction module, wherein the electrolytic cell topology network construction module constructs an electrolytic cell topology network according to the connection relationship between the distributed equipment and the plurality of electrolytic cells; an electrolytic cell identification module, wherein the electrolytic cell identification module determines a set of identified electrolytic cells among the plurality of electrolytic cells according to a start-stop identification component, and identifies an electrolytic cell as an electrolytic cell with a stop requirement; a connection subnetwork identification module, wherein the connection subnetwork identification module identifies, based on the electrolytic cell topology network, connection subnetworks between each identified electrolytic cell in the set of identified electrolytic cells and each distributed equipment; an impact assessment module, wherein the impact assessment module performs an impact assessment on the connection subnetworks between each identified electrolytic cell and each distributed equipment, and outputs a connection impact index; a start-stop scheduling module, wherein the start-stop scheduling module generates a start-stop scheduling plan based on the connection impact index, and executes start-stop scheduling of the plurality of electrolytic cells according to the start-stop scheduling plan.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: The present application obtains distribution equipment connected to multiple electrolytic cells; constructs an electrolytic cell topology network based on the connection relationship between the distribution equipment and the multiple electrolytic cells; determines a set of identified electrolytic cells in the multiple electrolytic cells based on the start-stop identification component, and identifies the electrolytic cell as an electrolytic cell with a stop requirement; identifies the connection subnetwork between each identified electrolytic cell in the set of identified electrolytic cells and each distribution equipment based on the electrolytic cell topology network; performs an impact assessment on the connection subnetwork between each identified electrolytic cell and each distribution equipment, and outputs a connection impact index; generates a start-stop scheduling scheme based on the connection impact index, and executes the start-stop scheduling of the multiple electrolytic cells according to the start-stop scheduling scheme. The present invention solves the technical problems of inaccurate start-stop scheduling of electrolytic cells and low resource allocation efficiency in the prior art, obtains the connection relationship between the distribution equipment and the electrolytic cell through data collection and topology modeling, combines the start-stop identification component and the connection impact assessment, and achieves the technical effect of accurate judgment of the operating status of the electrolytic cell and optimization of resource scheduling. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0009] Figure 1 A schematic diagram of a flow chart of an electrolytic cell intelligent scheduling method provided in an embodiment of the present application; Figure 2A schematic diagram of the structure of an intelligent scheduling device for an electrolytic cell provided in an embodiment of the present application.

[0010] Explanation of reference numerals: equipment acquisition module 11, electrolytic cell topology network construction module 12, electrolytic cell identification module 13, connection sub-network identification module 14, impact assessment module 15, start-stop scheduling module 16. DETAILED DESCRIPTION

[0011] The present application provides an intelligent scheduling method and device for electrolytic cells, aiming to solve the technical problems in the prior art of inaccurate start and stop scheduling of electrolytic cells and low resource allocation efficiency. The connection relationship between distributed equipment and electrolytic cells is obtained through data collection and topological modeling, and combined with start and stop identification components and connection impact assessment, the technical effect of accurate judgment of the operating status of the electrolytic cell and optimization of resource scheduling is achieved.

[0012] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0013] It should be noted that any variations of the terms "include" and "have" are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or inherent to these processes, methods, products or devices.

[0014] Embodiment 1, as Figure 1 As shown, the present application provides an electrolytic cell intelligent scheduling method, the method comprising: Step S100: Acquire distribution equipment connected to a plurality of electrolytic cells.

[0015] In an embodiment of the present application, all distributed devices connected to the electrolyzer are identified and acquired by scanning the device communication network. This method relies on industrial control protocols commonly used in modern electrolyzer systems, such as Modbus, etc., through which a communication relationship between the electrolyzer and its distributed devices is established. Specifically, a control system (such as PLC, SCADA system, etc.) is first used to initiate a network scanning request. The scanning tool detects all devices connected to the electrolyzer in the network in real time. The device information identified by the scanning tool, including the IP address, device type, and functional module of the device, determines the distributed devices connected to each electrolyzer. The distributed devices include power supply units, sensors, data acquisition units, control modules, etc.

[0016] Step S200: constructing an electrolytic cell topology network according to the connection relationship between the distribution equipment and the plurality of electrolytic cells.

[0017] In the embodiment of the present application, a network scanning tool such as Nmap or Modbus scanner is first used to automatically scan the network of the electrolytic cell system to obtain the connection information between the electrolytic cell and its associated distribution equipment. These tools identify the communication link between the electrolytic cell and the distribution equipment through identifiers such as the IP address or Modbus address of the equipment, and collect network information of the electrolytic cell and its connected equipment.

[0018] Then, the scanned connection information is mapped into the equipment management database using the equipment management system, such as SCADA or PLC control system. In this database, each electrolyzer is mapped one by one to the distribution equipment connected to it, ensuring that the relationship between the electrolyzer and the distribution equipment can be accurately recorded and stored.

[0019] Then, based on the collected device connection information, a graph theory algorithm, such as the Dijkstra algorithm, is used to construct an electrolyzer topology network, in which the electrolyzer and distribution equipment are regarded as nodes in the network, and the connections between the devices are regarded as edges.

[0020] Through the above process, the construction of the electrolytic cell topology network is completed.

[0021] Step S300: determining a set of identified electrolytic cells among the plurality of electrolytic cells according to the start / stop identification component, and identifying the electrolytic cells as electrolytic cells requiring stopping.

[0022] In an embodiment of the present application, firstly, by monitoring the working data of multiple electrolytic cells, multiple working status data sets are generated. The start-stop identification component extracts the key identification features for starting the cell and the key identification features for stopping the cell by performing feature recognition on these data sets. The value of the key identification feature for starting the cell is less than the first threshold, while the value of the key identification feature for stopping the cell is greater than or equal to the preset first threshold. Based on these features, the electrolytic cells that need to be stopped are judged to form an identified electrolytic cell set, in which the electrolytic cells are the electrolytic cells that need to be stopped. At the same time, the electrolytic cells that do not meet the stop requirement conditions are classified as a non-identified electrolytic cell set, indicating that they need to continue to be enabled.

[0023] Furthermore, in the method provided in the embodiment of the application, determining the set of identified electrolytic cells among the plurality of electrolytic cells according to the start-stop identification component further includes: Among them, the start-stop identification component includes a key identification feature for starting the slot and a key identification feature for stopping the slot, the value of the feature item in the key identification feature for starting the slot is less than a first threshold, and the value of the feature item in the key identification feature for stopping the slot is greater than or equal to the first threshold; the working data of the multiple electrolytic cells are monitored, and multiple working status data sets are output; according to the start-stop identification component, feature identification is performed on the multiple working status data sets to obtain a set of identified electrolytic cells and a set of non-identified electrolytic cells in the multiple electrolytic cells, wherein the identified electrolytic cells are electrolytic cells with a stop requirement, and the non-identified electrolytic cells are electrolytic cells with a start requirement.

[0024] In an embodiment of the present application, the start-stop identification component includes a key identification feature for starting the cell and a key identification feature for stopping the cell. The key identification feature for starting the cell is used to evaluate whether the electrolytic cell is suitable for continued operation. When the value of the feature item is less than the first threshold, it indicates that the operating state of the electrolytic cell is stable, the degree of abnormality is low, and it can continue to be enabled. The key identification feature for stopping the cell is used to evaluate whether the electrolytic cell needs to be stopped. When the value of the feature item is greater than or equal to the first threshold, it indicates that the degree of abnormality of the electrolytic cell is high, and there may be problems such as overload, temperature exceeding the limit, or reduced operating efficiency, and the cell needs to be stopped first. The first threshold is pre-set by technical experts, including a power utilization threshold, a temperature threshold, and a current fluctuation threshold. For example, the power utilization threshold is 85%, the temperature threshold is 80°C, and the current fluctuation threshold is 10%.

[0025] The operating parameters of multiple electrolyzers are monitored in real time through a distributed sensor network (such as temperature sensors, current sensors, power sensors, etc.) and an industrial control system (such as SCADA or PLC). The sensors collect key parameters such as power utilization, temperature, and current fluctuations, and output multiple working status data sets, each of which corresponds to an electrolyzer. For example, the power utilization of electrolyzer A is 42%, the temperature is 75°C, and the current fluctuation is 5%; the power utilization of electrolyzer B is 90%, the temperature is 85°C, and the current fluctuation is 12%.

[0026] Afterwards, the start-stop identification component extracts the key identification features for starting the cell and the key identification features for stopping the cell from the working status data set of each electrolytic cell through a feature extraction algorithm (such as rule-based feature screening or principal component analysis PCA), and compares them with the first threshold one by one. When the values ​​of all feature items are less than the first threshold, it is determined that the operating state of the electrolytic cell is normal and the degree of abnormality is low, and it is classified into the set of non-identified electrolytic cells (electrolytic cells with a start-up requirement). When the value of any feature item is greater than or equal to the first threshold, it is determined that the operating state of the electrolytic cell is abnormal and the degree of abnormality is high, and it is classified into the set of identified electrolytic cells (electrolytic cells with a stop-slot requirement).

[0027] For example, for electrolytic cell A, its power utilization rate = 42% (less than the first threshold 85%), temperature = 75°C (less than the first threshold 80°C), current fluctuation = 5% (less than the first threshold 10%), all characteristic values ​​are lower than the first threshold, and it is determined to be an electrolytic cell that needs to start the cell, and is included in the non-identified electrolytic cell set. For electrolytic cell B, its power utilization rate = 90% (greater than or equal to the first threshold 85%), temperature = 85°C (greater than or equal to the first threshold 80°C), current fluctuation = 12% (greater than or equal to the first threshold 10%), there is a characteristic value greater than the first threshold, it is determined to be an electrolytic cell that needs to stop the cell, and is included in the identified electrolytic cell set.

[0028] Step S400: Based on the electrolytic cell topology network, identifying the connection sub-network between each identified electrolytic cell in the identified electrolytic cell set and each distribution device.

[0029] In an embodiment of the present application, the equipment operating status of each distributed device is monitored based on the electrolytic cell topology network to obtain its operating data set; then, the connection relationship data between each identified electrolytic cell in the identified electrolytic cell set and each distributed device is extracted, and the edge weight between the identified electrolytic cell and the distributed device is defined based on these connection relationship data. The edge weight is used to quantify the characteristics of the connection, such as the load level or resource allocation. Finally, with each identified electrolytic cell as the central node and the distributed device as the edge node, a connection subnetwork is generated in combination with the edge weight to complete the identification of the connection subnetwork between each identified electrolytic cell and the distributed device in the identified electrolytic cell set.

[0030] Furthermore, in the method provided in the embodiment of the application, based on the electrolytic cell topology network, identifying the connection sub-network between each identified electrolytic cell in the identified electrolytic cell set and each distribution device, further includes: Based on the electrolytic cell topology network, monitoring is performed to obtain equipment operation data sets of each distributed device; connection relationship data between each identified electrolytic cell in the identified electrolytic cell set and each distributed device is obtained; based on the connection relationship data, edge weights between each identified electrolytic cell and each distributed device are defined; with each identified electrolytic cell as a network center node and each connected distributed device as an edge node, a connection subnetwork for each identified electrolytic cell is generated based on the edge weights.

[0031] In the embodiment of the present application, when monitoring is performed based on the electrolytic cell topology network, the distributed equipment is first monitored in real time through a distributed sensor network and data acquisition equipment, such as SCADA, to obtain the equipment operation data set of each distributed equipment. These data reflect the current working status of the distributed equipment, including important parameters such as output power, voltage, current, and load rate.

[0032] Next, the topology network parsing tool is used to extract the direct connection relationship data between each identified electrolyzer and the distribution equipment from the identified electrolyzer set, and to clearly identify the physical connection and resource allocation between the identified electrolyzer and the distribution equipment. These connection relationships include connection paths and interface attributes. For example, an identified electrolyzer is connected to two distribution equipments through a power supply interface, and the path load rates are 25% and 40% respectively.

[0033] Then, based on the extracted connection relationship data, the edge weights between each identified electrolyzer and each distributed device are further defined. The edge weights are calculated by multi-factor weighting to comprehensively reflect the degree of influence of the identified electrolyzer on the distributed device. Specifically, first, the load rate of the distributed device is calculated, and the formula is the ratio of the current load to the total capacity. For example, the load rate of a power supply device is 5 / 20=0.25; secondly, the resource occupancy rate of the identified electrolyzer is calculated, and the formula is the ratio of the amount of resources used by the identified electrolyzer to the total resource capacity of the distributed device. For example, the resource occupancy rate of a certain identified electrolyzer on the power supply device is 3 / 20=0.15. Substitute the above factors into the edge weight formula, where the load rate weight coefficient and the resource occupancy rate weight coefficient are pre-set by technical experts. Assuming that the load rate weight coefficient is 0.6 and the resource occupancy rate weight coefficient is 0.4, the edge weight is 0.6×0.25+0.4×0.15=0.21.

[0034] Finally, each identified electrolyzer is taken as the network center node, all directly connected distribution devices are taken as edge nodes, and the calculated edge weights are combined to generate the connected subnetwork of the identified electrolyzer. The connected subnetwork is represented in the form of a weighted graph, including a node set and an edge set.

[0035] Step S500: perform an impact assessment on the connection sub-networks between each identified electrolytic cell and each distribution device, and output a connection impact index.

[0036] In the embodiment of the present application, an impact assessment is performed on the connection sub-network of each identified electrolytic cell, and the assessment content includes the impact on the supply capacity of the distribution equipment caused by the stoppage of the cell, the impact on the equipment load, and the impact on the operation stability. By analyzing these influencing factors and combining the preset weight calculation formula, the evaluation results are weighted and calculated, and finally the connection impact index is generated and output.

[0037] Furthermore, in the method provided in the embodiment of the application, the connection sub-network of each marked electrolytic cell and each distribution device is impact evaluated, and the connection impact index is output, which also includes: An impact assessment is performed on the connected sub-network of each identified electrolytic cell, including the impact on the supply capacity, equipment load and operational stability of the distributed equipment due to cell shutdown; a weight layer calculation is performed based on the supply capacity impact, equipment load impact and operational stability impact, and a connection impact index is output.

[0038] In the embodiment of the present application, the impact assessment is performed on the connected sub-network of each identified electrolytic cell. First, it is necessary to clarify the degree of change in the supply capacity, equipment load and operation stability of the distributed equipment caused by the shutdown of the identified electrolytic cell. To this end, the operating data of the distributed equipment, including output power, load rate and operation stability parameters, is obtained through a distributed sensor network and a data acquisition system.

[0039] When evaluating the impact on supply capacity, that is, the degree of interference in the resource allocation capacity of the distribution equipment after the stop of the marker electrolyzer, the impact on supply capacity is calculated by extracting the total resource capacity of the distribution equipment and the actual resource occupancy of the marker electrolyzer. The calculation formula is: .

[0040] The next step is to evaluate the equipment load impact, that is, whether the tank stop will cause a significant change in the load rate of the distribution equipment. and the adjusted load factor , calculate the load influence, the calculation formula is .

[0041] Then, the impact on operation stability is evaluated and the analysis is conducted to identify whether the shutdown of the electrolytic cell will cause fluctuations in the operating parameters of the distributed equipment. and the total power capacity of the distribution equipment , calculate the operational stability impact, .

[0042] Finally, according to the impact of supply capacity, equipment load and operation stability, the connection impact index is comprehensively generated through the weight layer calculation formula. The calculation formula is: .in, , and Pre-set by technical experts.

[0043] Through the above calculations, the impact assessment of the connection sub-network between each identified electrolytic cell and each distribution device is completed, and the connection impact index is output.

[0044] Step S600: Based on the connection impact index, a start-stop scheduling plan is generated, and the start-stop scheduling of the plurality of electrolytic cells is performed according to the start-stop scheduling plan.

[0045] In the embodiment of the present application, based on the connection impact index, firstly, k identified electrolytic cells whose connection impact index is greater than a preset threshold value are screened in the identified electrolytic cell set. Then, the non-identified electrolytic cell set is analyzed, and k non-identified electrolytic cells that meet the start-up conditions are selected, and the identifications are exchanged with the above-mentioned identified electrolytic cells to generate an updated identified electrolytic cell set and a non-identified electrolytic cell set. Finally, a start-stop scheduling plan is generated according to the updated set, and the start-stop operations of multiple electrolytic cells are executed according to the plan.

[0046] Furthermore, in the method provided in the embodiment of the application, generating a start-stop scheduling scheme based on the connection impact indicator further includes: According to the connection impact index, k identified electrolytic cells whose connection impact index is greater than a preset connection impact index are obtained from the identified electrolytic cell set; the non-identified electrolytic cell set is analyzed and k non-identified electrolytic cells are output; the k identified electrolytic cells and the k non-identified electrolytic cells are exchanged for identification, and an updated identified electrolytic cell set and non-identified electrolytic cell set are output; a start-stop scheduling plan is generated according to the updated identified electrolytic cell set and non-identified electrolytic cell set.

[0047] In an embodiment of the present application, the connection influence index obtained by the above calculation is first compared with the preset connection influence index to obtain k identified electrolytic cells in the identified electrolytic cell set whose values ​​are greater than the preset connection influence index.

[0048] Next, the analysis is performed in the set of non-identified electrolytic cells. Specifically, by obtaining the second threshold (less than the first threshold), p non-identified electrolytic cells that meet the conditions are screened out from the set of non-identified electrolytic cells, and then the p electrolytic cells initially screened out are further analyzed, and finally k non-identified electrolytic cells are output, where p is greater than k.

[0049] Then, the selected k identified electrolytic cells are exchanged with the k non-identified electrolytic cells, that is, the stopped state of the identified electrolytic cells is transferred to the non-identified electrolytic cells, and the enabled state of the non-identified electrolytic cells is transferred to the identified electrolytic cells. This operation is completed by updating the identification state, and the updated identified electrolytic cell set and non-identified electrolytic cell set are output.

[0050] Finally, a start-stop scheduling scheme is generated based on the updated set of identified electrolytic cells and the set of non-identified electrolytic cells. Specifically, a stop instruction is issued to the electrolytic cells in the updated set of identified electrolytic cells, and a start instruction is issued to the electrolytic cells in the updated set of non-identified electrolytic cells.

[0051] Furthermore, in the method provided in the embodiment of the application, the analysis is performed in the non-identified electrolytic cell set, including: Obtain a second threshold value, which is smaller than the first threshold value; obtain p non-identification electrolytic cells in the non-identification electrolytic cell set based on the second threshold value; analyze the p non-identification electrolytic cells and output k non-identification electrolytic cells.

[0052] In the embodiment of the present application, a second threshold is first obtained, wherein the second threshold is less than the first threshold. Like the first threshold, the second threshold is also pre-set by technical experts, specifically including a power utilization threshold, a temperature threshold, and a current fluctuation threshold. For example, when the first threshold is set to a power utilization of 85%, a temperature of 80°C, and a current fluctuation of 10%, the second threshold is set to a power utilization of 50%, a temperature of 60°C, and a current fluctuation of 5%.

[0053] Next, according to the second threshold, p non-identification electrolyzers that meet the conditions are screened out from the set of non-identification electrolyzers. Specifically, the operating data of the non-identification electrolyzers are first monitored in real time by distributed sensors, including key parameters such as current power utilization, temperature, and current fluctuations. Subsequently, these parameters are compared one by one with the second threshold. For example, the power utilization rate of a non-identification electrolyzer is 40%, the temperature is 55°C, and the current fluctuation is 4%, all of which are less than the second threshold, so they meet the screening conditions. Through this process, p non-identification electrolyzers that meet the conditions are obtained.

[0054] Finally, all p non-marked electrolyzers that meet the conditions are sorted from low to high according to power utilization, and k electrolyzers with the smallest load are preferentially selected and output as k non-marked electrolyzers.

[0055] Furthermore, in the method provided in the embodiment of the application, the analysis is performed in the non-identified electrolytic cell set, and further includes: Obtain a connection subnetwork of each non-identification electrolytic cell in the non-identification electrolytic cell set; perform an impact assessment on the connection subnetwork of each non-identification electrolytic cell and each distribution device, output a connection impact index, and select p non-identification electrolytic cells whose connection impact index is less than the preset connection impact index; output k non-identification electrolytic cells based on the p non-identification electrolytic cells.

[0056] In the embodiment of the present application, the connection sub-network identification process of the identified electrolytic cell is the same as that of the aforementioned method. First, based on the electrolytic cell topology network, the connection relationship data between each non-identified electrolytic cell and the distributed device is extracted by real-time monitoring of the operating data of the distributed device, including resource occupancy rate, path load, etc. The edge weight between each non-identified electrolytic cell and each distributed device is defined according to the connection relationship. The non-identified electrolytic cell is taken as the network center node, and the connected distributed device is taken as the edge node. The connection sub-network of each non-identified electrolytic cell is generated in combination with the edge weight.

[0057] Next, the same method as the aforementioned process of impact assessment on the connection sub-network of each identified electrolytic cell and each distribution device and outputting the connection impact index is used to assess the impact of the connection sub-network of each non-identified electrolytic cell and each distribution device, and output the connection impact index.

[0058] Then, the connection influence index is compared with the preset connection influence index, and the non-identification electrolytic cells whose connection influence index is less than the preset connection influence index in the non-identification electrolytic cell set are selected. Through this process, p non-identification electrolytic cells are obtained.

[0059] Finally, the p non-identification electrolytic cells are arranged from small to large according to the connection influence index, and the first k non-identification electrolytic cells are selected. Through this process, k non-identification electrolytic cells are obtained, where k is less than p and k=0.2p. If k is not an integer, it is rounded up.

[0060] In the embodiments of the present application, in summary, the embodiments of the present application have at least the following technical effects: The present application obtains distribution equipment connected to multiple electrolytic cells; constructs an electrolytic cell topology network based on the connection relationship between the distribution equipment and the multiple electrolytic cells; determines a set of identified electrolytic cells in the multiple electrolytic cells based on the start-stop identification component, and identifies the electrolytic cell as an electrolytic cell with a stop requirement; identifies the connection subnetwork between each identified electrolytic cell in the set of identified electrolytic cells and each distribution equipment based on the electrolytic cell topology network; performs an impact assessment on the connection subnetwork between each identified electrolytic cell and each distribution equipment, and outputs a connection impact index; generates a start-stop scheduling scheme based on the connection impact index, and executes the start-stop scheduling of the multiple electrolytic cells according to the start-stop scheduling scheme. The present invention solves the technical problems of inaccurate start-stop scheduling of electrolytic cells and low resource allocation efficiency in the prior art, obtains the connection relationship between the distribution equipment and the electrolytic cell through data collection and topology modeling, combines the start-stop identification component and the connection impact assessment, and achieves the technical effect of accurate judgment of the operating status of the electrolytic cell and optimization of resource scheduling.

[0061] Embodiment 2, based on the same inventive concept as the electrolytic cell intelligent scheduling method in the above embodiment, Figure 2 As shown, the present application provides an electrolytic cell intelligent scheduling device, and the device and method embodiments in the present application embodiments are based on the same inventive concept. The device includes: An equipment acquisition module 11, wherein the equipment acquisition module 11 acquires distributed equipment connected to a plurality of electrolytic cells; an electrolytic cell topology network construction module 12, wherein the electrolytic cell topology network construction module 12 constructs an electrolytic cell topology network according to the connection relationship between the distributed equipment and the plurality of electrolytic cells; an electrolytic cell identification module 13, wherein the electrolytic cell identification module 13 determines a set of identified electrolytic cells in the plurality of electrolytic cells according to a start-stop identification component, and identifies an electrolytic cell as an electrolytic cell with a stop requirement; a connection subnetwork identification module 14, wherein the connection subnetwork identification module 14 identifies a connection subnetwork between each identified electrolytic cell in the set of identified electrolytic cells and each distributed equipment based on the electrolytic cell topology network; an impact assessment module 15, wherein the impact assessment module 15 performs an impact assessment on a connection subnetwork between each identified electrolytic cell and each distributed equipment, and outputs a connection impact index; a start-stop scheduling module 16, wherein the start-stop scheduling module 16 generates a start-stop scheduling plan based on the connection impact index, and executes the start-stop scheduling of the plurality of electrolytic cells according to the start-stop scheduling plan.

[0062] Furthermore, the device is also used to achieve the following functions: Among them, the start-stop identification component includes a key identification feature for starting the slot and a key identification feature for stopping the slot, the value of the feature item in the key identification feature for starting the slot is less than a first threshold, and the value of the feature item in the key identification feature for stopping the slot is greater than or equal to the first threshold; the working data of the multiple electrolytic cells are monitored, and multiple working status data sets are output; according to the start-stop identification component, feature identification is performed on the multiple working status data sets to obtain a set of identified electrolytic cells and a set of non-identified electrolytic cells in the multiple electrolytic cells, wherein the identified electrolytic cells are electrolytic cells with a stop requirement, and the non-identified electrolytic cells are electrolytic cells with a start requirement.

[0063] Furthermore, the device is also used to achieve the following functions: According to the connection impact index, k identified electrolytic cells whose connection impact index is greater than a preset connection impact index are obtained from the identified electrolytic cell set; the non-identified electrolytic cell set is analyzed and k non-identified electrolytic cells are output; the k identified electrolytic cells and the k non-identified electrolytic cells are exchanged for identification, and an updated identified electrolytic cell set and non-identified electrolytic cell set are output; a start-stop scheduling plan is generated according to the updated identified electrolytic cell set and non-identified electrolytic cell set.

[0064] Furthermore, the device is also used to achieve the following functions: Obtain a second threshold value, which is smaller than the first threshold value; obtain p non-identification electrolytic cells in the non-identification electrolytic cell set based on the second threshold value; analyze the p non-identification electrolytic cells and output k non-identification electrolytic cells.

[0065] Furthermore, the device is also used to achieve the following functions: Obtain a connection subnetwork of each non-identification electrolytic cell in the non-identification electrolytic cell set; perform an impact assessment on the connection subnetwork of each non-identification electrolytic cell and each distribution device, output a connection impact index, and select p non-identification electrolytic cells whose connection impact index is less than the preset connection impact index; output k non-identification electrolytic cells based on the p non-identification electrolytic cells.

[0066] Furthermore, the device is also used to achieve the following functions: Based on the electrolytic cell topology network, monitoring is performed to obtain equipment operation data sets of each distributed device; connection relationship data between each identified electrolytic cell in the identified electrolytic cell set and each distributed device is obtained; based on the connection relationship data, edge weights between each identified electrolytic cell and each distributed device are defined; with each identified electrolytic cell as a network center node and each connected distributed device as an edge node, a connection subnetwork for each identified electrolytic cell is generated based on the edge weights.

[0067] Furthermore, the device is also used to achieve the following functions: An impact assessment is performed on the connected sub-network of each identified electrolytic cell, including the impact on the supply capacity, equipment load and operational stability of the distributed equipment due to cell shutdown; a weight layer calculation is performed based on the supply capacity impact, equipment load impact and operational stability impact, and a connection impact index is output.

[0068] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0069] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0070] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. An intelligent scheduling method for electrolytic cells, characterized in that: The method comprises: obtaining a distribution device connected to a plurality of electrolytic cells; Constructing an electrolytic cell topology network according to the connection relationship between the distribution device and the plurality of electrolytic cells; Determine, according to the start-stop identification component, a set of identified electrolytic cells among the plurality of electrolytic cells, and identify the electrolytic cells as electrolytic cells requiring stopping; Based on the electrolytic cell topology network, identifying a connection subnetwork between each identified electrolytic cell in the identified electrolytic cell set and each distribution device; Conduct impact assessment on the connection sub-networks of each identified electrolytic cell and each distribution device, and output connection impact indicators; Based on the connection impact index, a start-stop scheduling plan is generated, and the start-stop scheduling of the multiple electrolytic cells is performed according to the start-stop scheduling plan.

2. The method according to claim 1, characterized in that The step of determining a set of identified electrolytic cells among the plurality of electrolytic cells according to the start / stop identification component, include: The start-stop identification component includes a slot start key identification feature and a slot stop key identification feature, the value of a feature item in the slot start key identification feature is less than a first threshold, and the value of a feature item in the slot stop key identification feature is greater than or equal to the first threshold; Monitoring the working data of the plurality of electrolytic cells and outputting a plurality of working status data sets; According to the start-stop identification component, feature recognition is performed on the multiple working status data sets to obtain a set of identified electrolytic cells and a set of non-identified electrolytic cells in the multiple electrolytic cells, wherein the identified electrolytic cells are electrolytic cells with a stop requirement, and the non-identified electrolytic cells are electrolytic cells with a start requirement.

3. The method according to claim 2, characterized in that The generating a start-stop scheduling scheme based on the connection impact indicator includes: According to the connection impact index, obtaining k identified electrolytic cells in the identified electrolytic cell set whose connection impact index is greater than a preset connection impact index; Analyze the non-identified electrolytic cells set and output k non-identified electrolytic cells; Exchange the identifications of the k identified electrolytic cells and the k non-identified electrolytic cells, and output an updated set of identified electrolytic cells and a set of non-identified electrolytic cells; A start-stop scheduling plan is generated based on the updated set of identified electrolytic cells and the set of non-identified electrolytic cells.

4. The method according to claim 3, characterized in that The analysis is performed in the non-identified electrolytic cell set, the method comprising: Obtaining a second threshold value, where the second threshold value is less than the first threshold value; Obtaining p non-identified electrolytic cells based on the second threshold value from the non-identified electrolytic cell set; Analysis is performed on the p non-identified electrolytic cells, and k non-identified electrolytic cells are output.

5. The method according to claim 3, characterized in that The analysis is performed in the non-identified electrolytic cell set, and the method further comprises: Obtaining a connection subnetwork of each non-identified electrolytic cell in the non-identified electrolytic cell set; Performing an impact assessment on the connection sub-networks of each non-identified electrolytic cell and each distributed device, outputting a connection impact index, and selecting p non-identified electrolytic cells whose connection impact index is less than the preset connection impact index; According to the p non-identification electrolytic cells, k non-identification electrolytic cells are output.

6. The method according to claim 1, characterized in that The method of identifying the connection subnetworks between each identified electrolytic cell and each distribution device in the identified electrolytic cell set based on the electrolytic cell topology network includes: Monitoring is performed based on the electrolytic cell topology network to obtain equipment operation data sets of each distributed equipment; Acquire connection relationship data between each identified electrolytic cell in the identified electrolytic cell set and each distribution device; According to the connection relationship data, defining the edge weight between each identified electrolytic cell and each distribution device; Taking each identified electrolytic cell as a network center node and each connected distribution device as an edge node, a connection subnetwork for each identified electrolytic cell is generated based on the edge weight.

7. The method according to claim 6, characterized in that The impact assessment is performed on the connection sub-networks of each identified electrolytic cell and each distribution device, and the connection impact index is output, including: Conduct an impact assessment on the connected sub-network of each identified electrolyzer, including the impact on the supply capacity of the distribution equipment due to the shutdown, the impact on equipment load, and the impact on operational stability; A weight layer calculation is performed based on the supply capacity impact, equipment load impact, and operation stability impact, and a connection impact index is output.

8. An intelligent scheduling device for electrolytic cells, characterized in that: The device comprises: An equipment acquisition module, wherein the equipment acquisition module acquires distributed equipment connected to a plurality of electrolytic cells; An electrolytic cell topology network construction module, wherein the electrolytic cell topology network construction module constructs an electrolytic cell topology network according to a connection relationship between the distribution device and the plurality of electrolytic cells; An electrolytic cell identification module, wherein the electrolytic cell identification module determines a set of identified electrolytic cells among the plurality of electrolytic cells according to the start-stop identification component, and identifies an electrolytic cell as an electrolytic cell requiring a stop; A connection sub-network identification module, wherein the connection sub-network identification module identifies the connection sub-networks between each identified electrolytic cell and each distribution device in the identified electrolytic cell set based on the electrolytic cell topology network; An impact assessment module, which performs an impact assessment on a connection sub-network between each identified electrolytic cell and each distribution device, and outputs a connection impact index; A start-stop scheduling module generates a start-stop scheduling plan based on the connection impact index, and executes the start-stop scheduling of the multiple electrolytic cells according to the start-stop scheduling plan.

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