Water resource treatment strategy determination method and device, computer equipment and storage medium

Abstract

The invention relates to a water resource treatment strategy determination method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring target water quality index data of an off-station water source of a power system in a target time period and water demand data of water equipment in the power system; wherein the target water quality index data comprises actual index values of at least two water quality indexes, and the water demand data comprises expected index values of at least two water quality indexes; determining a target water quality state of the water source outside the station according to the target water quality index data; and according to the water quality state of the water source outside the station and the water consumption demand data of the water consumption equipment in the power system, determining a target processing strategy of the water resource in the water source outside the station. By adopting the method, a flexible water resource treatment strategy can be formulated, so that the water resource is effectively and specifically treated.

Description

Technical Field

[0001] The present application relates to the technical field of power equipment operation and maintenance, and in particular to a method, device, computer equipment and storage medium for determining a water resource treatment strategy. Background Art

[0002] High-voltage transmission sites, including converter stations and substations, use water for domestic use, industrial use, and firefighting. Industrial water primarily provides supplemental water to external cooling water systems for power equipment like transformers and converter valves, replenishing cooling tower losses from evaporation, wind, and sewage discharge during operation. External cooling water is used to circulate cooling water within power equipment, absorbing heat generated by the equipment during operation to maintain its normal operating temperature. Power equipment like transformers and converter valves are core components of high-voltage power transmission. To ensure their reliable operation, the reliability of the external cooling water supply system is essential.

[0003] At present, the water resources of the power system are generally treated according to a fixed standardized water treatment plan, which requires the treatment plan to be designed according to the worst standards in most cases. However, the water treatment plan determined in this way is inflexible and cannot effectively and specifically treat water resources, resulting in substandard sewage discharge and, in turn, failure of the water-using equipment of the power system. Summary of the Invention

[0004] Based on this, it is necessary to provide a water resource treatment strategy determination method, device, computer equipment and storage medium to address the above technical problems, which can formulate flexible water resource treatment strategies and thus effectively and specifically treat water resources.

[0005] In a first aspect, the present application provides a method for determining a water resource treatment strategy, comprising:

[0006] Obtaining target water quality index data of an off-site water source of the power system within a target time period, and water demand data of water-using equipment within the power system; wherein the target water quality index data includes actual index values of at least two water quality indexes, and the water demand data includes expected index values of at least two water quality indexes;

[0007] Determining the target water quality state of the off-site water source according to the target water quality index data;

[0008] According to the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system, a target treatment strategy for the water resources in the off-site water source is determined.

[0009] In one embodiment, obtaining target water quality index data of an off-site water source of the power system within a target period includes:

[0010] Obtaining original water quality index data of the off-site water source within a target period of time by installing a water quality monitoring device at an off-site water source of the power system;

[0011] For each water quality index, determining the mean and standard deviation of the water quality index according to the index values of the water quality index in the original water quality index data;

[0012] The original water quality index data are preprocessed according to the mean and standard deviation of each water quality index and the index values of each water quality index in the original water quality index data to obtain target water quality index data of the off-site water source of the power system.

[0013] In one embodiment, the raw water quality index data is preprocessed based on the mean and standard deviation of each water quality index and the index values of each water quality index in the raw water quality index data to obtain target water quality index data of the off-site water source of the power system, including:

[0014] For each water quality index, the product of the mean and the standard deviation of the water quality index is used as an intermediate parameter, and the difference between each index value of the water quality index in the original water quality index data and the intermediate parameter is used as the actual index value of the water quality index;

[0015] According to the actual index value of each water quality index, the target water quality index data of the off-site water source of the power system is determined.

[0016] In one embodiment, determining the target water quality state of the off-site water source according to the target water quality index data includes:

[0017] Based on the target water quality index data, an initial water quality status assessment model is constructed based on the autoassociative memory network; wherein the initial water quality status assessment model includes at least two nodes and weights between any two nodes, and the nodes represent the index value of the water quality index;

[0018] Determining the network parameters and weight matrix of the initial water quality status assessment model based on the target water quality index data; wherein the weight matrix includes the weights between any two nodes;

[0019] configuring the initial water quality state assessment model according to the network parameters to obtain a target water quality state assessment model;

[0020] The weight matrix and the target water quality index data are input into the target water quality status assessment model to obtain the target water quality status of the off-site water source.

[0021] In one embodiment, determining a target treatment strategy for water resources in the off-site water source based on the water quality status of the off-site water source and water demand data of water-using equipment in the power system includes:

[0022] Inputting the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system into the strategy prediction model, and obtaining the target treatment strategy for the water resources in the off-site water source output by the strategy prediction model;

[0023] Among them, the strategy prediction model is obtained through sample data training; the sample data includes the sample water quality status of the off-site water source in the historical period, the sample processing strategy of the water resources, and the sample index value of the water quality index of the water resources of the off-site water source after being processed by the sample processing strategy.

[0024] In one embodiment, after determining a target treatment strategy for water resources in the off-site water source based on the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system, the method further includes:

[0025] Determining predicted water quality index data of the water resources of the off-site water source after being processed by the target processing strategy based on the target water quality index data and the target processing strategy of the power system for the water resources in the off-site water source;

[0026] Determining a water quality error of the target treatment strategy based on the predicted water quality index data and water demand of water-using equipment in the power system;

[0027] The target treatment strategy is optimized based on the water quality error.

[0028] In one embodiment, the at least two water quality indicators include at least two of the total dissolved solids (TDS) in water, solution pH, oxidation-reduction potential (ORP), and water level.

[0029] In a second aspect, the present application further provides a water resource treatment strategy determination device, comprising:

[0030] a data acquisition module, configured to acquire target water quality index data of an off-site water source of the power system within a target time period, and water demand data of water-using equipment within the power system; wherein the target water quality index data includes actual index values of at least two water quality indexes, and the water demand data includes expected index values of at least two water quality indexes;

[0031] A state determination module, configured to determine the target water quality state of the off-site water source based on the target water quality index data;

[0032] The strategy determination unit is used to determine a target processing strategy for the water resources in the off-site water source according to the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system.

[0033] In a third aspect, the present application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0034] Obtaining target water quality index data of an off-site water source of the power system within a target time period, and water demand data of water-using equipment within the power system; wherein the target water quality index data includes actual index values of at least two water quality indexes, and the water demand data includes expected index values of at least two water quality indexes;

[0035] Determining the target water quality state of the off-site water source according to the target water quality index data;

[0036] According to the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system, a target treatment strategy for the water resources in the off-site water source is determined.

[0037] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0038] Obtaining target water quality index data of an off-site water source of the power system within a target time period, and water demand data of water-using equipment within the power system; wherein the target water quality index data includes actual index values of at least two water quality indexes, and the water demand data includes expected index values of at least two water quality indexes;

[0039] Determining the target water quality state of the off-site water source according to the target water quality index data;

[0040] According to the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system, a target treatment strategy for the water resources in the off-site water source is determined.

[0041] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which, when executed by a processor, implements the following steps:

[0042] Obtaining target water quality index data of an off-site water source of the power system within a target time period, and water demand data of water-using equipment within the power system; wherein the target water quality index data includes actual index values of at least two water quality indexes, and the water demand data includes expected index values of at least two water quality indexes;

[0043] Determining the target water quality state of the off-site water source according to the target water quality index data;

[0044] According to the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system, a target treatment strategy for the water resources in the off-site water source is determined.

[0045] The above-mentioned water resource treatment strategy determination method, device, computer equipment and storage medium, after obtaining the target water quality index data of the off-site water source of the power system within the target time period, and the water demand data of the water-using equipment in the power system, since the target water quality index data includes the actual index values of at least two water quality indicators, and the water demand data includes the expected index values of at least two water quality indicators, therefore, according to the target water quality index data, the target water quality status of the off-site water source can be accurately determined; further, according to the water quality status of the off-site water source, and the water demand data of the water-using equipment in the power system, that is, comprehensively considering the water quality of the water resources and the needs of the water-using equipment, it is ensured that the determined target treatment strategy for the water resources in the off-site water source is more in line with the actual needs of the water-using equipment, and a flexible water resource treatment strategy can be formulated. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0047] Figure 1 A schematic flow chart of a method for determining a water resource treatment strategy in one embodiment;

[0048] Figure 2 A schematic diagram of a process for determining target water quality index data in one embodiment;

[0049] Figure 3 is a structural diagram of a water quality monitoring device in one embodiment;

[0050] Figure 4 A schematic diagram of a process for determining a target water quality state of an off-site water source in one embodiment;

[0051] Figure 5 A schematic diagram of a process for optimizing a target processing strategy in one embodiment;

[0052] Figure 6 A schematic flow chart of a method for determining a water resource treatment strategy in another embodiment;

[0053] Figure 7is a structural block diagram of a device for determining a water resource treatment strategy in one embodiment;

[0054] Figure 8 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0056] The water resource treatment strategy determination method provided in the embodiments of the present application can be applied in an application environment for water quality assessment and treatment of water resources required by water-consuming equipment in a power system. The water resource treatment strategy determination method provided in the embodiments of the present application can be executed by a computer device, which can be a server or a terminal with powerful computing capabilities.

[0057] In one embodiment, Figure 1 As shown, a method for determining a water resource treatment strategy is provided. The method is described by taking the application of the method to a server as an example. The method specifically includes the following steps:

[0058] S101, obtaining target water quality index data of an off-site water source of the power system within a target period of time, and water demand data of water-using equipment within the power system.

[0059] It should be noted that high-voltage transmission stations in the power system, including converter stations and substations, use water for domestic, industrial, and firefighting purposes. Industrial water primarily provides make-up water for external cooling water systems of power equipment like transformers and converter valves to compensate for evaporation, wind, and sewage losses during cooling tower operation. External cooling water is used to circulate cooling water within power equipment, absorbing heat generated by the operating converters to maintain their normal operating temperatures. Power equipment like transformers and converter valves are core components of high-voltage power transmission. To ensure their reliable operation, a reliable external cooling water supply system is essential. Therefore, a reliable station water source is crucial for daily production, daily life, and the safe and stable operation of high-voltage power transmission stations. Power stations typically require two external water sources, each derived from a different source, including water plants and natural sources like reservoirs. These external water sources require a water storage tank located several kilometers from the power station.

[0060] Among them, the target period is a preset period, which can be a historical period or a current period. The target water quality index data includes the actual index values of at least two water quality indicators, and the water demand data includes the expected index values of at least two water quality indicators. Water quality indicators are indicators that can evaluate the water quality of water resources. In the embodiment of the present application, the at least two water quality indicators include at least two of the total dissolved solids (TDS) in water, the potential of hydrogen (PH) of the solution, the oxidation-reduction potential (ORP) and the water level. The water demand data characterizes information such as the demand for water resources and water quality requirements of water-using equipment.

[0061] Among them, TDS refers to the solid residue obtained after water is filtered and dried at a certain temperature. It mainly includes non-volatile soluble salts, organic matter and insoluble particles that can pass through the filter. It is also called filterable solids or filterable residue. my country stipulates that the standard for total soluble solids in drinking water is ≤1000mg / L.

[0062] Optionally, a water quality monitoring system installed at an off-site water source in the power system can be used to obtain target water quality index data within a target period. At the same time, water demand data of water-using equipment within the power system can be obtained on the power system's Internet of Things (IOT) platform.

[0063] S102: Determine the target water quality status of the off-site water source based on the target water quality index data.

[0064] Among them, the target water quality status represents the water quality of the water resources in the water source outside the station.

[0065] Optionally, a water quality assessment model can be constructed in advance, and the target water quality index data can be input into the water quality assessment model so that the water quality assessment model can calculate and analyze the target water quality index data according to the model parameters, and the output of the water quality assessment model can be used as the target water quality status of the off-site water source.

[0066] S103, determining a target treatment strategy for water resources in the off-site water source based on the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system.

[0067] Among them, the target treatment strategy represents the treatment standard for water resources in the off-site water source. For example, the target treatment strategy includes but is not limited to the amount of reagent added, stirring time, etc.

[0068] Optionally, based on experience, a correspondence can be established between the water quality status of off-site water sources, the water demand data of water-using equipment and the target treatment strategy for water resources; further, based on this correspondence, the water quality status of off-site water sources and the water demand data of water-using equipment in the power system are determined, and the corresponding target treatment strategy is then used as the target treatment strategy for water resources in the off-site water sources.

[0069] Optionally, the water quality status of off-site water sources and water demand data for water-using equipment within the power system can be input into a strategy prediction model to output a target treatment strategy for the off-site water resources. The strategy prediction model is trained using sample data; the sample data includes sample water quality status of off-site water sources within a historical period, sample treatment strategies for water resources, and sample indicator values of water quality indicators of off-site water resources after being processed using the sample treatment strategies. The strategy prediction model can be constructed using a long short-term memory (LSTM) network.

[0070] Specifically, the sample water quality status of off-site water sources, the sample processing strategy of water resources, and the sample index values of water quality indicators of off-site water resources after being processed by the sample processing strategy within the historical period can be obtained as sample data, and then the sample data can be used to train the strategy prediction model to obtain the nonlinear relationship between multiple parameters such as sample water quality status, sample processing strategy and sample index value, that is, the trained strategy prediction model.

[0071] Furthermore, the water quality status of the water source outside the station and the water demand data of the water-using equipment in the power system are input into the strategy prediction model, so that the strategy prediction model can calculate and analyze the water quality status and water demand data according to the model parameters to obtain the target processing strategy for the water resources in the water source outside the station output by the strategy prediction model.

[0072] Furthermore, in an embodiment of this application, the water resource treatment strategy determination method provided herein can be integrated into an IoT platform to achieve fully automated data collection. Data is then uploaded to the IoT platform of the power system organization via the Message Queuing Telemetry Transport (MQTT) protocol. The power system organization's interface supports RESTful API calls. Operations and maintenance personnel can use the Zhikan system to monitor water quality at all times.

[0073] In the above-mentioned method for determining the water resource treatment strategy, after obtaining the target water quality index data of the off-site water source of the power system within the target time period and the water demand data of the water-using equipment in the power system, since the target water quality index data includes the actual index values of at least two water quality indexes, and the water demand data includes the expected index values of at least two water quality indexes, therefore, according to the target water quality index data, the target water quality status of the off-site water source can be accurately determined; further, according to the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system, that is, comprehensively considering the water quality of the water resources and the needs of the water-using equipment, it is ensured that the determined target treatment strategy for the water resources in the off-site water source is more in line with the actual needs of the water-using equipment, and a flexible water resource treatment strategy can be formulated.

[0074] Optionally, in one embodiment, Figure 2 As shown, a method for determining target water quality index data is provided to refine the above S101, specifically comprising the following steps:

[0075] S201, obtaining original water quality index data of the off-site water source within a target period of time through a water quality monitoring device installed at the off-site water source of the power system.

[0076] Among them, the water quality monitoring device is used to monitor the water quality index value of the water resources in the water source outside the station. In the embodiment of the present application, Figure 3 As shown in the figure, a structural diagram of a water quality monitoring device is provided. 301 is a water quality monitoring host, which has functions such as data acquisition, data calculation, and wireless networking. The water quality monitoring host connects to multiple sensors via a data port to collect data. 302 is a data channel connecting the water quality monitoring host and the sensors, such as a data bus like RS485. Multiple sensors can be connected to each channel, and sensor data can be obtained using a polling method. 303 is a water quality TDS + temperature sensor, 304 is a water quality pH + temperature sensor, 305 is a water quality ORP + temperature sensor, and 306 is a pool pressure (water level) sensor.

[0077] Optionally, a water quality monitoring device installed at an off-site water source of the power system will periodically send the original water quality index data of the off-site water source obtained by monitoring within a target period, and then the server can obtain the original water quality index data.

[0078] S202 : For each water quality index, determine the mean and standard deviation of the water quality index according to the index values of the water quality index in the original water quality index data.

[0079] Optionally, for each water quality index, the mean and standard deviation of the water quality index may be calculated based on a calculation formula for the mean and standard deviation and according to each index value of the water quality index in the original water quality index data.

[0080] S203 , preprocessing the original water quality index data according to the mean and standard deviation of each water quality index and the index values of each water quality index in the original water quality index data to obtain target water quality index data of the off-site water source of the power system.

[0081] Optionally, for each water quality index, the product between the mean and standard deviation of the water quality index is used as an intermediate parameter, and the difference between each index value of the water quality index in the original water quality index data and the intermediate parameter is used as the actual index value of the water quality index; based on the actual index value of each water quality index, the target water quality index data of the off-site water source of the power system is determined.

[0082] Specifically, for each water quality index, the actual index value of the water quality index can be expressed by the following formula (1):

[0083] (1)

[0084] in, is the actual value of the water quality indicator; is the index value of the water quality index in the original water quality index data; is the mean value of the water quality index; is the standard deviation of the water quality index.

[0085] It can be understood that the actual index values of the obtained water quality indexes are loaded with a standard normal distribution, that is, the mean is 0 and the standard deviation is 1.

[0086] In this embodiment, by introducing the mean and standard deviation of each water quality indicator and processing the index value of each water quality indicator based on the mean and standard deviation of each water quality indicator, it is ensured that the index value of each water quality indicator after processing conforms to the normal distribution, which helps to capture the dynamic non-steady-state mode of water quality and thus ensures the practicality of the obtained target water quality index data.

[0087] Optionally, in an exemplary embodiment, as Figure 4 As shown, a method for determining the target water quality state of an off-site water source is provided to refine the above S102, specifically comprising the following steps:

[0088] S401, based on the autoassociative memory network and according to the target water quality index data, construct an initial water quality status assessment model.

[0089] The Hopfield network, a self-associative memory network, can run autonomously and eventually converge to a preset equilibrium point given a set of initial values. This network is designed to store a set of equilibrium points, allowing the network to converge to these equilibrium points through autonomous operation. The initial water quality assessment model consists of at least two nodes and weights between any two nodes. The nodes represent the values of water quality indicators.

[0090] Optionally, an initial water quality status assessment model can be constructed based on the construction rules of the autoassociative memory network, with each indicator value in the target water quality indicator data as a node.

[0091] S402, determining the network parameters and weight matrix of the initial water quality status assessment model based on the target water quality index data.

[0092] The weight matrix includes the weights between any two nodes.

[0093] Optionally, the energy value of the initial water quality state assessment model is set, which can be specifically expressed by the following formula (2):

[0094] (2)

[0095] in, Indicates the energy value, Indicates the nodes and The weight between nodes; For the The index value at each node; For the The indicator value at each node.

[0096] Furthermore, based on the memory process of the autoassociative memory network, the network parameters are set, and according to the target water quality index data, the weight between any two nodes can be calculated based on the following formula (3):

[0097] (3)

[0098] (4)

[0099] Furthermore, a weight matrix can be constructed based on the weights between any two nodes.

[0100] S403: configuring the initial water quality status assessment model according to the network parameters to obtain a target water quality status assessment model.

[0101] Optionally, the initial water quality status assessment model is configured according to the network parameters to complete the network parameter setting process, and then the target water quality status assessment model can be obtained.

[0102] S404: Input the weight matrix and target water quality index data into the target water quality status assessment model to obtain the target water quality status of the off-site water source.

[0103] Alternatively, the target water quality assessment model can be based on the associative process of the autoassociative memory network, and iteratively calculate the target water quality of the off-site water source based on the input weight matrix and target water quality index data. It should be noted that the convergence condition of the iterative process is that the energy value in the above formula (2) no longer changes significantly.

[0104] In this embodiment, by introducing the autoassociative memory network, the simplicity and pertinence of the constructed target water quality status assessment model are ensured, and the demand for computing resources is reduced; furthermore, based on the weight matrix and the target water quality index data, the accuracy of the target water quality status of the determined off-site water source is ensured.

[0105] Optionally, in order to ensure the accuracy of the target processing strategy, in one embodiment, Figure 5 As shown, a method for optimizing a target processing strategy is provided, which specifically includes the following steps:

[0106] S501, based on target water quality index data and the target processing strategy of the power system for water resources in the off-site water source, determining predicted water quality index data of the off-site water source after the water resources are processed by the target processing strategy.

[0107] The predicted water quality index data are the index values of various water quality indicators of the water resources of the off-site water source obtained by prediction after being processed by the target processing strategy.

[0108] Optionally, a prediction model can be pre-built based on an LSTM network. This model is then trained using historical water quality data (e.g., TDS, pH, ORP, and water level) collected from the power system's ultra-high voltage converter stations for the period January to December, along with water treatment process parameters (e.g., reagent dosage and stirring time), and treated water quality indicators. The model is then trained using the Adam optimizer with a mean absolute error loss function. Specifically, the input parameters are set as historical water quality data and water treatment process parameters, and the output target is set as the predicted treated water quality indicator (e.g., TDS ≤ 600 mg / L, pH ∈ [6.5, 7.5]).

[0109] It should be noted that, in order to ensure the accuracy of the prediction model obtained through training, the steps S202-S203 in the above embodiment may be adopted, and the historical water quality data used for training may be preprocessed to improve the analysis efficiency of the prediction model.

[0110] S502: Determine the water quality error of the target treatment strategy based on the predicted water quality index data and the water demand of the water-using equipment in the power system.

[0111] Optionally, since the predicted water quality index data is the predicted water quality index data and the water demand of the water-using equipment in the power system is the actual water quality index data, the error between the predicted water quality index data and the actual water quality index data can be calculated as the water quality error of the target processing strategy.

[0112] S503: Optimize the target treatment strategy based on the water quality error.

[0113] Optionally, based on experience and according to water quality errors, the deficiencies and errors of the target treatment strategy can be analyzed, and the target treatment strategy can be optimized based on the analysis results.

[0114] In this embodiment, by entering the optimization process of the target treatment strategy and directly predicting the predicted water quality index data after being processed by the target treatment strategy based on the target water quality index data and the target treatment strategy, accurate optimization of the target treatment strategy can be achieved.

[0115] Figure 6 This is a flow chart of a method for determining a water resource treatment strategy in another embodiment. Based on the above embodiment, this embodiment provides an optional example of a method for determining a water resource treatment strategy. Figure 6 The specific implementation process is as follows:

[0116] S601, obtaining water demand data of water-using equipment in the power system, as well as water quality monitoring devices installed at off-site water sources in the power system, and original water quality index data of the off-site water sources during a target period.

[0117] The at least two water quality indicators include at least two of the total dissolved solids (TDS) in water, the solution pH, the oxidation-reduction potential (ORP), and the water level.

[0118] S602: Determine the mean and standard deviation of each water quality indicator according to the indicator value of each water quality indicator in the original water quality indicator data.

[0119] S603 , preprocessing the original water quality index data according to the mean and standard deviation of each water quality index and the index values of each water quality index in the original water quality index data to obtain target water quality index data of the off-site water source of the power system.

[0120] Optionally, for each water quality index, the product between the mean and standard deviation of the water quality index is used as an intermediate parameter, and the difference between each index value of the water quality index in the original water quality index data and the intermediate parameter is used as the actual index value of the water quality index; based on the actual index value of each water quality index, the target water quality index data of the off-site water source of the power system is determined.

[0121] S604: Based on the autoassociative memory network and the target water quality index data, an initial water quality status assessment model is constructed.

[0122] The initial water quality status assessment model includes at least two nodes and weights between any two nodes, and the nodes represent the index values of water quality indicators.

[0123] S605: Determine the network parameters and weight matrix of the initial water quality status assessment model based on the target water quality index data.

[0124] The weight matrix includes the weights between any two nodes.

[0125] S606: configuring the initial water quality status assessment model according to the network parameters to obtain a target water quality status assessment model.

[0126] S607: Input the weight matrix and target water quality index data into the target water quality status assessment model to obtain the target water quality status of the off-site water source.

[0127] S608: Input the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system into the strategy prediction model to obtain the target processing strategy for the water resources in the off-site water source output by the strategy prediction model.

[0128] Among them, the strategy prediction model is obtained through sample data training; the sample data includes the sample water quality status of the off-site water source in the historical period, the sample processing strategy of the water resources, and the sample index values of the water quality indicators of the off-site water source after being processed by the sample processing strategy.

[0129] S609, based on the target water quality index data and the target processing strategy of the power system for the water resources in the off-site water source, determining the predicted water quality index data of the off-site water source after the water resources are processed by the target processing strategy.

[0130] S610: Determine a water quality error of a target treatment strategy based on the predicted water quality index data and water demand of water-using equipment in the power system.

[0131] S611, optimize the target treatment strategy based on the water quality error.

[0132] The specific process of S601-S611 can be found in the description of the above method embodiment. The implementation principle and technical effects are similar and will not be repeated here.

[0133] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0134] Based on the same inventive concept, the embodiments of the present application also provide a water resource treatment strategy determination device for implementing the water resource treatment strategy determination method involved above. The implementation solution provided by this device is similar to the implementation solution described in the above method. Therefore, the specific limitations of one or more water resource treatment strategy determination device embodiments provided below can be referred to the limitations of the water resource treatment strategy determination method above, and will not be repeated here.

[0135] In an exemplary embodiment, Figure 7 As shown, a water resource treatment strategy determination device 700 is provided, comprising: a data acquisition module 710, a state determination module 720 and a strategy determination unit 730, wherein:

[0136] The data acquisition module 710 is used to obtain the target water quality index data of the off-site water source of the power system within the target time period, and the water demand data of the water-using equipment in the power system; wherein the target water quality index data includes the actual index values of at least two water quality indicators, and the water demand data includes the expected index values of at least two water quality indicators.

[0137] The state determination module 720 is used to determine the target water quality state of the off-site water source based on the target water quality index data.

[0138] The strategy determination unit 730 is used to determine a target processing strategy for water resources in the off-site water source according to the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system.

[0139] The above-mentioned water resource treatment strategy determination device, after obtaining the target water quality index data of the off-site water source of the power system within the target time period and the water demand data of the water-using equipment in the power system, since the target water quality index data includes the actual index values of at least two water quality indexes, and the water demand data includes the expected index values of at least two water quality indexes, therefore, according to the target water quality index data, the target water quality status of the off-site water source can be accurately determined; further, according to the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system, that is, comprehensively considering the water quality of the water resources and the needs of the water-using equipment, it is ensured that the determined target treatment strategy for the water resources in the off-site water source is more in line with the actual needs of the water-using equipment, and a flexible water resource treatment strategy can be formulated.

[0140] In one embodiment, the data acquisition module 710 includes:

[0141] The data acquisition unit is used to obtain the original water quality index data of the off-site water source within a target period through a water quality monitoring device installed at the off-site water source of the power system.

[0142] The data statistics unit is used to determine the mean and standard deviation of each water quality indicator according to each indicator value of the water quality indicator in the original water quality indicator data.

[0143] The data processing unit is used to pre-process the original water quality index data according to the mean and standard deviation of each water quality index and the index values of each water quality index in the original water quality index data to obtain the target water quality index data of the off-site water source of the power system.

[0144] In one embodiment, the data processing unit is specifically configured to:

[0145] For each water quality index, the product of the mean and standard deviation of the water quality index is used as the intermediate parameter, and the difference between each index value of the water quality index in the original water quality index data and the intermediate parameter is used as the actual index value of the water quality index; based on the actual index value of each water quality index, the target water quality index data of the off-site water source of the power system is determined.

[0146] In one embodiment, the state determination module 720 is specifically configured to:

[0147] Based on the autoassociative memory network, an initial water quality status assessment model is constructed according to the target water quality index data; wherein, the initial water quality status assessment model includes at least two nodes and weights between any two nodes, and the nodes represent the index values of the water quality index; according to the target water quality index data, the network parameters and weight matrix of the initial water quality status assessment model are determined; wherein, the weight matrix includes the weights between any two nodes; according to the network parameters, the initial water quality status assessment model is configured to obtain the target water quality status assessment model; the weight matrix and the target water quality index data are input into the target water quality status assessment model to obtain the target water quality status of the off-site water source.

[0148] In one embodiment, the policy determination unit 730 is specifically configured to:

[0149] The water quality status of the off-site water source and the water demand data of the water-using equipment in the power system are input into the strategy prediction model to obtain the target processing strategy for the water resources in the off-site water source output by the strategy prediction model; wherein, the strategy prediction model is obtained by training with sample data; the sample data includes the sample water quality status of the off-site water source in the historical period, the sample processing strategy of the water resources, and the sample index values of the water quality index of the water resources of the off-site water source after being processed by the sample processing strategy.

[0150] In one embodiment, the water resource treatment strategy determination device 700 is further configured to:

[0151] Based on the target water quality index data and the power system's target treatment strategy for water resources in off-site water sources, the predicted water quality index data of the off-site water sources after being treated by the target treatment strategy is determined; based on the predicted water quality index data and the water demand of water-using equipment in the power system, the water quality error of the target treatment strategy is determined; and based on the water quality error, the target treatment strategy is optimized.

[0152] In one embodiment, the at least two water quality indicators include at least two of the total dissolved solids (TDS), solution pH, oxidation-reduction potential (ORP), and water level.

[0153] Each module in the aforementioned water resource treatment strategy determination device may be implemented in whole or in part through software, hardware, or a combination thereof. Each module may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a memory in the computer device in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0154] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 8As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for determining a water resource treatment strategy is implemented.

[0155] Those skilled in the art will understand that Figure 8 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0156] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0157] Obtain target water quality index data of an off-site water source of the power system within a target time period, and water demand data of water-consuming equipment within the power system; wherein the target water quality index data includes actual index values of at least two water quality indexes, and the water demand data includes expected index values of at least two water quality indexes;

[0158] Determine the target water quality status of the water source outside the station based on the target water quality index data;

[0159] Based on the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system, the target treatment strategy for the water resources in the off-site water source is determined.

[0160] In one embodiment, when the processor executes the computer program to obtain target water quality index data of an off-site water source of the power system within a target period, the processor further implements the following steps:

[0161] By installing a water quality monitoring device at the off-site water source of the power system, the original water quality index data of the off-site water source within the target time period is obtained; for each water quality index, the mean and standard deviation of the water quality index are determined based on the various index values of the water quality index in the original water quality index data; based on the mean and standard deviation of each water quality index and the various index values of each water quality index in the original water quality index data, the original water quality index data are preprocessed to obtain the target water quality index data of the off-site water source of the power system.

[0162] In one embodiment, when a processor executes a computer program to pre-process the raw water quality index data based on the mean and standard deviation of each water quality index and the index value of each water quality index in the raw water quality index data to obtain target water quality index data of an off-site water source of the power system, the processor further implements the following steps:

[0163] For each water quality index, the product of the mean and standard deviation of the water quality index is used as the intermediate parameter, and the difference between each index value of the water quality index in the original water quality index data and the intermediate parameter is used as the actual index value of the water quality index; based on the actual index value of each water quality index, the target water quality index data of the off-site water source of the power system is determined.

[0164] In one embodiment, when the processor executes the computer program to determine the target water quality state of the off-site water source based on the target water quality index data, the processor further implements the following steps:

[0165] Based on the autoassociative memory network, an initial water quality status assessment model is constructed according to the target water quality index data; wherein, the initial water quality status assessment model includes at least two nodes and weights between any two nodes, and the nodes represent the index values of the water quality index; according to the target water quality index data, the network parameters and weight matrix of the initial water quality status assessment model are determined; wherein, the weight matrix includes the weights between any two nodes; according to the network parameters, the initial water quality status assessment model is configured to obtain the target water quality status assessment model; the weight matrix and the target water quality index data are input into the target water quality status assessment model to obtain the target water quality status of the off-site water source.

[0166] In one embodiment, when the processor executes the computer program to determine a target treatment strategy for water resources in the off-site water source based on the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system, the processor further implements the following steps:

[0167] The water quality status of the off-site water source and the water demand data of the water-using equipment in the power system are input into the strategy prediction model to obtain the target processing strategy for the water resources in the off-site water source output by the strategy prediction model; wherein, the strategy prediction model is obtained by training with sample data; the sample data includes the sample water quality status of the off-site water source in the historical period, the sample processing strategy of the water resources, and the sample index values of the water quality index of the water resources of the off-site water source after being processed by the sample processing strategy.

[0168] In one embodiment, after the processor executes the computer program to determine a target treatment strategy for water resources in the off-site water source based on the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system, the processor further implements the following steps:

[0169] Based on the target water quality index data and the power system's target treatment strategy for water resources in off-site water sources, the predicted water quality index data of the off-site water sources after being treated by the target treatment strategy is determined; based on the predicted water quality index data and the water demand of water-using equipment in the power system, the water quality error of the target treatment strategy is determined; and based on the water quality error, the target treatment strategy is optimized.

[0170] In one embodiment, the at least two water quality indicators include at least two of the total dissolved solids (TDS), solution pH, oxidation-reduction potential (ORP), and water level.

[0171] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0172] Obtain target water quality index data of an off-site water source of the power system within a target time period, and water demand data of water-consuming equipment within the power system; wherein the target water quality index data includes actual index values of at least two water quality indexes, and the water demand data includes expected index values of at least two water quality indexes;

[0173] Determine the target water quality status of the water source outside the station based on the target water quality index data;

[0174] Based on the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system, the target treatment strategy for the water resources in the off-site water source is determined.

[0175] In one embodiment, when the processor executes the computer program to obtain target water quality index data of an off-site water source of the power system within a target period, the processor further implements the following steps:

[0176] By installing a water quality monitoring device at the off-site water source of the power system, the original water quality index data of the off-site water source within the target time period is obtained; for each water quality index, the mean and standard deviation of the water quality index are determined based on the various index values of the water quality index in the original water quality index data; based on the mean and standard deviation of each water quality index and the various index values of each water quality index in the original water quality index data, the original water quality index data are preprocessed to obtain the target water quality index data of the off-site water source of the power system.

[0177] In one embodiment, when a processor executes a computer program to pre-process the raw water quality index data based on the mean and standard deviation of each water quality index and the index value of each water quality index in the raw water quality index data to obtain target water quality index data of an off-site water source of the power system, the processor further implements the following steps:

[0178] For each water quality index, the product of the mean and standard deviation of the water quality index is used as the intermediate parameter, and the difference between each index value of the water quality index in the original water quality index data and the intermediate parameter is used as the actual index value of the water quality index; based on the actual index value of each water quality index, the target water quality index data of the off-site water source of the power system is determined.

[0179] In one embodiment, when the processor executes the computer program to determine the target water quality state of the off-site water source based on the target water quality index data, the processor further implements the following steps:

[0180] Based on the autoassociative memory network, an initial water quality status assessment model is constructed according to the target water quality index data; wherein, the initial water quality status assessment model includes at least two nodes and weights between any two nodes, and the nodes represent the index values of the water quality index; according to the target water quality index data, the network parameters and weight matrix of the initial water quality status assessment model are determined; wherein, the weight matrix includes the weights between any two nodes; according to the network parameters, the initial water quality status assessment model is configured to obtain the target water quality status assessment model; the weight matrix and the target water quality index data are input into the target water quality status assessment model to obtain the target water quality status of the off-site water source.

[0181] In one embodiment, when the processor executes the computer program to determine a target treatment strategy for water resources in the off-site water source based on the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system, the processor further implements the following steps:

[0182] The water quality status of the off-site water source and the water demand data of the water-using equipment in the power system are input into the strategy prediction model to obtain the target processing strategy for the water resources in the off-site water source output by the strategy prediction model; wherein, the strategy prediction model is obtained by training with sample data; the sample data includes the sample water quality status of the off-site water source in the historical period, the sample processing strategy of the water resources, and the sample index values of the water quality index of the water resources of the off-site water source after being processed by the sample processing strategy.

[0183] In one embodiment, after the processor executes the computer program to determine a target treatment strategy for water resources in the off-site water source based on the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system, the processor further implements the following steps:

[0184] Based on the target water quality index data and the power system's target treatment strategy for water resources in off-site water sources, the predicted water quality index data of the off-site water sources after being treated by the target treatment strategy is determined; based on the predicted water quality index data and the water demand of water-using equipment in the power system, the water quality error of the target treatment strategy is determined; and based on the water quality error, the target treatment strategy is optimized.

[0185] In one embodiment, the at least two water quality indicators include at least two of the total dissolved solids (TDS), solution pH, oxidation-reduction potential (ORP), and water level.

[0186] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0187] Obtain target water quality index data of an off-site water source of the power system within a target time period, and water demand data of water-consuming equipment within the power system; wherein the target water quality index data includes actual index values of at least two water quality indexes, and the water demand data includes expected index values of at least two water quality indexes;

[0188] Determine the target water quality status of the water source outside the station based on the target water quality index data;

[0189] Based on the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system, the target treatment strategy for the water resources in the off-site water source is determined.

[0190] In one embodiment, when the processor executes the computer program to obtain target water quality index data of an off-site water source of the power system within a target period, the processor further implements the following steps:

[0191] By installing a water quality monitoring device at the off-site water source of the power system, the original water quality index data of the off-site water source within the target time period is obtained; for each water quality index, the mean and standard deviation of the water quality index are determined based on the various index values of the water quality index in the original water quality index data; based on the mean and standard deviation of each water quality index and the various index values of each water quality index in the original water quality index data, the original water quality index data are preprocessed to obtain the target water quality index data of the off-site water source of the power system.

[0192] In one embodiment, when a processor executes a computer program to pre-process the raw water quality index data based on the mean and standard deviation of each water quality index and the index value of each water quality index in the raw water quality index data to obtain target water quality index data of an off-site water source of the power system, the processor further implements the following steps:

[0193] For each water quality index, the product of the mean and standard deviation of the water quality index is used as the intermediate parameter, and the difference between each index value of the water quality index in the original water quality index data and the intermediate parameter is used as the actual index value of the water quality index; based on the actual index value of each water quality index, the target water quality index data of the off-site water source of the power system is determined.

[0194] In one embodiment, when the processor executes the computer program to determine the target water quality state of the off-site water source based on the target water quality index data, the processor further implements the following steps:

[0195] Based on the autoassociative memory network, an initial water quality status assessment model is constructed according to the target water quality index data; wherein, the initial water quality status assessment model includes at least two nodes and weights between any two nodes, and the nodes represent the index values of the water quality index; according to the target water quality index data, the network parameters and weight matrix of the initial water quality status assessment model are determined; wherein, the weight matrix includes the weights between any two nodes; according to the network parameters, the initial water quality status assessment model is configured to obtain the target water quality status assessment model; the weight matrix and the target water quality index data are input into the target water quality status assessment model to obtain the target water quality status of the off-site water source.

[0196] In one embodiment, when the processor executes the computer program to determine a target treatment strategy for water resources in the off-site water source based on the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system, the processor further implements the following steps:

[0197] The water quality status of the off-site water source and the water demand data of the water-using equipment in the power system are input into the strategy prediction model to obtain the target processing strategy for the water resources in the off-site water source output by the strategy prediction model; wherein, the strategy prediction model is obtained by training with sample data; the sample data includes the sample water quality status of the off-site water source in the historical period, the sample processing strategy of the water resources, and the sample index values of the water quality index of the water resources of the off-site water source after being processed by the sample processing strategy.

[0198] In one embodiment, after the processor executes the computer program to determine a target treatment strategy for water resources in the off-site water source based on the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system, the processor further implements the following steps:

[0199] Based on the target water quality index data and the power system's target treatment strategy for water resources in off-site water sources, the predicted water quality index data of the off-site water sources after being treated by the target treatment strategy is determined; based on the predicted water quality index data and the water demand of water-using equipment in the power system, the water quality error of the target treatment strategy is determined; and based on the water quality error, the target treatment strategy is optimized.

[0200] In one embodiment, the at least two water quality indicators include at least two of the total dissolved solids (TDS), solution pH, oxidation-reduction potential (ORP), and water level.

[0201] It should be noted that the data involved in this application (including but not limited to data used for analysis, storage, display, etc.) are all information and data fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0202] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), data processing logic devices based on quantum computing, and the like.

[0203] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0204] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for determining a water resource treatment strategy, characterized in that: The method comprises: Obtaining target water quality index data of an off-site water source of the power system within a target time period, and water demand data of water-using equipment within the power system; wherein the target water quality index data includes actual index values of at least two water quality indexes, and the water demand data includes expected index values of at least two water quality indexes; Determining the target water quality state of the off-site water source according to the target water quality index data; According to the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system, a target treatment strategy for the water resources in the off-site water source is determined.

2. The method according to claim 1, characterized in that The obtaining of target water quality index data of an off-site water source of the power system within a target period includes: Obtaining original water quality index data of the off-site water source within a target period of time by installing a water quality monitoring device at the off-site water source of the power system; For each water quality index, determining the mean and standard deviation of the water quality index according to the index values of the water quality index in the original water quality index data; The original water quality index data are preprocessed according to the mean and standard deviation of each water quality index and the index values of each water quality index in the original water quality index data to obtain target water quality index data of the off-site water source of the power system.

3. The method according to claim 2, characterized in that The raw water quality index data is preprocessed based on the mean and standard deviation of each water quality index and the index values of each water quality index in the raw water quality index data to obtain target water quality index data of the off-site water source of the power system, including: For each water quality index, the product of the mean and the standard deviation of the water quality index is used as an intermediate parameter, and the difference between each index value of the water quality index in the original water quality index data and the intermediate parameter is used as the actual index value of the water quality index; According to the actual index value of each water quality index, the target water quality index data of the off-site water source of the power system is determined.

4. The method according to claim 1, wherein Determining the target water quality state of the off-site water source according to the target water quality index data includes: Based on the target water quality index data, an initial water quality status assessment model is constructed based on the autoassociative memory network; wherein the initial water quality status assessment model includes at least two nodes and weights between any two nodes, and the nodes represent the index value of the water quality index; Determining the network parameters and weight matrix of the initial water quality status assessment model based on the target water quality index data; wherein the weight matrix includes the weights between any two nodes; configuring the initial water quality state assessment model according to the network parameters to obtain a target water quality state assessment model; The weight matrix and the target water quality index data are input into the target water quality status assessment model to obtain the target water quality status of the off-site water source.

5. The method according to claim 1, wherein Determining a target treatment strategy for water resources in the off-site water source based on the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system includes: Inputting the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system into the strategy prediction model, and obtaining the target treatment strategy for the water resources in the off-site water source output by the strategy prediction model; Among them, the strategy prediction model is obtained through sample data training; the sample data includes the sample water quality status of the off-site water source in the historical period, the sample processing strategy of the water resources, and the sample index value of the water quality index of the water resources of the off-site water source after being processed by the sample processing strategy.

6. The method according to claim 1, characterized in that After determining a target treatment strategy for water resources in the off-site water source based on the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system, the method further includes: Determining predicted water quality index data of the water resources of the off-site water source after being processed by the target processing strategy based on the target water quality index data and the target processing strategy of the power system for the water resources in the off-site water source; Determining a water quality error of the target treatment strategy based on the predicted water quality index data and water demand of water-using equipment in the power system; The target treatment strategy is optimized based on the water quality error.

7. The method according to claim 1, characterized in that The at least two water quality indicators include at least two of the total amount of dissolved solids (TDS) in water, solution pH, oxidation-reduction potential (ORP), and water level.

8. A device for determining a water resource treatment strategy, characterized in that: The device comprises: a data acquisition module, configured to acquire target water quality index data of an off-site water source of the power system within a target time period, and water demand data of water-using equipment within the power system; wherein the target water quality index data includes actual index values of at least two water quality indexes, and the water demand data includes expected index values of at least two water quality indexes; A state determination module, configured to determine the target water quality state of the off-site water source based on the target water quality index data; The strategy determination unit is used to determine a target processing strategy for the water resources in the off-site water source according to the water quality status of the off-site water source and the water demand data of the water-using equipment in the power system.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

Images