Water resource scheduling method and device for cascade hydropower stations

Abstract

The invention discloses a water resource scheduling method and device for cascade hydropower stations, and relates to the technical field of water resource scheduling. Comprising the steps of obtaining water resource data of each hydropower station in cascade hydropower stations at the current moment; for each hydropower station, judging whether the hydropower station is in a safe operation state or not according to the cleaned water resource data of the hydropower station; when it is determined that each hydropower station is in a safe operation state, according to the water resource data of each hydropower station, a preset electricity price scheme and target historical data, using an artificial intelligence deep learning method to determine whether to perform water resource scheduling; and if the water resource scheduling is determined, determining a water resource scheduling scheme based on the water resource data of each hydropower station and the water resource scheduling model. Therefore, under the condition that each hydropower station is in a safe operation state, the purposes of obtaining higher power generation income of the power plant as much as possible and reasonably scheduling water resources are achieved.

Description

Technical Field

[0001] The present application relates to the technical field of water resource scheduling, and in particular to a method and device for scheduling water resources in a cascade hydropower station. Background Art

[0002] Cascade hydropower stations are a series of hydropower stations built through cascade development. This development method starts from the upper reaches of the river and plans a series of water conservancy hubs in one river section after another from top to bottom, in a stepped distribution form. The power generation principle of cascade hydropower stations is to use the kinetic energy generated by the drop of water under the action of gravity, introduce water into the plant through the water diversion system, drive the turbine generator set to rotate, and thus convert water energy into electrical energy.

[0003] In the development and utilization of cascade hydropower stations, close coordination of various hydropower stations is essential. In order to ensure the safe and efficient operation of the entire hydropower system, it is necessary to comprehensively consider the water level management of each hydropower station and conduct fine scheduling according to the power generation efficiency and power generation income at different water levels. However, in this process, reservoir safety and power generation facility safety must always be given priority to avoid natural disasters or facility damage caused by excessive water storage or discharge. Therefore, how to obtain higher power generation income as much as possible and reasonably schedule water resources under the premise of ensuring that each hydropower station is in a safe operating state has become one of the technical problems that need to be solved in the field of water resources management technology. Summary of the invention

[0004] Based on the above problems, the present application provides a water resource scheduling method for cascade hydropower stations, which is used to reasonably schedule water resources while obtaining higher power plant power generation revenue as much as possible while ensuring that each hydropower station is in a safe operating state.

[0005] The embodiments of the present application disclose the following technical solutions: The first aspect of the present application discloses a water resource scheduling method for a cascade hydropower station, comprising: Obtain water resource data of each hydropower station in the cascade hydropower station at the current moment; For each of the hydropower stations, judging whether the hydropower station is in a safe operating state according to the water resources data of the hydropower station; When it is determined that all the hydropower stations are in the safe operation state, judging whether to perform water resource scheduling according to the water resource data of each hydropower station, the preset electricity price scheme and the target historical data; the target historical data includes the average water consumption for power generation and the average power plant revenue corresponding to the month at the current moment; If it is determined to carry out water resource scheduling, a water resource scheduling plan is determined based on the water resource data and water resource scheduling model of each hydropower station; the water resource scheduling model is a pre-trained model for outputting a water resource scheduling plan; the water resource scheduling plan includes day-ahead scheduling and seasonal scheduling.

[0006] In an optional implementation, the safe operation state includes a water conservation safety state; for each of the hydropower stations, judging whether the hydropower station is in a safe operation state according to the water resources data of the hydropower station includes: For each of the hydropower stations, obtaining the measured velocity rise rate and the measured turbine hydrostatic pressure from the water resource data of the hydropower station; For each of the hydropower stations, if the measured speed increase rate is less than the theoretical speed increase rate, and the measured turbine hydrostatic pressure is less than the theoretical turbine hydrostatic pressure, it is determined that the hydropower station is in the water conservation safety state; If the measured speed increase rate is greater than or equal to the theoretical speed increase rate, or the measured turbine hydrostatic pressure is greater than or equal to the theoretical turbine hydrostatic pressure, it is determined that the hydropower station is not in the water conservation safety state.

[0007] In an optional implementation, the safe operation state includes a vibration safety state, and for each of the hydropower stations, judging whether the hydropower station is in a safe operation state according to water resource data of the hydropower station includes: For each of the hydropower stations, the power of the turbine engine is obtained from the water resource data of the hydropower station, and recorded as the first power; Determining whether the first power is within a preset power range; If the first power is within the preset power range, the first power is adjusted to the second power; the second power is outside the preset power range; If the first power is outside the preset power range, it is determined whether the hydropower station is in the vibration safety state.

[0008] In an optional implementation, the determining whether the hydropower station is in the vibration-safe state includes: For each of the hydropower stations, the rotation speed of the turbine engine and actual vibration values ​​of different parts of the turbine engine are obtained from the water resource data of the hydropower station; For each of the hydropower stations, if the actual vibration value of each of the parts is less than the vibration allowable value corresponding to the part at the rotation speed, it is determined that the hydropower station is in the vibration safety state; Otherwise, it is determined that the hydropower station is not in the vibration safe state.

[0009] In an optional implementation, before obtaining the water resource data of each hydropower station in the cascade hydropower stations at the current moment, the method further includes: A load shedding test is performed on the cascade hydropower stations to determine whether the operating parameters of each hydropower station in the cascade hydropower stations meet the requirements of preset load shedding test indicators.

[0010] In an optional implementation, judging whether to perform water resource scheduling according to the water resource data of each hydropower station, a preset electricity price scheme and target historical data includes: Based on the water resource data of each hydropower station and the preset electricity price scheme, determine the actual water consumption for power generation of each hydropower station and the actual power plant revenue of each hydropower station as current actual data; Based on the difference between the current actual data and the target historical data, it is determined whether to perform water resource scheduling.

[0011] In an optional implementation, determining the actual water consumption for power generation of each hydropower station and the actual power plant revenue of each hydropower station based on the water resource data of each hydropower station and the preset electricity price scheme includes: For each of the hydropower stations, the actual power generation and actual water consumption in a target time period are obtained from the water resource data of the hydropower station; the target time period is a period of time in the past with the current moment as the end point; For each of the hydropower stations, based on the actual power generation and actual water consumption during the target time period, the actual power generation and water consumption during the target time period are obtained; For each of the hydropower stations, the actual power plant revenue for the target time period is determined based on the electricity price plan corresponding to the target time period and the actual water level of the hydropower station.

[0012] In an optional implementation, the method for acquiring the target historical data includes: Count the historical water consumption for power generation and the historical power plant revenue for each month in the past N years; N is an integer greater than or equal to 1; For each month, based on the N historical power generation water consumption corresponding to the month, a historical power generation water consumption map corresponding to the month is obtained; and based on the N historical power plant revenues corresponding to the month, a historical power plant revenue map corresponding to the month is obtained; the historical power generation water consumption map represents the relationship between the historical power generation water consumption and time; the historical power plant revenue map represents the relationship between the historical power plant revenue and time; The average power generation water consumption corresponding to the historical power generation water consumption map corresponding to the month of the current moment and the average power plant revenue corresponding to the historical power plant revenue map corresponding to the month of the current moment are used as the target historical data.

[0013] In an optional implementation, the training step of the water resource scheduling model includes: Acquire training data; the training data includes sample water resource data of each hydropower station in the cascade hydropower stations at a sample time point, an electricity price plan at the sample time point, and a sample water resource scheduling plan at the sample time point; the sample time point is any time point among multiple time points at which the hydropower station operates under full working conditions; the sample water resource data includes historical water consumption for power generation, historical power plant revenue, and historical average water assets; the sample water resource scheduling plan includes day-ahead scheduling and seasonal scheduling; Inputting the training data into a deep learning model to obtain a predicted water resources scheduling plan corresponding to the training data; Taking the sample water resource scheduling plan as the true value, the back propagation error between the sample water resource scheduling plan and the predicted water resource scheduling plan is determined through the loss function, and the network parameters of the deep learning model are updated based on the back propagation error until the back propagation error reaches the set value, thereby obtaining the water resource scheduling model.

[0014] The second aspect of the present application discloses a water resource dispatching device for a cascade hydropower station, comprising: A data acquisition module is used to obtain water resource data of each hydropower station in the cascade hydropower station at the current moment; A safety status determination module, for determining, for each of the hydropower stations, whether the hydropower station is in a safe operating state according to the water resources data of the hydropower station; A water resource scheduling judgment module is used to determine whether to perform water resource scheduling based on the water resource data of each hydropower station, a preset electricity price plan and target historical data when it is determined that each hydropower station is in the safe operation state; the target historical data includes the average power generation water consumption and the average power plant revenue corresponding to the month at the current time; A water resource scheduling scheme determination module is used to determine the water resource scheduling scheme based on the water resource data and water resource scheduling model of each hydropower station if it is determined to perform water resource scheduling; the water resource scheduling model is a pre-trained model for outputting the water resource scheduling scheme; the water resource scheduling scheme includes day-ahead scheduling and seasonal scheduling.

[0015] A third aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method introduced in any implementation manner of the first aspect.

[0016] A fourth aspect of the present application provides an electronic device, including: a memory having a computer program stored thereon; A processor is used to execute the computer program in the memory to implement the steps of the method introduced in any implementation manner of the first aspect.

[0017] Compared with the prior art, this application has the following beneficial effects: The present application discloses a method for water resource dispatching of cascade hydropower stations, including: obtaining water resource data of each hydropower station in the cascade hydropower station at the current moment; for each hydropower station, judging whether the hydropower station is in a safe operation state according to the water resource data of the hydropower station; when it is determined that each hydropower station is in a safe operation state, judging whether to perform water resource dispatching according to the water resource data of each hydropower station, a preset electricity price scheme and target historical data; if it is determined that water resource dispatching is to be performed, determining a water resource dispatching scheme based on the water resource data of each hydropower station and a water resource dispatching model. Through the scheme in the present application, when it is determined that each hydropower station is in a safe operation state, a water resource dispatching scheme that obtains as high a power generation benefit as possible can be directly generated based on the water resource dispatching model trained with historical data and the water resource data of each hydropower station at the current moment, thereby realizing reasonable dispatching of water resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 creative labor.

[0019] Figure 1 A flow chart of a water resource scheduling method provided in an embodiment of the present application; Figure 2A A schematic diagram of the historical water consumption for power generation in each month of an upstream hydropower station provided in an embodiment of the present application; Figure 2B A schematic diagram of the historical water consumption for power generation in each month of a downstream hydropower station provided in an embodiment of the present application; Figure 2C A schematic diagram of the historical power plant revenue corresponding to each month of an upstream hydropower station provided in an embodiment of the present application; Figure 2D A schematic diagram of the historical power plant revenue corresponding to each month of a downstream hydropower station provided in an embodiment of the present application; Figure 3A A schematic diagram of water assets corresponding to each month of an upstream hydropower station provided in an embodiment of the present application; Figure 3B A schematic diagram of water assets corresponding to each month of a downstream hydropower station provided in an embodiment of the present application; Figure 4 A schematic diagram of a water resource scheduling scheme for a cascade hydropower station provided in an embodiment of the present application; Figure 5 A schematic diagram of the interaction between a power plant and a power grid provided in an embodiment of the present application; Figure 6 A flow chart of another water resource scheduling method provided in an embodiment of the present application; Figure 7 A schematic diagram of the structure of a water resource scheduling device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0020] There are a series of issues that need to be considered in the water resource dispatch of cascade hydropower stations. For example, cascade hydropower stations are generally composed of multiple single-stage power stations in series. The upper and lower hydropower stations are connected through storage return water. The control range can be extended from the confluence to the entire basin. The risk of some out-of-control in the upstream power station is transmitted through water flow fluctuations, superimposed and accumulated in the downstream hydropower station, which may cause serious risk events; for example, during the operation of each hydropower station in the cascade hydropower station, it is necessary to consider the reservoir safety (water level should be appropriate) and unit safety of each hydropower station; for example, during the operation of each hydropower station in the cascade hydropower station, it is necessary to consider the unit operation safety caused by sudden accidents in the power grid (such as failure to receive electricity from the interconnection point, sudden load shedding); for example, under the premise of reservoir safety and hydropower generation equipment safety, how to improve the power supply quality, promote the safe operation of the power grid, increase the power supply income, and realize the full utilization of water resources.

[0021] Based on the above problems, the present application discloses a water resource scheduling method for cascade hydropower stations, including: obtaining water resource data of each hydropower station in the cascade hydropower station at the current moment; for each hydropower station, judging whether the hydropower station is in a safe operation state according to the water resource data of the hydropower station; when it is determined that each hydropower station is in a safe operation state, judging whether to perform water resource scheduling according to the water resource data of each hydropower station, a preset electricity price scheme and target historical data; if it is determined to perform water resource scheduling, determining a water resource scheduling scheme based on the water resource data of each hydropower station and a water resource scheduling model. Through the scheme in the present application, when it is determined that each hydropower station is in a safe operation state, a water resource scheduling scheme that can obtain as high a power generation benefit as possible can be directly generated based on the water resource scheduling model trained with historical data and the water resource data of each hydropower station at the current moment, thereby realizing reasonable scheduling of water resources.

[0022] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiment of the present application is clearly and completely described below in conjunction with the drawings in the embodiment of the present application. Obviously, the described embodiment is only a part of the embodiment of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0023] Figure 1 A flow chart of a water resource scheduling method provided in an embodiment of the present application. Figure 1 As shown, the water resource scheduling method disclosed in this application includes: S101, obtaining water resource data of each hydropower station in the cascade hydropower station at the current moment.

[0024] The water resource data of the hydropower station in this application include but are not limited to: the measured water level of the reservoir where the hydropower station is located (referred to as "measured water level"), the measured velocity increase rate of the water flow velocity in the reservoir where the hydropower station is located (referred to as "measured velocity increase rate"), the measured turbine static pressure (also called "measured turbine static water pressure"), the rated speed of the turbine generator, the working power of the turbine generator, the installed capacity of the power station, the maximum / rated / minimum head, the maximum runaway speed, the rated output of the turbine and the wheel tube diameter, etc.

[0025] Table 1-1 is a table of water volume entering the reservoir of an upstream hydropower station provided in this application. Table 1-1 shows the water volume entering the reservoir of the upstream hydropower station from January to December in different years, and the unit of water volume is 10,000 m³.

[0026] For example, the following data can be read from Table 1-1: the water inflow into the reservoir of the upstream hydropower station in January 2016 was 7.75 million m³; the water inflow into the reservoir of the upstream hydropower station in February 2023 was 12.57 million m³.

[0027] It should be noted that the upstream hydropower station refers to the hydropower station located upstream among the cascade hydropower stations.

[0028] Table 1-1

[0029] Table 1-2

[0030] Table 1-2 is a table of water volume changes of an upstream hydropower station provided by this application. Table 1-2 shows the daily water volume changes of the upstream hydropower station from January 23 to January 30. Specifically, it includes: current water storage (m³), current reservoir energy storage (100 million kWh), current water level (m), yesterday's average inflow (m³ / s), yesterday's average outflow (m³ / s) and yesterday's power generation water consumption rate (m³ / kWh).

[0031] S102: for each of the hydropower stations, judging whether the hydropower station is in a safe operating state according to the water resource data of the hydropower station.

[0032] The safe operation status in this application mainly refers to the water conservation safety status and the vibration safety status.

[0033] In this application, when judging whether a hydropower station is in a water conservation safety state, two indicators, namely the measured turbine static water pressure and the measured speed rise rate, are mainly considered.

[0034] The measured turbine hydrostatic pressure, also known as volute pressure, refers to the actual net water pressure at the turbine volute inlet; it is usually affected by water velocity, water flow direction, turbine structure and reservoir water level. The measured turbine hydrostatic pressure is of great significance for evaluating the operating efficiency of turbines, predicting the wear of turbines and formulating turbine maintenance plans.

[0035] The measured rate of increase refers to the actual rate of increase of the reservoir water level within a certain period of time, expressed as the amount of water level change per unit time; it is usually affected by the amount of water entering the reservoir, the amount of water leaving the reservoir, rainfall conditions and the reservoir regulation capacity. The measured rate of increase is of great significance for evaluating the water storage capacity of the reservoir, predicting future water level changes and formulating reservoir scheduling plans.

[0036] Usually, the measured speed rise rate and the measured turbine static pressure can be obtained through corresponding sensors; the theoretical speed rise rate and the theoretical turbine static pressure can be obtained from the technical documentation of the hydropower station.

[0037] It should be emphasized that the theoretical speed rise rate in this application is the maximum actual rise rate of the reservoir water level allowed within a certain period of time during the safe operation of the hydropower station; the theoretical turbine hydrostatic pressure in this application is the maximum actual net water pressure at the turbine volute inlet allowed during the safe operation of the hydropower station.

[0038] Table 2

[0039] Table 2 is a table of volute pressures measured on different dates provided by the present application. Table 2 gives the unit output (MW), upstream water level (m), downstream water level (m), volute pressure (Mpa) and guide vane opening values ​​of different units detected at 09:04 am, 15:00 pm and 18:25 pm on August 18, 2018, and 09:25 am and 13:50 pm on August 19, 2018.

[0040] In an optional implementation, whether each hydropower station in the cascade hydropower station is in a water conservation safety state can be determined by the following steps, specifically: For each hydropower station, the measured speed rise rate and the measured turbine hydrostatic pressure are obtained from the water resource data of the hydropower station; then, the measured speed rise rate of the hydropower station is compared with the theoretical speed rise rate, and the measured turbine hydrostatic pressure of the hydropower station is compared with the theoretical turbine hydrostatic pressure.

[0041] If the measured speed rise rate is less than the theoretical speed rise rate, and the measured turbine hydrostatic pressure is less than the theoretical turbine hydrostatic pressure, it is determined that the hydropower station is in a water conservation safety state; if the measured speed rise rate is greater than or equal to the theoretical speed rise rate, or the measured turbine hydrostatic pressure is greater than or equal to the theoretical turbine hydrostatic pressure, it is determined that the hydropower station is not in a water conservation safety state.

[0042] It is understandable that equipment in a hydropower station, such as a turbine generator, will generate vibrations during operation. The amplitude and frequency of these vibrations are important indicators for evaluating the operating status of the equipment. Excessive vibration may mean that the equipment is worn, loose, unbalanced or has other potential problems. In this application, the determination of whether a hydropower station is in a vibration-safe state mainly takes into account the actual working power of the turbine engine and the vibration conditions of the various components of the turbine engine.

[0043] In an optional implementation, whether each hydropower station in the cascade hydropower station is in a vibration safe state can be determined by the following method, specifically: Step 1: For each hydropower station, the power of the turbine engine (actual working power) is obtained from the water resource data of the hydropower station, which is recorded as the first power.

[0044] It should be noted that, in the process of the power of the water turbine engine rising from 0 to the maximum power (full load power), in certain power intervals (referred to as the preset power interval in this application), due to various reasons such as frequency resonance, there will be a situation where the vibration of various components of the water turbine engine is very large. In order to avoid the water turbine engine being damaged due to excessive vibration or the vibration triggering the protection trip, this application will focus on the actual working power of the water turbine engine at the current moment (i.e., the first power in this application).

[0045] The second step is to determine whether the first power is within a preset power range.

[0046] It should be noted that the preset power range can be obtained according to a variable power vibration test.

[0047] The third step is to quickly adjust the first power to the second power if the first power is within the preset power range; wherein the second power is outside the preset power range.

[0048] If it is determined that the first power is within the preset power range, it means that the vibration of various parts of the current hydro-generator is large, which may easily cause damage to the hydro-generator. At this time, the working power of the hydro-generator is quickly adjusted, for example, the first power can be quickly adjusted to the second power outside the preset power range to avoid excessive vibration of the hydro-generator due to frequency resonance and other reasons.

[0049] The fourth step is to determine whether the hydropower station is in a vibration safety state if the first power is outside the preset power range.

[0050] If it is determined that the first power is outside the preset power range, it can be determined that the hydro-generator will not vibrate excessively at the first power due to frequency resonance, etc. At this time, it is necessary to further determine whether the hydropower station is in a vibration safety state.

[0051] In an optional implementation, the process of determining whether the hydropower station is in a vibration-safe state is as follows: Firstly, for each hydropower station, the rotation speed of the turbine engine of the hydropower station and the actual vibration values ​​of different parts of the turbine engine are obtained from the water resource data of the hydropower station.

[0052] Then, after the actual water turbine engine speed is determined, the actual vibration values ​​of different parts of the water turbine engine measured at the speed are compared with the vibration allowable values ​​corresponding to the parts.

[0053] For each hydropower station, if at the current speed of the turbine engine, the actual vibration values ​​of different parts of the turbine engine are all less than the corresponding allowable vibration values, then the hydropower station is determined to be in a vibration safe state; if the actual vibration value of a certain part of the turbine engine is greater than or equal to the corresponding allowable vibration value of that part, then the hydropower station is determined to be not in a vibration safe state and there is a vibration risk.

[0054] Table 3

[0055] Table 3 is a table of vibration allowable values ​​of various parts of a hydro-turbine generator provided by the present application. As shown in Table 3, the hydro-turbine engine has different vibration allowable values ​​at different rotation speeds. For example, when the rotation speed is less than 100 r / min, the vibration allowable value of the vertical vibration of the thrust bearing bracket of the vertical unit of the hydro-turbine generator is 0.1 mm. When the actual vibration value of the vertical vibration of the thrust bearing bracket is greater than 0.1 mm when the rotation speed is less than 100 r / min, it is considered that the vertical unit of the hydro-turbine generator has equipment vibration risks.

[0056] When it is determined that each hydropower station in the cascade hydropower station is in a water conservation safety state and a vibration safety state, that is, when it is determined that each hydropower station is in a safe operation state, the steps of the subsequent embodiments of the present application can be continued.

[0057] It is understandable that if it is determined that each hydropower station in the cascade hydropower station is not in a safe operating state and there are water conservation safety issues or vibration safety risks, it is necessary to shut down for maintenance until the problem is fixed, and then restart the power generation facilities in each hydropower station; after restarting, verify that each hydropower station is in a safe operating state, and then execute the steps of the subsequent embodiments of this application.

[0058] S103, when it is determined that each of the hydropower stations is in the safe operation state, judging whether to perform water resource scheduling according to the water resource data of each of the hydropower stations, a preset electricity price plan and target historical data.

[0059] It is understandable that for hydropower generators, while being able to safely operate the power plant's power generation equipment, it is necessary to accurately adjust the water level of the reservoir corresponding to the power station. In this way, higher power generation revenue can be obtained while meeting the power demand of the power grid.

[0060] Specifically, first, the actual water consumption and actual power plant revenue of each hydropower station should be determined based on the water resource data of each hydropower station and the preset electricity price plan as the current actual data of the hydropower station. Then, based on the difference between the current actual data and the target historical data, it is determined whether water resource scheduling is needed. Among them, the target historical data includes the average water consumption and average power plant revenue of the current month.

[0061] If the difference between the current actual data and the target historical data is too large and exceeds the preset difference threshold, it is determined that water resource scheduling is required; otherwise, it is determined that water resource scheduling is not required. The specific value of the preset difference threshold is not limited in this application, and those skilled in the art can set the preset difference threshold according to actual needs.

[0062] In the subsequent embodiments of this application, the process of obtaining the current actual data and the process of obtaining the target historical data will be described in detail.

[0063] In an optional implementation, the following method can be used to determine the actual power generation water consumption and actual power plant revenue of each hydropower station based on the water resource data of each hydropower station and the preset electricity price plan as the current actual data of the hydropower station. Specifically: The first step is to obtain the actual power generation and actual water consumption in the target time period from the water resource data of each hydropower station, where the target time period is a period of time in the past with the current moment as the end point.

[0064] For example, the actual power generation and actual water consumption in the past hour can be obtained from the water resource data of hydropower station A obtained at the current moment, where the past hour is the target time period.

[0065] The actual power generation and the actual water consumption can be obtained through corresponding detection equipment. For example, the actual water consumption within the target time can be measured by an ultrasonic flow tester.

[0066] In the second step, for each hydropower station, the actual power generation and water consumption in the target time period are obtained based on the actual power generation and actual water consumption in the target time period.

[0067] Exemplarily, after obtaining the actual water consumption and actual power generation of hydropower station A in the last hour, the actual water consumption is divided by the actual power generation, and then divided by the target time period to obtain the actual water consumption for power generation.

[0068] The actual water consumption for power generation in this application reflects the capacity characteristics of water resources required per unit time and per unit power generation of the hydropower station. The actual water consumption for power generation is a high-level abstract data, which can be compared with the specific heat index of thermal power stations and the wind resource utilization coefficient of wind power stations to determine the degree and performance of resource utilization by power nodes; it reflects the specific function of power stations on resource energy consumption.

[0069] The third step is to determine the actual power plant revenue in the target time period for each hydropower station based on the corresponding segmented electricity price plan in the target time period and the actual water level of the hydropower station.

[0070] The segmented electricity price plan (referred to as the electricity price plan) in this application is an electricity fee plan related to the month and reservoir water volume.

[0071] For ease of understanding, the specific form of the segmented electricity price scheme is introduced by taking the segmented electricity price scheme corresponding to the cascade hydropower station including the upstream power station (also called the upstream reservoir power station) and the downstream power station (also called the downstream reservoir power station) as an example: (a) Upstream reservoir power station, i.e. upstream hydropower station: The upstream reservoir power station implements quarterly regulation and calculates prices according to different water levels in different seasons.

[0072] From January to March, the water level is between 250-260m above sea level. If the water level of the upstream reservoir is above 255m, the on-grid electricity price is J-0.001 / m; if the water level of the upstream reservoir is below 255m, the on-grid electricity price is J+0.001 / m; the electricity price for other water levels in the interval is: if the water level is higher than the upper limit, the upper limit is calculated, and if the water level is lower than the lower limit, the lower limit is calculated; where J in this application is the preset basic value of the on-grid electricity price.

[0073] From April to June, the water level is between 210-250 m above sea level. If the water level of the upstream reservoir is above 230 m, the on-grid electricity price is J-0.001 / m; if the water level of the upstream reservoir is below 230 m, the on-grid electricity price is J+0.001 / m; the electricity price for other water levels within the interval is calculated as follows: if the water level is above the upper limit, the upper limit is calculated; if the water level is below the lower limit, the lower limit is calculated.

[0074] From July to September, the water level is between 250-260 m above sea level. If the water level of the upstream reservoir is above 255 m, the on-grid electricity price is J-0.001 / m; if the water level of the upstream reservoir is below 255 m, the on-grid electricity price is J+0.001 / m; the electricity price for other water levels within the interval is calculated as follows: if the water level is above the upper limit, the upper limit is calculated; if the water level is below the lower limit, the lower limit is calculated.

[0075] From October to December, the water level is between 258 and 262 m above sea level. If the water level of the upstream reservoir is above 260 m, the on-grid electricity price is J-0.001 / m; if the water level of the upstream reservoir is below 260 m, the on-grid electricity price is J+0.001 / m; the electricity price for other water levels within the interval is calculated as follows: if the water level is above the upper limit, the upper limit is calculated; if the water level is below the lower limit, the lower limit is calculated.

[0076] The water levels of the upstream and downstream reservoirs are between 262-265 m and 115-120 m, and the electricity price is the full electricity price of US$0.073 per kilowatt-hour. The water levels of the upstream and downstream reservoirs are below 235 m and 100 m, which are unsafe water levels and cannot generate electricity.

[0077] Table 4

[0078] Table 4 is a table of the relationship between the reservoir water level and electricity price of an upstream hydropower station provided by this application. The upstream reservoir power station can directly give the increase or decrease price according to the water level in each quarter according to the content shown in Table 4, and obtain the actual electricity price PR corresponding to the current month 实 .

[0079] In Table 4, the water level is represented by the letter L; the unit of water level and median water level is meter; the actual electricity price PR 实The unit is (US dollars / degree). When the month is January to March, the water level is in the range of 250-260 meters, and the median water level is 255 meters; within this month range, if the water level L is less than the median water level of 255 meters, then PR 实 The value of is generated based on the full electricity price of 0.073 (US dollars / kWh) and the floating electricity price of 0.001. In each month in Table 4, when the water level L is greater than the median water level, PR 实 is (0.073+0.001) (USD / kWh); when the water level L is less than the median water level, PR 实 Yes (0.073-0.001) (US dollars / kWh).

[0080] In this application, by analyzing the water resource data, it is found that the data of each quarter has the characteristics of clustering, that is, the quarterly water levels in Table 4 show segmented characteristics, which reflects the characteristics of hydrology and water levels of hydropower stations. Only by better using the production factors of nature (referred to as primary indicators in this application) can the benefits of water resource utilization be maximized and the cost of hydropower water use be market-oriented. Therefore, this application adopts the method of targeting the median water level, comparing it with the median value of the historical water level (the historical water level is one of the data samples for deep learning), judging the measured water inflow and the amount of water entering the reservoir, so as to determine a reasonable power generation price.

[0081] It is understandable that if other patterns are discovered during the analysis of historical water resource data or other data, this may further guide the water level scheduling strategy adopted in this application, further improve the underlying logic of data-based scheduling agents emphasized in this application, and avoid errors caused by artificially abstracting data and specifying water resource scheduling plans.

[0082] (b) Downstream reservoir power station, i.e. downstream hydropower station: The downstream reservoirs implement day-ahead scheduling, regardless of the season.

[0083] The water level is between 105-110 m above sea level. If the water level of the downstream reservoir is above 107 m, the on-grid electricity price is J-0.001 / m; if the water level of the downstream reservoir is below 107 m; the electricity price for other water levels in the interval is: if the water level is higher than the upper limit, the upper limit is used for pricing; if the water level is lower than the lower limit, the lower limit is used for pricing.

[0084] Table 5 is a table of the relationship between the reservoir water level and electricity price of a downstream hydropower station provided by this application. The downstream reservoir power station can directly give the increase or decrease price according to the water level in each quarter according to the content shown in Table 5, and obtain the actual electricity price PR corresponding to the current month 实 In Table 5, the water level is represented by the letter L. The units of the water level and the median water level are both meters. The actual electricity price PR 实The unit is (US dollars / degree). In Table 5, when the water level L is greater than the median water level, PR 实 is (0.073+0.001) (USD / kWh); when the water level L is less than the median water level, PR 实 Yes (0.073-0.001) (US dollars / kWh).

[0085] Table 5

[0086] For each hydropower station in the cascade hydropower station, after obtaining the corresponding segmented electricity price plan for the target time period and the actual water level of the hydropower station, the actual power plant revenue for the target time period can be determined based on the following formula. The target formula is: (1.1) (1.2) (1.3) The meanings of the letters in formula (1.1), formula (1.2) and formula (1.3) are as follows: Q1 represents the fee that the power grid should pay to the hydropower station when the power grid fails and the hydropower station cannot generate electricity normally (pay as is); Q2 represents the actual income corresponding to the potential electricity at the current moment; Q3 represents the actual power generation income corresponding to the actual generated electricity at the current moment. The sum of formula (1.1) and formula (1.3) represents the actual power plant income of the hydropower station; the sum of formula (1.1), formula (1.2) and formula (1.3) represents the water assets of the hydropower station.

[0087] D represents the number of turbine generators included in the hydropower station, and D is a positive integer greater than 1; PR 实 is the actual electricity price corresponding to the current month; PR 平 represents the average electricity price in the target time period (i.e., the target pricing time period); i is a turbine generator in the hydropower station, i=1,2…D; P 实 is the power generation (actual electric energy) within the target time period; Gi is the rated power of the i-th turbine generator in the hydropower station; Hi is the continuous power generation time of the i-th turbine generator in the hydropower station at the rated power within the target pricing time period; F iJ is the derated power of the i-th turbine generator in the hydropower station; Hiz is the interruption duration of the i-th turbine generator in the hydropower station during the high water level period.

[0088] The high water level is the water level at which the hydropower station can generate electricity. If the contract stipulates that the hydropower station can generate electricity when the water level is within the range of 240-265m, then 240-265m is the high water level in this application.

[0089] Through deep learning of water level data, seasonal water level changes can be discovered and extended research can be conducted; general rules can be obtained through the data features of water level (or other quantities); through the target formula or generalized electricity price scheme in the aforementioned embodiment, based on basic data such as electricity charges and water consumption for power generation, related data such as power plant power generation revenue can be finally obtained; then the characteristics and correlations of data such as water level, electricity charges, power plant power generation revenue, power plant power generation costs, and water consumption for power generation can be extracted to establish a model of the median of water level and electricity price; through deep learning and association research, a reasonable scheduling strategy for hydropower station revenue and water resource assets can be obtained. Among them, the scheduling strategy is not limited to upstream quarterly power generation.

[0090] Table 6 is a data calculation table for cascade hydropower stations provided in this application. The cascade hydropower stations in Table 6 include an upstream hydropower station and a downstream hydropower station, a total of two hydropower stations. The data in Table 6 are calculated based on the water resource data of each hydropower station in the cascade hydropower station at the current moment, formula (1.1), formula (1.2) and formula (1.3).

[0091] Those skilled in the art can calculate the power generation income for other months in 2023 by referring to the electricity charges for different quarters and water levels provided in the above embodiments, formula (1.1), formula (1.2) and formula (1.3).

[0092] It should be noted that the upper dam in Table 6 refers to the upstream reservoir; the lower dam refers to the downstream reservoir; the upper plant refers to the plant of the hydropower station corresponding to the upstream reservoir; and the lower plant refers to the plant of the hydropower station corresponding to the downstream reservoir.

[0093] The unit of water volume in Table 6 is 10,000 m³; the unit of water level is m; the unit of flow rate is m³ / s; the unit of rainfall is mm; and the unit of electricity is 10,000 kw.h. The meanings of the letters in Table 6 refer to the introduction of the above embodiment and will not be repeated here.

[0094] Table 6

[0095] In an optional implementation, the target historical data of each hydropower station is obtained as follows: First, the historical water consumption for power generation and historical power plant revenue for each month in the past N years are counted, where N is an integer greater than or equal to 1.

[0096] For example, the amount of water entering the reservoir of hydropower station A in a specific month, such as January 2024, can be obtained; the reservoir capacity of hydropower station A in January 2024 can be obtained; the amount of water entering the reservoir minus the reservoir capacity can be used to obtain the water consumption of hydropower station A in January 2024. The power generation and power generation duration of hydropower station A in January 2024 are counted; the water consumption of hydropower station A in January 2024 is divided by the power generation of hydropower station A in January 2024, and then divided by the power generation duration of hydropower station A in January 2024, to obtain the historical power generation water consumption of hydropower station A in January 2024.

[0097] Figure 2A A schematic diagram of the historical water consumption for power generation of an upstream hydropower station corresponding to each month provided in an embodiment of the present application. Figure 2A The unit of the horizontal axis is cubic meter / kilowatt-hour; the unit of the vertical axis is month. Figure 2A The historical water consumption for power generation of the upstream hydropower stations from January to December 2023 and from January to December 2024 is given in the table. The data for November 2024 and December 2024 are the historical water consumption for power generation calculated based on historical data.

[0098] Figure 2B A schematic diagram of the historical water consumption for power generation in a downstream hydropower station corresponding to each month provided in an embodiment of the present application. Figure 2B The unit of the horizontal axis is cubic meter / kilowatt-hour; the unit of the vertical axis is month. Figure 2B The historical water consumption for power generation of downstream hydropower stations from January to December 2023 and from January to December 2024 is given in the table. The data for November 2024 and December 2024 are the historical water consumption for power generation calculated based on historical data.

[0099] based on Figure 2A and Figure 2B By comparing the water consumption for power generation, it can be clearly seen that it is more appropriate to implement quarterly regulation (also called quarterly scheduling) in the upstream, while it is more appropriate to implement day-ahead regulation (also called day-ahead scheduling) in the downstream.

[0100] As described in the above embodiment, the sum of formula (1.1) and formula (1.3) represents the actual power plant revenue of the hydropower station. Therefore, by substituting historical relevant data into formula (1.1) and formula (1.3), the historical power plant revenue can be obtained.

[0101] Figure 2C A schematic diagram of the historical power plant revenue corresponding to each month of an upstream hydropower station provided in an embodiment of the present application. Figure 2C The horizontal axis is in dollars; the vertical axis is in months. Figure 2CThe historical power plant revenues of the upstream hydropower stations for each month from January 2023 to December 2023 and from January 2024 to December 2024 are given in the table. The data for November 2024 and December 2024 are the historical power plant revenues calculated based on historical data.

[0102] Figure 2D A schematic diagram of the historical power plant revenue corresponding to each month of a downstream hydropower station provided in an embodiment of the present application. Figure 2D The horizontal axis is in dollars; the vertical axis is in months. Figure 2D The historical power plant revenues of downstream hydropower stations from January 2023 to December 2023 and from January 2024 to December 2024 are given in the table. The data for November 2024 and December 2024 are the historical power plant revenues calculated based on historical data.

[0103] Furthermore, the water asset data of each power plant in each month can also be calculated. The water asset of each power plant in this application refers to the sum of formula (1.1), formula (1.2) and formula (1.3).

[0104] Figure 3A A schematic diagram of the water assets corresponding to each month of an upstream hydropower station provided in an embodiment of the present application. Figure 3A The horizontal axis represents the amount of water assets in US dollars, and the vertical axis is in months. Figure 3A The historical water assets of the upstream hydropower stations for each month from January 2023 to December 2023 and from January 2024 to December 2024 are given in the table. The data for November 2024 and December 2024 are historical water assets calculated based on historical data.

[0105] Figure 3B A schematic diagram of the water assets corresponding to each month of a downstream hydropower station provided in an embodiment of the present application. Figure 3B The horizontal axis represents the amount of water assets in US dollars, and the vertical axis is in months. Figure 3B The historical water assets of the downstream hydropower stations for each month from January 2023 to December 2023 and from January 2024 to December 2024 are given in the table. The data for November 2024 and December 2024 are historical water assets calculated based on historical data.

[0106] For ease of understanding, this application Figure 2A , Figure 2B , Figure 2C , Figure 2D , Figure 3A and Figure 3BThe historical water consumption for power generation, historical power plant income and historical water assets (income) of each hydropower station in the cascade hydropower station including two hydropower stations, the upstream hydropower station and the downstream hydropower station, in each month are given. Those skilled in the art can refer to the method described in the above embodiment to obtain the historical water consumption for power generation, historical power plant income and historical water assets (income) of each hydropower station in other cascade hydropower stations in each month.

[0107] Then, for each month, a graph is drawn based on the N historical power generation water consumption corresponding to the month to obtain a historical power generation water consumption graph corresponding to the month.

[0108] For example, for January, the historical water consumption for power generation in January 2010, January 2011, January 2012, and even January 2024 can be obtained; a graph with the year as the horizontal axis and the historical water consumption for power generation as the historical water consumption map for power generation corresponding to January is generated.

[0109] Similarly, for February, we can get the historical water consumption for power generation in February 2010, February 2011, February 2012, and even February 2024; generate a graph with the year as the horizontal axis and the historical water consumption for power generation as the corresponding historical water consumption map for power generation in February.

[0110] For each month, based on the N historical power plant revenues corresponding to the month, a historical power plant revenue map corresponding to the month is obtained.

[0111] For example, for January, the historical power plant revenues of January 2010, January 2011, January 2012, and even January 2024 can be obtained; a graph with the horizontal axis being the year and the vertical axis being the historical power plant revenue is generated as the historical power plant revenue map for January.

[0112] Among them, the historical power generation water consumption map represents the relationship between historical power generation water consumption and time; the historical power plant revenue map represents the relationship between historical power plant revenue and time.

[0113] Finally, the average power generation water consumption corresponding to the historical power generation water consumption map corresponding to the current month and the average power plant revenue corresponding to the historical power plant revenue map corresponding to the current month are taken as target historical data.

[0114] The average water consumption for power generation is the average of the historical water consumption for power generation included in the historical water consumption map for power generation. The average power plant revenue is the average of the historical power plant revenue included in the historical power plant revenue map.

[0115] After obtaining the current actual data and the target historical data, it is determined whether to perform water resource scheduling based on the difference between the current actual data and the target historical data. Specifically: Determine whether the difference between the actual power generation water consumption and the average power generation water consumption is within the preset allowable value of the power generation water consumption difference (first judgment condition), and determine whether the difference between the actual power plant profit and the average power plant profit is within the preset allowable value of the power plant profit difference (second judgment condition).

[0116] If the first judgment condition and the second judgment condition are met at the same time, water resource scheduling is not required and the process directly returns to S101 ; if the above two judgment conditions are not met at the same time, it is considered that water resource scheduling is required and the process proceeds to S104 .

[0117] Furthermore, the actual water assets of the hydropower station corresponding to the current month of the hydropower station can also be calculated (the sum of formula (1.1), formula (1.2) and formula (1.3)); the average water assets of the hydropower station corresponding to the current month of the hydropower station can be obtained; and it can be determined whether the difference between the actual water assets corresponding to the current month and the average water assets is within the preset allowable value of the water asset difference (the third judgment condition), and whether water resources scheduling is required.

[0118] That is, when the first judgment condition, the second judgment condition and the third judgment condition are met, it is determined that water resource scheduling is not required, and the process directly returns to S101; otherwise, it is considered that water resource scheduling is required, and the process proceeds to S104.

[0119] It should be noted that the present application does not limit the values ​​of the preset allowable difference value of water used for power generation, the preset allowable difference value of power plant revenue and the preset allowable difference value of water assets, and those skilled in the art may limit the above values ​​as needed.

[0120] S104: If it is determined to perform water resource scheduling, a water resource scheduling plan is determined based on the water resource data and water resource scheduling model of each of the hydropower stations.

[0121] Among them, the water resources scheduling model is a model that is trained in advance and used to output water resources scheduling plans.

[0122] In an optional implementation, the training steps of the water resource scheduling model include: The first step is to obtain training data.

[0123] The training data in this application includes sample water resource data obtained by each hydropower station in the cascade hydropower stations at a sample time point, an electricity price plan at the sample time point, and a sample water resource scheduling plan at the sample time point.

[0124] It should be noted that the sample time point in this application is any one of the multiple time points of the operation of the hydropower station under all working conditions. In other words, the sample time point can be a time point when the hydropower station is in normal operation, and the data corresponding to the sample time point is the data corresponding to the normal operation of the hydropower station; the sample time point can also be a time point when the hydropower station conducts a load shedding test, a water conservation test, or a vibration test, and the data corresponding to the sample time point is the data corresponding to the hydropower station under the above experimental conditions.

[0125] Sample water resource data include historical water consumption for power generation, historical power plant revenue and historical average water assets; sample water resource scheduling plans include day-ahead scheduling and seasonal scheduling.

[0126] It is understandable that the water resource dispatching of each hydropower station in the cascade is a very complex process. At different points in time, the water level of the reservoir where each hydropower station is located, the actual operating parameters of the power generation facilities and the amount of precipitation are different, and the water resource dispatching scheme adopted is different.

[0127] It is understandable that the storage capacity of the upstream hydropower station in the cascade hydropower station is greater than the storage capacity of the downstream hydropower station; the water volume regulation space of the upstream hydropower station is greater than the water volume regulation space of the downstream hydropower station. Based on the above reasons, in the water resource scheduling scheme included in the training data given in this application, the upstream hydropower station adopts the quarterly regulation method (also called quarterly scheduling and quarterly regulation), and the downstream hydropower station adopts the day-ahead regulation method (also called day-ahead scheduling and day-ahead regulation).

[0128] Among them, seasonal regulation refers to adjusting the reservoir capacity of the hydropower station to store a part of the runoff during the flood season of the year for use during the dry season. This regulation method enables the hydropower station to achieve effective redistribution of water resources within a year, especially between seasons with uneven water resources distribution. Seasonal regulation can store excess water in the season of sufficient water and release the stored water in the season of scarce water to ensure the stable operation and continuous power generation of the hydropower station.

[0129] Day-ahead dispatch refers to the redistribution of runoff within a day and night. This regulation method is mainly used to deal with short-term (such as within a day) changes in water resources and fluctuations in electricity demand. Through day-ahead dispatch, hydropower stations can flexibly adjust their power generation plans and water resource allocation according to real-time water resource conditions and electricity demand to ensure the stability and reliability of power supply.

[0130] Seasonal dispatch focuses on the balanced allocation of water resources between seasons to achieve long-term stable operation and power generation efficiency, while day-ahead regulation focuses more on the dynamic balance of water resources and power demand in the short term to ensure the stability and reliability of power supply. Hydropower stations adopt these two regulation methods in combination according to their own reservoir conditions, water resources conditions, and power market demand to achieve efficient use of water resources and optimization of power supply.

[0131] It is precisely because of the day-ahead scheduling of the downstream and the seasonal scheduling of the upstream that the calculation of water assets is meaningful. Both pursue the balance between cost and economy. The downstream is mainly for power generation, while the upstream is mainly for controlling the water volume and water level of the entire basin. Figure 2A and Figure 2B In the comparison between the upstream and downstream day-ahead dispatch and quarterly dispatch, the kilowatt-hour water consumption is 0.018 m 3 / kWh and 0.026m 3 / kWh, because more emphasis is placed on monthly profits these days, indicating that downstream power generation is more efficient, while upstream quarterly scheduling focuses more on the overall basin, taking power generation into account, and by comparing the monthly accumulation of upstream and downstream water assets, it is possible to clearly see that there are more details of water assets upstream than downstream, which further illustrates the importance of adopting quarterly conditions upstream.

[0132] By abstracting and analyzing high-order features of the data, especially the research on water consumption for power generation and water assets, the two scheduling methods are able to implement different scheduling strategies for the upstream and downstream of the hydropower station through data-driven intelligent entities with two scheduling functions, under the premise of ensuring the safety of the smart hydropower station, that is, when all operating conditions meet the requirements of load shedding, variable power vibration measurement and water conservation safety.

[0133] Figure 4 A schematic diagram of a water resource scheduling scheme for a cascade hydropower station provided in an embodiment of the present application. The cascade hydropower station includes an upstream hydropower station and a downstream hydropower station. Figure 4 The meanings of the letters are as follows: J1 represents the cost electricity price; S1 represents the actual water level of the upstream hydropower station; S2 represents the actual water level of the downstream hydropower station; R represents the minimum water level allowed for power generation at the downstream hydropower station; Q represents the minimum water level allowed for power generation at the upstream hydropower station; J represents the current on-grid transaction electricity price, which is also the basic value of the preset on-grid electricity price mentioned in the aforementioned embodiment.

[0134] Combination Figure 4 As shown in the figure, the water resource dispatching plan of the cascade hydropower station is as follows: S401, determine the cost electricity price J1, the measured water level S1 of the upstream hydropower station and the measured water level S2 of the downstream hydropower station.

[0135] S402, determine whether S2<R.

[0136] Determine whether the measured water level of the downstream hydropower station is less than the minimum water level allowed for power generation at the downstream hydropower station. If S2 is less than R, proceed to S403; otherwise, proceed to S406.

[0137] S403, determine whether S1>Q and the cost electricity price<on-grid electricity price.

[0138] That is, it is determined whether the measured water level of the upstream hydropower station is greater than the minimum water level allowed for power generation at the upstream hydropower station, and whether the cost electricity price is less than the grid-connected electricity price (the grid-connected electricity price at the current moment). If yes, it proceeds to S404; otherwise, it proceeds to S407.

[0139] S404, conduct quarterly regulation of upstream hydropower stations.

[0140] Among them, the quarterly adjustment in this application is also called seasonal scheduling.

[0141] S405, to make day-ahead adjustments for downstream hydropower stations.

[0142] Among them, the day-ahead adjustment in this application is also called day-ahead scheduling.

[0143] S406, waiting for a shutdown instruction due to a power grid failure or water shortage in the power plant.

[0144] S407, determine whether the on-grid electricity price changes J=J±0.001, and the cost electricity price J1<J.

[0145] If yes, go to step S404; otherwise, go to S408.

[0146] S408, high frequency adjustment of water level, changing water level.

[0147] It should be emphasized that Figure 4 The water resource scheduling scheme shown in the figure is only for the convenience of understanding, and is a water resource scheduling scheme that may be used in the actual working process. Different targeted water resource scheduling schemes will be adopted for different cascade hydropower stations, at different times, and when the water resource data of each hydropower station is different.

[0148] The second step is to input the training data into a deep learning model to obtain a predicted water resources scheduling plan corresponding to the training data.

[0149] Exemplarily, convolutional neural networks, long short-term memory networks, gated recurrent units, etc. can be used as deep learning models in this application.

[0150] The sample water resource data obtained at the sample time point for each hydropower station in the cascade hydropower stations in the training data and the electricity price plan at the sample time point are input into the deep learning model, and the deep learning model inputs the predicted water resource scheduling plan.

[0151] In the third step, taking the sample water resources scheduling plan as the true value, the back propagation error of the sample water resources scheduling plan and the predicted water resources scheduling plan is determined through the loss function, and the network parameters of the deep learning model are updated based on the back propagation error until the back propagation error reaches the set value to obtain a trained water resources scheduling model.

[0152] In this application, the sample water resource scheduling plan at the sample time point in the training data is taken as the true value, and the difference between the sample water resource scheduling plan and the predicted water resource scheduling plan, that is, the back propagation error, is calculated through the loss function. The back propagation error is used as the loss value, and the network parameters in the deep learning model, such as weights and biases, are updated through the loss value to reduce future back propagation errors. When the latest back propagation error reaches the set value, the training is stopped to obtain a trained water resource scheduling model.

[0153] Common loss functions include mean square error and mean absolute error, etc. The specific form of the loss function is not limited in this application.

[0154] In summary, the present application provides a method for water resource scheduling of cascade hydropower stations, including: obtaining water resource data of each hydropower station in the cascade hydropower station at the current moment; for each hydropower station, judging whether the hydropower station is in a safe operating state based on the water resource data of the hydropower station; when it is determined that each hydropower station is in a safe operating state, judging whether to perform water resource scheduling based on the water resource data of each hydropower station, a preset electricity price plan and target historical data; if it is determined to perform water resource scheduling, then determining a water resource scheduling plan based on the water resource data of each hydropower station and a water resource scheduling model. In this way, by replacing the method of manual experience with a water resource scheduling model, the most excellent water resource scheduling plan can be determined based on the water resource data of each hydropower station at different times, under the premise of ensuring the safe operating state of the hydropower station, so as to obtain as high a power generation income as possible.

[0155] It should be noted that in addition to the method for determining whether each hydropower station in a cascade hydropower station is in a safe operating state mentioned in the aforementioned embodiment of the present application, it is also necessary to conduct a load shedding test on each reservoir in the cascade hydropower station before the cascade hydropower station is officially put into operation to determine whether the operating parameters of each hydropower station in the cascade hydropower station meet the preset load shedding test index requirements under emergency conditions; that is, to determine whether the power generation equipment of each hydropower station in the cascade hydropower station can work normally under emergency conditions, thereby verifying the dynamic performance of the equipment under extreme conditions.

[0156] Among them, load shedding is because the power load of end users is reduced (for example, failure of large-scale power equipment or power outage due to line failure in a large area), and the power generation of the power plant's turbine generator exceeds the amount delivered to users. At this time, the power plant is required to reduce the power generation to a value that is consistent with the actual load; or it is due to internal reasons of the power plant, the grid outlet circuit breaker suddenly trips, and the load of the turbine generator suddenly drops to basically zero. The power plant executes these actions.

[0157] After the load shedding occurs in the hydro-turbine generator set, the huge residual energy causes the speed of the unit to rise rapidly. The speed governor quickly closes the guide vanes, and after a period of adjustment, it stabilizes and operates under no-load conditions again. During the load shedding process, in addition to the maximum speed increase value and the maximum water hammer pressure increase value, the quality indicators of the load shedding dynamic process must also be evaluated.

[0158] The load rejection test indicators in this application include but are not limited to: speed rise rate, speed adjustment time, speed overshoot, volute water pressure rise rate, lead angle closing time, tailwater pipe vacuum, etc.

[0159] It can be understood that when a cascade hydropower station conducts a load shedding test, it is only when each operating parameter in the test process, such as the speed rise rate, speed adjustment time, speed overshoot, volute water pressure rise rate, lead angle closing time, and tailwater pipe vacuum, meets the corresponding load shedding test indicators that the cascade hydropower station is determined to have passed the load shedding test; otherwise, the cascade hydropower station needs to be overhauled until the cascade hydropower station can meet the requirements of the load shedding indicators, and then the contents of S101-S104 in this application can be executed.

[0160] It should be emphasized that the water conservation test, vibration test and load rejection test mentioned in the above embodiments can obtain a large amount of experimental data, which can be digitized and become a data resource. After obtaining a large amount of experimental data, that is, a large amount of data resources, various required deep learning models can be trained based on deep learning; after obtaining the water resources data at the current moment, various prediction index data indicating the safety of the hydropower station can be obtained based on the trained deep learning model; including but not limited to: speed adjustment time, lead angle closing time, etc., these prediction index data are compared with the real index data specified in the contract, which can effectively determine whether there are safety hazards in the hydropower station, and can make a more accurate estimate of the safety of the hydropower station indicated by the water resources data at the current moment. In this way, various risks that may arise in the hydropower station during the power generation process can be effectively avoided, so that the turbine generators of each hydropower station in the cascade hydropower station are operated under safe conditions.

[0161] Figure 5 A schematic diagram of the interaction between a power plant and a power grid provided in an embodiment of the present application. Figure 5A schematic diagram of the interaction between a cascade hydropower station and a power grid is given, including an upstream hydropower station and a downstream hydropower station, a total of two hydropower stations. Figure 5 The power plant side includes the upstream hydropower station and the downstream hydropower station. Among them, the upstream hydropower station implements seasonal scheduling, and the downstream hydropower station implements day-ahead scheduling.

[0162] Combination Figure 5 As shown in the figure, the upstream hydropower station analyzes the characteristic production factor data to find the seasonal variation pattern of the water level of the upstream hydropower station; and determines the median water level in each season. On the one hand, the upstream hydropower station calculates the electricity price operator function (i.e., PR real) according to the determined median water level; on the other hand, it notifies the downstream hydropower station to determine the median water level of the downstream hydropower station. Based on the water level and electricity price operator function, the upstream hydropower station calculates the power plant revenue (power plant power generation revenue) and the kilowatt-hour water consumption (water consumption per kilowatt-hour), and sends the calculated power plant revenue and kilowatt-hour water consumption to the downstream hydropower station.

[0163] While determining the median water level and the electricity price operator function (i.e., PR real), the downstream hydropower station receives the power plant revenue and power consumption sent by the upstream hydropower station, calculates the total power plant revenue and total power consumption of the cascade hydropower stations, and sends the calculated data to the grid side.

[0164] It should be noted that the grid side needs to calculate the grid stability in real time. Only when the grid is stable can subsequent work be carried out, including receiving the total power plant revenue and total kilowatt-hour water consumption sent by the downstream hydropower station, and then conducting deep learning and updating based on the dispatch strategy library, and feeding back the dispatch strategy to the downstream hydropower station.

[0165] Next, the downstream hydropower station will successively calculate the safety and stability of the downstream units (i.e., calculate the safety and stability of the downstream units), execute the clearing power and unit actions, and send the relevant information to the power grid; the upstream hydropower station will successively calculate the safety and stability of the upstream units (i.e., calculate the safety and stability of the upstream units), and send the calculation results to the power grid, and apply to the power grid for the transaction power and electricity price; after receiving the above data, the power grid will collect them; according to the results of the downstream clearing power and the upstream application power, the stability of the power grid will be calculated again. Since the upstream hydropower station has an impact on the safety of the entire water area, in the process of calculating the stability of the power grid again according to the results of the downstream clearing power and the upstream application power, the value of the upstream application power is more important than the value of the downstream clearing power.

[0166] After determining that the grid is stable, the grid side sends the clearing electricity price and electricity dispatch instructions to the upstream hydropower station; the upstream hydropower station executes the clearing electricity and unit action; the upstream and downstream hydropower stations respectively calculate the hydropower assets (hydropower assets are the water assets mentioned in the above embodiments).

[0167] Figure 6 A flow chart of another water resource scheduling method provided in an embodiment of the present application. Figure 6 As shown, another water resource scheduling method of the present application includes: S601, obtain hydrological data of upstream and downstream reservoirs as basic data.

[0168] S602, perform digital calculations of upstream and downstream reservoir capacity, flow, etc.

[0169] S603, perform digital calculations for water conservation safety.

[0170] S604, performing hydropower generation safety calculations.

[0171] S605: Determine whether water resource scheduling is required based on upstream and downstream hydrological data.

[0172] If water resource scheduling is required, proceed to S606; if water resource scheduling is not required, return to S602.

[0173] S606: Provide a scheduling plan based on upstream and downstream hydrological data and water resources scheduling model.

[0174] Among them, the scheduling plan is the water resources scheduling plan; in this plan, the downstream hydropower stations implement day-ahead scheduling, the upstream hydropower stations implement quarterly scheduling (also called seasonal scheduling), and it is given whether to carry out high-frequency scheduling of the water level in the hydropower stations.

[0175] For the contents of S601-S606, please refer to the introduction of the relevant contents in S101-S104 and S401-S408, which will not be repeated here.

[0176] Based on the water resource scheduling method for the cascade hydropower station provided in the aforementioned embodiment, the present application also discloses a water resource scheduling device for the cascade hydropower station. Figure 7 A schematic diagram of the structure of a water resource scheduling device provided in an embodiment of the present application. Figure 7 As shown, the water resource scheduling device 700 disclosed in the present application includes: The data acquisition module 701 is used to acquire the water resource data of each hydropower station in the cascade hydropower station at the current moment; A safety status determination module 702 is used to determine, for each of the hydropower stations, whether the hydropower station is in a safe operating state according to the water resources data of the hydropower station; The water resource scheduling judgment module 703 is used to judge whether to perform water resource scheduling according to the water resource data of each hydropower station, the preset electricity price scheme and the target historical data when it is determined that each hydropower station is in the safe operation state; the target historical data includes the average water consumption for power generation and the average power plant revenue corresponding to the month at the current time; The water resource scheduling scheme determination module 704 is used to determine the water resource scheduling scheme based on the water resource data and water resource scheduling model of each hydropower station if it is determined to perform water resource scheduling; the water resource scheduling model is a pre-trained model for outputting the water resource scheduling scheme.

[0177] In an optional implementation, the security status determination module 702 includes: A first data acquisition unit is used to acquire, for each of the hydropower stations, a measured velocity rise rate and a measured turbine hydrostatic pressure from water resource data of the hydropower station; A first determination unit is used for, for each of the hydropower stations, determining that the hydropower station is in the water conservation safety state if the measured speed increase rate is less than the theoretical speed increase rate and the measured turbine hydrostatic pressure is less than the theoretical turbine hydrostatic pressure; The second determination unit is used to determine that the hydropower station is not in the water conservation safety state if the measured speed increase rate is greater than or equal to the theoretical speed increase rate, or the measured turbine hydrostatic pressure is greater than or equal to the theoretical turbine hydrostatic pressure.

[0178] In an optional implementation, the security status determination module 702 includes: A second data acquisition unit is used to acquire the power of the turbine engine from the water resource data of each hydropower station, and record it as the first power; A first judging unit, configured to judge whether the first power is within a preset power range; a third determining unit, configured to adjust the first power to a second power if the first power is within the preset power interval; and the second power is outside the preset power interval; The fourth determination unit is configured to determine whether the hydropower station is in the vibration safety state if the first power is outside the preset power range.

[0179] In an optional implementation manner, the fourth determining unit includes: A first data acquisition subunit is used to acquire, for each of the hydropower stations, the rotation speed of the turbine engine and actual vibration values ​​of different parts of the turbine engine from the water resource data of the hydropower station; A first judgment subunit is used for, for each of the hydropower stations, determining that the hydropower station is in the vibration safety state if the actual vibration value of each of the parts is less than the vibration allowable value corresponding to the part at the rotation speed; The second judgment subunit is used to determine that the hydropower station is not in the vibration safety state otherwise.

[0180] In an optional implementation, the water resource scheduling device 700 further includes: The load shedding test module is used to perform a load shedding test on the cascade hydropower stations to determine whether the operating parameters of each hydropower station in the cascade hydropower stations meet the requirements of preset load shedding test indicators.

[0181] In an optional implementation, the water resource scheduling judgment module 703 includes: an actual data acquisition unit, configured to determine, based on the water resource data of each hydropower station and the preset electricity price scheme, the actual water consumption for power generation of each hydropower station and the actual power plant revenue of each hydropower station as current actual data; The second judgment unit is used to judge whether to perform water resource scheduling based on the difference between the current actual data and the target historical data.

[0182] In an optional implementation, the actual data acquisition unit includes: A second data acquisition subunit is used to acquire, for each of the hydropower stations, the actual power generation and actual water consumption in a target time period from the water resource data of the hydropower station; the target time period is a period of time in the past with the current moment as the end point; A third data acquisition subunit is used to obtain, for each of the hydropower stations, the actual power generation and water consumption in the target time period based on the actual power generation and water consumption in the target time period; The fourth data acquisition subunit is used to determine, for each of the hydropower stations, the actual power plant revenue in the target time period based on the electricity price plan corresponding to the target time period and the actual water level of the hydropower station.

[0183] In an optional implementation, the water resource scheduling device 700 further includes a target historical data acquisition module, and the target historical data acquisition module specifically includes: A historical data acquisition unit, used to count the historical water consumption for power generation and the historical power plant revenue for each month in the past N years; N is an integer greater than or equal to 1; A map acquisition unit is used to obtain, for each month, a historical power generation water consumption map corresponding to the month based on N historical power generation water consumption corresponding to the month; and obtain a historical power plant revenue map corresponding to the month based on N historical power plant revenues corresponding to the month; the historical power generation water consumption map represents the relationship between the historical power generation water consumption and time; the historical power plant revenue map represents the relationship between the historical power plant revenue and time; The target historical data acquisition unit is used to use the average power generation water consumption corresponding to the historical power generation water consumption map corresponding to the month where the current moment is located, and the average power plant revenue corresponding to the historical power plant revenue map corresponding to the month where the current moment is located, as the target historical data.

[0184] In an optional implementation, the water resource scheduling device 700 further includes: A training data acquisition module is used to acquire training data; the training data includes sample water resource data of each hydropower station in the cascade hydropower stations at a sample time point, an electricity price plan at the sample time point, and a sample water resource scheduling plan at the sample time point; the sample time point is any time point among multiple time points at which the hydropower station operates under full working conditions; the sample water resource data includes historical water consumption for power generation, historical power plant revenue, and historical average water assets; the sample water resource scheduling plan includes day-ahead scheduling and seasonal scheduling; A debugging scheme prediction module is used to input the training data into a deep learning model to obtain a predicted water resource scheduling scheme corresponding to the training data; The water resource model training module is used to take the sample water resource scheduling plan as the true value, determine the back propagation error between the sample water resource scheduling plan and the predicted water resource scheduling plan through a loss function, and update the network parameters of the deep learning model based on the back propagation error until the back propagation error reaches a set value, thereby obtaining the water resource scheduling model.

[0185] Based on the water resource scheduling method and device for the cascade hydropower station provided in the aforementioned embodiments, the present application also provides a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements some or all of the steps in the water resource scheduling method for the cascade hydropower station mentioned above.

[0186] Based on the water resource scheduling method and device for cascade hydropower stations provided in the above embodiments, the present application further provides an electronic device, including: a memory having a computer program stored thereon; The processor is used to execute the computer program in the memory to implement part or all of the steps in the water resources scheduling method for cascade hydropower stations provided in the above embodiment.

[0187] It should be noted that each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The device embodiment described above is merely schematic, in which the unit described as a separate component may or may not be physically separated, and the component prompted as a unit may or may not be a physical unit, that is, it may be located in one place, or it may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative work.

[0188] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A water resource dispatching method for a cascade hydropower station, characterized in that: The method comprises: Obtain water resource data of each hydropower station in the cascade hydropower station at the current moment; For each of the hydropower stations, judging whether the hydropower station is in a safe operating state according to the water resources data of the hydropower station; When it is determined that all the hydropower stations are in the safe operation state, judging whether to perform water resource scheduling according to the water resource data of each hydropower station, the preset electricity price scheme and the target historical data; the target historical data includes the average water consumption for power generation and the average power plant revenue corresponding to the month at the current moment; If it is determined to carry out water resource scheduling, a water resource scheduling plan is determined based on the water resource data and water resource scheduling model of each hydropower station; the water resource scheduling model is a pre-trained model for outputting a water resource scheduling plan; the water resource scheduling plan includes day-ahead scheduling and seasonal scheduling.

2. The method according to claim 1, characterized in that The safe operation state includes a water conservation safety state; For each of the hydropower stations, judging whether the hydropower station is in a safe operating state according to the water resources data of the hydropower station includes: For each of the hydropower stations, obtaining the measured velocity rise rate and the measured turbine hydrostatic pressure from the water resource data of the hydropower station; For each of the hydropower stations, if the measured speed increase rate is less than the theoretical speed increase rate, and the measured turbine hydrostatic pressure is less than the theoretical turbine hydrostatic pressure, it is determined that the hydropower station is in the water conservation safety state; If the measured speed increase rate is greater than or equal to the theoretical speed increase rate, or the measured turbine hydrostatic pressure is greater than or equal to the theoretical turbine hydrostatic pressure, it is determined that the hydropower station is not in the water conservation safety state.

3. The method according to claim 1, characterized in that The safe operation state includes a vibration safety state. For each of the hydropower stations, judging whether the hydropower station is in a safe operation state according to the water resources data of the hydropower station includes: For each of the hydropower stations, the power of the turbine engine is obtained from the water resource data of the hydropower station, and recorded as the first power; Determining whether the first power is within a preset power range; If the first power is within the preset power range, the first power is adjusted to the second power; the second power is outside the preset power range; If the first power is outside the preset power range, it is determined whether the hydropower station is in the vibration safety state.

4. The method according to claim 3, characterized in that: The determining whether the hydropower station is in the vibration safe state comprises: For each of the hydropower stations, the rotation speed of the turbine engine and actual vibration values ​​of different parts of the turbine engine are obtained from the water resource data of the hydropower station; For each of the hydropower stations, if the actual vibration value of each of the parts is less than the vibration allowable value corresponding to the part at the rotation speed, it is determined that the hydropower station is in the vibration safety state; Otherwise, it is determined that the hydropower station is not in the vibration safe state.

5. The method according to claim 1, characterized in that Before obtaining the water resource data of each hydropower station in the cascade hydropower station at the current moment, the method further includes: A load shedding test is performed on the cascade hydropower stations to determine whether the operating parameters of each hydropower station in the cascade hydropower stations meet the requirements of preset load shedding test indicators.

6. The method according to claim 1, characterized in that The determining whether to perform water resource dispatch according to the water resource data of each hydropower station, the preset electricity price scheme and the target historical data includes: Based on the water resource data of each hydropower station and the preset electricity price scheme, determine the actual water consumption for power generation of each hydropower station and the actual power plant revenue of each hydropower station as current actual data; Based on the difference between the current actual data and the target historical data, it is determined whether to perform water resource scheduling.

7. The method according to claim 6, characterized in that The determining of the actual water consumption for power generation of each hydropower station and the actual power plant revenue of each hydropower station based on the water resource data of each hydropower station and the preset electricity price scheme includes: For each of the hydropower stations, the actual power generation and actual water consumption in a target time period are obtained from the water resource data of the hydropower station; the target time period is a period of time in the past with the current moment as the end point; For each of the hydropower stations, based on the actual power generation and actual water consumption during the target time period, the actual power generation and water consumption during the target time period are obtained; For each of the hydropower stations, the actual power plant revenue for the target time period is determined based on the electricity price plan corresponding to the target time period and the actual water level of the hydropower station.

8. The method according to any one of claims 1 to 7, characterized in that The method for acquiring the target historical data includes: Count the historical water consumption for power generation and the historical power plant revenue for each month in the past N years; N is an integer greater than or equal to 1; For each month, based on the N historical power generation water consumption corresponding to the month, a historical power generation water consumption map corresponding to the month is obtained; and based on the N historical power plant revenues corresponding to the month, a historical power plant revenue map corresponding to the month is obtained; the historical power generation water consumption map represents the relationship between the historical power generation water consumption and time; the historical power plant revenue map represents the relationship between the historical power plant revenue and time; The average power generation water consumption corresponding to the historical power generation water consumption map corresponding to the month of the current moment and the average power plant revenue corresponding to the historical power plant revenue map corresponding to the month of the current moment are used as the target historical data.

9. The method according to any one of claims 1 to 7, characterized in that: The training steps of the water resource scheduling model include: Acquire training data; the training data includes sample water resource data of each hydropower station in the cascade hydropower stations at a sample time point, an electricity price plan at the sample time point, and a sample water resource scheduling plan at the sample time point; the sample time point is any time point among multiple time points at which the hydropower station operates under full working conditions; the sample water resource data includes historical water consumption for power generation, historical power plant revenue, and historical average water assets; the sample water resource scheduling plan includes day-ahead scheduling and seasonal scheduling; Inputting the training data into a deep learning model to obtain a predicted water resources scheduling plan corresponding to the training data; Taking the sample water resource scheduling plan as the true value, the back propagation error between the sample water resource scheduling plan and the predicted water resource scheduling plan is determined through the loss function, and the network parameters of the deep learning model are updated based on the back propagation error until the back propagation error reaches the set value, thereby obtaining the water resource scheduling model.

10. A water resource dispatching device for a cascade hydropower station, characterized in that: The device comprises: A data acquisition module is used to obtain water resource data of each hydropower station in the cascade hydropower station at the current moment; A safety status determination module, for determining, for each of the hydropower stations, whether the hydropower station is in a safe operating state according to the water resources data of the hydropower station; A water resource scheduling judgment module is used to determine whether to perform water resource scheduling based on the water resource data of each hydropower station, a preset electricity price plan and target historical data when it is determined that each hydropower station is in the safe operation state; the target historical data includes the average power generation water consumption and the average power plant revenue corresponding to the month at the current time; A water resource scheduling scheme determination module is used to determine the water resource scheduling scheme based on the water resource data and water resource scheduling model of each hydropower station if it is determined to perform water resource scheduling; the water resource scheduling model is a pre-trained model for outputting the water resource scheduling scheme; the water resource scheduling scheme includes day-ahead scheduling and seasonal scheduling.

Images