A short-, medium- and long-term coupled water storage scheduling method and system based on digital twins

Abstract

The present invention belongs to the intersection of reservoir water storage scheduling and new generation information technology, and in particular relates to a short-, medium- and long-term coupled water storage scheduling method and system based on digital twins. The method includes the following steps: obtaining initial reservoir data, determining a medium- and long-term water storage scheduling plan and a short-term water storage scheduling plan, comparing the water level values of the nearest ten-day node in the future medium- and long-term and the water level values of the nearest ten-day node in the future short-term, issuing a water storage risk warning within the system based on the comparison results, and making corrections and adjustments to the scheduling process within the forecast period, and displaying and outputting the reservoir scheduling process on the digital twin system interface. The present invention is suitable for real-time water storage scheduling analysis and decision-making during the reservoir water storage period and the construction of its digital twin system. It determines the medium- and long-term water storage optimal control indicators through an optimization algorithm, and conducts real-time analysis and decision-making on the reservoir scheduling process in combination with short-term forecasts, so that it continuously approaches the optimal scheduling process, providing technical support for reservoir management departments to fully utilize water resources.

Description

Technical Field

[0001] The present invention belongs to the intersection of reservoir water storage scheduling and new generation information technology, and in particular relates to a short-, medium- and long-term coupled water storage scheduling method and system based on digital twins. Background Art

[0002] Reservoir water storage and scheduling is of great significance to the efficient use of water resources. With the development of reservoir scheduling technology, many scholars have conducted research on reservoir water storage and scheduling, focusing on the determination of water storage strategies under typical conditions and the research on water storage and scheduling optimization models.

[0003] The paper "Multi-Objective Stochastic Programming and Cluster Analysis for Reservoir Cluster Water Storage Scheduling" constructs a multi-objective stochastic programming model for reservoir clusters based on indicators such as power generation, storage capacity, ecology, and upstream and downstream flood control safety. It analyzes the water storage patterns of cascade reservoir clusters for typical dry years and proposes a reference water storage scheduling strategy, which can provide a reference for the formulation of reservoir cluster water storage plans. The paper "Water Storage Scheduling Strategy for Cascade Reservoirs under Extreme Dry Conditions: A Case Study of the Jinsha River Lower Reaches - Three Gorges Cascade" combines the principle of maximizing water storage benefits with water supply scheduling requirements to propose a water storage scheduling method for cascade reservoirs under extreme dry conditions. It also defines a coordinated scheduling strategy for the Jinsha River and the Three Gorges Cascade to meet water supply scheduling requirements, as well as the principles and sequence for water storage when all cascade reservoirs cannot be fully filled. The paper "Research on Joint Water Storage and Scheduling of a Giant Reservoir Group" adopts zoning strategy, large system aggregation and decomposition, parameter simulation optimization method and parallel successive approximation optimization algorithm to construct a multi-objective joint optimization scheduling model for advance water storage, and verifies the model solution effect with a giant reservoir group of 30 reservoirs as the research object, which can provide a new solution research method for water storage and scheduling.

[0004] Although these studies have certain guiding significance for the actual water storage and scheduling of reservoirs, they are still scheme studies carried out under certain conditions. They cannot flexibly adjust the scheduling process according to real-time and rolling forecast water inflows under forecast uncertainty conditions. Therefore, they provide weak support for real-time water storage and scheduling decisions, because forecast uncertainty has a greater impact on reservoir water storage and scheduling. Summary of the Invention

[0005] The present invention aims to overcome the problems existing in the prior art by proposing a short-, medium-, and long-term coupled water storage scheduling method and system based on digital twins to meet the decision-making and analysis needs of real-time water storage scheduling. This method addresses the technical problems of the prior art, which lack support for real-time water storage scheduling decisions and the significant impact of forecast uncertainty on reservoir water storage scheduling.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The present invention designs a short-, medium- and long-term coupled water storage scheduling method based on digital twins, which includes the following steps:

[0008] Access basic reservoir operation data, real-time operation data, reservoir storage operation constraints, and future inflow forecast data from the digital twin system;

[0009] Medium- and long-term water storage scheduling plan; determine the medium- and long-term water storage control target of the reservoir based on the water storage scheduling plan or optimization algorithm, and obtain the water level value of the nearest ten-day node in the medium and long term ;

[0010] Short-term water storage scheduling plan: Based on the real-time water level and short-term water inflow forecast, combined with the short-term power generation demand, calculate the reservoir water level process in each period in the next ten days, determine the short-term scheduling plan, and obtain the water level value of the nearest ten-day node in the future short term ;

[0011] The water level value of the nearest ten-day node in the future medium and long term , the water level value of the nearest ten-day node in the short term in the future Comparisons are made, and based on the comparison results, water storage risk warnings are issued within the system, and the scheduling process within the forecast period is corrected and adjusted until the water level is within an acceptable range at the end of the forecast period;

[0012] The reservoir scheduling process is displayed and output on the digital twin system interface.

[0013] As a preferred solution, the digital twin system is used to access basic reservoir operation data, real-time operation data, reservoir water storage operation constraints, and future inflow forecast data, specifically:

[0014] Access basic reservoir operation data, including characteristic parameters such as reservoir dead water level, flood limit water level, normal water level, output coefficient, as well as curve data such as water level storage capacity curve, discharge capacity curve, and tailwater level curve;

[0015] Access to real-time reservoir operation data, including real-time water level, inflow and outflow data;

[0016] The constraints on reservoir water storage scheduling during the access water storage period include:

[0017] Reservoir water level constraints:

[0018] ;

[0019] For the reservoir t The lowest water level allowed during the period, For the reservoir t The maximum water level allowed during the time period;

[0020] Outbound flow constraints:

[0021] ;

[0022] For the reservoir t The minimum outbound flow allowed within the time period, For the reservoir t The maximum outbound flow allowed within the time period;

[0023] Access to future inflow runoff forecast data, including: mid- to long-term forecast inflow runoff on a ten-day scale during the water storage period , short-term water inflow forecast for the next 10 days in the current period .

[0024] Furthermore, the minimum outflow allowed by the reservoir during period t is Obtained as follows:

[0025] Get the water storage period of the reservoir t Minimum discharge flow to meet downstream ecological needs within the time period , the reservoir is t Minimum downstream flow rate to meet downstream shipping needs within the time period , the reservoir is t Minimum discharge flow to meet the downstream river water intake demand within the time period , the reservoir is t Minimum downstream flow rate to meet power generation demand within the time period , the minimum discharge flow when the reservoir meets other downstream needs ;

[0026] The maximum value is used to calculate the reservoir t Minimum outbound flow allowed within the time period .

[0027] As a preferred solution, the medium- and long-term water storage scheduling plan; based on the water storage scheduling plan or the optimization algorithm, the medium- and long-term water storage control target of the reservoir is determined, and the water level value of the nearest ten-day node in the medium and long term is obtained. , specifically:

[0028] Select the method for determining the medium- and long-term water storage control target of the reservoir on the digital twin system, including determination based on the water storage plan and determination based on the optimization algorithm;

[0029] If the water storage scheduling plan is selected, the stored annual water storage scheduling plan is read in the digital twin system to obtain the water level sequence at the end of each decade of the reservoir. ;

[0030] If the optimization algorithm is selected, the reservoir optimization scheduling model in the digital twin system model platform is called. Based on the medium- and long-term water forecast, the combined goals of maximum water storage and maximum power generation are set to calculate the water level sequence at the end of each decade of the reservoir. ;

[0031] Based on the water level series at the end of each decade of the above reservoir , obtain the water level value of the nearest ten-day node in the future medium and long term .

[0032] As the preferred option, short-term water storage scheduling plan; based on the real-time water level and short-term water inflow forecast, combined with the short-term power generation demand, calculate the reservoir water level process in each period in the next ten days, determine the short-term scheduling plan, and obtain the water level value of the nearest ten-day node in the future short term. , specifically:

[0033] Get real-time reservoir water level , check the water level storage capacity curve to get the corresponding real-time storage capacity ;

[0034] Obtaining the outbound flow process in the short-term scheduling plan

[0035] ,

[0036] Short-term water forecast As a condition, the reservoir storage capacity at the end of each period is calculated according to the following formula:

[0037] ;

[0038] in, p is the time period number, For the reservoir p Reservoir capacity at the end of the period, For the reservoir p-1 Reservoir capacity at the end of the period, For short-term periods p Outbound flow within For short-term periods p Forecast water inflow within

[0039] According to the reservoir storage capacity process at the end of each period, the reservoir water level process at the end of each period can be obtained by checking the water level storage capacity curve. , extract the water level value at the nearest ten-day node in the short term in the future from the current moment .

[0040] As a preferred solution, the water level value of the nearest ten-day node in the future medium and long term , the water level value of the nearest ten-day node in the short term in the future Comparison is made, and based on the comparison results, water storage risk warnings are issued within the system, and the scheduling process within the forecast period is corrected and adjusted until the water level is within an acceptable range at the end of the forecast period, as follows:

[0041] Set water level deviation range ;

[0042] like , then the short-term operation of the reservoir meets the medium- and long-term water demand requirements and no correction or adjustment is required;

[0043] like , the early warning prompts that the reservoir is filling up too fast and there may be a flood risk due to insufficient reserved flood control storage capacity. A manual interactive interface is provided to increase the short-term outflow process of the reservoir and lower the reservoir water level until ;

[0044] like , then the early warning prompts that the reservoir is insufficiently filled and there may be a risk of water abandonment. A manual interactive interface is provided to reduce the short-term outflow process of the reservoir and increase water storage until .

[0045] The present invention also designs a short-, medium- and long-term coupled water storage scheduling system based on digital twins, which includes the following modules:

[0046] The initial data acquisition module is used to access basic reservoir operation data, real-time operation data, reservoir water storage operation constraints, and future inflow forecast data from the digital twin system;

[0047] The medium- and long-term water storage scheduling module is used for medium- and long-term water storage scheduling plans; based on the water storage scheduling plan or optimization algorithm, the medium- and long-term water storage control target of the reservoir is determined, and the water level value of the nearest ten-day node in the future medium- and long-term is obtained. ;

[0048] The short-term water storage scheduling module is used for short-term water storage scheduling plans. Based on the real-time water level and short-term water inflow forecast, combined with the short-term power generation demand, the reservoir water level process in each period in the next ten days is calculated, the short-term scheduling plan is determined, and the water level value of the node in the nearest ten days in the future is obtained. ;

[0049] The early warning adjustment module is used to adjust the water level value of the nearest ten-day node in the future medium and long term. , the water level value of the nearest ten-day node in the short term in the future Comparisons are made, and based on the comparison results, water storage risk warnings are issued within the system, and the scheduling process within the forecast period is corrected and adjusted until the water level is within an acceptable range at the end of the forecast period;

[0050] The result display module is used to display and output the reservoir scheduling process on the digital twin system interface.

[0051] Beneficial effects of the present invention:

[0052] The short-, medium- and long-term coupled water storage scheduling decision-making analysis method based on digital twins described in the present invention can be applied to real-time water storage scheduling analysis and decision-making during the reservoir storage period and the construction of its digital twin system. It determines the medium- and long-term optimal water storage control indicators through optimization algorithms, and combines short-term forecasts to conduct real-time analysis and decision-making on the reservoir scheduling process, so that it continuously approaches the optimal scheduling process. It can improve the scientific nature of reservoir water storage scheduling, increase water storage capacity, and provide technical support for reservoir management departments to fully utilize water resources.

[0053] 1. This invention provides a complete decision-making process for water storage scheduling that couples different time scales. It determines water storage control targets through medium- and long-term optimization scheduling calculations, providing scientific and clear control targets for water storage scheduling. Rolling adjustments to scheduling plans based on short-term forecasts allow real-time scheduling to more closely approximate the optimal process, providing more refined decision-making support.

[0054] 2. This invention combines a digital twin system with real-time rolling updates of reservoir operation and forecast data, and conducts rolling decision analysis, thereby improving the scientific nature of scheduling and reducing the impact of forecast uncertainty on reservoir water storage scheduling.

[0055] 3. The present invention combines the digital twin system to visualize the decision-making process, thereby improving decision makers' perception of the decision-making process. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 This is a flow chart of the water storage scheduling principle of the present invention. DETAILED DESCRIPTION

[0057] The following detailed description of the embodiments of the present invention is given in conjunction with the accompanying drawings, which do not limit the present invention but are merely examples. The description makes the advantages of the present invention clearer and easier to understand.

[0058] Reservoir water storage scheduling is a key area of focus for the efficient use of water resources. Current research provides limited support for real-time water storage scheduling, making it difficult to flexibly adjust scheduling based on real-time and rolling water inflow forecasts under forecast uncertainty. As the water conservancy industry is actively developing digital twins, access to real-time water and rainfall information, coupled with the computing power of model platforms, makes it possible to support real-time water storage scheduling decisions based on digital twins. Therefore, it is necessary to propose new water storage scheduling analysis methods to enhance consultation and decision-making capabilities and maximize the comprehensive benefits of reservoirs.

[0059] The present invention considers combining medium- and long-term water storage scheduling with short-term water storage scheduling, provides water storage control targets for reservoirs through medium- and long-term optimized scheduling, and further analyzes and makes decisions on the short-term water storage scheduling process to ensure that it meets the optimal water storage process; considering the uncertainty of the forecast, the impact of forecast uncertainty on water storage scheduling is reduced by rolling updating of forecast data and conducting water storage decision analysis, so that it can be continuously revised to the scheduling plan that best suits the actual water conditions.

[0060] Based on the above-mentioned inventive concept, the present invention provides a short-, medium- and long-term coupled water storage scheduling method based on digital twins. A complete short-, medium- and long-term coupled water storage scheduling decision analysis based on digital twins is specifically implemented according to the following steps (1) to (5):

[0061] (1) Accessing basic reservoir operation data, real-time operation data, reservoir storage operation constraints, and future inflow forecast data from the digital twin system;

[0062] (2) Medium- and long-term water storage scheduling plan: Based on the approved water storage scheduling plan or optimization algorithm, the medium- and long-term water storage control target of the reservoir is obtained, and the water level value of the nearest ten-day node in the medium and long term is obtained. ;

[0063] (3) Short-term water storage scheduling plan: Based on the real-time water level and short-term water inflow forecast, combined with the short-term power generation demand, calculate the reservoir water level process in each period in the next ten days, determine the short-term scheduling plan, and obtain the water level value of the nearest ten-day node in the future short term. Ten days refers to the first ten days, the middle ten days and the last ten days of a month, which are called the first ten days, the middle ten days and the last ten days respectively.

[0064] (4) The water level value at the nearest ten-day node in the future medium and long term , the water level value of the nearest ten-day node in the short term in the future Comparisons are made, and based on the results, it is determined whether the staged water storage control target can be achieved by the end of the ten-day period. If not, a water storage risk warning is issued within the system, and the scheduling process within the forecast period is corrected and adjusted until the water level is within an acceptable range by the end of the forecast period; the end of the ten-day period refers to the last ten days of a month;

[0065] (5) Display and output the reservoir scheduling process on the digital twin system interface.

[0066] Furthermore, the step (1) includes:

[0067] (1.1) Access basic reservoir operation data, including reservoir dead water level, flood limit water level, normal water level, output coefficient and other characteristic parameters, as well as water level storage capacity curve, discharge capacity curve, tailwater level curve and other curve data;

[0068] (1.2) Access to real-time reservoir operation data, including real-time water level, inflow and outflow data;

[0069] (1.3) Constraints on reservoir water storage operation during the access water storage period. These include:

[0070] Reservoir water level constraints:

[0071]

[0072] For the reservoir t The lowest water level allowed during the period, For the reservoir t The maximum water level allowed during the time period;

[0073] Outbound flow constraints:

[0074]

[0075] For the reservoir t The minimum outbound flow allowed within the time period, For the reservoir t The maximum outbound flow allowed within the time period;

[0076] The minimum outflow allowed by the reservoir in period t in (1.3) Obtained as follows:

[0077] (1.3.1) Obtain the reservoir water storage period t Minimum discharge flow to meet downstream ecological needs within the time period , the reservoir is t Minimum downstream flow rate to meet downstream shipping needs within the time period , the reservoir is t Minimum discharge flow to meet the downstream river water intake demand within the time period , the reservoir is t Minimum downstream flow rate to meet power generation demand within the time period , the minimum discharge flow when the reservoir meets other downstream needs .

[0078] (1.3.2) Using the maximum value calculation method, we can get the reservoir t Minimum outbound flow allowed within the time period

[0079] (1.4) Access to future inflow forecast data, including: mid- to long-term inflow forecasts on a ten-day scale during the water storage period; , short-term water inflow forecast for the next 10 days in the current period .

[0080] The step (2) includes:

[0081] (2.1) Selecting a method for determining the medium- and long-term reservoir water storage control target based on the digital twin system, including determination based on the water storage plan and determination based on the optimization algorithm;

[0082] (2.2) If the water storage scheduling plan is selected, the annual water storage scheduling plan stored in the digital twin system is read to obtain the water level sequence at the end of each decade of the reservoir. ;

[0083] (2.3) If the optimization algorithm is selected, the reservoir optimization scheduling model in the digital twin system model platform is called. Based on the long-term water forecast, the maximum water storage and maximum power generation combined objectives are set to calculate the water level sequence at the end of each decade. .

[0084] Among them, the reservoir optimization scheduling model is an existing technology. It is used to determine the water storage control target through medium- and long-term optimization scheduling calculations, providing a scientific and clear control target for water storage scheduling. It combines short-term forecasts to make rolling adjustments to the scheduling plan, making real-time scheduling closer to the optimal process.

[0085] (2.4) Display the reservoir water level sequence at the end of each decade on the digital twin system , based on the reservoir water level series at the end of each decade , obtain the water level value of the nearest ten-day node in the future medium and long term .

[0086] The step (3) includes:

[0087] (3.1) Obtain real-time reservoir water level , check the water level storage capacity curve to get the corresponding real-time storage capacity ;

[0088] (3.2) Obtaining the outbound flow process in the short-term scheduling plan , based on short-term water forecast As a condition, the reservoir storage capacity at the end of each period is calculated according to the following formula

[0089] ;

[0090] in, p is the time period number, For the reservoir p Reservoir capacity at the end of the period, For the reservoir p-1 Reservoir capacity at the end of the period, For short-term periods p Outbound flow within For short-term periodsp Forecast water inflow within

[0091] (3.3) According to the reservoir storage capacity process at the end of each period, the reservoir water level process at the end of each period is obtained by checking the water level storage capacity curve. , extract the water level value at the nearest ten-day node in the short term in the future from the current moment .

[0092] The step (4) includes:

[0093] (4.1) Long-term water storage control targets in reservoirs Extract the water level value at the nearest ten-day node in the future from the current moment ;

[0094] (4.2) and Compare and issue warnings based on the comparison results and adjust the scheduling process.

[0095] Step (4.2) specifically includes:

[0096] (4.2.1) Set the water level deviation range ;

[0097] (4.2.2) If , then the short-term operation of the reservoir meets the medium- and long-term water demand requirements and no correction or adjustment is required;

[0098] (4.2.3) If , the early warning prompts that the reservoir is filling up too fast, and there may be flood control risks such as insufficient reserved flood control storage capacity, and provides a manual interactive interface to increase the short-term outflow process of the reservoir and lower the reservoir water level until ;

[0099] (4.2.4) If , then the early warning prompts that the reservoir is insufficiently filled and there may be risks such as water abandonment, etc., and provides a manual interactive interface to reduce the short-term outflow process of the reservoir and increase water storage until .

[0100] It should be understood that the specific order or hierarchy of steps in the processes disclosed herein are examples of exemplary methods. Based on design preferences, it should be understood that the specific order or hierarchy of steps in the processes may be rearranged without departing from the scope of the present disclosure. The accompanying method claims present elements of the various steps in an exemplary order and are not intended to be limited to the specific order or hierarchy described.

[0101] The present invention also provides a short-, medium- and long-term coupled water storage scheduling system based on digital twins, including the following modules:

[0102] The initial data acquisition module is used to access basic reservoir operation data, real-time operation data, reservoir water storage operation constraints, and future inflow forecast data from the digital twin system;

[0103] The medium- and long-term water storage scheduling module is used for medium- and long-term water storage scheduling plans; based on the water storage scheduling plan or optimization algorithm, the medium- and long-term water storage control target of the reservoir is determined, and the water level value of the nearest ten-day node in the future medium- and long-term is obtained. ;

[0104] The short-term water storage scheduling module is used for short-term water storage scheduling plans. Based on the real-time water level and short-term water inflow forecast, combined with the short-term power generation demand, the reservoir water level process in each period in the next ten days is calculated, the short-term scheduling plan is determined, and the water level value of the node in the nearest ten days in the future is obtained. ;

[0105] The early warning adjustment module is used to adjust the water level value of the nearest ten-day node in the future medium and long term. , the water level value of the nearest ten-day node in the short term in the future Comparisons are made, and based on the comparison results, water storage risk warnings are issued within the system, and the scheduling process within the forecast period is corrected and adjusted until the water level is within an acceptable range at the end of the forecast period;

[0106] The result display module is used to display and output the reservoir scheduling process on the digital twin system interface.

[0107] Compared with the prior art, the beneficial technical effects of the present invention using the above technical solution are as follows:

[0108] 1. This invention provides a complete decision-making process for water storage scheduling that couples different time scales. It determines water storage control targets through medium- and long-term optimization scheduling calculations, providing scientific and clear control targets for water storage scheduling. Rolling adjustments to scheduling plans based on short-term forecasts allow real-time scheduling to more closely approximate the optimal process, providing more refined decision-making support.

[0109] 2. The present invention combines the digital twin system to improve the scientific nature of scheduling and reduce the impact of forecast uncertainty on reservoir scheduling through real-time rolling updates of reservoir scheduling operation data and forecast data, and rolling decision analysis.

[0110] 3. The present invention combines the digital twin system to visualize the decision-making process, thereby improving decision makers' perception of the decision-making process.

[0111] Taking a large reservoir SX as an example, a short-, medium- and long-term coupled water storage scheduling decision analysis based on digital twins was conducted, with the decision time being September 5, 2023.

[0112] Step 1: Access the SX reservoir scheduling basic data, real-time scheduling operation data, and future inflow forecast data from the digital twin system.

[0113] Access the basic data of SX reservoir scheduling, including reservoir dead water level, flood limit water level, normal water level, output coefficient and other characteristic parameters as well as water level storage capacity curve, discharge capacity curve, tail water level curve and other curve data; read the real-time water level of SX reservoir on September 5, 2023, which is 158.04m, and the real-time inflow is 13900m 3 / s, outbound flow 14300m 3 / s; read water level constraints during storage period , outbound flow constraints ; Read the long-term runoff forecast for each ten-day period from September 5th to October 31st during the water storage period (expressed as average flow, unit m 3 / s, the same below); =[13000,16000,…,13100], read the short-term and medium-term water inflow forecast for the next 10 days on September 5 =[13300,13000,…,16200].

[0114] Step 2: Obtain the medium- and long-term water storage control target of the reservoir based on the approved water storage scheduling plan or optimization algorithm.

[0115] The method for determining the medium- and long-term water storage control target of the reservoir is determined based on the optimization algorithm. The reservoir optimization scheduling model in the digital twin system model platform is called, and the combined target of maximum water storage and maximum power generation is set based on the long-term forecast water inflow, and the water level sequence of the reservoir at the end of each decade is calculated. =[159.10,164.62,…,175].

[0116] In step (3), based on the real-time water level and short-term water inflow forecast, combined with the short-term dispatching plan, the reservoir water level process in each period within the next ten days is calculated.

[0117] The scheduling plan for SX reservoir in the next 10 days is: =[12000,12000,…,11200], based on the real-time water level =158.04m Check the water level storage capacity curve to get the initial storage capacity =24.867 billion m 3 , combined with the short-term and medium-term water inflow forecast for the next 10 days =[13300,13000,…,16200], calculate the reservoir storage capacity at the end of each period according to the following formula

[0118]

[0119] =[249.79,250.65,…,284.45], and the corresponding water level is obtained by checking the water level and storage capacity curve. =[158.20,158.33,…,162.94], extract the water level value of the nearest ten-day node in the future, September 10th, from the current moment =158.66.

[0120] Step 4: Determine whether the staged water storage control target can be achieved at the end of the ten-day period. If not, issue a water storage risk warning within the system and revise the scheduling process within the forecast period. Repeat steps (3) to (4) until the water level is within an acceptable range at the end of the forecast period.

[0121] Long-term water storage control targets in reservoirs Extract the water level value of September 10th, the nearest ten-day node in the future from the current moment =159.10. Set the water level deviation range =0.2m, and Compare, yes Therefore, the early warning indicates that the reservoir is insufficiently filled and there is a risk of not being able to fill it up. According to the water level difference, the outflow of the reservoir from September 5th to 10th is reduced in the manual interaction interface, and the short-term water level process is recalculated until .

[0122] Finally, the scheduling calculation results are displayed and output in the digital twin system.

[0123] When the reservoir inflow forecast is updated, the above process is repeated to make real-time rolling decisions on water storage scheduling plans.

Claims

1. A short-, medium- and long-term coupled water storage scheduling method based on digital twins, characterized by: The following steps are involved: Access basic reservoir operation data, real-time operation data, reservoir storage operation constraints, and future inflow forecast data from the digital twin system; Medium- and long-term water storage scheduling plan; determine the medium- and long-term water storage control target of the reservoir based on the water storage scheduling plan or optimization algorithm, and obtain the water level value of the nearest ten-day node in the medium and long term ; Select the method for determining the medium- and long-term water storage control target of the reservoir on the digital twin system, including determination based on the water storage plan and determination based on the optimization algorithm; If the water storage scheduling plan is selected, the stored annual water storage scheduling plan is read in the digital twin system to obtain the water level sequence at the end of each decade of the reservoir. ; If the optimization algorithm is selected, the reservoir optimization scheduling model in the digital twin system model platform is called. Based on the medium- and long-term water forecast, the combined goals of maximum water storage and maximum power generation are set to calculate the water level sequence at the end of each decade of the reservoir. ; Based on the water level series at the end of each decade of the above reservoir , obtain the water level value of the nearest ten-day node in the future medium and long term ; Short-term water storage scheduling plan: Based on the real-time water level and short-term water inflow forecast, combined with the short-term power generation demand, calculate the reservoir water level process in each period in the next ten days, determine the short-term scheduling plan, and obtain the water level value of the nearest ten-day node in the future short term ; Get real-time reservoir water level , check the water level storage capacity curve to get the corresponding real-time storage capacity ; Obtaining the outbound flow process in the short-term scheduling plan ， Short-term water forecast As a condition, the reservoir storage capacity at the end of each period is calculated according to the following formula: ； in, p is the time period number, For the reservoir p Reservoir capacity at the end of the period, For the reservoir p-1 Reservoir capacity at the end of the period, For short-term periods p Outbound flow within For short-term periods p Forecast water inflow within According to the reservoir storage capacity process at the end of each period, the reservoir water level process at the end of each period can be obtained by checking the water level storage capacity curve. , extract the water level value at the nearest ten-day node in the short term in the future from the current moment ; The water level value of the nearest ten-day node in the future medium and long term , the water level value of the nearest ten-day node in the short term in the future Comparisons are made, and based on the comparison results, water storage risk warnings are issued within the system, and the scheduling process within the forecast period is corrected and adjusted until the water level is within an acceptable range at the end of the forecast period; The reservoir scheduling process is displayed and output on the digital twin system interface.

2. A short-, medium- and long-term coupled water storage scheduling method based on digital twins according to claim 1, characterized in that: The basic data of reservoir operation, real-time operation data, reservoir water storage operation constraints and future inflow forecast data are accessed from the digital twin system, specifically: Access basic reservoir operation data, including characteristic parameters such as reservoir dead water level, flood limit water level, normal water level, output coefficient, as well as curve data such as water level storage capacity curve, discharge capacity curve, and tailwater level curve; Access to real-time reservoir operation data, including real-time water level, inflow and outflow data; The constraints on reservoir water storage scheduling during the access water storage period include: Reservoir water level constraints: ； For the reservoir t The lowest water level allowed during the period, For the reservoir t The maximum water level allowed during the time period; Outbound flow constraints: ； For the reservoir t The minimum outbound flow allowed within the time period, For the reservoir t The maximum outbound flow allowed within the time period; Access to future inflow runoff forecast data, including: mid- to long-term forecast inflow runoff on a ten-day scale during the water storage period , short-term water inflow forecast for the next 10 days in the current period .

3. The short-, medium- and long-term coupled water storage scheduling method based on digital twin according to claim 2 is characterized in that: The minimum outflow allowed by the reservoir during period t Obtained as follows: Get the water storage period of the reservoir t Minimum discharge flow to meet downstream ecological needs within the time period , the reservoir is t Minimum downstream flow rate to meet downstream shipping needs within the time period , the reservoir is t Minimum discharge flow to meet the downstream river water demand within the time period , the reservoir is t Minimum downstream flow rate to meet power generation demand within the time period , the minimum discharge flow when the reservoir meets other downstream needs ; The maximum value is used to calculate the reservoir t Minimum outbound flow allowed within the time period .

4. The short-, medium- and long-term coupled water storage scheduling method based on digital twin according to claim 1 is characterized in that: The water level value of the nearest ten-day node in the future medium and long term , the water level value of the nearest ten-day node in the short term in the future Comparison is made, and based on the comparison results, water storage risk warnings are issued within the system, and the scheduling process within the forecast period is corrected and adjusted until the water level is within an acceptable range at the end of the forecast period, as follows: Set water level deviation range ; like , then the short-term operation of the reservoir meets the medium- and long-term water demand requirements and no correction or adjustment is required; like , the early warning prompts that the reservoir is filling up too fast and there may be a flood risk due to insufficient reserved flood control storage capacity. A manual interactive interface is provided to increase the short-term outflow process of the reservoir and lower the reservoir water level until ; like , then the early warning prompts that the reservoir is insufficiently filled and there may be a risk of water abandonment. A manual interactive interface is provided to reduce the short-term outflow process of the reservoir and increase water storage until .

5. A short-, medium- and long-term coupled water storage scheduling system based on digital twins, characterized by: Includes the following modules, The initial data acquisition module is used to access basic reservoir operation data, real-time operation data, reservoir water storage operation constraints, and future inflow forecast data from the digital twin system; The medium- and long-term water storage scheduling module is used for medium- and long-term water storage scheduling plans; based on the water storage scheduling plan or optimization algorithm, the medium- and long-term water storage control target of the reservoir is determined, and the water level value of the nearest ten-day node in the future medium- and long-term is obtained. ; Select the method for determining the medium- and long-term water storage control target of the reservoir on the digital twin system, including determination based on the water storage plan and determination based on the optimization algorithm; If the water storage scheduling plan is selected, the stored annual water storage scheduling plan is read in the digital twin system to obtain the water level sequence at the end of each decade of the reservoir. ; If the optimization algorithm is selected, the reservoir optimization scheduling model in the digital twin system model platform is called. Based on the medium- and long-term water forecast, the combined goals of maximum water storage and maximum power generation are set to calculate the water level sequence at the end of each decade of the reservoir. ; Based on the water level series at the end of each decade of the above reservoir , obtain the water level value of the nearest ten-day node in the future medium and long term ; The short-term water storage scheduling module is used for short-term water storage scheduling plans. Based on the real-time water level and short-term water inflow forecast, combined with the short-term power generation demand, the reservoir water level process in each period in the next ten days is calculated, the short-term scheduling plan is determined, and the water level value of the node in the nearest ten days in the future is obtained. ; Get real-time reservoir water level , check the water level storage capacity curve to get the corresponding real-time storage capacity ; Obtaining the outbound flow process in the short-term scheduling plan ， Short-term water forecast As a condition, the reservoir storage capacity at the end of each period is calculated according to the following formula: ； in, p is the time period number, For the reservoir p Reservoir capacity at the end of the period, For the reservoir p-1 Reservoir capacity at the end of the period, For short-term periods p Outbound flow within For short-term periods p Forecast water inflow within According to the reservoir storage capacity process at the end of each period, the reservoir water level process at the end of each period can be obtained by checking the water level storage capacity curve. , extract the water level value at the nearest ten-day node in the short term in the future from the current moment ; The early warning adjustment module is used to adjust the water level value of the nearest ten-day node in the future medium and long term. , the water level value of the nearest ten-day node in the short term in the future Comparisons are made, and based on the comparison results, water storage risk warnings are issued within the system, and the scheduling process within the forecast period is corrected and adjusted until the water level is within an acceptable range at the end of the forecast period; The result display module is used to display and output the reservoir scheduling process on the digital twin system interface.

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