Flood defense interaction decision-making method driven by virtual-real twinborn plan

Abstract

The invention provides a virtual-real twinborn plan-driven flood defense interaction decision-making method, which comprises the following steps of carrying out basin flood control situation analysis based on a flood control scene, and judging whether a flood hidden danger exists or not; if not, executing a conventional deduction state; and if so, executing a real-time mutual feedback deduction state. According to the method, real-scene-plan real-time mutual feedback deduction is innovatively provided, and through a time progressive mode, by combining the current situations of hydropower stations, flood control sections, reservoirs and the like at all levels detected by equipment in a drainage basin and deduced by a model and the real situations of real-time water and rain working conditions, the scenes are deduced by utilizing water and rain condition forecast data, a scheduling scheme, flood control situation analysis and the like, so that the real-time water and rain working conditions are obtained. And generating a scheduling scheme which is verified by hydrodynamics simulation, good in effect risk evaluation and standard in flood control effect.

Description

Technical Field

[0001] The present invention relates to the field of flood defense and emergency management technology, and in particular to a flood defense interactive decision-making method driven by virtual-real twin plans. Background Art

[0002] Floods are one of the most common and destructive natural disasters worldwide. Traditional flood emergency management relies primarily on post-event responses, but this passive approach often fails to effectively mitigate losses. Furthermore, traditional flood prevention decision-making methods often rely on empirical judgment and historical data, which presents certain limitations.

[0003] As the number of water projects using joint scheduling plans increases, the scope of water conservancy scheduling is gradually expanding from upstream to upstream and midstream main and tributary rivers; the scheduling targets are gradually expanding from reservoir groups to drainage pumping stations, flood storage areas, water diversion projects and other water projects; and the scheduling period is extending from flood season scheduling to pre-flood drawdown, flood prevention during the flood season, post-flood water storage, year-round water supply and emergency response. The increasing complexity of flood simulation and the increasing sophistication of scheduling decisions are increasing, and the demand for real-time scheduling feedback systems is becoming increasingly strong.

[0004] However, the current level of integration and automation of flood simulation systems is low, and human-computer interaction lacks humanization, which limits the ability to respond quickly to floods. Moreover, most systems are based on numerical models such as hydrology and hydrodynamics, with huge amounts of data, and the formulation of real-time forecasting and scheduling plans has the problem of poor timeliness. The use of water flow numerical visualization technology to achieve real-time and high-speed flood simulation still faces huge challenges. Summary of the Invention

[0005] In response to the defects of the existing technology, the present invention provides a flood defense interactive decision-making method driven by virtual and real twin plans, which can effectively solve the above problems.

[0006] The technical solution adopted in the present invention is as follows:

[0007] The present invention provides a flood defense interactive decision-making method driven by a virtual-real twin plan, comprising the following steps:

[0008] Step S1, obtain the hydrological characteristics of the study basin, determine the flood control section according to the hydrological characteristics of the study basin; set the flood scheduling deduction cycle S of the study basin to an initial value of 1; set the scheduling plan D corresponding to the flood scheduling deduction cycle S s The initial value is empty; obtain the hydrological characteristics of each flood control section at the beginning of the flood scheduling simulation cycle S to form the flood control scene Scene0;

[0009] Step S2: Analyze the flood control situation of the basin based on the flood control scene Scene0 and determine whether there is a flood hazard; if not, execute step S3; if yes, execute step S4;

[0010] Step S3, enter the normal deduction state:

[0011] Step S3.1: Based on the flood control scenario Scene0 and the conventional deduction state scheduling target S0, a conventional deduction scheduling plan D is formulated. S，0 ;

[0012] Step S3.2, based on the conventional deduction scheduling scheme D S，0 Perform conventional state simulation on flood evolution and construct a scheduling plan for executing the conventional simulation. S，0 The flood control scenario Scenario 0 is used to analyze the flood control situation of the basin and determine whether there is a flood hazard. If not, the flood control scenario Scenario 0 is used to update the flood control scenario Scenario 0. The scheduling plan D S = Conventional simulation scheduling plan D S，0 ; S=S+1, return to step S3.1; if yes, go to step S4;

[0013] Step S4: Enter the real-time mutual feedback deduction state:

[0014] Step S4.1, set the real-time mutual feedback deduction number variable i=1; determine the scheduling target S during the i-th real-time mutual feedback deduction i ;

[0015] Step S4.2, based on the flood control scenario Scene0 and the scheduling target S during the i-th real-time mutual feedback deduction i , formulate M types of flood dispatching plans corresponding to the flood dispatching simulation period S during the i-th real-time mutual feedback simulation, expressed as: D S，i，k , k = 1, 2, ..., M;

[0016] Step S4.3, based on each scheduling plan D S，i，k Conduct real-time feedback simulations on flood evolution to evaluate the effectiveness and risks of various dispatching plans, and select the best dispatching plan from various dispatching plans as the flood defense plan. S，i ;

[0017] Step S4.4, construct and execute the flood defense plan D S，i Flood prevention scene after i ; Based on the flood control scenario i Analyze the flood control situation in the basin and determine whether there is a flood risk; if not, use the flood control scenarioi Update flood control scenario Scene0; set scheduling plan D S =D S，i , S=S+1, return to step S3.1; if yes, go to step S4.5;

[0018] Step S4.5, the flood defense plan D S，i Conduct effect evaluation and decide on the implementation of the flood defense plan D S，i Whether the flood control effect after the flood control meets the expected flood control target; if so, the flood control scenario is adopted i Update the flood prevention scene Scene0; let D S =D S，i , S=S+1, return to step S4.1; if not, go to step S4.6;

[0019] Step S4.6, according to the scheduling target S during the i-th real-time mutual feedback deduction i Determine the scheduling target for the (i+1)th real-time mutual feedback simulation; let i=i+1, and return to step S4.2.

[0020] Preferably, in step S1, the hydrological characteristics of each flood control section at the beginning of the flood scheduling simulation cycle S are the hydrological characteristics of each flood control section based on the forecast, including the flow and water level of the flood control section.

[0021] Preferably, in step S2, basin flood control situation analysis is performed based on the flood control scene Scene0, and whether there is a flood hazard is determined, specifically:

[0022] Read the flow and water level of each flood control section in the flood control scene Scene0, and determine whether the following judgment formula is satisfied:

[0023]

[0024] Where: Q j，t represents the flow of flood control section j in period t of flood scheduling simulation cycle S; t = 1, 2, ..., T, T represents the number of periods in flood scheduling simulation cycle S; j = 1, 2, ..., m, m represents the number of flood control sections in the study basin; Q warn_j represents the warning flow of flood control section j; Z j，t represents the water level of flood control section j in time period t of flood dispatch simulation cycle S; Z warn_j represents the warning water level of flood control section j;

[0025] If the discriminant formula is satisfied, there is no flood hazard; otherwise, there is a flood hazard.

[0026] Preferably, in step S3.1, based on the flood control scenario Scene0 and the conventional deduction state scheduling target S0, a conventional deduction scheduling plan D is formulated. S，0 , specifically:

[0027] Based on the water and rainfall forecast data obtained at the starting time t0 of the flood scheduling simulation cycle S, the current time t * The measured data of water and rain conditions in the research basin, the flood control scenario Scene0 and the conventional deduction state scheduling target S0 are used to formulate the conventional deduction scheduling plan D S，0 .

[0028] Preferably, functions f1, f2, f3 and f4 are set as follows:

[0029] f1 is the minimum water loss function in the studied basin;

[0030]

[0031] W t D is the water shortage in the water supply area during the flood scheduling simulation period S at time t; t is the water demand of the water supply area in the flood dispatch simulation period at time t; t is the water supply of all hydropower stations in the flood dispatch simulation period S during time period t;

[0032] f2 is the objective function of river ecological water volume;

[0033]

[0034] W ex (t) is the amount of water exceeding the ecological flow threshold in the flood scheduling simulation period S at time period t; Q out_l，t To study the outflow of the l-th level hydropower station in the basin at time period t; K min (t) is the lower limit of the ecological flow threshold range of the study basin during period t; K max (t) is the upper limit of the ecological flow threshold range of the study basin during period t;

[0035] f3 is the objective function for maximizing power generation efficiency;

[0036]

[0037] Where: N l，t is the average output of the l-th hydropower station in the study basin during time period t, l = 1, 2, ..., n, n is the total number of hydropower stations in the study basin; Δt is the number of hours in time period t; k is the output coefficient; H l，t The head of the l-th level hydropower station in the study basin at time period t; Z up_l，t To study the water level of the l-th hydropower station in the basin at time period t; Zdown_l，t To study the downstream tailwater level of the l-th level hydropower station in the basin at time t; H min_l and H max_l , are the lowest and highest water levels of the l-th level hydropower station when considering flood hazards; Q min_l and Q max_l , are the minimum and maximum outflow rates of the l-th level hydropower station when considering flood risks;

[0038]

[0039] Among them: a l , b j , c j They are the first target weight, the second target weight and the third target weight respectively;

[0040] is the highest operating water level of the l-th level hydropower station in the flood dispatch simulation period S;

[0041] and are the maximum and minimum water levels allowed for the l-th level hydropower station during the flood dispatch simulation period S;

[0042] Q j，t represents the flow of flood control section j in the flood dispatch simulation period S period t; Q min_j ≤Q j，t ≤Q max_j ;Q min_j and Q max_j , are the lower and upper bounds of the allowable overflow flow at flood control section j respectively;

[0043] is the excess flow of flood control section j in period t after the hydropower station is regulated and stored. j，t Does not exceed the upper limit Q of the overflow flow max_j hour, is 0; when Q j，t Exceeding the upper limit of overflow flow Q max_j hour, Q j，t，ce is the excess flow of flood control section j in time period t without storage by the hydropower station;

[0044] The conventional deduction state scheduling target S0 is: S0 = {f1, f2, f3};

[0045] The scheduling target S during the i-th real-time mutual feedback deduction i ={f1, f2, f3, f4}.

[0046] Preferably, setting boundary constraints includes:

[0047] (1) Water balance equation: V l，t =V l，t-1 +(Q in_l，t-1 -Q out_l , -1 )Δt

[0048] Where: V l，t is the storage capacity of the l-th level hydropower station in time period t; V l，t-1 is the storage capacity of the l-th level hydropower station in time period t-1;

[0049] Q in_l，t-1 and Q out_l，t-1 , are the inflow and outflow of the l-th level hydropower station in time period t-1; Δt is the number of hours in time period t;

[0050] (2) Hydropower station tailwater function: Z down_l，t =h l (Q out_l，t )

[0051] Where: Z down_l，t is the downstream tailwater level of the l-th level hydropower station in time period t; h l (Q out_l，t ) is the relationship function between the outflow of the l-th level hydropower station in time period t and the downstream tailwater level;

[0052] (3) Hydropower station water level storage capacity function:

[0053] Where: Z up_l，t is the water level of the l-th level hydropower station in time period t; is the water level and storage capacity relationship function of the l-th level hydropower station;

[0054] (4) Hydraulic head equation: H l，t =Z up_l，t -Z down_l，t

[0055] Among them: H l，t is the water head of the l-th level hydropower station in time period t;

[0056] (5)Output equation: N l，t =kQ out_l，t H l，t

[0057] Where: N l，t is the average output of the l-th hydropower station in time period t, l = 1, 2, ..., n, n is the total number of hydropower stations in the study basin; k is the output coefficient; Q out_l，t is the outflow of the l-th level hydropower station in time period t;

[0058] The conventional deduction state scheduling target S0={f1, f3, f3} and the boundary constraint condition form a conventional deduction state scheduling model;

[0059] The scheduling target S during the i-th real-time mutual feedback deduction i ={f1, f2, f3, f4} and the boundary constraints form a real-time mutual feedback deduction state scheduling model.

[0060] Preferably, the conventional deduction scheduling scheme D S，0 Perform conventional state simulation on flood evolution and construct a scheduling plan for executing the conventional simulation. S，0 The flood prevention scene after Scene'0 is as follows:

[0061] Based on the conventional deduction scheduling scheme D S，0 , taking the outflow of each level of hydropower station in time period t as the decision variable, solve the conventional deduction state scheduling model, and obtain the conventional deduction scheduling scheme D S，0 Then, the outflow Q of each hydropower station in the basin during the flood dispatch simulation period S is studied. out_l，t ;

[0062] Based on the current time t * The measured data of water and rainfall conditions in the research basin and the outflow Q of each hydropower station in the research basin during the flood dispatch simulation period S in each time period t out_l，t , conduct flood simulation on the study basin, obtain the flow and water level of each flood control section, and then obtain the execution of the conventional deduction scheduling plan D S，0 Flood prevention scene after Scene'0.

[0063] Preferably, the scheduling plan D based on each S，i，k Conduct real-time feedback simulations of flood evolution to evaluate the effectiveness and risks of various dispatch plans, specifically:

[0064] Based on the scheduling plan D S，i，k , taking the outflow of each level of hydropower station in time period t as the decision variable, solve the real-time mutual feedback deduction state scheduling model, and obtain the S，i，k Then, the outflow Q of each hydropower station in the basin during the flood dispatch simulation period S is studied. out_l，t ;

[0065] Based on the current time t * The measured data of water and rainfall conditions in the research basin and the outflow Q of each hydropower station in the research basin during the flood dispatch simulation period S in each time period t out_l，t , flood simulation was conducted on the study basin to obtain the flow and water level of each flood control section;

[0066] The effectiveness and risks of the dispatching plan are evaluated based on the flow and water level of each flood control section.

[0067] Preferably, in step S4.5, the following discriminant formula is used to determine the flood defense scheme D S，i Conduct effect evaluation and decide on the implementation of the flood defense plan D S，i Whether the flood control effect after the test meets the expected flood control goals:

[0068]

[0069] Where: Q exp_j is the expected maximum flow of flood control section j; Z exp_j is the expected maximum water level of flood control section j;

[0070] If the above-mentioned discriminant formula is satisfied, the flood control effect meets the expected flood control target; otherwise, it does not meet the expected flood control target.

[0071] The flood defense interactive decision-making method driven by virtual-real twin plans provided by the present invention has the following advantages:

[0072] The present invention innovatively proposes a real-time mutual feedback deduction of "reality-scenario-plan". Through a time-progressive approach, it combines the current status of hydropower stations, flood control sections, reservoirs, etc. at all levels detected by various equipment in the basin and derived by the model with the real-time water and rainfall conditions. It uses deduction scenarios such as water and rainfall forecast data, scheduling plans and flood control situation analysis to generate a scheduling plan that has been verified by hydrodynamic simulation, has a good effect risk assessment, and meets the flood control effect standards. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 A flowchart of a flood defense interactive decision-making method driven by a virtual-real twin plan provided by the present invention;

[0074] Figure 2 A diagram illustrating an implementation of a flood defense interactive decision-making method driven by a virtual-real twin plan provided by the present invention;

[0075] Figure 3 A real-time mutual feedback flow chart of the flood defense interactive decision-making method provided by the present invention;

[0076] Figure 4 A nested relationship diagram of scheduling at different time scales for the interactive decision-making method for flood defense provided by the present invention;

[0077] Figure 5 This is an example diagram of the flood control and dispatching operation process of the Three Gorges Reservoir in 2020. DETAILED DESCRIPTION

[0078] In order to make the technical problems, technical solutions and beneficial effects solved by the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0079] The present invention is applied to the field of digital twin technology, more specifically a "reality-scenario-plan" real-time mutual feedback plan deduction technology that connects virtual and real mapping, and then uses this method to establish a basin-wide flood "virtual and real twin" scenario deduction demonstration system.

[0080] See Figure 1 The present invention provides a flood defense interactive decision-making method driven by a virtual-real twin plan, comprising the following steps:

[0081] Step S1, obtain the hydrological characteristics of the study basin, determine the flood control section according to the hydrological characteristics of the study basin; set the flood scheduling deduction cycle S of the study basin to an initial value of 1; set the scheduling plan D corresponding to the flood scheduling deduction cycle S S The initial value is empty; obtain the hydrological characteristics of each flood control section at the beginning of the flood scheduling simulation cycle S to form the flood control scene Scene0;

[0082] In this step, the hydrological characteristics of each flood control section at the beginning of the flood scheduling simulation cycle S are the hydrological characteristics of each flood control section based on the forecast, including but not limited to the flow and water level of the flood control section.

[0083] In the specific implementation, after obtaining the hydrological characteristics of the study basin, the basin real base map can be drawn to obtain the basin virtual model; dynamic monitoring and prediction can be carried out in combination with real-time data, including: real-time monitoring of the current moment t * The measured data of water and rainfall conditions in the research basin are used to obtain the water and rainfall forecast data at the starting time t0 of the flood scheduling simulation cycle S in real time, and then the hydrological characteristics of each flood control section at the beginning of the flood scheduling simulation cycle S are obtained, including but not limited to the flow and water level of the flood control section, to form the flood control scene Scene0, and realize the connection between the real scenario of real-time water and rainfall conditions and the flood control scene.

[0084] Step S2: Analyze the flood control situation of the basin based on the flood control scene Scene0 and determine whether there is a flood hazard; if not, execute step S3; if yes, execute step S4;

[0085] In this step, the flood control situation of the basin is analyzed based on the flood control scene Scene0, and whether there is a flood hazard is determined. Specifically:

[0086] Read the flow and water level of each flood control section in the flood control scene Scene0, and determine whether the following judgment formula is satisfied:

[0087]

[0088] Where: Q j，t represents the flow of flood control section j in period t of flood scheduling simulation cycle S; t = 1, 2, ..., T, T represents the number of periods in flood scheduling simulation cycle S; j = 1, 2, ..., m, m represents the number of flood control sections in the study basin; Q warn_j represents the warning flow of flood control section j; Z j，t represents the water level of flood control section j in time period t of flood dispatch simulation cycle S; Z warn_j represents the warning water level of flood control section j;

[0089] If the discriminant formula is satisfied, there is no flood hazard; otherwise, there is a flood hazard.

[0090] Step S3, enter the normal deduction state:

[0091] Step S3.1: Based on the flood control scenario Scene0 and the conventional deduction state scheduling target S0, a conventional deduction scheduling plan D is formulated. S，0 ;

[0092] This step is specifically as follows: based on the water and rainfall forecast data at the starting time t0 of the flood scheduling simulation period S, the current time t * The measured data of water and rain conditions in the research basin, the flood control scenario Scene0 and the conventional deduction state scheduling target S0 are used to formulate the conventional deduction scheduling plan D S，0 This step realizes the association of “reality-scenario-contingency plan, i.e. scheduling solution”.

[0093] Step S3.2, based on the conventional deduction scheduling scheme D S，0 Perform conventional state simulation on flood evolution and construct a scheduling plan for executing the conventional simulation. S，0 The flood control scenario Scenario 0 is used to analyze the flood control situation of the basin and determine whether there is a flood hazard. If not, the flood control scenario Scenario 0 is used to update the flood control scenario Scenario 0. The scheduling plan D S = Conventional simulation scheduling plan D S，0 ; S=S+1, return to step S3.1; if yes, go to step S4;

[0094] Step S4: Enter the real-time mutual feedback deduction state:

[0095] Step S4.1, set the real-time mutual feedback deduction number variable i=1; determine the scheduling target S during the i-th real-time mutual feedback deduction i ;

[0096] Step S4.2, based on the flood control scenario Ssene0 and the scheduling target S during the i-th real-time mutual feedback deduction i , formulate M types of flood dispatching plans corresponding to the flood dispatching simulation period S during the i-th real-time mutual feedback simulation, expressed as: D S，i，k , k = 1, 2, ..., M;

[0097] Step S4.3, based on each scheduling plan D S，i，k Conduct real-time feedback simulations on flood evolution to evaluate the effectiveness and risks of various dispatching plans, and select the best dispatching plan from various dispatching plans as the flood defense plan. S，i ;

[0098] Step S4.4, construct and execute the flood defense plan D S，i Flood prevention scene after i ; Based on the flood control scenario i Analyze the flood control situation in the basin and determine whether there is a flood risk; if not, use the flood control scenario i Update flood control scenario Scene0; set scheduling plan D S =D S，i , S=S+1, return to step S3.1; if yes, go to step S4.5;

[0099] Step S4.5, the flood defense plan D S，i Conduct effect evaluation and decide on the implementation of the flood defense plan D S，i Whether the flood control effect after the flood control meets the expected flood control target; if so, the flood control scenario is adopted i Update the flood prevention scene Scene0; let D S =D S，i , S=S+1, return to step S4.1; if not, go to step S4.6;

[0100] Step S4.6, according to the scheduling target S during the i-th real-time mutual feedback deduction i Determine the scheduling target for the (i+1)th real-time mutual feedback simulation; let i=i+1, and return to step S4.2.

[0101] In this step S4.5, the following discriminant formula is used to determine the flood defense scheme D S，i Conduct effect evaluation and decide on the implementation of the flood defense plan D S，i Whether the flood control effect after the test meets the expected flood control goals:

[0102]

[0103] Where: Q exp_j is the expected maximum flow of flood control section j; Z exp_j is the expected maximum water level of flood control section j;

[0104] If the above-mentioned discriminant formula is satisfied, the flood control effect meets the expected flood control target; otherwise, it does not meet the expected flood control target.

[0105] Therefore, in the present invention, in step S2, the flood control situation of the basin is analyzed, and when the presence of flood hidden dangers is monitored, the real-time mutual feedback deduction state is entered; when entering the real-time mutual feedback deduction state, a variety of scheduling plans will be formulated according to the scheduling goals and flood control scenarios during the real-time mutual feedback deduction, and the plan with the highest evaluation value will be selected from the multiple scheduling plans as the flood defense plan. After the flood defense plan is executed, the flood control situation of the basin is further analyzed, and it is determined whether there are flood hidden dangers. If there are no flood hidden dangers at this time, the flood defense plan will be used as the final scheduling plan formulated in this flood scheduling deduction cycle, and the next flood scheduling deduction cycle will first enter the regular If there are still flood hazards, further judge whether the flood control effect after the implementation of the flood defense plan meets the expected flood control target; if so, the flood defense plan is still used as the final scheduling plan for this flood scheduling simulation cycle, but the next flood scheduling simulation cycle is required to perform real-time mutual feedback simulation; if not, the scheduling target during the real-time mutual feedback simulation is revised, and then the scheduling plan is revised, so as to continuously perform multiple real-time mutual feedback simulations until the flood hazards are eliminated or the flood control effect meets the expected flood control target, and then enter the next flood scheduling simulation cycle, thereby formulating the scheduling plan for this flood scheduling simulation cycle.

[0106] In the present invention, when performing conventional state deduction of flood evolution and real-time mutual feedback deduction of flood evolution, it is necessary to adopt a conventional deduction state scheduling model and a real-time mutual feedback deduction state scheduling model.

[0107] The conventional simulation state scheduling model and the real-time feedback simulation state scheduling model are established as follows:

[0108] (1) Set up functions f1, f2, f3, and f4:

[0109] f1 is the minimum water loss function in the studied basin;

[0110]

[0111] W t D is the water shortage in the water supply area during the flood scheduling simulation period S at time t; t is the water demand of the water supply area in the flood dispatch simulation period at time t;t is the water supply of all hydropower stations in the flood dispatch simulation period S during time period t;

[0112] f2 is the objective function of river ecological water volume;

[0113]

[0114] W ex (t) is the amount of water exceeding the ecological flow threshold in the flood scheduling simulation period S at time period t; Q out_l，t To study the outflow of the l-th level hydropower station in the basin at time period t; K min (t) is the lower limit of the ecological flow threshold range of the study basin during period t; K max (t) is the upper limit of the ecological flow threshold range of the study basin during period t;

[0115] f3 is the objective function for maximizing power generation efficiency;

[0116]

[0117] Where: N l，t is the average output of the l-th hydropower station in the study basin during time period t, l = 1, 2, ..., n, n is the total number of hydropower stations in the study basin; Δt is the number of hours in time period t; k is the output coefficient; H l，t The head of the l-th level hydropower station in the study basin at time period t; Z up_l，t To study the water level of the l-th hydropower station in the basin at time period t; Z down_l，t To study the downstream tailwater level of the l-th level hydropower station in the basin at time t; H min_l and H max_l , are the lowest and highest water levels of the l-th level hydropower station when considering flood hazards; Q min_l and Q max_l , are the minimum and maximum outflow rates of the l-th level hydropower station when considering flood risks;

[0118]

[0119] Among them: a l , b j , c j They are the first target weight, the second target weight and the third target weight respectively;

[0120] is the highest operating water level of the l-th level hydropower station in the flood dispatch simulation period S;

[0121] and are the maximum and minimum water levels allowed for the l-th level hydropower station during the flood dispatch simulation period S;

[0122] Q j，t represents the flow of flood control section j in the flood dispatch simulation period S period t; Q min_j ≤Q j，t ≤Q max_j ;Q min_j and Q max_j , are the lower and upper bounds of the allowable overflow flow at flood control section j respectively;

[0123] is the excess flow of flood control section j in period t after the hydropower station is regulated and stored. j，t Does not exceed the upper limit Q of the overflow flow max_j hour, is 0; when Q j，t Exceeding the upper limit of overflow flow Q max_j hour, Q j，t，ce is the excess flow of flood control section j in time period t without storage by the hydropower station;

[0124] The conventional deduction state scheduling target S0 is: S0 = {f1, f2, f3};

[0125] The scheduling target S during the i-th real-time mutual feedback deduction i ={f1, f2, f4, f4}.

[0126] (2) Setting boundary constraints includes:

[0127] (1) Water balance equation: V l，t =V l,t-1 +(Q in_l,t-1 -Q out_l,t-1 )Δt

[0128] Where: V l，t is the storage capacity of the l-th level hydropower station in time period t; V l，t-1 is the storage capacity of the l-th level hydropower station in time period t-1;

[0129] Q in_l，t-1 and Q out_l，t-1 , are the inflow and outflow of the l-th level hydropower station in time period t-1; Δt is the number of hours in time period t;

[0130] (2) Hydropower station tailwater function: Z down_l，t =h l (Q out_l，t )

[0131] Where: Z down_l，tis the downstream tailwater level of the l-th level hydropower station in time period t; h l (Q out_l，t ) is the relationship function between the outflow of the l-th level hydropower station in time period t and the downstream tailwater level;

[0132] (3) Hydropower station water level storage capacity function:

[0133] Where: Z up_l，t is the water level of the l-th level hydropower station in time period t; is the water level and storage capacity relationship function of the l-th level hydropower station;

[0134] (4) Hydraulic head equation: H l，t =Z up_l，t -Z down_l，t

[0135] Among them: H l，t is the water head of the l-th level hydropower station in time period t;

[0136] (5)Output equation: N l，t =kQ out_l，t H l，t

[0137] Where: N l，t is the average output of the l-th hydropower station in time period t, l = 1, 2, ..., n, n is the total number of hydropower stations in the study basin; k is the output coefficient; Q out_l，t is the outflow of the l-th level hydropower station in time period t;

[0138] (3) The conventional deduction state scheduling target S0 = {f1, f2, f3} and the boundary constraints form a conventional deduction state scheduling model;

[0139] The scheduling target S during the i-th real-time mutual feedback deduction i ={f1, f2, f3, f4} and the boundary constraints form a real-time mutual feedback deduction state scheduling model.

[0140] (IV) The conventional deduction scheduling scheme D S，0 Perform conventional state simulation on flood evolution and construct a scheduling plan for executing the conventional simulation. S，0 The flood prevention scene after Scene'0 is as follows:

[0141] Based on the conventional deduction scheduling scheme D S，0 , taking the outflow of each level of hydropower station in time period t as the decision variable, solve the conventional deduction state scheduling model, and obtain the conventional deduction scheduling scheme D S，0 Then, the outflow Q of each hydropower station in the basin during the flood dispatch simulation period S is studied.out_l，t ;

[0142] Based on the current time t * The measured data of water and rainfall conditions in the research basin and the outflow Q of each hydropower station in the research basin during the flood dispatch simulation period S in each time period t out_l，t , conduct flood simulation on the study basin, obtain the flow and water level of each flood control section, and then obtain the execution of the conventional deduction scheduling plan D S，0 Flood prevention scene after Scene'0.

[0143] (V) Based on each dispatch plan D S，i，k Conduct real-time feedback simulations of flood evolution to evaluate the effectiveness and risks of various dispatch plans, specifically:

[0144] Based on the scheduling plan D S，i，k , taking the outflow of each level of hydropower station in time period t as the decision variable, solve the real-time mutual feedback deduction state scheduling model, and obtain the S，i，k Then, the outflow Q of each hydropower station in the basin during the flood dispatch simulation period S is studied. out_l，t ;

[0145] Based on the current time t * The measured data of water and rainfall conditions in the research basin and the outflow Q of each hydropower station in the research basin during the flood dispatch simulation period S in each time period t out_l，t , conduct flood simulation on the study basin to obtain the flow and water level of each flood control section; based on the flow and water level of each flood control section, evaluate the effectiveness and risk of the scheduling plan.

[0146] The present invention provides a flood defense interactive decision-making method driven by virtual-real twin plans, which has the following characteristics:

[0147] The present invention introduces the concept of flood warning scheduling status, including conventional deduction status and real-time mutual feedback deduction status; the results of basin flood control situation analysis affect the regulation of these two states, and are also one of the main decision-making conditions for flood defense plan verification. The innovative "reality-scenario-plan" real-time mutual feedback deduction is proposed. Through a time-progressive approach, combined with the current status of hydropower stations, flood control sections, reservoirs, etc. at all levels detected by various equipment in the basin and derived by the model and the real-time water and rainfall conditions, the water and rainfall forecast data, scheduling plans and flood control situation analysis and other deduction scenarios are used to generate scheduling plans that have been verified by hydrodynamic simulation, have good effect risk assessment, and meet flood control effect standards.

[0148] The plan-driven interactive decision-making method provided by the present invention improves the efficiency and accuracy of flood emergency response through real-time feedback and optimization adjustment, providing a more efficient solution for dealing with complex flood risks in the future.

[0149] By dynamically selecting flood scheduling plans under different states, the present invention can screen out the best scheduling plan from multiple scheduling plans based on real-time water and rainfall information when a flood forecast arrives, so as to achieve maximum flood prevention and control.

[0150] When selecting flood dispatch plans, classification and selection are primarily based on actual changes in water and rainfall conditions and forecasts. The specific selection steps include: acquiring real-time water and rainfall data; selecting the optimal dispatch plan from multiple dispatch plans based on the acquired water and rainfall data and forecasts; and dynamically adjusting the selected dispatch plan based on measured data and evaluation results.

[0151] For each flood alert, there is a corresponding set of scheduling options, which includes multiple scheduling options under different scheduling conditions. Based on the water alert and real-time water and rainfall data, the scheduling option with the highest evaluation value is selected from the scheduling option set as the final implementation plan. This includes: for each scheduling option in the set, its impact on flood control project capacity, protection sections and levees, and its potential impact on watershed losses is evaluated; these evaluation indicators are aggregated as the scheme evaluation value; and finally, the scheme with the highest evaluation value is selected as the implementation plan.

[0152] When the forecast shows that a flood is about to come, the system can quickly obtain a corresponding set of scheduling plans based on real-time water and rainfall information and select the best scheduling plan from them. The present invention provides an efficient and flexible technical solution for flood defense work.

[0153] In the field of flood prevention, this invention enables flexible adjustment of scheduling plans based on actual conditions, which is crucial for protecting life and property. During the flood warning phase, swift and effective scheduling measures are crucial for flood prevention. The present invention demonstrates how to flexibly switch between conventional scheduling and real-time feedback loops based on real-time flood monitoring data and forecast information, ensuring timely responses in various situations and improving the timeliness and effectiveness of flood prevention.

[0154] The following examples are used to illustrate the present invention but are not intended to limit the scope of the present invention.

[0155] Combine Figures 2 to 5The present invention has been put into practical application in the simulation of the 2020 flood in the Yangtze River Basin. Taking the Dongting Lake area as an example, the flood evolution simulation was carried out through the mutual feedback intelligent adaptation method of the flood control project scheduling plan and the deduction scenario, and then the flood emergency plan effect was evaluated and the risk situation was analyzed, so as to obtain the scheduling plan with the lowest risk. Taking the formulation of the 2020 Yangtze River Basin flood defense scheduling plan as an example, the interactive deduction method provided by the present invention includes two states: normal state and real-time mutual feedback deduction state, which is based on Figure 4 The different time scales shown are scheduled to run nested. Figure 5 It shows the daily simulation status of the middle and lower reaches of the Yangtze River during the Three Gorges Reservoir operation.

[0156] From July 5th to July 9th, the system conducted plan calculations, hydrodynamic simulations, and dispatch effectiveness evaluations in accordance with the regular daily dispatch requirements. The evaluation results showed no flood hazard alarms within the foreseeable 5-7 days. Therefore, the current dispatch plan would continue to be implemented, and the regular dispatch status would be maintained, so the system remained in normal operation.

[0157] From the 7th to the 10th, the system evaluated the effectiveness of the daily dispatch plan. Finding that the dispatch results fell short of expectations and triggering a flood risk alarm, the system immediately transitioned to real-time feedback simulation. Based on current and forecast water and rainfall conditions, the system proposed new dispatch targets and generated a set of dispatch plans based on flood prevention scenarios. The dispatch plans were then subjected to hydrodynamic simulations, effectiveness, and risk assessments, ultimately resulting in the optimal dispatch plan being designated as the flood prevention plan.

[0158] After obtaining the flood defense plan, it was incorporated into the scenario data, the outflow from the Three Gorges Reservoir was calculated, and a hydrodynamic simulation was performed to analyze the flood control situation in the basin. After the flood defense plan was revised, no flood risks were found, so it was adjusted back to normal status and implemented according to the new scheduling plan.

[0159] From July 7th to 11th, the system evaluated the effectiveness of the daily dispatch plan and found that it had not met expectations, triggering a flood risk alarm. The system then entered real-time feedback simulation mode. The system then used the same steps to determine the optimal flood prevention plan, which it then adopted as the dispatch plan. This plan was then applied to the scenario data, calculating the Three Gorges Reservoir outflow and performing a hydrodynamic flood simulation, revealing that flood risks still existed. The system then maintained real-time feedback simulation mode and evaluated the plan to see if it met its objectives. Once the dispatch plan's implementation met its objectives, the revised dispatch plan was implemented and the system remained in real-time feedback simulation mode.

[0160] From July 7th to 12th, the flood control situation will be assessed based on measured data. If a flood alert is still in effect, real-time feedback loops will continue, with operations similar to those on July 11th. If flood risks persist and the projected targets are not being met, the existing dispatch plan will be revised, the dispatch targets will be changed, and a new dispatch plan set will be screened, developed, and re-verified until it meets the expected flood control targets. The plan will then be implemented and real-time feedback loops will continue.

[0161] From July 13th to 30th, the above operations were repeated, and flood risk alerts still existed, so the dispatch plan was modified daily and the real-time mutual feedback simulation status was maintained.

[0162] On July 31, when the system tested the plan, it was found that there was no flood risk and the status was restored to normal, which also indicated that the previous floods No. 2 and No. 3 had been eliminated.

[0163] Then, the above method is used every day to conduct progressive analysis and calculations, verify the scheduling plan in real time, realize daily inspection and correction of the scheduling plan, reduce large-scale plan formulation and selection work, and highly integrate "reality-scenario-plan".

[0164] The present invention provides a flood defense interactive decision-making method driven by virtual-real twin plans, which has the following advantages:

[0165] The present invention has a flexible time scheduling mechanism: by adjusting the flood scheduling simulation cycle S unit, the present invention can flexibly adapt to the scheduling needs of different flood scheduling simulation cycles S, realize the dynamic formulation of scheduling plans, and improve the adaptability and convenience of scheduling plans; all-weather flood defense monitoring: combining the normal state with the real-time mutual feedback simulation state, the present invention realizes the full-process monitoring of flood defense, ensures that a high level of vigilance can be maintained under any circumstances, and enhances the real-time and effectiveness of flood defense; feedback plan formulation method: by simulating and deducing the scheduling results, and making judgments based on these results, the present invention proposes a feedback plan formulation method. This method ensures that the formulation of the plan is closer to the actual flood situation, and improves the practicality and accuracy of the plan; data linkage and real-time response: the present invention realizes data sharing and real-time updating through the linkage of reality, scenarios, and plans. This mechanism enables the scheduling plan to keep up with actual needs, closely fit the actual flood situation, and improve the timeliness and accuracy of the scheduling plan.

[0166] This invention not only improves the efficiency of flood control plan formulation but also enhances the plan's reliability and practicality. By applying virtual-reality twin technology, this invention provides an innovative decision-making support tool for flood prevention, enhancing real-time monitoring and response capabilities for flood situations. It can effectively respond to complex and changing flood situations, providing strong technical support for flood prevention and disaster reduction efforts.

[0167] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A flood defense interactive decision-making method driven by virtual-real twin plans, characterized by: The following steps are involved: Step S1, obtain the hydrological characteristics of the study basin, determine the flood control section according to the hydrological characteristics of the study basin; set the flood scheduling deduction cycle S of the study basin to an initial value of 1; set the scheduling plan D corresponding to the flood scheduling deduction cycle S S The initial value is empty; obtain the hydrological characteristics of each flood control section at the beginning of the flood scheduling simulation cycle S to form the flood control scene Scene0; Step S2: Analyze the flood control situation of the basin based on the flood control scene Scene0 and determine whether there is a flood hazard; if not, proceed to step S3; If yes, proceed to step S4; Step S3, enter the normal deduction state: Step S3.1: Based on the flood control scenario Scene0 and the conventional deduction state scheduling target S0, a conventional deduction scheduling plan D is formulated. S，0 ; Step S3.2, based on the conventional deduction scheduling scheme D S，0 Perform conventional state simulation on flood evolution and construct a scheduling plan for executing the conventional simulation. S，0 The flood control scenario Scenario 0 is used to analyze the flood control situation of the basin and determine whether there is a flood hazard. If not, the flood control scenario Scenario 0 is used to update the flood control scenario Scenario 0. The scheduling plan D S = Conventional simulation scheduling plan D S，0 ; S=S+1, return to step S3.1; if yes, go to step S4; Step S4: Enter the real-time mutual feedback deduction state: Step S4.1, set the real-time mutual feedback deduction number variable i=1; Determine the scheduling target S during the i-th real-time mutual feedback simulation i ; Step S4.2, based on the flood control scenario Scene0 and the scheduling target S during the i-th real-time mutual feedback deduction i , formulate M types of flood dispatching plans corresponding to the flood dispatching simulation period S during the i-th real-time mutual feedback simulation, expressed as: D S，i，k , k = 1, 2, ..., M; Step S4.3, based on each scheduling plan D S，i，k Conduct real-time feedback simulations on flood evolution to evaluate the effectiveness and risks of various dispatching plans, and select the best dispatching plan from various dispatching plans as the flood defense plan. S，i ; Step S4.4, construct and execute the flood defense plan D S，i Flood prevention scene after i ; Based on the flood control scenario i Analyze the flood control situation in the basin and determine whether there is a flood risk; if not, use the flood control scenario i Update flood control scenario Scene0; set scheduling plan D S =D S，i , S=S+1, return to step S3.1; If yes, proceed to step S4.5; Step S4.5, the flood defense plan D S，i Conduct effect evaluation and decide on the implementation of the flood defense plan D S，i Whether the flood control effect after the flood control meets the expected flood control target; if so, the flood control scenario is adopted i Update the flood prevention scene Scene0; let D S =D S，i , S=S+1, return to step S4.1; if not, go to step S4.6; Step S4.6, according to the scheduling target S during the i-th real-time mutual feedback deduction i Determine the scheduling target for the i+1th real-time feedback simulation; Let i=i+1 and return to step S4.

2.

2. The method for interactive decision-making for flood defense driven by virtual-real twin plans according to claim 1 is characterized in that: In step S1, the hydrological characteristics of each flood control section at the beginning of the flood scheduling simulation cycle S are the hydrological characteristics of each flood control section based on the forecast, including the flow and water level of the flood control section.

3. The method for interactive decision-making for flood defense driven by virtual-real twin plans according to claim 1 is characterized in that: In step S2, basin flood control situation analysis is performed based on the flood control scene Scene0, and whether there is a flood hazard is determined, specifically: Read the flow and water level of each flood control section in the flood control scene Scene0, and determine whether the following judgment formula is satisfied: Where: Q j，t represents the flow of flood control section j in time period t of flood scheduling simulation cycle S; i = 1, 2, ..., T, T represents the number of time periods in flood scheduling simulation cycle S; i = 1, 2, ..., m, m represents the number of flood control sections in the study basin; Q warn_j represents the warning flow of flood control section j; Z j，t represents the water level of flood control section j in time period t of flood dispatch simulation cycle S; Z warn_j represents the warning water level of flood control section j; If the discriminant formula is satisfied, there is no flood hazard; otherwise, there is a flood hazard.

4. The method for interactive decision-making for flood defense driven by virtual-real twin plans according to claim 1 is characterized in that: In step S3.1, based on the flood control scenario Scene0 and the conventional deduction state scheduling target S0, a conventional deduction scheduling plan D is formulated. S，0 , specifically: Based on the water and rainfall forecast data obtained at the starting time t0 of the flood scheduling simulation cycle S, the current time t * The measured data of water and rain conditions in the research basin, the flood control scenario Scene0 and the conventional deduction state scheduling target S0 are used to formulate the conventional deduction scheduling plan D S，0 .

5. The method for interactive decision-making for flood defense driven by virtual-real twin plans according to claim 1 is characterized in that: Set up functions f1, f2, f3, and f4: f1 is the minimum water loss function in the studied basin; W t D is the water shortage in the water supply area during the flood scheduling simulation period S at time t; t is the water demand of the water supply area in the flood scheduling simulation period S at time period t; P t is the water supply of all hydropower stations in the flood dispatch simulation period S during time period t; f2 is the objective function of river ecological water volume; W ex (t) is the amount of water exceeding the ecological flow threshold in the flood scheduling simulation period S at time period t; Q out_l，t To study the outflow of the l-th level hydropower station in the basin at time period t; K min (t) is the lower limit of the ecological flow threshold range of the study basin during period t; K max (t) is the upper limit of the ecological flow threshold range of the study basin during period t; f3 is the objective function for maximizing power generation efficiency; H min_l ≤H l，t ≤H max_l Q min_l ≤Q out_l，t ≤Q max_l Where: N l，t is the average output of the l-th hydropower station in the study basin during time period t, l = 1, 2, ..., n, n is the total number of hydropower stations in the study basin; Δt is the number of hours in time period t; k is the output coefficient; H l，t The head of the l-th level hydropower station in the study basin at time period t; Z up_l，t To study the water level of the l-th hydropower station in the basin at time period t; Z down_l，t To study the downstream tailwater level of the l-th level hydropower station in the basin at time t; H min_l and H max_l , are the lowest and highest water levels of the l-th level hydropower station when considering flood hazards; Q min_l and Q max_l , are the minimum and maximum outflow rates of the l-th level hydropower station when considering flood risks; Among them: a l , b j , c j They are the first target weight, the second target weight and the third target weight respectively; is the highest operating water level of the l-th level hydropower station in the flood dispatch simulation period S; and are the maximum and minimum water levels allowed for the l-th level hydropower station during the flood dispatch simulation period S; Q j，t represents the flow of flood control section j in the flood dispatch simulation period S period t; Q min_j ≤Q j，t ≤Q max_j ;Q min_j and Q max_j , are the lower and upper bounds of the allowable overflow flow at flood control section j respectively; is the excess flow of flood control section j in period t after the hydropower station is regulated and stored. j，t Does not exceed the upper limit Q of the overflow flow max_j hour, is 0; when Q j，t Exceeding the upper limit of overflow flow Q max_j hour, Q j，t，ce is the excess flow of flood control section j in time period t without storage by the hydropower station; The conventional deduction state scheduling target S0 is: S0 = {f1, f2, f3}; The scheduling target S during the i-th real-time mutual feedback deduction i ={f1, f2, f3, f4}.

6. The method for interactive decision-making for flood defense driven by virtual-real twin plans according to claim 5 is characterized in that: Setting boundary constraints includes: (1) Water balance equation: V l，t =V l，t-1 +(Q in_l，t-1 -Q out_l，t-1 )Δt Where: V l，t is the storage capacity of the l-th level hydropower station in time period t; V l，t-1 is the storage capacity of the l-th level hydropower station in time period t-1; Q in_l，t-1 and Q out_l，t-1 , are the inflow and outflow of the l-th level hydropower station in time period t-1; Δt is the number of hours in time period t; (2) Hydropower station tailwater function: Z down_l，t =h l (Q out_l，t ) Where: Z down_l，t is the downstream tailwater level of the l-th level hydropower station in time period t; h l (Q out_l，t ) is the relationship function between the outflow of the l-th level hydropower station in time period t and the downstream tailwater level; (3) Hydropower station water level storage capacity function: Where: Z up_l，t is the water level of the l-th level hydropower station in time period t; is the water level and storage capacity relationship function of the l-th level hydropower station; (4) Hydraulic head equation: H l，t =Z up_l，t -Z down_l，t Among them: H l，t is the water head of the l-th level hydropower station in time period t; (5)Output equation: N l，t =kQ out_l，t H l，t Where: N l，t is the average output of the l-th level hydropower station in time period t, l = 1, 2, ..., n, n is the total number of hydropower stations in the study basin; k is the output coefficient; Q out_l，t is the outflow of the l-th level hydropower station in time period t; The conventional deduction state scheduling target S0={f1, f2, f3} and the boundary constraint condition form a conventional deduction state scheduling model; The scheduling target S during the i-th real-time mutual feedback deduction i ={f1, f2, f3, f4} and the boundary constraints form a real-time mutual feedback deduction state scheduling model.

7. The method for interactive decision-making for flood defense driven by virtual-real twin plans according to claim 6 is characterized in that: The conventional deduction scheduling scheme D S，0 Perform conventional state simulation on flood evolution and construct a scheduling plan for executing the conventional simulation. S，0 The flood prevention scene after Scene'0 is as follows: Based on the conventional deduction scheduling scheme D S，0 , taking the outflow of each level of hydropower station in time period t as the decision variable, solve the conventional deduction state scheduling model, and obtain the conventional deduction scheduling scheme D S，0 Then, the outflow Q of each hydropower station in the basin during the flood dispatch simulation period S is studied. out_l，t ; Based on the current time t * The measured data of water and rainfall conditions in the research basin and the outflow Q of each hydropower station in the research basin during the flood dispatch simulation period S in each time period t out_l，t , conduct flood simulation on the study basin, obtain the flow and water level of each flood control section, and then obtain the execution of the conventional deduction scheduling plan D S，0 Flood prevention scene after the flood.

8. The method for interactive decision-making for flood defense driven by virtual-real twin plans according to claim 6 is characterized in that: Based on each scheduling plan D S，i，k Conduct real-time feedback simulations of flood evolution to evaluate the effectiveness and risks of various dispatch plans, specifically: Based on the scheduling plan D S，i，k , taking the outflow of each level of hydropower station in time period t as the decision variable, solve the real-time mutual feedback deduction state scheduling model, and obtain the S，i，k Then, the outflow Q of each hydropower station in the basin during the flood dispatch simulation period S is studied. out_l，t ; Based on the current time t * The measured data of water and rainfall conditions in the research basin and the outflow Qou of each hydropower station in the research basin in each time period t during the flood dispatch simulation cycle S are t_l，t , flood simulation was conducted on the study basin to obtain the flow and water level of each flood control section; The effectiveness and risks of the dispatching plan are evaluated based on the flow and water level of each flood control section.

9. The method for interactive decision-making for flood defense driven by virtual-real twin plans according to claim 6 is characterized in that: In step S4.5, the following discriminant formula is used to determine the flood defense scheme D S，i Conduct effect evaluation and decide on the implementation of the flood defense plan D S，i Whether the flood control effect after the test meets the expected flood control target: Where: Q exp_j is the expected maximum flow of flood control section j; Z exp_j is the expected maximum water level of flood control section j; If the above-mentioned discriminant formula is satisfied, the flood control effect meets the expected flood control target; otherwise, it does not meet the expected flood control target.

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