Decision method of cascade reservoirs considering hydrological requirements of fish spawning drift eggs

Abstract

The application discloses a kind of step reservoir decision-making methods for the hydrological requirements of fish spawning drift eggs, which includes the following steps: step 1, determine the authority of environmental protection department and power generation department in the dispatching of cascade reservoirs and the relationship between them;Step 2, based on the method of eco-hydraulics, the suitable ecological flow of typical fish spawning drift eggs is quantified, and the dispatching target of the environmental protection department is constructed;Step 3, based on the two-layer programming theory, the ecological optimization scheduling model of cascade reservoirs is constructed, which takes into account the power generation benefit and the promotion of fish spawning drift eggs;Step 4, combined with the two-layer nested algorithm and the direct strategy search method, the ecological optimization scheduling model is optimized and solved, and the ecological scheduling strategy of cascade reservoirs for promoting fish spawning drift eggs is obtained.The present application makes up for the lack of consideration of the mutual feedback relationship between ecological flow control and power generation operation strategy in existing multi-objective ecological scheduling model, and plays an important decision support role in coordinating the ecological benefit and power generation benefit of cascade reservoirs.

Description

Technical Field

[0001] The present invention relates to the technical field of reservoir ecological regulation, and in particular to a cascade reservoir decision-making method that takes into account the spawning hydrological needs of fish that lay drifting eggs. Background Art

[0002] Reservoir operation is a crucial means of optimizing water resource allocation and meeting diverse human needs. In recent years, the proportion of large, comprehensive reservoirs has gradually increased, leading to the formation of cascade reservoir systems. These reservoirs have become increasingly complex, and their operational objectives have shifted from single-sector needs to diversified development and operation that balances multiple demands, including flood control, water supply, power generation, navigation, and ecological needs. However, the construction and operation of these reservoir systems have led to significant changes in the hydrological rhythms of downstream rivers, causing ecological challenges such as flattening of flow patterns and weakening of the flood pulses required for fish spawning. This has led to a significant decline in spawning fish stocks and a deterioration in the overall ecosystem service function. Therefore, it is necessary to integrate the need to promote the spawning of spawning spawning fish into the operation and management of cascade reservoirs. Coordinating the relationship between ecological needs and power generation benefits has become a core issue in reservoir ecological operation.

[0003] There is a highly complex, asymmetric competitive relationship between the ecological needs and the power generation needs of cascade reservoirs. Current research on the optimal operation of cascade reservoirs primarily focuses on determining ecological flow processes and multi-objective optimization modeling. Specifically, ecological objectives are constructed and a compromise solution between ecology and power generation is derived through multi-objective optimization and decision-making models. However, multi-objective optimization models assume a centralized decision-making model with a single decision-maker. They describe the competitive relationship between ecological needs, such as promoting the spawning of drifting fish, and power generation needs as a non-inferiority relationship on the Pareto front. However, these models fail to consider the following issues: 1) In operational practice, operational objectives, such as ecology and power generation, are driven by corresponding stakeholders. These stakeholders participate in decision-making and implement operational strategies to ensure the achievement of their respective operational objectives and meet their own interests, rather than a centralized decision-maker making unified decisions. 2) Reservoir operation and management are characterized by a hierarchical management structure, characterized by "power generation subordinate to flood control, which in turn subordinates to ecology." Multi-objective models, however, only employ varying degrees of importance in operational objectives and fail to reflect the two-tiered competitive relationship among operational decision-makers. Therefore, the actual scheduling decision is a decision-making strategy formed by multiple stakeholders based on the mutual feedback of rights and responsibilities. How to comprehensively consider the mutual feedback relationship between the ecological level and the power generation level in the ecological scheduling decision-making process of cascade reservoirs to promote the spawning of drifting fish, coordinate the competitive and synergistic relationship between ecological needs and power generation benefits, and construct a decision-making method for the ecological scheduling strategy of cascade reservoirs to promote the spawning of drifting fish while taking into account power generation benefits under the condition of participation of multiple stakeholders is a technical problem that needs to be solved urgently.

[0004] Therefore, it is necessary to design a cascade reservoir decision-making method that takes into account the spawning hydrological needs of drift-eating fish to overcome the above problems. Summary of the Invention

[0005] In order to avoid the above problems, a cascade reservoir decision-making method that takes into account the hydrological needs of spawning drift-laying fish is provided. It is used to solve the problem that the existing technology cannot consider the impact of hierarchical competition relationships among multiple stakeholders in the ecological scheduling of cascade reservoirs on the scheduling strategy, so as to achieve the purpose of constructing an ecological scheduling strategy that promotes the spawning of drift-laying fish and is more in line with the actual management structure.

[0006] The present invention provides a cascade reservoir decision-making method that takes into account the hydrological requirements for spawning of fish that lay drifting eggs, comprising the following steps:

[0007] Step 1: Determine the authority of the environmental protection department and the power generation department in the operation of cascade reservoirs and the relationship between them;

[0008] Step 2: Based on the ecohydraulics method, the suitable ecological flow for spawning of typical drifting fish is quantified to construct the scheduling target of the environmental protection department;

[0009] Step 3: Based on the two-level planning theory, an ecological optimization scheduling model for cascade reservoirs is constructed to balance power generation efficiency and promote spawning of drifting fish.

[0010] Step 4: Combine the two-layer nested algorithm with the direct strategy search method to optimize and solve the ecological optimization scheduling model, and obtain the ecological scheduling strategy of cascade reservoirs to promote the spawning of drifting fish.

[0011] Preferably, in step 1, the authority of the environmental protection department and the power generation department in the cascade reservoir scheduling and the relationship between the two are as follows:

[0012] The environmental protection department aims to achieve the best spawning effect for drifting fish. It is responsible for organizing, managing and supervising the ecological scheduling of cascade reservoirs and has the authority to determine and issue ecological scheduling strategies for cascade reservoirs. The power generation department aims to maximize the power generation of cascade reservoirs to obtain maximum power generation benefits. It is responsible for coordinating the needs of all parties to formulate power generation operation scheduling strategies and execute various scheduling instructions received. There is a two-level competitive relationship between the two, which is a two-level planning structure. During the fish spawning period, the environmental protection department is the upper level and the power generation department is the lower level.

[0013] Preferably, in step 2, the method for quantifying the suitable ecological flow for spawning of typical drifting fish is as follows:

[0014] 2.1 Collect the spawning locations, times and spawning numbers of typical drifting fish species in the target river section;

[0015] 2.2 A two-dimensional hydrodynamic model of a typical drifting fish spawning habitat was established using the MIKE 21FM. The boundary conditions were determined using actual hydrological data. The Mesh Generator tool was used to divide the simulation area into U locally encrypted triangular meshes to simulate the hydrodynamic distribution characteristics of the habitat during the spawning and reproduction period of typical drifting fish.

[0016] 2.3 Using water depth and flow velocity as hydrodynamic factors affecting the spawning habitat of typical drifting fish, and river geology as an environmental factor affecting the spawning habitat of typical drifting fish, these factors were correlated with habitat suitability indicators. Suitability standards were developed to quantify the suitability of each habitat factor for typical drifting fish. The habitat suitability index of each factor was quantified, and a combined suitability factor (CSF) was calculated to create a habitat suitability curve suitable for the spawning and reproduction of typical drifting fish.

[0017] 2.4 Input the macro-cross-sectional data, relative distances, and corresponding water levels and flow velocities of each representative section of the target river section as the boundary conditions of the hydrodynamic model. Through model simulation, the water depth and flow velocity of each section of the section are obtained.

[0018] 2.5 The physical habitat model (PHABSIM model) was constructed by coupling the hydrodynamic model with the habitat suitability curves of typical drifting fish. Physical habitat simulation was performed by combining the water depth and flow velocity simulated by the hydraulic model with the suitability index given by the habitat suitability curves. The weighted usable area (WUA) of the target river section under different flow rates was calculated as follows:

[0019]

[0020] CSF(V u ,H u ,C u )=f(V u )×f(H u )×f(C u )

[0021] Where:

[0022] CSF(V u ,H u ,C u ) is the combined fitness value of the u-th grid, where u ranges from 1 to U; Au is the horizontal area of ​​the u-th grid; f(V u ) is the flow velocity of the u-th grid; f(H u ) is the water depth of the u-th grid; f(C u ) is the bottom quality of the u-th grid.

[0023] Preferably, in step 3, the ecological optimization scheduling model structure of the cascade reservoirs includes a model for pursuing the optimal spawning effect of drifting fish by the upper environmental protection department and a model for pursuing the optimal power generation benefit by the lower power generation department. The expression of the ecological optimization scheduling model of the cascade reservoirs is:

[0024]

[0025] Where:

[0026] Upper objective function F:R e The ecological benefits of cascade reservoirs in promoting the spawning of drifting fish are expressed as the optimal fit of the appropriate ecological flow required by the target fish in the downstream river. That is, when scheduling according to the optimized ecological and power generation scheduling rules, the absolute value of the difference between the discharge flow and the ecological flow of the cascade reservoirs in each time period during the scheduling period is counted, and their average is calculated; the appropriate ecological flow required for the spawning of fish in the downstream river of the cascade reservoirs is The discharge flow of the cascade reservoir is T is the total number of calculation periods; δ is the fit penalty coefficient, and its value is determined as follows: and are the lower and upper limits of suitable ecological flow, respectively. When it is within the ecological flow range, Take δ=1; when When it is outside the ecological flow range, OR Take δ = 2;

[0027] Lower layer objective function f: E avg is the power generation benefit of the cascade reservoirs, defined as the average power generation over many years; N i,t is the output of reservoir i during period t; η i is the comprehensive output coefficient of the power station at reservoir i; H i,t is the net water head of reservoir i during period t; q i,t is the power generation flow of reservoir i in period t; n is the number of years; m is the number of cascade reservoirs;

[0028] Upper-level decision variable x=(x i,1 ,x i,2 ,…,x i,k ) is the ecological regulation rule for cascade reservoirs to promote spawning of drifting fish, x i,k It represents the ecological flow control water level of reservoir i in each decade. This water level is between the dead water level and the normal water level of the reservoir. The default control line rises evenly in other periods.

[0029] Lower level decision variable y=(y i,1 ,y i,2 ,…,y i,k) is the power generation dispatching rule of cascade reservoirs, y i,k Indicates the power generation flow control water level of reservoir i in each decade. This water level is between the dead water level and the normal water level of the reservoir. The default control line rises evenly in other periods.

[0030] described is the dead water level of reservoir i;

[0031] described is the normal water level of reservoir i;

[0032] The V i,t is the water storage capacity of reservoir i at the beginning of period t;

[0033] I i,t is the inflow of reservoir i during period t;

[0034] The Q i,t is the outflow of reservoir i during period t;

[0035] The S i,t is the water discharge of reservoir i during period t;

[0036] The L i,t is the evaporation and leakage loss of reservoir i during period t;

[0037] The Δ t is the time step;

[0038] The QJ i,t is the interval flow between reservoir i and reservoir i+1 during period t;

[0039] The V i,t,min is the lower limit of the water storage capacity of reservoir i during period t;

[0040] The V i,t,max is the upper limit of the water storage capacity of reservoir i during period t;

[0041] The q i,t,min is the lower limit of the outflow of reservoir i during period t;

[0042] The q i,t,max is the upper limit of the outflow of reservoir i during period t;

[0043] The N i,min is the minimum output of reservoir i during period t;

[0044] The N i,max is the maximum output of reservoir i during period t;

[0045] The ΔZ i is the water level change of reservoir i in a unit time period;

[0046] The ΔZi,max is the maximum water level variation of reservoir i within a unit time period.

[0047] Preferably, the optimization solution method of the ecological optimization scheduling model in step 4 is as follows:

[0048] 4.1 The Hybrid Two-Level Multi-Population Sequential Evolutionary Group Heuristic Intelligent Algorithm (HBLSHIO) is used to optimize and solve the scheduling rules. A non-parametric penalty function method is used to handle the constraints, and a nested iterative calculation method is combined to approach the global optimal solution of the two-level programming model.

[0049] 4.2 A direct strategy search method based on the implicit random scheduling rule optimization concept is used. By using the model decision variables obtained in step 4.1, a scheduling rule is generated to simulate the scheduling of a long series of historical runoff sequences, and the storage and release process of the reservoir is obtained. Then, the objective function value of the ecological optimization scheduling model is calculated to evaluate the optimal scheduling scheme.

[0050] 4.3 Repeat steps 4.1 and 4.2, iterate repeatedly until the set stopping condition is met, and output the optimal solution of the ecological and power generation scheduling rules in the two-level planning model. The optimal solution of the ecological and power generation scheduling rules is the ecological scheduling strategy of cascade reservoirs to promote the spawning of drifting fish while taking into account power generation benefits; the set stopping condition is that the difference in ecological benefits between the results of the previous and next ten iterations is less than 0.001 or the number of iterations exceeds 1000 times.

[0051] Preferably, step 4.1 specifically includes:

[0052] 4.1.1 After the upper ecological model determines a set of P evolutionary particles representing the initial ecological flow to ensure the water level x, it passes them to the lower power generation model;

[0053] 4.1.2 The lower layer guarantees the water level x according to each representative initial ecological flow given by the upper layer s The evolutionary particles, 1≤s≤P, are used to optimize the lower power generation model based on the HBLSHIO algorithm to determine the water level x corresponding to each group of ecological flow. s A set of output control lines y, each set of ecological flow to ensure the water level x s and output control line y s,k The simulation is run using step 4.2, so that the ecological flow in the upper layer is given to ensure the water level x s Lower reservoir power generation benefits To achieve the optimal, the optimal output control line y s,k pass it on to the upper level;

[0054] 4.1.3 The upper layer guarantees the water level x for each ecological flow group given by the lower layer. s Output control line y s,kBased on the HBLSHIO algorithm, the upper ecological model is optimized and solved, and the ecological flow is adjusted to ensure the water level. Ensure the water level x for each group of ecological flow s and output control line y s,k Use step 4.2 to simulate the operation and make it run at the given output control line y s,k Ecological benefit R e Best, adjust the ecological flow to ensure water level Passed to the underlying model.

[0055] Preferably, step 4.2 specifically includes:

[0056] 4.2.1 Based on the guaranteed water level x for each set of ecological flows given in step 4.1 s and output control line y s,k , generate ecological dispatching rules and power generation rules, determine the discharge flow of each reservoir in the current period, and determine the reservoir water level or storage capacity at the end of the period based on the reservoir water level or storage capacity at the beginning of the period and the water balance equation;

[0057] 4.2.2 Calculation of the appropriate ecological flow compatibility R for period t t :

[0058] 4.2.3 Calculation of power generation E during period t t :

[0059] 4.2.4 Repeat steps 4.2.2 to 4.2.3 to obtain the water level, storage capacity, outflow, and suitable ecological flow fit R of each reservoir in the entire period 1-T. t and the power generation E during the period t Then, according to the scheduling objective function, each group of ecological flow guarantees the water level x s and output control line y s,k The corresponding ecological benefit F of the cascade reservoirs in promoting the spawning of drifting fish and the power generation benefit f of the cascade reservoirs are fed back to step 4.1, which is the fitness value of each particle.

[0060] Compared with existing technologies, the present invention has the following advantages: It addresses the problem that existing ecological scheduling models for promoting the spawning of drifting fish in cascade reservoirs only describe a single-agent centralized decision-making model and ignore the hierarchical decision-making structure of multiple stakeholders, which leads to changes in the optimization boundaries of scheduling strategies. This invention provides a method for optimizing and extracting scheduling strategies under the conditions where multiple stakeholders from environmental protection and power generation participate in scheduling decisions. By fully considering the hierarchical decision-making structure between environmental protection and power generation, the two-level planning and scheduling decision-making method for cascade reservoirs to promote the spawning of drifting fish determined by the present invention can maximize the combined ecological and power generation benefits of reservoirs within the constraints of actual scheduling management systems, rather than scheduling decisions that are theoretically feasible but unattainable under actual management systems. The present invention considers and analyzes the responsibilities and hierarchical connections between environmental protection and power generation departments in the practical scheduling of promoting the spawning of drifting fish. This improves the current theoretical model of reservoir optimization scheduling, which is difficult to adapt to the characteristics and needs of actual scheduling decisions, narrows the gap between theoretical models and practical applications, and provides important reference value for further improving more scientific and reasonable cascade reservoir scheduling decision-making models and fully realizing the comprehensive benefits of reservoirs. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a schematic diagram of the two-layer structure of the present invention;

[0062] Figure 2 A diagram showing the steps for solving the multi-stakeholder two-tier programming model of the present invention;

[0063] Figure 3 A schematic diagram of the planar position of cascade reservoirs according to a preferred embodiment of the present invention;

[0064] Figure 4 This is the water level and flow process of the upstream reservoir A during the ecological regulation of the cascade reservoirs in a preferred embodiment of the present invention;

[0065] Figure 5 This is the water level and flow process of the downstream reservoir B during the ecological regulation of the cascade reservoirs in a preferred embodiment of the present invention;

[0066] Figure 6 This is a preferred embodiment of the present invention showing the fish spawning amount and flow process in the downstream river monitoring section before and after the ecological regulation period of the cascade reservoirs. DETAILED DESCRIPTION

[0067] like Figures 1 to 6As shown, this first embodiment specifically illustrates the method of the present invention. In this embodiment, a cascade of reservoirs, consisting of Reservoir A in the upper middle reaches of the Yangtze River and Reservoir B in the lower reaches, is selected as the scheduling target. Comprehensive scheduling is carried out to promote the spawning of drifting fish downstream of the cascade reservoirs. During the scheduling period, the ecological flow processes required for the spawning of drifting fish must be met as much as possible, while the power generation of the cascade reservoirs must be increased to improve operational efficiency and enhance power supply capabilities.

[0068] The unique topography, geomorphology, and hydrological and hydrodynamic environment of the downstream river channel of this cascade reservoir provide an excellent spawning and habitat for fish. Furthermore, the cascade reservoirs are located in a river section rich in hydropower resources, possessing a significant installed capacity and forming a key component of a hydropower base in my country. Therefore, the cascade reservoirs face significant challenges in both promoting the spawning of drifting fish and generating electricity.

[0069] Drifting fish are a major component of the Yangtze River system's fish resources. The conservation and utilization of their germplasm are directly related to the quality and quantity of my country's freshwater fisheries and reflect the health and integrity of the basin's ecosystem. Flooding rivers are a key factor in spawning these species. Drifting eggs have a higher specific gravity than water, and their spawning, fertilization, and swelling require certain water flow conditions to prevent them from sinking and necrotic necrosis due to lack of oxygen in stagnant water. Furthermore, these species have evolved specialized ecological requirements for migratory migration over long evolutionary processes, requiring migration distances ranging from as little as 30 km to as much as 150 km, and reaching sexual maturity under the stimulation of water flow during these migrations. However, the obstruction of river hydrology by cascade reservoirs has significantly altered the river's hydrological regime. In particular, the flattening of flow caused by reservoir storage and release has become a significant threat to the spawning and reproduction of various drifting fish species.

[0070] The downstream section of the river near this cascade reservoir is a key spawning area for numerous rare and endemic drifting or commercial fish species, including the goby, cylindrical goby, longfin goby, Yichang goby, silver goby, silver goby, heterotrophic goby, round-mouthed copperfish, and the four major carps: black carp, grass carp, silver carp, and bighead carp. It is a key component of a national nature reserve for rare and endemic fishes. However, since the construction and operation of the cascade reservoirs, the drifting fish resources in this section have shown a significant decline. For example, natural reproduction of the round-mouthed copperfish, a key drifting fish species, has not been observed in this section for 14 consecutive years. Therefore, implementing ecological regulation in cascade reservoirs to adjust runoff and create a hydrological regime suitable for the spawning of drifting fish is crucial to the ecological health of the watershed. Developing a scientific, rational, and mutually acceptable ecological regulation plan to fully realize the ecological benefits of cascade reservoirs is crucial.

[0071] The ecological scheduling problem of promoting the spawning of drifting fish in the cascade reservoirs was taken as an example. According to the general spawning pattern of the representative drifting fish in this river section, namely the four major carps, their spawning time is concentrated in May and June. Therefore, May 21st to June 10th was selected as the ecological scheduling period for a long series of optimization scheduling simulations.

[0072] Taking the ecological benefits of promoting the spawning of drifting fish as the goal of the upper-level environmental protection department and maximizing power generation as the goal of the lower-level power generation department, a two-level planning model is constructed. The two-level nested algorithm is combined with the direct strategy search method to optimize and solve the scheduling scheme for promoting the spawning of drifting fish under the hierarchical competition relationship among multiple stakeholders of cascade reservoirs.

[0073] The present invention provides a cascade reservoir decision-making method that takes into account the hydrological requirements for spawning fish that lay drifting eggs, comprising the following steps, which are performed in sequence:

[0074] Step 1: Describe the authority of the environmental protection department and the power generation department in the operation of cascade reservoirs and the relationship between them.

[0075] The environmental protection department aims to achieve the best spawning effect for drifting fish. It is responsible for organizing, managing, and supervising the ecological scheduling of cascade reservoirs and has the authority to determine and issue ecological scheduling strategies for cascade reservoirs. The power generation department aims to maximize the power generation of cascade reservoirs to obtain maximum benefits. It is responsible for coordinating the needs of all parties to formulate power generation operation scheduling strategies and execute various scheduling instructions received. There is a hierarchical competitive relationship between the two, which can be described as a two-layer planning structure. During the fish spawning period, the environmental protection department is the upper entity and the power generation department is the lower entity. Figure 1 shown.

[0076] Step 2: Based on the ecohydraulics method, the suitable ecological flow for spawning of typical drifting fish is quantified to construct the scheduling target of the environmental protection department;

[0077] The monitoring results of the spawning location, time and number of spawning of typical drifting fish in the target river section from 2012 to 2019 were collected. According to statistics, the suitable flow velocity during the spawning period of typical drifting fish in this river section is 0.6-1.3m / s, the optimal flow velocity is 0.9-1.0m / s, the suitable water depth is 3.0-18.0m, and the optimal water depth is 9.0-12.0m.

[0078] A two-dimensional hydrodynamic model of a typical drifting fish spawning habitat was established using the MIKE 21FM. This model employed an unstructured irregular triangular mesh, which accurately depicted the shoreline conditions of the simulated area. The mesh size was determined based on computational efficiency and the spatial distribution of the terrain, and the boundary conditions were determined using actual hydrological data. A 1:2000 riverbed topographic map was used as the terrain data. The Mesh Generator tool was used to divide the simulated area into locally encrypted triangular meshes. Typical daily average flow velocities at two sections were selected for velocity verification. The simulated values ​​of water level and flow velocity were highly consistent with the measured values. The average water level error at the two sections was within 0.08 m, and the maximum water level error was within 0.22 m. The flow velocity had a slightly larger error due to the influence of the outflow from the upstream reservoir, with an average error of 0.07 m / s and a maximum error of 0.12 m / s.

[0079] Water depth and flow velocity were used as hydrodynamic factors affecting the spawning habitat of typical drifting fish, and river geology was used as an environmental factor affecting the spawning habitat of typical drifting fish. These factors were correlated with habitat suitability indicators, and a value between 0 and 1 was used to define the preference of typical drifting fish for these habitat factors, with 0 indicating completely unsuitable and 1 indicating completely suitable. The closer the value is to 1, the greater the preference of typical drifting fish for this habitat factor. The combined suitability factor (CSF) was calculated, and a habitat suitability curve suitable for the spawning and reproduction of typical drifting fish was drawn.

[0080] Input the large-scale cross-sectional data, relative distances, and corresponding water levels and flow velocities of each representative section of the target river section as the boundary conditions of the hydrodynamic model. Through model simulation, the water depth and flow velocity of each section of the cross-section are obtained.

[0081] The physical habitat model (PHABSIM model) was constructed by coupling the hydrodynamic model with the habitat suitability curves of typical drifting fish. Physical habitat simulation was performed by combining the water depth and flow velocity simulated by the hydraulic model with the suitability index given by the habitat suitability curves. The weighted usable area (WUA) of the target river section under different flow rates was calculated as follows:

[0082]

[0083] CSF(V u ,H u ,C u )=f(V u )×f(H u )×f(C u )

[0084] Where:

[0085] CSF(V u ,H u ,C u ) is the combined fitness value of the u-th grid, where u ranges from 1 to U; Au is the horizontal area of ​​the u-th grid; f(V u ) is the flow velocity of the u-th grid; f(H u ) is the water depth of the u-th grid; f(C u ) is the bottom quality of the u-th grid.

[0086] The lowest and highest flows of the typical river section during the spawning period of typical drifting fish were counted. Ten operating conditions were evenly selected within the above flow range for physical habitat simulation. The weighted available area change characteristics of the habitat of the four major carps under different outflow flows were counted. The outflow flow was 3000m 3 / s as an example, the WUA area is 3.66km 2 , accounting for 24.26% of the total area of ​​this typical river section. Based on this, a curve of the relationship between outflow and WUA was drawn. Taking the WUA area accounting for 20% of the total area of ​​this typical river section as the limit, the suitable ecological flow for spawning typical drifting fish in this river section was quantified as 2000-4500m 3 / s.

[0087] Step 3: Based on the two-level planning theory, a mathematical optimization model for ecological scheduling of cascade reservoirs to promote the spawning of drifting fish is constructed, taking into account power generation benefits.

[0088] The structure of the mathematical optimization model for ecological regulation of cascade reservoirs includes a model in which the upper environmental protection department pursues the optimal spawning effect of drifting fish and a model in which the lower power generation department pursues the optimal power generation benefit.

[0089] The upper objective function F of the mathematical optimization model for ecological regulation of cascade reservoirs is:

[0090]

[0091] R e The ecological benefit of the cascade reservoirs in promoting the spawning of drifting fish is expressed as the optimal fit of the appropriate ecological flow required for the production of drifting fish in the river downstream of the cascade reservoirs. That is, when the dispatch is carried out according to the optimized ecological and power generation dispatch rules, the absolute value of the difference between the discharge flow of the cascade reservoirs in each period during the dispatch period and the ecological flow is counted, and their average is calculated; the appropriate ecological flow required for the river downstream of the cascade reservoirs is The discharge flow of the cascade reservoir is T is the total number of calculation periods; δ is the fit penalty coefficient, and its value is determined as follows: and They are the lower and upper limits of the ecological flow suitable for drifting fish in the downstream river of the cascade reservoirs. When it is within the ecological flow range, Take δ=1; when When it is outside the ecological flow range, OR Take δ=2.

[0092] The lower objective function f of the mathematical optimization model for ecological regulation of cascade reservoirs is:

[0093]

[0094] E avg is the power generation benefit of the cascade reservoirs, defined as the average power generation of the cascade reservoirs over many years; N A and N B are the outputs of reservoir A and reservoir B during period t; η A and η B are the comprehensive output coefficients of the power stations of reservoirs A and B respectively; H A,t and H B,t are the net water heads of reservoir A and reservoir B during period t; q A,t and q B,t are the power generation flows of reservoir A and reservoir B in period t; the dispatching period is 55 years; the number of cascade reservoirs is 2;

[0095] Upper-level decision variable x=(x i,1 ,x i,2 ,…,x i,k )=(x A,1 ,x A,2 ,…,x A,k ,x B,1 ,x B,2 ,…,x B,k ) is the ecological regulation rule of the cascade reservoir, x A,k represents the ecological flow control water level of reservoir A every ten days, which is between the dead water level of 540m and the normal water level of 600m; x B,k The ecological flow control water level of Reservoir B for each ten-day period is between the dead water level of 370m and the normal water level of 380m. The default control line for other periods rises evenly.

[0096] Lower level decision variable y=(y i,1 ,y i,2 ,…,y i,k )=(y A,1 ,y A,2 ,…,y A,k ,y B,1 ,y B,2 ,…,y B,k ) is the power generation dispatching rule of the cascade reservoirs, y A,krepresents the power generation flow control water level of reservoir A every ten days, which is between the reservoir dead water level of 540m and the normal water level of 600m; x B,k The ecological flow control water level of Reservoir B for each ten-day period is between the dead water level of 370m and the normal water level of 380m. The default control line for other periods rises evenly.

[0097] The constraints solved by the cascade reservoir ecological operation model based on the two-level planning structure include ecological flow control water level position constraints, water balance constraints, upstream and downstream reservoir linkage constraints, storage capacity constraints, turbine constraints, output constraints, water level fluctuation constraints, output control water level position constraints and reservoir downstream ecological base flow constraints.

[0098] in:

[0099] (1) Ecological flow control water level position constraints:

[0100]

[0101]

[0102] Where: is the dead water level of reservoir A, i.e. 540m, is the normal water level of reservoir A, i.e. 600m; is the dead water level of reservoir B, i.e. 370m, is the normal water level of reservoir B, i.e. 380m.

[0103] (2) Output control water level position constraint:

[0104]

[0105]

[0106] (3) Water balance constraints:

[0107] V A,t+1 =V A,t +(I A,t -Q A,t )Δ t -L A,t ,Q A,t =q A,t +S A,t

[0108] V B,t+1 =V B,t +(I B,t -Q B,t )Δ t -L B,t ,Q B,t =q B,t+S B,t

[0109] Where: V A,t and V B,t are the water storage capacity of reservoir A and reservoir B at the beginning of period t, V A,t+1 and V B,t+1 are the water storage of reservoir A and reservoir B at the beginning of period t+1, I A,t and I B,t are the inflows of reservoir A and reservoir B during period t, Q A,t and Q B,t are the outflows of reservoir A and reservoir B during period t, S A,t and S B,t are the discharge flows of reservoir A and reservoir B during period t, L A,t and L B,t are the evaporation and leakage losses of reservoir A and reservoir B during period t, Δ t is the time step.

[0110] (4) Constraints on upstream and downstream reservoirs:

[0111] I B,t =Q B,t +QJ t

[0112] Where: QJ i,t is the interval flow between reservoir i and reservoir i+1 during period t.

[0113] (5) Storage capacity constraints:

[0114] V i,t,min ≤V i,t ≤V i,t,max

[0115] Where: V i,t,min is the lower limit of the water storage capacity of reservoir i during period t, V i,t,max is the upper limit of the water storage capacity of reservoir i in period t.

[0116] (6) Outbound flow constraints:

[0117] q i,t,min ≤q i,t ≤q i,t,max

[0118] Where: q i,t,min is the lower limit of the power generation flow of reservoir i during period t, q i,t,max is the upper limit of the power generation flow of reservoir i during period t. To meet the navigation needs of the downstream river, the minimum outflow of the two reservoirs is 1200m 3 / s, the maximum outbound flow is 12000m 3 / s.

[0119] (7) Output constraints:

[0120] N i,min ≤η i H i,t q i,t ≤N i,max

[0121] Where: N i,min is the guaranteed output of reservoir i during period t, N i,max is the installed capacity output of reservoir i in period t.

[0122] (8) Water level fluctuation constraint

[0123] ΔZ i ≤ΔZ i,max

[0124] Where: ΔZ i is the water level change of reservoir i in a unit time period, ΔZ i,max is the maximum water level variation of reservoir i within a unit time period.

[0125] Step 4: Combine the two-layer nested algorithm and the direct strategy search method to optimize and solve the ecological optimization scheduling model and obtain the ecological scheduling strategy for the cascade reservoirs. Figure 2 As shown, this step includes the following specific solution steps:

[0126] Step 4.1: Use the Hybrid Two-Level Multi-Population Sequential Evolutionary Group Heuristic Intelligent Algorithm (HBLSHIO) to optimize and solve the scheduling rules, use a non-parametric penalty function method to handle the constraints, and combine the nested iterative calculation method to approximate the global optimal solution of the two-level programming model. Specifically, it includes steps 4.1.1 to 4.1.4:

[0127] Step 4.1.1: After the upper ecological model determines a set of P (P > 20) evolutionary particles representing the initial ecological flow guaranteeing the water level x, it passes them to the lower power generation model;

[0128] Step 4.1.2, the lower layer guarantees the water level x according to each representative initial ecological flow given by the upper layer s The evolutionary particles, 1≤s≤P, are used to optimize the lower power generation model based on the HBLSHIO algorithm to determine the water level x corresponding to each group of ecological flow. s A set of output control lines y, each set of ecological flow to ensure the water level x s and output control line y s,k The simulation is run using step 3.2, so that the ecological flow given in the upper layer guarantees the water level x s Lower reservoir power generation benefits To achieve the optimal, the optimal output control line y s,kpass it on to the upper level;

[0129] Step 4.1.3: The upper layer guarantees the water level x for each group of ecological flows given by the lower layer. s Output control line y s,k , based on the HBLSHIO algorithm to optimize and solve the upper ecological model, adjust the ecological flow to ensure the water level x' s , ensure the water level x for each group of ecological flow s and output control line y s,k Use step 3.2 to simulate the operation and make it run at the given output control line y s,k Ecological benefit R e The best way is to adjust the ecological flow to ensure the water level x' s Passed to the lower model;

[0130] Step 4.2 uses a direct strategy search method based on the implicit random scheduling rule optimization concept. By using the model decision variables obtained in step 4.1, a scheduling rule is generated to simulate the scheduling of a long series of historical runoff sequences, and the storage and release process of the reservoir is obtained. Then, the optimization model objective function value is calculated to evaluate the preferred scheduling solution. The specific steps include steps 4.2.1-4.2.4:

[0131] Step 4.2.1: Based on the ecological flow rate guarantee water level x for each group given in step 4.1 s and output control line y s,k , generate ecological dispatching rules and power generation rules, determine the discharge flow of each reservoir in the current period, and determine the reservoir water level or storage capacity at the end of the period based on the reservoir water level or storage capacity at the beginning of the period and the water balance equation;

[0132] Step 4.2.2: Calculate the appropriate ecological flow compatibility R for period t t :

[0133]

[0134] Step 4.2.3, calculate the power generation E during period t t :

[0135]

[0136] Step 4.2.4, repeat steps 4.2.2-4.2.3 to obtain the water level, storage capacity, outflow and suitable ecological flow fit R of the two reservoirs in the whole period 1-T t and the power generation E during the period t Then, according to the scheduling objective function, each group of ecological flow guarantees the water level x s and output control line y s,kThe corresponding ecological benefit F of the cascade reservoir and the power generation benefit f of the cascade reservoir are fed back to step 3.1, which is the fitness value of each particle;

[0137] Step 4.3: Repeat steps 4.1 and 4.2, and iterate repeatedly until the set stopping condition is met (the difference in ecological benefits between the ten iterations is less than 0.001 or the number of iterations exceeds 1000), and output the optimal solution of the two-level planning model and power generation rules. The optimal solution of the ecological and power generation rules is the ecological scheduling strategy for cascade reservoirs that takes into account power generation benefits.

[0138] According to the above steps, the multi-stakeholder decision-making scheduling scheme of the cascade reservoir is used for optimized scheduling, which can achieve better ecological benefits while taking into account the power generation benefits. The operation status of the reservoir during the ecological scheduling of the cascade reservoir in a typical dry year is analyzed. During the ecological scheduling period, the scheduling strategy of the cascade reservoir significantly changed the natural runoff process. By significantly increasing the outflow of the reservoir, a significant water rise process suitable for the spawning and reproduction of drifting fish was formed, which is more in line with the suitable ecological flow process. At the same time, during the ecological scheduling period, the cumulative power generation of the cascade reservoir reached 1.675 billion kWh, which better took into account the power generation benefits. Figure 3 During the ecological operation period, the water level of the upstream reservoir A in the cascade reservoir slowly dropped from 564.3m at the beginning of the operation period to 556.5m at the end of the operation period, with an average outflow of 2998m 3 / s, which is 1912m higher than the average inflow flow 3 / s. The water level of the downstream reservoir B in the cascade reservoir dropped from 376.8m at the beginning of the scheduling period to 375.5m at the end of the scheduling period, and the average outflow was 3350m 3 / s, which is higher than the average inflow flow of 3237m 3 / s, such as Figure 4 and Figure 5 In this optimized scheduling strategy, both reservoirs begin the ecological scheduling process from a high-water-level operating state, ensuring the high-head power generation benefits of the power station. Subsequently, both reservoirs gradually draw down their own water levels, thereby obtaining a larger outflow, creating a rising water flow suitable for spawning and reproduction of drifting fish, maintaining a suitable ecological flow in the downstream river, and coordinating the achievement of the reservoir water level drawdown target during the drawdown period.

[0139] The early monitoring results of fish resources also reflect the significant effect of the ecological regulation of cascade reservoirs. During the flood period of ecological regulation, a peak of spawning of four major carps, a type of drifting fish, was detected at a monitoring section in the downstream river, with an egg and fry runoff of about 600,000 grains. After the flood process, large-scale spawning of four major carps was detected at the section, with a peak egg and fry runoff of more than 4 million grains. Figure 6It can be seen that the optimization scheduling decision-making method of the cascade reservoir is quite effective. It can greatly meet the river flow process requirements of spawning and reproduction of drifting fish while taking into account the benefits of power generation.

[0140] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A decision-making method for cascade reservoirs that takes into account the hydrological requirements for spawning of drifting egg-laying fish, characterized in that: The steps include: Step 1: Determine the authority of the environmental protection department and the power generation department in the operation of cascade reservoirs and the relationship between them; Step 2: Based on the ecohydraulics method, the suitable ecological flow for spawning of typical drifting fish is quantified to construct the scheduling target of the environmental protection department; Step 3: Based on the two-level planning theory, an ecological optimization scheduling model for cascade reservoirs is constructed to balance power generation efficiency and promote spawning of drifting fish. Step 4: Combine the two-layer nested algorithm and the direct strategy search method to optimize and solve the ecological optimization scheduling model, and obtain the ecological scheduling strategy for cascade reservoirs to promote the spawning of drifting fish; In step 3, the ecological optimization scheduling model structure of the cascade reservoirs includes the upper-level environmental protection department's pursuit of the optimal drifting fish spawning effect model and the lower-level power generation department's pursuit of the optimal power generation benefit model. The expression of the cascade reservoir ecological optimization scheduling model is: Where: Upper objective function F:R e The ecological benefits of cascade reservoirs in promoting the spawning of drifting fish are expressed as the optimal fit between the appropriate ecological flow required by the target fish in the downstream river. That is, when the cascade reservoirs are dispatched according to the optimized ecological and power generation dispatching rules, the absolute value of the difference between the downstream flow and the ecological flow in each period of the dispatching period is calculated and the average is calculated. The suitable ecological flow required for fish spawning in the downstream river of the cascade reservoir is The discharge flow of the cascade reservoir is T is the total number of calculation periods; δ is the fit penalty coefficient, and its value is determined as follows: and are the lower and upper limits of suitable ecological flow, respectively. When it is within the ecological flow range, Take δ=1; when When it is outside the ecological flow range, OR Take δ = 2; Lower layer objective function f: E avg is the power generation benefit of the cascade reservoirs, defined as the average power generation over many years; N i,t is the output of reservoir i during period t; η i is the comprehensive output coefficient of the power station at reservoir i; H i,t is the net water head of reservoir i during period t; q i,t is the power generation flow of reservoir i in period t; n is the number of years; m is the number of cascade reservoirs; Upper-level decision variable x=(x i,1 ,x i,2 ,…,x i,k ) is the ecological regulation rule for cascade reservoirs to promote spawning of drifting fish, x i,k It represents the ecological flow control water level of reservoir i in each decade. This water level is between the dead water level and the normal water level of the reservoir. The default control line rises evenly in other periods. Lower level decision variable y=(y i,1 ,y i,2 ,…,y i,k ) is the power generation dispatching rule of cascade reservoirs, y i,k Indicates the power generation flow control water level of reservoir i in each decade. This water level is between the dead water level and the normal water level of the reservoir. The default control line rises evenly in other periods. described is the dead water level of reservoir i; described is the normal water level of reservoir i; The V i,t is the water storage capacity of reservoir i at the beginning of period t; I i,t is the inflow of reservoir i during period t; The Q i,t is the outflow of reservoir i during period t; The S i,t is the water discharge of reservoir i during period t; The L i,t is the evaporation and leakage loss of reservoir i during period t; The Δ t is the time step; The QJ i,t is the interval flow between reservoir i and reservoir i+1 during period t; The V i,t,min is the lower limit of the water storage capacity of reservoir i during period t; The V i,t,max is the upper limit of the water storage capacity of reservoir i during period t; The q i,t,min is the lower limit of the outflow of reservoir i during period t; The q i,t,max is the upper limit of the outflow of reservoir i during period t; The N i,min is the minimum output of reservoir i during period t; The N i,max is the maximum output of reservoir i during period t; The ΔZ i is the water level change of reservoir i in a unit time period; The ΔZ i,max is the maximum water level variation of reservoir i within a unit time period; The optimization solution method of the ecological optimization scheduling model in step 4 is as follows: 4.1 A hybrid two-level multi-population sequential evolutionary group heuristic intelligent algorithm is used to optimize and solve the scheduling rules. A non-parametric penalty function method is used to handle the constraints, and a nested iterative calculation method is combined to approach the global optimal solution of the two-level programming model. 4.2 A direct strategy search method based on the implicit random scheduling rule optimization concept is used. By using the model decision variables obtained in step 4.1, a scheduling rule is generated to simulate the scheduling of a long series of historical runoff sequences, and the storage and release process of the reservoir is obtained. Then, the objective function value of the ecological optimization scheduling model is calculated to evaluate the optimal scheduling scheme. 4.3 Repeat steps 4.1 and 4.2, iterate repeatedly until the set stopping condition is met, and output the optimal solution of the ecological and power generation scheduling rules in the two-level planning model. The optimal solution of the ecological and power generation scheduling rules is the ecological scheduling strategy of cascade reservoirs to promote the spawning of drifting fish while taking into account power generation benefits; the set stopping condition is that the difference in ecological benefits between the results of the previous and next ten iterations is less than 0.001 or the number of iterations exceeds 1000 times.

2. A cascade reservoir decision-making method that takes into account the hydrological requirements for spawning of fish that lay drifting eggs as described in claim 1, characterized in that: In step 1, the authority of the environmental protection department and the power generation department in the cascade reservoir operation and the relationship between them are as follows: The environmental protection department aims to achieve the best spawning effect for drifting fish. It is responsible for organizing, managing and supervising the ecological scheduling of cascade reservoirs and has the authority to determine and issue ecological scheduling strategies for cascade reservoirs. The power generation department aims to increase the power generation of cascade reservoirs to obtain maximum power generation benefits. It is responsible for coordinating the needs of all parties to formulate power generation operation scheduling strategies and execute various scheduling instructions received. There is a two-level competitive relationship between the two, which is a two-level planning structure. During the fish spawning period, the environmental protection department is the upper level and the power generation department is the lower level.

3. The cascade reservoir decision-making method for taking into account the hydrological requirements for spawning of fish with drifting eggs as described in claim 1 is characterized by: In step 2, the quantification method for the ecologically suitable flow rate for spawning of typical drifting fish is as follows: 2.1 Collect the spawning locations, times and spawning numbers of typical drifting fish species in the target river section; 2.2 A two-dimensional hydrodynamic model of a typical drifting fish spawning habitat was established using the MIKE 21FM. The boundary conditions were determined using actual hydrological data. The Mesh Generator tool was used to divide the simulation area into U locally encrypted triangular meshes to simulate the hydrodynamic distribution characteristics of the habitat during the spawning and reproduction period of typical drifting fish. 2.3 Using water depth and flow velocity as hydrodynamic factors affecting the spawning habitat of typical drifting fish, and river geology as an environmental factor affecting the spawning habitat of typical drifting fish, these factors were correlated with habitat suitability indicators. Suitability standards were developed to quantify the suitability of each habitat factor for typical drifting fish. The habitat suitability index for each factor was quantified, and a combined fitness factor (CSF) was calculated to create a habitat suitability curve suitable for the spawning and reproduction of typical drifting fish. 2.4 Input the macro-cross-sectional data, relative distances, and corresponding water levels and flow velocities of each representative section of the target river section as the boundary conditions of the hydrodynamic model. Through model simulation, the water depth and flow velocity of each section of the section are obtained. 2.5 The physical habitat model was constructed by coupling the hydrodynamic model with the habitat suitability curve of typical drifting fish. The physical habitat simulation was performed by combining the water depth and flow velocity simulated by the hydraulic model with the suitability index given by the habitat suitability curve. The weighted available area (WUA) of the target river section under different flow rates was calculated as follows: CSF(V u ,H u ,C u )=f(V u )×f(H u )×f(C u ) Where: CSF(V u ,H u ,C u ) is the combined fitness value of the u-th grid, where u ranges from 1 to U; A u is the horizontal area of ​​the u-th grid; f(V u ) is the flow velocity of the u-th grid; f(H u ) is the water depth of the u-th grid; f(C u ) is the bottom quality of the u-th grid.

4. The cascade reservoir decision-making method for taking into account the hydrological requirements for spawning of drifting-eating fish as claimed in claim 1, wherein step 4.1 specifically comprises: 4.1.1 After the upper ecological model determines a set of P evolutionary particles representing the initial ecological flow to ensure the water level x, it passes them to the lower power generation model; 4.1.2 The lower layer guarantees the water level x according to each representative initial ecological flow given by the upper layer s The evolutionary particles, 1≤s≤P, are used to optimize the lower power generation model based on the HBLSHIO algorithm to determine the water level x corresponding to each group of ecological flow. s A set of output control lines y, each set of ecological flow to ensure the water level x s and output control line y s,k The simulation is run using step 4.2, so that the ecological flow in the upper layer is given to ensure the water level x s Lower reservoir power generation benefits To achieve the optimal, the optimal output control line y s,k pass it on to the upper level; 4.1.3 The upper layer guarantees the water level x for each ecological flow group given by the lower layer. s Output control line y s,k , based on the HBLSHIO algorithm to optimize and solve the upper ecological model, adjust the ecological flow to ensure the water level x' s , ensure the water level x for each group of ecological flow s and output control line y s,k Use step 4.2 to simulate the operation and make it run at the given output control line y s,k Ecological benefit R e The best way is to adjust the ecological flow to ensure the water level x' s Passed to the underlying model.

5. The cascade reservoir decision-making method taking into account the hydrological requirements for spawning of fish with drifting eggs as claimed in claim 1, characterized in that: Step 4.2 specifically includes: 4.2.1 Based on the guaranteed water level x for each set of ecological flows given in step 4.1 s and output control line y s,k , generate ecological dispatching rules and power generation rules, determine the discharge flow of each reservoir in the current period, and determine the reservoir water level or storage capacity at the end of the period based on the reservoir water level or storage capacity at the beginning of the period and the water balance equation; 4.2.2 Calculation of the appropriate ecological flow compatibility R for period t t : 4.2.3 Calculation of power generation E during period t t : 4.2.4 Repeat steps 4.2.2 to 4.2.3 to obtain the water level, storage capacity, outflow, and suitable ecological flow fit R of each reservoir in the entire period 1-T. t and the power generation E during the period t Then, according to the scheduling objective function, each group of ecological flow guarantees the water level x s and output control line y s,k The corresponding ecological benefit F of the cascade reservoirs in promoting the spawning of drifting fish and the power generation benefit f of the cascade reservoirs are fed back to step 4.1, which is the fitness value of each particle.

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