29 results about "Reservoir optimization" patented technology

The invention discloses a deep and large reservoir ecological scheduling method, system and equipment based on a data-driven model of a coupling physical mechanism, and belongs to the technical field of water resource management and environmental protection. Firstly, a physical water temperature model is constructed based on measured data, diversified water temperature change scenes are generated, and a deep learning model constrained by a physical mechanism is constructed. Secondly, carrying out sensitivity analysis to identify key influence factors for driving water temperature change, constructing a reservoir optimization scheduling model, coupling a deep learning model constrained by a physical mechanism, and deducing a scheduling rule set on the premise of meeting a water temperature target; and finally, carrying out multi-index optimization analysis. The invention further provides a deep and large reservoir ecological scheduling system and electronic equipment, and the deep and large reservoir ecological scheduling method is realized. According to the method, the power generation scheduling rule set of the deep and large reservoir can be scientifically deduced, the optimal scheduling scheme with both ecological benefits and economic benefits is screened out by introducing the multi-index optimization method, and overall balance of ecological requirements and power generation benefits is achieved.

The invention relates to the technical field of reservoir flood control dispatching, and discloses a dam hydraulic opening and closing control method, device and equipment and a storage medium. The method comprises the steps that multi-source hydrological data, weather forecast information and unit operation states of a current reservoir are collected; inputting the multi-source hydrological data and the weather forecast information into a preset hydrological prediction model, and outputting a hydrological prediction result; based on the hydrological prediction result and the real-time reservoir area water level and the unit operation state in the multi-source hydrological data, a gate opening control instruction is generated through a reservoir optimization scheduling model; and a hydraulic opening and closing system is adjusted according to the gate opening control instruction, and the current reservoir flood discharge gate opening is controlled. According to the method, data such as upstream incoming water, reservoir area water level and water consumption are utilized, weather forecast information is combined, a hydrological prediction model is constructed, a reservoir dispatching scheme is optimized according to a hydrological model prediction result, the reservoir area water level and unit operation conditions, and on the premise that flood prevention safety is guaranteed, reservoir dispatching is optimized, the reservoir area water level is automatically adjusted, and power generation benefits are improved.

The invention relates to the technical field of reservoir optimization scheduling, in particular to a dynamic multi-objective optimization control system and method for the water level of a reservoir in a flood season. The method comprises the following steps: acquiring real-time monitoring data of a reservoir; extracting current water level state information according to the real-time monitoring data of the reservoir; establishing a reservoir water balance basic model based on the current water level state information; analyzing pipeline water supply flow change characteristics according to the reservoir water balance basic model; identifying response lag time of pipeline fluid inertia according to pipeline water supply flow change characteristics; predicting a water supply line pressure fluctuation risk based on the response lag time; and determining the water level regulation and control advance according to the water supply pipeline pressure fluctuation risk and the response lag time. According to the method, the multi-objective optimization model is adopted, the flood control safety margin and the water supply guarantee degree can be balanced, and it is ensured that the reservoir can cope with the flood risk in the flood season and can stably meet the water supply requirement.

The invention discloses a cascade reservoir scheduling method and system based on an artificial bee colony algorithm, and the method comprises the following steps: the system collects multi-source hydrological data in real time through a hydrological perception and preprocessing module, and introduces a large language model to carry out the semantic judgment and anomaly labeling of an abnormal hydrological time sequence; inputting the processed high-quality data into a reservoir model construction module, establishing a cascade reservoir optimal scheduling system, and setting corresponding boundary conditions and operation constraints in combination with reservoir scheduling regulations; the scheduling optimization module receives model input, adopts a variable structure taking a water level as a core to construct an optimization individual, and completes population initialization, disturbance generation and fitness evaluation based on a potential solution guide mechanism in an improved artificial bee colony algorithm; the system transmits the scheduling sequence optimized and output by the scheduling optimization module into an LLM intelligent auxiliary module; and the intelligent text interpretation generated by the LLM and the scheduling optimization solution enter a result evaluation and visualization module together. According to the scheduling method and system, a high-quality and physically feasible scheduling scheme can be output within reasonable calculation time.

This invention provides a method for linearizing the power output function of a hydropower station based on a simplified constraint strategy. The method includes: equally dividing the feasible region of the power output function into rectangular grids; defining a corresponding plane for each rectangular grid; constructing a quadratic programming model for calibrating the plane cluster parameters that approximate the power output surface of the hydropower station based on the characteristic parameters of the planes and the simplified plane set corresponding to the rectangular grids generated using the simplified constraint strategy; solving the quadratic programming model to obtain a set of plane equation parameters that approximate the optimal power output of the hydropower station; and in a reservoir optimization scheduling model where the scheduling objective includes maximizing the power output or power generation of the hydropower station within the scheduling period, using the parameters of the solved plane equations to construct a linearized expression for the hydropower output function in the reservoir optimization scheduling model. This invention avoids introducing integer variables, reduces the size of the quadratic programming model while ensuring the accuracy of fitting the hydropower station's power output, and greatly improves the solution efficiency.

The invention belongs to the technical field of water resource optimal scheduling, and discloses a reservoir optimal scheduling method based on hybrid swarm intelligent optimization, which comprises the following steps: S1, collecting data required by reservoir historical inflow, a reservoir capacity curve, a water supply demand and a scheduling constraint condition; s2, setting a constraint condition and a scheduling target, and establishing a reservoir scheduling optimization model; s3, constructing a candidate solution group on the basis of combining reservoir scheduling decision variables, performing initial fitness calculation by utilizing an objective function of the reservoir scheduling optimization model, introducing a hybrid group intelligent optimization algorithm, performing multi-objective optimization scheduling calculation on the reservoir scheduling optimization model, and performing iterative updating; s4, completing all set iterations, and outputting a reservoir optimization scheduling scheme meeting constraint conditions; according to the method, the premature convergence problem of a traditional swarm intelligence optimization algorithm is effectively avoided, the convergence speed and the solution stability are improved, and the method is suitable for optimization solution of single-library and multi-library systems in single-target or multi-target scheduling problems of water supply, flood control, power generation and the like.

The invention relates to a reservoir optimization scheduling system and scheduling method for generating multiple objectives based on AI, the reservoir optimization scheduling system comprises a data input module, a multi-objective optimization module, a constraint processing module, a result output module and a visualization module, the data input module is configured to obtain basic data of a reservoir; the multi-objective optimization module is configured to construct an optimization model based on a particle swarm optimization algorithm, minimize the maximum discharged flow, minimize the flood exceeding storage capacity and minimize the discharged flow change rate as objective functions, and search the optimal discharged flow process through particle iteration; the constraint processing module is configured to perform constraint check on the discharged flow and the water level of the reservoir and apply punishment to solutions violating constraints so as to ensure the feasibility of the scheduling scheme; the result output module is configured to output the optimized discharge flow process, the optimized water level process and the optimized flood limit exceeding storage capacity process; the visualization module is configured to draw a water level-flow process chart and optimize a target convergence curve.

The invention discloses equipment and a method for predicting, controlling and dispatching the scouring and silting amount of a downstream river channel of a dam, which are taken into account the influence of a flood process on the scouring and silting amount of the river channel and comprehensively consider the influence of water and sediment elements and flood characteristics on the scouring and silting amount of the downstream river channel of the dam. Water surface gradient, flow, peak pattern coefficient, jacking coefficient, sediment content and sediment grading elements are incorporated to predict the erosion and deposition amount of the downstream river channel of the dam, a calculation formula structure of the erosion and deposition amount of the downstream river channel of the dam and a matched calculation method are constructed, a corresponding table of the erosion and deposition amount of the downstream river channel of the dam is compiled according to the method, and reverse derivation can be achieved through table query. When the scouring and silting amount of the downstream river channel of the dam is controlled to be a fixed value, key dispatching parameters such as reservoir outlet flow and peak pattern coefficient required to be regulated and controlled by an upstream reservoir; a reservoir management department can formulate a scientific reservoir optimization scheduling scheme through the method, technical guarantee is provided for river regime stability and bank slope protection of a downstream river channel of a dam, flood control standard improvement and shipping safety maintenance are effectively supported, and a decision basis is provided for exerting comprehensive benefits of the reservoir.

The application discloses an ecological regulation method for relieving the retention of the biogenic substance of a deep and large reservoir, and belongs to the technical field of water resource management and environmental protection technology. The steps are as follows: first, collecting characteristic parameters and multiple types of hydrological and water quality monitoring data of the deep and large reservoir; second, constructing a three-dimensional hydrodynamic-water quality model of the deep and large reservoir; third, based on the three-dimensional hydrodynamic-water quality model of the deep and large reservoir, combining a long series of multiple inputs and multiple output sequences, a data-driven proxy model is constructed; fourth, constructing a reservoir optimization regulation model to deduce suitable regulation rules for decision makers. The application improves the hydrodynamic condition by discharge to reduce the retention of the biogenic substance, and realizes the activation and transportation by using the water temperature stratification condition of the reservoir area, so that the effective biogenic substance is transported to the downstream while the power generation capacity is ensured, thereby realizing the 'quantity, energy and quality comprehensive regulation and control' considering the power generation, ecological flow and biogenic substance, and providing technical support for the comprehensive management of optimizing the utilization of water resources and ecological environment protection of the basin.

The application discloses a kind of arid region reservoir water and sand prediction and coordinated regulation potential evaluation method and system, belong to water resources, silt treatment and reservoir optimization scheduling technical field.The technical problems of traditional model prediction accuracy insufficient caused by arid region hydrology data scarcity, water and sand prediction process is fragmented and reservoir desilting and silt reduction and water storage benefit difficult to be synergistically optimized, its gist is that: long short-term memory network is used to predict future runoff sequence by fusing attention mechanism, and the sediment concentration is calculated by combining the water and sand relationship formula;By setting the critical sediment concentration threshold, the high sediment concentration period is identified and the available water for dredging is calculated;At the same time, the flood resource potential is evaluated by combining reservoir capacity and water demand constraints;Finally, the coordinated scheduling scheme is generated by comparing the two potentials.The application realizes the integrated accurate prediction of water and sand process in arid region and the simultaneous quantitative evaluation of regulation potential, and provides intelligent decision support for multi-objective optimization scheduling of reservoir.

This invention relates to the field of water resource optimization scheduling technology in water conservancy and hydropower engineering, specifically to a reservoir optimization scheduling method and related products based on intertemporal sensitivity sparse repair. The method involves constructing and solving implicit equations for power generation and water volume, establishing an evaluation system and calculating intertemporal sensitivity to obtain a set of key time periods. Then, sparse repair is implemented on the initial power generation plan within this set, and the repair operation is embedded in an iterative optimization framework. This invention avoids the use of empirical estimation or coarse trial calculations in traditional reservoir scheduling, enhances the water resource safety net of reservoirs, suppresses the oscillation phenomenon of traditional intelligent evolutionary algorithms, and maintains the scheduling intent and temporal consistency of the initial predetermined plan on the power grid side.

A deep reservoir ecological scheduling method, system and device based on a data-driven model of a coupled physical mechanism belong to the technical field of water resources management and environmental protection. First, a physical water temperature model is constructed based on measured data, diversified water temperature change scenarios are generated, and a deep learning model with physical mechanism constraints is constructed. Second, sensitivity analysis is carried out to identify key influencing factors driving water temperature change, a reservoir optimization scheduling model is constructed, and a deep learning model with physical mechanism constraints is coupled to derive a set of scheduling rules under the premise of meeting water temperature targets. Finally, multi-index optimization analysis is carried out. A deep reservoir ecological scheduling system and electronic device are also provided to implement the above deep reservoir ecological scheduling method. The present application can scientifically derive a set of power generation scheduling rules for deep reservoirs, filter out the optimal scheduling scheme with both ecological and economic benefits by introducing a multi-index optimization method, and achieve the overall balance of ecological demand and power generation benefit.

The present invention belongs to the field of reservoir optimization and intelligent scheduling, and specifically provides a reservoir multi-objective optimization and intelligent scheduling method based on deep reinforcement learning and a deterministic policy gradient algorithm. The method includes collecting original hydrological data and reservoir characteristic curves of the target reservoir; establishing a multi-objective optimization and scheduling model including objective functions and constraints; mapping the multi-objective optimization and scheduling model into a Markov decision process and establishing a corresponding reinforcement learning environment; selecting a deep reinforcement learning deterministic policy gradient algorithm for interactive training with the environment to build a reservoir multi-objective optimization and intelligent scheduling model; and performing multi-objective optimization and intelligent scheduling of the reservoir using the reservoir multi-objective optimization and intelligent scheduling model. This method solves the problem in the prior art that deep reinforcement learning methods generally use fixed weights to design incentive functions, resulting in insufficient flexibility in the learned scheduling strategy and difficulty in achieving real-time dynamic coordinated optimization of the scheduling objectives of each reservoir according to the environmental state.

The invention discloses a long and short term coupling scheduling method for a hybrid pumped storage power station, and belongs to the technical field of power station scheduling. According to the method, based on an existing medium-and-long-term reservoir optimization scheduling model, a long-and-short-term coupling scheduling model considering medium-and-long-term constraints and short-term operation characteristics of the hybrid pumped storage power station at the same time is constructed, a typical day is selected every month, and medium-and-long-term monthly scale constraints and short-term typical day constraints are incorporated into the model; the model comprises an objective function, medium and long term monthly scale constraints, short term typical day constraints and long and short term coupling constraints, nonlinear constraints are linearized and converted into a mixed integer linear programming problem, and the problem is solved by a gurobi solver. The method solves the problem that a traditional model is difficult to accurately describe a'water pumping-power generation 'mode, avoids the deviation of scheduling schemes of different time scales, guides the efficient operation of the hydropower station, improves the power generation benefit, and can be widely applied to the scheduling of the hybrid pumped storage power station.

The application discloses a weight calculation method of a continental shale reservoir fracturability evaluation model, and belongs to the technical field of hydraulic fracturing. The application scientifically determines the weight of each index by fusing geological modeling and fracturing simulation results, introducing weight calculation methods such as the analytic hierarchy process and the grey correlation method, reduces the dependence degree on field monitoring data, simultaneously, establishes a quantitative correlation with actual productivity, quantifies the contribution of three types of capacity indexes to productivity, and finally determines a fracturability comprehensive evaluation model with engineering guiding value, so that the fracturing reconstruction potential of a reservoir can be more accurately represented, and a scientific theoretical basis can be provided for reservoir optimization and fracturing design.

The invention discloses a reservoir optimization scheduling method based on uniform design, relates to the technical field of water conservancy projects, and aims to solve the problem that an existing reservoir scheduling method may generate an inaccurate or low-efficiency scheduling result when facing a complex hydrological environment and multi-target demands.The reservoir optimization scheduling method comprises the following steps that S1, basic data of a reservoir are collected, and the basic data are stored in a database; comprise historical hydrological data, real-time hydrological data, reservoir characteristic parameters and flood control requirements, abnormal values are removed through data cleaning, data of different dimensions are uniformly converted into a [0, 1] interval by adopting a standardization method, and a high-quality data basis is provided for subsequent analysis; s2, determining the decision variables of the drainage flow, the reservoir level and the scheduling time period according to the drainage scheduling scene in the feasible region of each variable; the method has the advantages of maximizing the utilization efficiency of water resources, improving the scheduling capability of the reservoir and reducing the waste of the water resources through the uniformly designed optimal scheduling method.

The invention relates to the field of oil and gas exploration and development, in particular to a method for rapidly and quantitatively calculating the fracture network volume after low-permeability shale oil volume fracturing by means of recovery data after fracturing. Comprising the following steps: arranging single well production data, and converting wellhead flow pressure into oil layer middle flow pressure; drawing a relation curve of the accumulative actual liquid production capacity and the converted oil layer middle flowing pressure; the regression fracture network controls the slope of a linear decreasing section when the oil layer middle flowing pressure in the flowing period is increased along with the accumulative actual liquid production capacity; calculating a crude oil volume coefficient linear change slope n; and calculating the effective flow fracture network volume. The method is easy and convenient to predict, economical and practical, capable of rapidly calculating the effective fracture network volume of fracturing construction by utilizing measured data including wellhead yield, wellhead pressure and flowing bottomhole pressure which are easily obtained in the initial stage of extraction after fracturing, low in cost, high in universality, wide in application, simple and convenient in quantitative algorithm and high in accuracy, and basic data can be collected daily without large-scale construction. And the productivity of a single well after fracturing can be effectively evaluated, and technical support is provided for reservoir optimization and fracturing effect evaluation.

The invention provides a water-wind-light complementary power generation and flood control scheduling optimization method considering water energy storage, and relates to the field of reservoir optimization scheduling, the method considers a pumped storage power station taking a built reservoir as a lower reservoir or a reversible unit taking the built reservoir as an upper reservoir and a lower reservoir, and constructs a water-wind-light complementary power generation and flood control scheduling optimization model; and solving the water-wind-light complementary power generation and flood control scheduling optimization model by using a reference point-based non-dominated solution sorting genetic algorithm to obtain a three-target Pareto curved surface and a compromise solution, and outputting corresponding water level, flow and power generation process to complete optimization of water-wind-light complementary power generation and flood control scheduling. According to the method, the hydropower dispatching decision problem faced by multi-power-supply cooperative operation and water safety guarantee in a water-energy coupling system under the background that wind-solar new energy high-proportion power generation of a novel electric power system tends to be strong and tends to be frequency of climatic change flood events is solved.

The application discloses a kind of high-efficiency solving methods of cascade reservoir joint power generation optimization scheduling model, comprising: determining the storage capacity of cascade reservoir at the beginning and end of scheduling period, and the inflow of leading reservoir in whole scheduling period, interval inflow between each reservoir, various constraints of cascade reservoir;The storage capacity value of each reservoir is discretized within the upper and lower limits of storage capacity according to the discrete accuracy requirement;In time period t , for all possible storage capacity combinations of cascade reservoir at the beginning of time period, find the corresponding optimal storage capacity combination of cascade reservoir at the end of time period, and store such a correspondence as optimal state transition relationship;Let t = t -1, repeat step 3 until all time periods in scheduling period are traversed;According to the stored optimal state transition relationship, start backtracking from the beginning of the first time period, and obtain the optimal storage capacity process of cascade reservoir in the whole scheduling period;The application can improve the solving efficiency of cascade reservoir optimization scheduling model, while ensuring the quality of solution, so that the calculation result is close to the global optimal solution.

The present application relates to the technical field of reservoir optimization scheduling, and particularly relates to a reservoir flood season water level dynamic multi-objective optimization control system and method. The method comprises the following steps: obtaining real-time monitoring data of the reservoir; extracting current water level state information according to the real-time monitoring data of the reservoir; establishing a reservoir water balance basic model based on the current water level state information; analyzing the pipeline water supply flow variation characteristics according to the reservoir water balance basic model; identifying the response lag time of the pipeline fluid inertia according to the pipeline water supply flow variation characteristics; predicting the water supply pipeline pressure fluctuation risk based on the response lag time; and determining the water level regulation advance according to the water supply pipeline pressure fluctuation risk and the response lag time. The present application adopts a multi-objective optimization model, can balance between the flood control safety margin and the water supply guarantee degree, and ensures that the reservoir can not only cope with the flood risk in the flood season, but also stably meet the water supply demand.

The invention discloses a mathematical description method of a cascade reservoir group joint scheduling system based on a complex network. The mathematical description method comprises the following steps: step 1, determining a network type; 2, defining nodes of the cascade reservoir group complex network; 3, defining edges of the cascade reservoir group complex network; 4, defining an adjacent matrix A of the cascade reservoir group complex network; step 5, defining node attributes of the cascade reservoir group complex network and a constraint set of the node attributes; 6, defining natural incoming water as an input variable of the reservoir group system; 7, describing a hydraulic coupling relationship between the cascade reservoirs; 8, describing a state transition equation between the cascade reservoirs; according to the method, the mutual relation between the reservoirs can be more comprehensively captured, the network property between the reservoirs in a cascade reservoir group combined dispatching system is visually reflected, more analysis angles are provided for reservoir optimization dispatching, and a systematic mathematical description method is provided for complex network analysis of the reservoir groups.

The invention discloses an ecological scheduling method for relieving biogenic substance retention of a deep and large reservoir, and belongs to the technical field of water resource management and environmental protection. The method comprises the following steps: 1, collecting deep and large reservoir characteristic parameters and various hydrology and water quality monitoring data; 2, constructing a three-dimensional hydrodynamic force-water quality model of the deep and large reservoir; step 3, based on the three-dimensional hydrodynamic force-water quality model of the deep and large reservoir, constructing a data-driven proxy model in combination with a long-series multi-input and multi-output sequence of the model; and 4, constructing a reservoir optimization scheduling model, and deducing a proper scheduling rule for a decision maker. The hydrodynamic condition is improved through drainage, biogenic substance retention is reduced, the activation conveying effect is achieved through the reservoir area water temperature layering condition, downstream conveying of effective biogenic substances is enhanced while the power generation amount is guaranteed, and therefore comprehensive quantity, energy and quality regulation and control considering power generation, ecological flow and biogenic substances are achieved; and a technical support is provided for optimizing comprehensive management of basin water resource utilization and ecological environment protection.

The invention provides a carbon dioxide multilayer reservoir optimization method and device based on geological sequestration, and relates to the technical field of carbon sequestration. The method comprises the following steps: determining initial injection parameters corresponding to each reservoir, wherein the initial injection parameters comprise initial injection flow and initial injection pressure; for any reservoir stratum, flow control valves and pressure adjusting equipment installed on branch injection pipelines corresponding to the reservoir stratum are adjusted according to the initial injection parameters corresponding to the reservoir stratum, each branch injection pipeline corresponds to one reservoir stratum, and each branch injection pipeline is connected with the same main injection pipeline; carbon dioxide is injected into the main injection pipeline, and the carbon dioxide is injected into all the reservoirs through the main injection pipeline and the branch injection pipelines; real-time monitoring data corresponding to all the reservoirs are collected, and adjusting strategies corresponding to all the reservoirs are determined based on the real-time monitoring data so that flow control valves and pressure adjusting devices installed on branch injection pipelines of all the reservoirs can be adjusted in real time.

The invention relates to a reservoir optimization scheduling method and system considering a water volume time value, and the method comprises the steps: constructing a water volume time value quantitative model, and dynamically calculating a comprehensive value index of the unit water volume of each time period through coupling the sensitivity of an electricity price time period, an ecological flow demand curve and a water supply priority coefficient; designing a scheduling scheme generation mechanism based on an improved multi-target whale optimization algorithm, and introducing a time dimension constraint processing strategy; a double-layer decision model is established, the upper layer adopts fuzzy clustering to divide time frame types, and the lower layer performs scheme optimization in combination with an entropy weight-grey correlation analysis method. The system integrates the hydrological monitoring module, the numerical simulation module and the intelligent decision-making module, and self-adaptive optimization of a scheduling scheme is realized, so that the collaborative optimization capability of reservoir scheduling between the time dynamic benefit and the power generation benefit is effectively improved.

The invention provides a cascade reservoir dispatching method and device, electronic equipment and a readable storage medium, and relates to the technical field of water resource management. According to the water demand, the water resource allocation amount and the water shortage rate of each water consumption department of each water consumption unit of the reservoir participating in cooperation in a preset time period, constructing a water consumption unit space equilibrium target model; according to the comprehensive output coefficient of each reservoir participating in cooperation, the power generation flow in the preset time period and the power generation water head, constructing a cascade reservoir optimization scheduling model; and based on the fuzzy set theory and the cooperation modes of the cascade reservoirs, solving the water consumption unit space equalization target model and the cascade reservoir optimization scheduling model to obtain a solving result corresponding to each cooperation mode. And determining a solution result with the highest comprehensive satisfaction degree of the water utilization unit space equilibrium target model and the cascade reservoir optimal scheduling model from the plurality of solution results as a target scheme for scheduling the cascade reservoirs, so as to achieve the balance between reservoir water supply and power generation.

The embodiment of the invention discloses a deep learning short-term and medium-term runoff forecasting method fusing a physical mechanism, and relates to the technical field of hydrological forecasting, and the method comprises the steps: obtaining the hydrometeorological data and weather forecasting data of a target drainage basin; inputting the hydrometeorological data and the weather forecast data into the trained multivariable mixed downscaling model to obtain model weather forecast data of a forecast period; inputting model weather forecast data and hydro meteorological data into the trained hybrid model to obtain forecast runoff data of a forecast period; determining a posterior probability density function through back calculation forecasting, and determining a probability distribution result of the actual runoff data based on the posterior probability density function; and performing flood early warning based on a probability distribution result. The method is suitable for scenes of runoff forecasting of large and medium-sized drainage basins, mountain torrent early warning of small and medium-sized drainage basins, reservoir optimization scheduling, hydropower station operation management and the like, and can provide key technical support for water safety, water resource management and water ecological protection.

The invention belongs to the related technical field of reservoir drought-resistant scheduling, and discloses a cascade reservoir double-layer nested combined drought-resistant scheduling method and system, and the method comprises the steps: collecting the related data of each reservoir in a drainage basin, determining the constraint condition of each reservoir scheduling process, and building a cascade reservoir double-layer nested combined drought-resistant scheduling model; wherein the cascade reservoir double-layer nested joint drought-resisting scheduling model comprises an inner-layer optimization index and an outer-layer optimization index, the outer layer optimizes the multi-year regulation water elimination and falling level by taking the minimum water shortage index related index as the target, and the inner layer optimizes the annual storage and drainage order of the reservoir by taking the maximum water supply benefit related index as the target; and adopting a double-layer nested optimization algorithm to obtain a reservoir optimization scheduling scheme. According to the method, a cascade reservoir double-layer nested joint drought-resisting scheduling model is constructed, the outer layer achieves inter-year water shortage space-time balance with the minimum water shortage index as the target, the inner layer guarantees the drought-resisting benefit within the year with the maximum water supply benefit as the target, and water resource balanced scheduling can be achieved through inner layer-outer layer nested optimization.

This invention discloses a reservoir scheduling method and system based on hydrological simulation, belonging to the field of reservoir optimization scheduling methods. The method comprises: constructing a hydrological environment simulation model based on hydrological environment data and a pre-set soil and water conservation model; obtaining initial watershed runoff data based on the hydrological environment simulation model; obtaining initial watershed drought characteristics based on the initial watershed runoff data and a pre-set drought assessment model; constructing a reservoir balance model based on reservoir characteristic information; constructing a multi-objective reservoir scheduling model based on the initial watershed runoff data, initial watershed drought characteristics, and the reservoir balance model; and solving the multi-objective reservoir scheduling model to obtain an optimized reservoir scheduling scheme, thereby achieving multi-objective reservoir scheduling. Therefore, by implementing this invention, the limitations of existing reservoir scheduling optimization schemes in practical applications are solved. By constructing a model, flexible scheduling and real-time control of multi-objective reservoirs are achieved, avoiding hydrological drought problems.

The invention discloses a water engineering multi-target robust optimization scheduling method in an uncertain environment, and belongs to the technical field of reservoir optimization scheduling, and the method comprises the following steps: S1, constructing a water engineering multi-target robust optimization scheduling model; s2, introducing two types of risk disturbance variables; s3, a robust double-population collaborative evolution algorithm is adopted for optimizing and solving; and S4, executing a dynamic robust fitness evaluation mechanism. According to the multi-target robust optimization scheduling method for the underwater engineering in the uncertain environment, a double-population elite cooperation strategy, a multi-strategy cooperation updating mechanism, an optimization population archiving and updating mechanism and a dynamic robust fitness evaluation mechanism are integrated, so that the optimality and robustness can be ensured while high-dimensional complex problems are solved; and a robust solution set with excellent comprehensive performance is output for the complex problem.