167 results about "Reservoir operation" patented technology

The invention discloses a reservoir flood control monitoring system and method based on digital twinning, and relates to the technical field of reservoir flood control monitoring, and the system comprises a multi-source data collection module which is used for building a digital twinning model according to the real-time monitoring data of the multi-source data collection module, and transmitting the digital twinning model to a reservoir flood control monitoring module. The coupling module is used for receiving the fusion data set provided by the digital twin module, performing dynamic simulation on the fusion data set, and providing dynamic prediction results of dam seepage, deformation and flood routing; the dynamic early warning module comprises a dynamic threshold adjusting unit and an early warning unit; compared with a traditional early warning system with a fixed threshold value, the system can adapt to changes of dam body states and environmental conditions, identify potential abnormal events in advance, provide sufficient time for flood control of a reservoir to perform emergency response and scheduling decision making, and improve the flood control efficiency. Therefore, the disaster risk is effectively reduced, and the safety of reservoir operation is ensured.

The invention discloses a reservoir scheduling decision support system for multi-objective optimization, and relates to the technical field of hydraulic engineering scheduling. According to the system, comprehensive optimization of flood control, power generation and ecological targets is realized through cooperative work of the multi-source dynamic constraint analysis module, the collaborative optimization module, the scheduling module and the correction module. A dynamic constraint boundary table is generated by collecting meteorological, hydrological and ecological data in real time. And matching a multi-target coordination rule through a physical constraint double-depth network algorithm, generating a Pareto feasible solution set, and mapping the Pareto feasible solution set into a coordination strategy of flood discharge flow and power generation output. In combination with a hydraulic model, flood control and power generation weights are adjusted, an executable dispatching instruction is generated, it is ensured that the ecological flow reaches the standard, and the influence of a downstream submerged area is optimized. And correcting the dynamic constraint boundary table according to actual monitoring data, and continuously optimizing a scheduling decision. Accurate management and multi-objective optimization of reservoir dispatching are realized, and the utilization efficiency of water resources is improved.

Disclosed is a reservoir ecological operation method integrating ecological flow process and water temperature process requirements of fish species, including: establishing a habitat model for a target fish species and deducing an ecological flow process of a lift history of the target fish species; calculating a critical spawning water temperature threshold and a critical gonadal development accumulated temperature threshold; establishing a multi-objective reservoir operation model to obtain flow process and water level after optimized reservoir operation; establishing a multi-objective reservoir ecological operation model integrating both the ecological flow process and the water temperature process, and calculating reservoir outflow water temperatures before and after the optimized reservoir operation; and calculating an improvement difference between the critical water temperature threshold and the accumulated temperature threshold of the target fish species on arrival dates after the reservoir ecological operation and those before the optimized reservoir operation.

A fuzzy cloud-based risk assessment method for reservoir operation schemes, including: collecting basic data of target reservoirs; constructing optimal operation model of conventional reservoirs to obtain model calculation results; acquiring change process of operation characteristics during whole operating period according to model calculation results, and constructing multi-level reservoir multi-dimensional risk assessment index system; dividing different risk level intervals according to multi-level reservoir multi-dimensional risk assessment index system; obtaining large number of sample data xij of reservoir risk index under corresponding working conditions by multiple parallel calculations to conduct risk assessment; calculating cloud digital features of different indexes by inverse cloud generator; and weighting indexes in index layer and criterion layer by Analytic Hierarchy Process to obtain multi-dimensional risk assessment results. In order to promote sustainable development and utilization of water resources and enhance level of reservoir risk management, scientific evaluation of reservoir risk is conducted by comprehensively considering various uncertainties.

The invention discloses a reservoir multi-target optimization scheduling scheme optimization method and system based on multi-party coupling, and belongs to the field of reservoir scheduling. The system comprises the steps that firstly, boundary conditions of a simulation system are determined, and then a reservoir multi-target optimization scheduling model is constructed; and then solving the reservoir multi-objective optimization scheduling model by using a non-dominated sorting genetic algorithm of the reference points, verifying the effectiveness of the solving method by using a standard multi-objective test function, and evaluating and optimizing a reservoir scheduling scheme by using a method of combining a grey target theory, a cumulative foreground theory and a fuzzy mathematical method. According to the system, the multi-objective optimization problem among flood control, power generation and ecology of the reservoir is coordinated, decision support is provided for formulating a reservoir dispatching scheme of multi-objective optimization dispatching of the reservoir, the contradiction among flood control, power generation and downstream river ecology can be effectively coordinated, and the flood control and power generation benefits are increased on the basis of considering the downstream ecological flow demand as much as possible.

The invention discloses a three-dimensional digital twin modeling method, system, equipment and medium taking a reservoir as an object, and relates to the technical field of reservoir monitoring, and the method comprises the steps: constructing a three-dimensional space model facing a reservoir entity, and forming a visual simulation environment; accessing multi-source data related to reservoir operation, and establishing a unified data aggregation and management mechanism; integrating a real-time operation state in the three-dimensional space model, and dynamically mapping perception information and business activities of the reservoir; and based on a set analysis model and a determination rule, carrying out intelligent processing on the reservoir operation data, identifying potential risks and generating an early warning result. According to the invention, by establishing a multi-type analysis model and a judgment rule system, real-time calculation and risk identification are carried out on key indexes, intelligent early warning of risks such as emergencies, trend anomalies and historical extreme value overrun is realized, and the risk prevention and control capability of the reservoir is effectively improved.

The invention discloses a reservoir scheduling method based on a deep learning adaptive dynamic network and reinforcement learning, which relates to the technical field of reservoir scheduling and comprises the following steps: acquiring real-time water level data, meteorological data and radar image data of regional cloud and earth surface characteristics of a reservoir and performing data fusion on the three data; the fused data are input into a preset self-adaptive dynamic Transform network model, prediction output is obtained, and the prediction output is a reservoir water level sequence, a reservoir inflow sequence and a discharged flow sequence; constructing a reinforcement learning state space; the reinforcement learning state space is input into a preset reinforcement learning network, an action space of the reinforcement learning network comprises flood discharge, power generation flow and ecological flow, an optimization target of the reinforcement learning network is maximized accumulated discount rewards, and a reward function is a weighting function of a flood prevention reward item, a power generation reward item and an ecological reward item. According to the invention, the cooperative management efficiency of multiple targets such as reservoir flood control safety, power generation benefits and ecological protection is improved.

The invention relates to the technical field of reservoir dispatching, in particular to a method for handling events influencing cascade reservoir dispatching operation, which comprises the following steps: acquiring real-time monitoring data of a cascade reservoir to be detected; performing data preprocessing on the real-time monitoring data of the to-be-detected cascade reservoir to obtain preprocessed data; inputting the preprocessed data into a trained key factor determination model, and obtaining a key data type and corresponding data; determining whether an abnormal event occurs or not and the type of the abnormal event according to the key data type and the corresponding data; when an abnormal event occurs, inputting the type of the abnormal event into a preset intelligent diagnosis system, and obtaining a plurality of exception handling schemes; and SWOT analysis is carried out on the various exception handling schemes to obtain a final handling result. According to the method, the safety and reliability of cascade reservoir dispatching operation are improved, and the cascade reservoir operation management level is improved.

The invention relates to the technical field of hydraulic engineering operation management, in particular to a hydraulic engineering operation management system which comprises a water resource scheduling management module, a water quality monitoring and analysis module, an engineering safety management and control service module, an engineering operation and maintenance intelligent management and control module and an engineering maintenance module. According to the invention, the water demand of each water receiving area is satisfied, the water quality condition of the reservoir after engineering operation and the influence of the water quality of the reservoir on the river are comprehensively known, the reservoir and the reservoir entering river are continuously monitored, and the service application demand of the large reservoir operation management of the official road is deeply combined to construct the reservoir dam safety management and control system. Therefore, the operation management and control capability of the reservoir is improved, a project operation and maintenance management system is constructed, the working efficiency is improved, and long-term storage and effective utilization of archive data are ensured.

The invention provides a cascade reservoir operation risk and benefit evaluation method considering prediction uncertainty, and the evaluation method comprises the steps: building a day-ahead wind-light-water optimal complementary model, and employing a two-stage robust method to process the power generation amount deviation generated by the wind-light uncertainty; the method comprises the following steps: identifying the worst condition of photovoltaic power output which causes maximum water consumption and power imbalance to obtain a day-ahead total power generation plan of the wind-solar hybrid system capable of realizing maximum resource utilization rate; according to the evaluation method, a benefit and risk evaluation model based on power generation complementary benefit, power generation stability, power supply reliability and water level fluctuation is further provided, the risk of complementary operation of the reservoir system is quantified through indexes, the risk and benefit of cascade reservoir operation can be reasonably evaluated and balanced on the basis of considering the uncertainty of wind and light power generation, and the method is suitable for popularization and application. And the overall efficiency and reliability of the power system are improved.

The invention relates to the technical field of reservoir dam safety evaluation, in particular to a reservoir dam flood safety risk evaluation method, a computer storage medium and equipment. The reservoir dam flood safety risk assessment method comprises the following steps: deducing estimated values of hydrological statistical parameters of a sample series; randomly simulating a longer series of flood peak flow long series samples, and obtaining a flood hydrograph corresponding to the simulated flood peak flow series; flood regulation calculation is carried out according to a set scheduling scheme by combining the reservoir capacity curve and discharge curve data of the reservoir, and a flood regulation highest water level value is obtained; and deducing the conditional probability that the reservoir level exceeds different characteristic water levels due to the flood based on the obtained flood regulation highest water level value, and evaluating the flood safety risk of the reservoir dam according to the conditional probability. According to the method, simulation and calculation results can be visually presented, the calculation process is direct and clear, and the method has important practical significance and good application prospects in reservoir operation dam safety risk assessment.

The invention belongs to the technical field of reservoir scheduling, and particularly discloses an intelligent reservoir scheduling method based on HHO and MPA dual optimization driving, and the method comprises the steps: taking the maximization of the total power generation amount of a cascade reservoir group as an optimization target, and building a target function; setting constraint conditions of the target function, wherein the constraint conditions comprise equality constraints and inequality constraints meeting reservoir operation; the objective function is solved based on an improved predation strategy optimization algorithm, and the operation water levels of all the reservoirs in the cascade reservoir group at different moments in the dispatching time period are obtained; wherein the improved predation strategy optimization algorithm is realized by introducing the following operations in a search strategy selection stage of the HHO algorithm: global exploration based on an escape energy adaptive switching MPA algorithm and local development of the HHO algorithm. According to the method, the problem that the HHO algorithm is unbalanced in the exploration and development process in cascade reservoir group joint optimization scheduling application is effectively solved, effective balance of global search and local development is achieved, and high robustness is achieved.

The invention relates to the technical field of reservoir safety monitoring and early warning, in particular to a reservoir operation state prediction analysis method based on environmental data. The method comprises the following steps: collecting original resistance response sequences of reservoir bottom mud at different depths by adopting low-frequency alternating-current signals through a laid vertical resistivity probe array; performing polarization effect compensation processing on the original resistance response sequence to obtain a sediment resistivity layer spectrogram; collecting reservoir environment data; performing time sequence coupling analysis on the reservoir environment data and the sediment resistivity layer spectrogram to obtain a sediment stability influence factor spectrum; constructing a bottom mud layered structure model according to the bottom mud resistivity layer spectrogram and the bottom mud stability influence factor spectrum; and carrying out basic stress field calculation on the bottom mud layered structure model to obtain an initial stress distribution diagram. Through a full-chain technical route from sediment internal monitoring to multi-factor comprehensive analysis, the early warning timeliness, accuracy and reliability of reservoir sediment disasters are remarkably improved.

The invention provides a reservoir staged and graded drought limit water level determination method and system based on a hedera helix algorithm. The method comprises the steps that 1, reservoir incoming water data, water demand data and reservoir dispatching regulations are collected and sorted; 2, performing preliminary staging on a reservoir scheduling period based on the reservoir scheduling procedure, and adding staging nodes based on the incoming water data and the water demand data of the reservoir; further grading based on the water demand data to obtain a plurality of staged and graded drought limit water levels; 3, the multiple stages and stages of drought limit water levels serve as parameters, and a drought limit water level multi-target optimization model is constructed; and 4, solving the drought limit water level multi-objective optimization model to obtain non-inferior solution sets obtained through optimization, sorting the non-inferior solution sets obtained through optimization, and determining final staged and graded drought limit water levels. The method has the characteristics of high convergence speed and few algorithm parameters; and a parameter simulation optimization method is adopted, so that the obtained explicit scheduling rule better meets the actual requirement, and the drought-resistant water replenishing scheduling can be better guided.

The invention discloses a double-layer optimization method considering well control and profile control and flooding agent parameter setting, and belongs to the field of oil and gas field development engineering.The method comprises the following steps that an oil reservoir profile control and flooding synergistic optimization control model is built, and dynamic profile control and flooding optimization variables are defined; based on actual reservoir operation constraints, constructing a concentration and dosage constraint judgment method of the profile control and flooding agent; a data-driven optimization algorithm is adopted, and a prediction model is trained and constructed to evaluate the effects of different profile control and flooding schemes; a plurality of injection agent opportunity schemes are generated based on a Gibbs sampling method, and each injection agent scheme is optimized to obtain the optimal injection and production liquid quantity and the optimal injection agent concentration; constructing a proxy model mapping relation; iteratively optimizing the profile control and flooding scheme, performing profile control and flooding simulation real evaluation, and updating the profile control and flooding experience library; and iteratively optimizing and outputting an optimal scheme. By introducing the dynamic profile control and displacement strategy and the advanced optimization algorithm, the design efficiency and effect of the profile control and displacement scheme in the complex oil reservoir environment are improved, and powerful support is provided for efficient development of oil and gas fields.

The invention discloses a flood control reservoir flood season application method giving consideration to water resource utilization, and the method comprises the steps: calculating and designing a water inflow process, a water demand process and a minimum reserve water amount and water level process according to the obtained long series of data of a drainage basin; according to the activation mechanism and the quit mechanism, timely developing a flood-control reservoir flood-season water resource application mode or a flood-season reservoir floating water level operation control strategy, and finally, after flood-season operation is finished, evaluating and evaluating the effect of the flood-control reservoir flood-season water resource application mode. The method can more scientifically guide the reserve water amount of the flood control reservoir at the proper time in the flood season to cope with the influence of drought events on downstream water supply safety, and the drainage basin flood and drought disaster prevention and water resource optimal allocation capacity is improved.

The invention relates to the technical field of hydraulic engineering, and discloses a reservoir scheduling optimization method and system based on artificial intelligence, and the system comprises a data collection and preprocessing module, a prediction module, an optimization module, a decision support module and a control execution module, and also comprises an edge calculation node, a federal learning coordination module and a man-machine collaborative decision interface. Through the combination of the deep learning prediction model and the optimization algorithm, the reservoir scheduling accuracy and efficiency are improved, and the prediction reliability under the complex meteorological condition is improved. The system can automatically generate an optimal reservoir scheduling scheme according to real-time data and a prediction result, so that the cost of manual intervention is reduced, and the management efficiency is improved; edge calculation is supported, the scheduling strategy generation delay is less than 1 minute, and flood control emergency requirements are met.

The invention discloses a flood forecast evaluation method adapted to reservoir dispatching characteristics, which comprises the following steps: respectively driving the same hydrological model by using historical observation rainfall and forecast rainfall, quantifying the error contribution of the hydrological model and rainfall forecast through double-track difference, and constructing a sample evaluation weight in combination with a rainfall score; constructing a weighting condition error distribution model based on the weight, and generating a reservoir flow forecasting scene set containing physical cause characteristics; and inputting the scene set into a reservoir scheduling model containing flood control and benefit-making rules, and outputting a comprehensive scheduling risk index containing a downstream over-alarm risk and water abandoning loss through water balance and downstream evolution calculation. According to the method, the statistical weight is corrected through error attribution, the abstract forecast error is converted into specific engineering risk and economic loss, the hidden risk working condition which is difficult to find by a traditional statistical index is effectively identified, and a quantitative basis is provided for risk decision making of reservoir dispatching and targeted optimization of a forecast system.

The invention provides a three gorges reservoir operation period staging design flood and staging storage level determination method, which is characterized in that a flood season is divided into a previous flood season, a main flood season and a later flood season by considering a flood seasonal change rule on the basis of a long-series rainfall flow data series; taking the corrected reservoir coefficient as a covariable to consider the regulation and storage influence of the upstream reservoir group, and adopting a P-III distribution time-varying moment model to deduce stage design flood and flood control water level in the reservoir operation period; a Jinsha river downstream cascade and Three Gorges reservoir combined water storage multi-target scheduling model is constructed, and on the premise of keeping flood control standards unchanged, the three Gorges reservoir staged water storage level is determined through a parameterization-simulation-optimization framework and an intelligent algorithm. The reservoir operation period staging design flood and staging water storage level determination method provided by the invention is reasonable and feasible in technology, and provides an important and operable reference basis for three gorges reservoir operation scheduling management.

The invention discloses a cascade reservoir hydro-fluctuation period water abandoning risk analysis method based on a water abandoning prevention guide line. The method comprises the following steps: collecting data; generalizing the maximum power generation flow constraint matrix of the most downstream reservoir in the hydro-fluctuation period; obtaining a cascade reservoir inflow runoff process after runoff recalculation calculation; determining the threshold value of the removable reservoir capacity on the abandoned water prevention guide line and the reservoir capacity boundary condition at the end of the hydro-fluctuation period; deducing abandoned water prevention guide line clusters of the cascade reservoirs over the years; and forming a water abandoning risk probability query chart. The method provided by the invention has the advantages of being simple, practical, reasonable, reliable, easy to popularize and the like, and according to the characteristics of cascade reservoir dispatching application, an anti-abandoned water dispatching operation guide line under different incoming water conditions of the cascade reservoir and the probability of the water abandoning risk of different to-be-eliminated reservoir capacities in the hydro-fluctuation period are quickly given; the method and the device accord with the operation characteristics of actual reservoir scheduling, and can provide support for a reservoir operation management department to adjust a scheduling strategy in real time.

The invention belongs to the technical field of reservoir dispatching, and particularly provides a cross-basin water dispatching, supply and distribution integrated decision-making method for guaranteeing ecological flow, which comprises the following steps: constructing a two-stage optimization dispatching model of a cross-basin water supply reservoir system based on a dynamic optimality principle; quantitatively describing ecological water demand processes of a water source area and a water receiving area in the cross-basin system engineering under different ecological water demand levels by utilizing a Tennant method; performing optimization calculation on the optimization scheduling model under different ecological water demand levels by utilizing dynamic planning to obtain a regional water regulation and supply process; constructing a regional water resource optimal configuration model according to the water regulation and supply results; factors such as ecological water demand guarantee degree and decision manager preference are comprehensively considered, and a practical regional water distribution scheme is formulated. According to the method, the water transfer amount and the water supply amount of the cross-basin reservoir system can be effectively determined, meanwhile, the water competition problem of'life, living and living 'of a region is solved, and technical support is provided for reasonability and scientificity of decision making of the cross-basin reservoir system.

The invention discloses a reservoir dispatching method for guaranteeing stability of a reservoir bank slope. The reservoir dispatching method comprises the following steps of collecting various data related to a small reservoir; evaluating the stability of the bank slope of the small reservoir; setting different risk scenes and carrying out risk prediction; formulating a reservoir scheduling scheme according to a risk analysis result; and dynamically adjusting the reservoir scheduling scheme according to the monitoring data. According to the method, the slope stability analysis model comprehensively considering various factors such as water level change and rainfall infiltration is established, the stability condition of the reservoir bank slope under different scheduling schemes can be evaluated more accurately, in the reservoir scheduling process, the maximization of a certain target is not pursued purely any more, and the stability of the reservoir bank slope is improved. Multiple targets such as slope stability, flood control benefits and power generation benefits are considered as a whole, an advanced multi-target optimization algorithm is applied, an optimal balance point among the targets is found, and a scientific and reasonable reservoir dispatching scheme which can guarantee stability of a reservoir bank slope and can also take the flood control benefits, the power generation benefits and the like into consideration is formulated.

The invention provides a data query and auxiliary reservoir operation method and system applying a context engineering enhancement agent, and relates to the field of data processing, and the method comprises the steps: determining a set of seed tasks for assisting reservoir operation; determining a data interface, a static enterprise knowledge access interface and an application sub-model of the seed task; user questions are received; performing context enhancement processing on the user questions to generate a data demand list; according to the data demand list, the intelligent agent obtains data related to user questions and an application sub-model from a data interface of the seed task, a static enterprise knowledge access interface and the application sub-model; the application sub-model generates auxiliary reservoir operation information according to data related to user questions; and the agent receives the auxiliary reservoir operation information returned by the application sub-model and compiles the auxiliary reservoir operation information into structured output. The method has the advantage of improving the automation level of reservoir operation.

The invention discloses a runoff prediction method, a runoff prediction device and a storage medium. The runoff prediction method comprises the following steps: calculating dynamic response characteristics of each grid unit at each moment by using meteorological input; extracting static influence characteristics of the static attributes on the runoff error; extracting features reflecting time and space influences at the same time, and obtaining an error correction value generated based on meteorological input and underlying surface information; constructing a reservoir scheduling substitution network, and outputting a correction component of the reservoir scheduling to the runoff; and constructing a loss function, superposing the correction component and the output of the preliminary hydrological model, and updating parameters of each module through end-to-end back propagation to obtain runoff prediction. According to the runoff prediction method, the influence of dynamic changes such as rainfall and air temperature, underlying surface distribution and reservoir regulation on drainage basin runoff is fully captured, and the precision and stability of runoff simulation are remarkably improved.

The invention belongs to the technical field of water ecological protection and water resource management, and particularly provides a cascade reservoir operation ecological benefit evaluation method based on a habitat model, and the method comprises the steps: collecting the topographic data of a downstream fish spawning site of a cascade reservoir, the actual measurement hydrological data of a hydrological station, and the biological data of target fishes; performing unstructured triangular mesh division on the research river reach by adopting a finite volume method, and simulating flow velocity and water depth distribution of a research area through a continuity equation and a momentum equation; according to the biological data of the target fish, a suitability curve of the flow velocity and the water depth is constructed, and the habitat suitability index HIS of each grid is calculated in combination with the flow velocity and water depth data output by the hydrodynamic module; and calculating an effective available area WUA and an overall suitability index OSI based on the HSI value for ecological benefit assessment. The method comprehensively considers the influence of the cascade reservoirs on the correlation factors, accurately evaluates the ecological benefits, and provides a scientific basis for ecological scheduling of the cascade reservoirs and fish resource protection.

The invention provides a reservoir operation risk real-time early warning method based on digital twinning, and relates to the technical field of reservoir operation engineering safety monitoring, and the method comprises the steps: firstly constructing a reservoir digital twinning body, collecting hydrological, structural and environmental data in real time through a multi-source sensor, and uploading the hydrological, structural and environmental data to a cloud processing center; then dynamically calibrating twin model parameters by using a machine learning algorithm based on historical and real-time data to realize virtual-real synchronous mapping; then calculating a hydrological situation deviation degree representing a hydrological abnormal state and a structure response coupling coefficient representing a structure response characteristic; generating a comprehensive risk index through a risk fusion algorithm, and triggering graded early warning according to a dynamic threshold value; and finally, the early warning information is displayed through a visual platform, and disposal suggestions are provided. According to the invention, real-time, accurate and panoramic perception and intelligent early warning processing of the reservoir operation risk are realized, and the initiative and reliability of reservoir safety management are significantly improved.

The invention relates to a flood wave classification evolution characteristic calculation method and system and a medium. The method comprises the following specific steps: collecting reservoir operation data and long-series hydrological data of important control stations of a river channel; according to the flood routing characteristics of the reservoir-river channel class, the similar flood process of the downstream of the reservoir is judged; judging whether the flood routing process of each control site of the river channel is influenced by the jacking of the water level of the downstream reservoir or not according to the flood routing characteristics of the river channel-reservoir class; based on the reservoir dispatching regulation and the reservoir engineering characteristics, analyzing whether the historical typical reservoir drainage mode meets the flood wave classification requirement or not; a control variable method is adopted to analyze the relationship between evolution characteristics such as flood peak evolution duration, a tanning coefficient and rising response time and elements such as initial reservoir outbound flow, maximum rise of the reservoir outbound flow, the increase rate of the reservoir outbound flow, maximum duration of the reservoir outbound flow and the water level of the reservoir, and a correlation curve is constructed. According to the invention, specific analysis of flood routing in various flood routing scenes is realized.

The invention provides a reservoir scheduling rule extraction method and system based on a multi-source remote sensing satellite. The method comprises the following steps: respectively acquiring a Sentinel-1 remote sensing image and a GF-3 remote sensing image of a target reservoir and preprocessing the Sentinel-1 remote sensing image and the GF-3 remote sensing image; respectively carrying out mask cutting processing and binarization processing on the preprocessed Sentinel-1 remote sensing image and the preprocessed GF-3 remote sensing image; on the basis of the Sentinel-1 remote sensing image and the GF-3 remote sensing image which are subjected to binarization processing, complete water boundaries are obtained respectively, and then the water surface area is calculated; the water surface area calculated based on the Sentinel-1 remote sensing image and the GF-3 remote sensing image is corrected, and a corrected and uniformized water surface area sequence is obtained; based on the water body boundary and the corrected and uniformized water surface area sequence, reservoir scheduling rule extraction is carried out; the invention constructs a method for judging the long-term reservoir regulation rule in the non-control area drainage basin only through remote sensing image information and runoff hydrological data. Therefore, the data collection process is simplified, and the real-time performance and accuracy of data acquisition are improved.

The invention discloses a cascade reservoir short-term scheduling method considering the influence of dynamic reservoir capacity and backwater jacking. The method comprises the following steps: constructing a target function; setting constraint conditions; initial water levels of upstream and downstream power stations, upstream power station reservoir flow, downstream representative station water levels of downstream power stations, cascade power station interval runoff and power load plans are obtained, and initial reservoir capacities of all hydropower stations are obtained according to the reservoir capacity curve; assuming the end water level of the upstream power station in the time period, and calculating the corresponding ex-reservoir flow, the end water level, the power generation water head and the power station output; if the output of the upstream power station meets the load plan requirement in the period, adjusting and calculating the output of the downstream power station in the period; according to the upstream reservoir outlet flow and the interval runoff, the downstream reservoir inlet flow is calculated; if the load plan requirement of the downstream power station in the time period is met, adjusting calculation in the next time period is carried out; according to the method, the influence of the dynamic reservoir capacity and the backwater jacking is fully considered, and real-time optimal scheduling of the cascade reservoir is realized.

The invention discloses a water diversion scheduling method based on a large reservoir, which belongs to the field of hydraulic engineering and comprises the following steps: inputting basic information and related historical data of the large reservoir; carrying out demand prediction and water level simulation by utilizing a machine learning algorithm; formulating an optimal water diversion scheduling strategy according to the prediction result and the scheduling target; converting the scheduling strategy into an operation instruction and implementing the operation instruction; monitoring reservoir operation data in real time and performing comparative analysis; and performing feedback optimization on the scheduling strategy according to the actual operation effect. A water diversion strategy can be dynamically adjusted according to actual requirements and reservoir conditions, and optimal configuration and efficient utilization of water resources are achieved; demand prediction and water level simulation are performed by using a machine learning algorithm, so that the prediction precision and the scheduling efficiency are improved; an optimal water diversion scheduling strategy is formulated in combination with an optimization algorithm, so that the realization of a scheduling target is ensured; and the real-time monitoring and feedback optimization mechanism ensures the real-time performance and accuracy of the scheduling strategy.