Reservoir real-time flood control multi-target robust optimization regulation and control method for resisting flood forecast error disturbance

Abstract

The invention discloses a reservoir real-time flood control multi-target robust optimization regulation and control method for resisting flood forecast error disturbance. The method comprises the steps: collecting and arranging flood forecast error samples in a reservoir system database, and randomly simulating to generate a real-time flood control scheduling flood error scene set; establishing a reservoir flood control dispatching multi-target robust optimization model: taking the upstream and downstream flood control risk rates and the conditional value-at-risk of the upstream and downstream flood control risk loss as optimization targets, and generating a multi-target robust optimization non-inferior scheme solution set; and carrying out multi-attribute risk decision-making under the uncertain condition: introducing different weight parameters for different decision-making preferences, and obtaining optimal equilibrium solutions under different preferences by adopting a TOPSIS method. According to the method, a prediction-scheduling-decision-making whole process decision-making support model set integrating error scene simulation, risk robust regulation and control and non-inferior solution set decision-making is created in the field of reservoir flood control scheduling, and the reliability and safety of reservoir flood control scheduling can be improved.

Description

technical field [0001] The invention relates to a reservoir scheduling method in the field of water conservancy engineering, in particular to a multi-objective robust optimization control method for real-time flood control of a reservoir that resists flood forecast error disturbance. Background technique [0002] Reservoirs are important engineering measures to resist flood disasters and control the flood process. Scientific and rational use of reservoirs for flood control dispatch can significantly reduce the impact of flood disasters and effectively protect the safety of people's livelihood and property in upstream and downstream areas. With the continuous development of forecasting technology, traditional single-value flood forecasting is no longer suitable for modern flood control dispatching, and probabilistic ensemble forecasting has been adopted by more and more river basin management agencies. Although probabilistic flood forecasting can greatly improve the forecast ...

AI Technical Summary

Problems solved by technology

However, the existing stochastic programming methods fail to take into account the management and control needs of reservoir risk avoidance and risk reduction, and are not comprehensive in dealing with risks: when dealing with uncertain forecast scenarios, they can reduce the probability of reservoir flood control risk events under different forecast inflow scenarios for the target

Although the probability of occurrence of risk events can be effectively controlled, it is impossible to effectively control the loss of risk events. In the face of major flood events, the processing capacity is insufficient, it is difficult to ensure the dispatch safety of major risk events beyond the standard, and there is a lack of probability flood forecasting Robustness when

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