Reservoir stage power generation scheduling rule extraction method

Abstract

The invention provides a reservoir stage power generation scheduling rule extraction method. Stage influence factors are screened based on grey relational analysis, a multivariate nonlinear regressionmodel, a support vector machine model and a BP artificial neural network model are adopted to fit and then obtain a stage reservoir power generation scheduling function, and a Bayesian model averaging method is applied to perform multi-model weighted averaging to obtain a final stage reservoir power generation scheduling function. According to the invention, GRA is introduced into the reservoir scheduling rule simulation for influence factor screening, so redundant attributes are removed, the model complexity is reduced, and the model simulation efficiency is improved; GRA and EVA are combined to realize the stage extraction of reservoir power generation rules, so the inconsistency of the correlation between decision variables and the influence factors for different periods of reservoir scheduling is balanced, the uncertainty of a single model which may be caused by the model structure is balanced, and the model simulation precision is improved; the requirement for reservoir power generation scheduling rule extraction is met, and the benefits of determinacy optimization scheduling in the power generation process are well inherited.

Description

technical field [0001] The invention relates to the field of water conservancy and hydropower, in particular to a method for extracting scheduling rules for phased generation of reservoirs. Background technique [0002] The research on optimal operation of reservoirs began in 1955. Since it can obtain more benefits from hydropower operation, a series of fruitful theoretical achievements have been made on optimal operation models so far. However, the deterministic optimal dispatching model is often operated under the premise of known runoff, which cannot guide the actual operation and dispatching of reservoirs. Therefore, it is of great practical significance to guide the actual operation of the reservoir and improve the hydropower efficiency of the reservoir by summarizing the optimal operation rules of the reservoir from the optimal process obtained by the optimal operation model of the reservoir, and then forming the operation rules. [0003] At present, the most commonly...

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Problems solved by technology

[0005] Purpose of the invention: The purpose of the present invention is to provide a method for extracting staged power generation scheduling rules of reservoirs in view of the differences in the prior art, so as to solve the problem that most current scheduling rule studies do not carry out screening operations of influencing factors and decision variables and influencing factors in different time periods Correlation is not consistent, and based on BMA, it provides a multi-model composite scheduling rule with high precision and meaning, providing theoretical basis and scientific support for the actual optimal operation of hydropower stations

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