Simulation verification method for simulating wind power generation system based on deep learning

Abstract

The invention provides a simulation verification method for simulating a wind power generation system based on deep learning. The simulation verification method comprises the following steps: performing simulation verification on a plurality of independent fields in the system; extracting data of multiple sliding window lengths through a convolutional neural network, extracting data features for multiple times to obtain advanced data features, and judging the optimal length of the data; performing check operation and noise reduction operation on the simulation data set of the wind power generation system to obtain simulation data of multiple fields in the wind power generation system, and fitting the simulation data through a unary linear fitting method; obtaining a qualitative trend of the simulation data in each field, and judging a derivative of the qualitative trend according to the qualitative trend; classifying the domain simulations according to the relationship to obtain independent domain simulations, comparing each domain simulation with the corresponding real scene, and judging whether the model is consistent with the simulation or not to obtain a similarity level; and outputting a simulation similarity grade value K of all fields.

Description

technical field [0001] The invention relates to a simulation verification method for simulating a wind power generation system based on deep learning. Background technique [0002] The wind power generation system plays a very important role in the energy field and the economic field. For the establishment of wind power generation facilities in an area, the cost of a unit is expected to be 2-3 million. This patent studies the wind power generation system in Inner Mongolia, China, and judges the area Which places are suitable for building wind power plants, etc…. [0003] At present, the simulation method is used to study the weather simulation data set M α , Inner Mongolia terrain dataset M β , the power simulation data set M of wind power generating units in each area p , economic benefit simulation data M q , these data together constitute the system simulation data set M of the wind power generation system in Inner Mongolia α , M β ,...,M p ,...M η . The specific...

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Problems solved by technology

[0005] The purpose of the present invention is to provide a simulation verification method for simulating a wind power generation system based on deep learning, which can solve the verification problem of the simulation system in a complex network environment

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