INFORMATION PROCESSING SYSTEM, METHOD FOR ESTIMATING WIND SPEED ATTENUATION AND TURBULENCE EFFECT, AND PROGRAM

To obtain a prediction result of a wind condition downstream of a wind power generation device based on a realistic simulation and to expand a use range of the prediction result compared to the use range of a prediction result not based on the realistic simulation.SOLUTION: In a control section 51 o...

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Main Authors MURAKAMI NORIO, WATANABE KEIICHIRO, YAMAZAKI MASAHIDE, BABA YOSHITAKA, TAKAKUWA SUSUMU, UCHIDA TAKANORI, HASEGAWA SEIYA, HIDAKA KUNIHIKO, FUJIKAWA RINTARO
Format Patent
LanguageEnglish
Japanese
Published 01.02.2024
Subjects
BLASTING
HEATING
LIGHTING
MACHINES OR ENGINES FOR LIQUIDS
MECHANICAL ENGINEERING
OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
PRODUCING MECHANICAL POWER
WEAPONS
WIND MOTORS
WIND, SPRING WEIGHT AND MISCELLANEOUS MOTORS
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Summary:To obtain a prediction result of a wind condition downstream of a wind power generation device based on a realistic simulation and to expand a use range of the prediction result compared to the use range of a prediction result not based on the realistic simulation.SOLUTION: In a control section 51 of a management server 50, a wind condition information acquisition section 501 acquires wind condition information about a condition of incoming wind coming to a wind turbine which rotates a plurality of blades. A wake information acquisition section 503 acquires wake information about wind speed attenuation, direction, and turbulence effect of the incoming wind caused by rotation of the blades. The acquired wind condition and wake information are stored as training data. Also, in the control section 51, a model generation section 504 generates a learning model which outputs effect information according to the input wind condition information based on the training data. A wake estimation section 505 estimates the wind speed attenuation, direction, and turbulence effect of the incoming wind from the wind condition information about each of one or more wind turbines using the learning model.SELECTED DRAWING: Figure 3 【課題】風力発電装置の後方の風況の予測を実態に即したものとすることで、実態に即していない予測に比べて予測結果の利用範囲を拡大させる。【解決手段】管理サーバ５０の制御部５１では、風況情報取得部５０１が、複数枚のブレードを回転させる風車に流入する流入風の状況に関する風況情報を取得し、ウエイク情報取得部５０３が、ブレードの回転に起因する流入風の風速の減衰、風向、および乱れの効果に関するウエイク情報を取得する。取得された風況情報およびウエイク情報は、教師データとして記憶される。また、制御部５１では、モデル生成部５０４が、入力された風況情報に応じた効果情報を出力する学習モデルを教師データに基づいて生成し、ウエイク推定部５０５が、学習モデルを用いて、１または複数の風車の各々の風況情報から、流入風の風速の減衰、風向き、および乱れの効果を推定する。【選択図】図３
Bibliography:Application Number: JP20220117258