Multi-gen genetic programming based improved innovative model for extrapolation of wind data at high altitudes, case study: Turkey. (May 2022)

• Record Type: Journal Article
• Authors: Emeksiz, Cem
• Is Part Of: Computers & electrical engineering. Volume 100(2022)
• Publication Date: 2022-05
• Subjects: Log-law -- Multi-gen genetic programming -- Power-law -- Wind shear coefficient -- Wind speed extrapolation; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2022.107966
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: Innovative method was improved for extrapolation of wind data at high altitudes. Estimation accuracy and stability were improved via the suggested innovative method. This method was used for the first time in the field of wind energy. This method allows to evaluate the wind source shorter by using measurement masts. Abstract: Wind speed is the most important input of wind energy conversion systems and has higher values at high altitudes. Therefore, tall wind measurement masts are used in the wind power industry to determine the wind speed at high altitudes. However, this situation brings many engineering problems (cost escalation, de-erection and re-erection of the masts due to the failure of the anemometer and sensors, lightning strikes, mechanical failures etc.). In this study, it is aimed to estimate the data at the hub height levels of the proposed wind power generators by placing shorter wind masts as a suitable alternative for longer masts. Therefore, we proposed an innovative model that uses multigene genetic programming to estimate wind speed at high altitudes. According to the power and logarithmic law, analysis results show that root mean square error (RMSE) values were decreased with proposed method in the wind speed estimation, 58.62% and 58.77% respectively. Graphical abstract: Image, graphical abstract