A new reference wind year approach to estimate long term wind characteristics

Saban Pusat,Yasin Karagöz

doi:10.1177/16878140211021268

Abstract

The typical meteorological year (TMY) method has common applications in building energy performance and solar energy studies. However, there is not any well accepted method for the wind energy applications such as the TMY. In the present study, a new reference year approach is proposed for wind energy applications. By using the proposed method, the reference wind year (RWY) datasets may be generated as in the TMY methodology for any measurement station which has the possibility to be used as a reference station in the measure-correlate-predict (MCP) analyses. The MCP calculations are so significant to estimate the long term wind conditions for a candidate wind farm site. In this study, a case study is performed for Turkey after giving the details of the proposed method. The results for the RWY approach has a good agreement with the long term data as in the TMY method. Therefore, the RWY concept has the possibility to make the MCP studies easier and faster.

Highlights

Today, hourly or shorter-term data is used in any analysis and simulation, and the works are done for yearly basis
The typical solar radiation year (TSRY) datasets are used in assessment of solar energy applications
After the selection of the best months for the generation of the reference wind year (RWY) datasets, it would be very useful to compare the monthly averages of the RWY data with the long term (LT) means and averages of wind site

Summary

Introduction

Hourly or shorter-term data is used in any analysis and simulation, and the works are done for yearly basis. A reference wind year (RWY) approach for wind energy applications is presented. The proposed method is similar to the TMY method and it uses the meteorological data (wind speed, wind direction, temperature and pressure) of the reference station. The RWY dataset can be used in the prediction of the candidate site long term wind resources effectively.

Results

Conclusion