Integrated approach for the determination of an accurate wind-speed distribution model

• Published in: Energy conversion and management Vol. 173; pp. 56 - 64
• Main Author: Masseran, Nurulkamal
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.10.2018; Elsevier Science Ltd
• Subjects: case studies; Criteria; data collection; Electricity generation; energy; Goodness of fit; Graphical representations; Kurtosis; Malaysia; Multi-criteria evaluation; Multiplicative aggregation; Probability distribution; Ranking score; Statistical analysis; Statistical distributions; uncertainty; Velocity; Wind power; Wind speed; Wind-speed modeling; Malaysia; Multiplicative aggregation; Ranking score; Wind-speed modeling; Multi-criteria evaluation; Goodness of fit
• ISSN: 0196-8904; 1879-2227
• DOI: 10.1016/j.enconman.2018.07.066

•Several criteria were integrated in selecting the optimal wind-speed distribution model.•Standardized scores were proposed to establish a comparable form for each criterion.•Multi-criteria approach is superior to single-criterion for distribution model selection. The distribution model of wind-speed data is critical for the assessment of wind-energy potential because it reduces uncertainties in the estimation of wind power output. Thus, an accurate distribution model for describing wind-speed data should be determined before a detailed analysis of energy potential is conducted. In this study, information from several goodness-of-fit criteria, e.g., the R2 coefficient, Kolmogorov–Smirnov statistic, Akaike’s information criterion, and deviation in skewness/kurtosis were integrated for the conclusive selection of the best-fit distribution model of wind-speed data. The proposed approach integrates standardized scores and subjects each criterion to multiplicative aggregation. The approach was applied in a case study to fit eight statistical distributions to hourly wind-speed data collected at two stations in Malaysia. The results showed that the proposed approach provides a good basis for the selection of the optimal wind-speed distribution model. Furthermore, graphical representations agreed with the analytical results.