### Abstract

Wind energy is a prime sector of the composite renewable energy sector which is supposed to be the prime energy producing force in years to come [1]. The ever increasing demand of wind energy and its renewable nature has led to an emphatic push in development of this sector. Wind speed has been one of those important parameters which form the basic element for design of any wind energy system. Thus, in order to build effective systems, exemplary assessment of wind speed deviation is single handedly the most mandatory parameter that is required to be studied. This leads us to investigate probability density functions which are used to describe wind speed frequency distributions. In this paper, we have modeled wind speed characteristics with respect to Weibull, Rayleigh, Gamma distributions and have simultaneously compared them with respect to statistical parameters such as Chi-square error test, Root mean square error and R^{2} test as ruling criteria to evaluate the pertinence of the respective distribution functions. Weibull and Gamma give a good fit with Weibull giving a better fit.

Original language | English |
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Title of host publication | 2016 International Conference on Energy Efficient Technologies for Sustainability, ICEETS 2016 |

Publisher | Institute of Electrical and Electronics Engineers Inc. |

Pages | 34-37 |

Number of pages | 4 |

ISBN (Electronic) | 9781509015344 |

DOIs | |

Publication status | Published - 04-10-2016 |

Externally published | Yes |

Event | 2016 International Conference on Energy Efficient Technologies for Sustainability, ICEETS 2016 - Nagercoil, India Duration: 07-04-2016 → 08-04-2016 |

### Conference

Conference | 2016 International Conference on Energy Efficient Technologies for Sustainability, ICEETS 2016 |
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Country | India |

City | Nagercoil |

Period | 07-04-16 → 08-04-16 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Energy Engineering and Power Technology
- Renewable Energy, Sustainability and the Environment

### Cite this

*2016 International Conference on Energy Efficient Technologies for Sustainability, ICEETS 2016*(pp. 34-37). [7582895] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICEETS.2016.7582895

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*2016 International Conference on Energy Efficient Technologies for Sustainability, ICEETS 2016.*, 7582895, Institute of Electrical and Electronics Engineers Inc., pp. 34-37, 2016 International Conference on Energy Efficient Technologies for Sustainability, ICEETS 2016, Nagercoil, India, 07-04-16. https://doi.org/10.1109/ICEETS.2016.7582895

**Statistical estimation for fitting wind speed distribution.** / Chowdhury, Srinjoy Nag; Dhawan, Saniya.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Statistical estimation for fitting wind speed distribution

AU - Chowdhury, Srinjoy Nag

AU - Dhawan, Saniya

PY - 2016/10/4

Y1 - 2016/10/4

N2 - Wind energy is a prime sector of the composite renewable energy sector which is supposed to be the prime energy producing force in years to come [1]. The ever increasing demand of wind energy and its renewable nature has led to an emphatic push in development of this sector. Wind speed has been one of those important parameters which form the basic element for design of any wind energy system. Thus, in order to build effective systems, exemplary assessment of wind speed deviation is single handedly the most mandatory parameter that is required to be studied. This leads us to investigate probability density functions which are used to describe wind speed frequency distributions. In this paper, we have modeled wind speed characteristics with respect to Weibull, Rayleigh, Gamma distributions and have simultaneously compared them with respect to statistical parameters such as Chi-square error test, Root mean square error and R2 test as ruling criteria to evaluate the pertinence of the respective distribution functions. Weibull and Gamma give a good fit with Weibull giving a better fit.

AB - Wind energy is a prime sector of the composite renewable energy sector which is supposed to be the prime energy producing force in years to come [1]. The ever increasing demand of wind energy and its renewable nature has led to an emphatic push in development of this sector. Wind speed has been one of those important parameters which form the basic element for design of any wind energy system. Thus, in order to build effective systems, exemplary assessment of wind speed deviation is single handedly the most mandatory parameter that is required to be studied. This leads us to investigate probability density functions which are used to describe wind speed frequency distributions. In this paper, we have modeled wind speed characteristics with respect to Weibull, Rayleigh, Gamma distributions and have simultaneously compared them with respect to statistical parameters such as Chi-square error test, Root mean square error and R2 test as ruling criteria to evaluate the pertinence of the respective distribution functions. Weibull and Gamma give a good fit with Weibull giving a better fit.

UR - http://www.scopus.com/inward/record.url?scp=84994129720&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84994129720&partnerID=8YFLogxK

U2 - 10.1109/ICEETS.2016.7582895

DO - 10.1109/ICEETS.2016.7582895

M3 - Conference contribution

AN - SCOPUS:84994129720

SP - 34

EP - 37

BT - 2016 International Conference on Energy Efficient Technologies for Sustainability, ICEETS 2016

PB - Institute of Electrical and Electronics Engineers Inc.

ER -