One Day Ahead Prediction of Wind Speed Based on Power and Exponential

Mostafa Gholami; Gevorg B. Gharehpetian; Masoud Davari

doi:10.1109/PEOCO.2010.5559177

One Day Ahead Prediction of Wind Speed Based on Power and Exponential

Mostafa Gholami, Gevorg B. Gharehpetian, Masoud Davari

Electrical & Computer Engineering

Amirkabir University of Technology

Research output: Contribution to conference › Presentation

Abstract

This paper presents a new model for predicting wind speed. This technique is based on using a power and a exponential model relating the predicted interval to its corresponding one-year old data. The accuracy of the model for predicting wind speeds and directions up to 24 h ahead have been investigated using two sets of data. Generated results are compared with reference [1]. The presented results validate the effectiveness and accuracy of the proposed prediction model for wind speed.

Original language	American English
DOIs	https://doi.org/10.1109/PEOCO.2010.5559177
State	Published - Jun 23 2010
Event	International Power Engineering and Optimization Conference (PEOCO) - Shah Alam, Malaysia Duration: Jun 23 2010 → …

Conference

Conference	International Power Engineering and Optimization Conference (PEOCO)
Period	06/23/10 → …

Keywords

Computational modeling
Data models
Electrical engineering
Least-square method
Predictive models
Wind farms
Wind forecasting
Wind speed
Wind speed prediction

DC Disciplines

Engineering
Electrical and Computer Engineering

Access to Document

10.1109/PEOCO.2010.5559177License: Unspecified

Cite this

@conference{017e1f6cd5384ff0995180aded767154,

title = "One Day Ahead Prediction of Wind Speed Based on Power and Exponential",

abstract = " This paper presents a new model for predicting wind speed. This technique is based on using a power and a exponential model relating the predicted interval to its corresponding one-year old data. The accuracy of the model for predicting wind speeds and directions up to 24 h ahead have been investigated using two sets of data. Generated results are compared with reference [1]. The presented results validate the effectiveness and accuracy of the proposed prediction model for wind speed.",

keywords = "Computational modeling, Data models, Electrical engineering, Least-square method, Predictive models, Wind farms, Wind forecasting, Wind speed, Wind speed prediction",

author = "Mostafa Gholami and Gharehpetian, {Gevorg B.} and Masoud Davari",

note = "This paper presents a new model for predicting wind speed. This technique is based on using a power and a exponential model relating the predicted interval; International Power Engineering and Optimization Conference (PEOCO) ; Conference date: 23-06-2010",

year = "2010",

month = jun,

day = "23",

doi = "10.1109/PEOCO.2010.5559177",

language = "American English",

}

TY - CONF

T1 - One Day Ahead Prediction of Wind Speed Based on Power and Exponential

AU - Gholami, Mostafa

AU - Gharehpetian, Gevorg B.

AU - Davari, Masoud

N1 - This paper presents a new model for predicting wind speed. This technique is based on using a power and a exponential model relating the predicted interval

PY - 2010/6/23

Y1 - 2010/6/23

N2 - This paper presents a new model for predicting wind speed. This technique is based on using a power and a exponential model relating the predicted interval to its corresponding one-year old data. The accuracy of the model for predicting wind speeds and directions up to 24 h ahead have been investigated using two sets of data. Generated results are compared with reference [1]. The presented results validate the effectiveness and accuracy of the proposed prediction model for wind speed.

AB - This paper presents a new model for predicting wind speed. This technique is based on using a power and a exponential model relating the predicted interval to its corresponding one-year old data. The accuracy of the model for predicting wind speeds and directions up to 24 h ahead have been investigated using two sets of data. Generated results are compared with reference [1]. The presented results validate the effectiveness and accuracy of the proposed prediction model for wind speed.

KW - Computational modeling

KW - Data models

KW - Electrical engineering

KW - Least-square method

KW - Predictive models

KW - Wind farms

KW - Wind forecasting

KW - Wind speed

KW - Wind speed prediction

UR - https://doi.org/10.1109/PEOCO.2010.5559177

U2 - 10.1109/PEOCO.2010.5559177

DO - 10.1109/PEOCO.2010.5559177

M3 - Presentation

T2 - International Power Engineering and Optimization Conference (PEOCO)

Y2 - 23 June 2010

ER -

One Day Ahead Prediction of Wind Speed Based on Power and Exponential

Abstract

Conference

Keywords

DC Disciplines

Access to Document

Other files and links

Fingerprint

Cite this