Wind speed reconstruction from synoptic pressure patterns using an evolutionary algorithm

被引：17

作者：

Carro-Calvo, L. ^{[1
]}

Salcedo-Sanz, S. ^{[1
]}

Prieto, L. ^{[3
]}

Kirchner-Bossi, N. ^{[2
]}

Portilla-Figueras, A. ^{[1
]}

Jimenez-Fernandez, S. ^{[1
]}

机构：

[1] Univ Alcala, Dept Signal Theory & Commun, Madrid 28871, Spain

[2] Univ Complutense Madrid, Dept Phys Earth Astron & Astrophys 2, E-28040 Madrid, Spain

[3] Iberdrola Renovables, Dept Energy Resource, Valencia, Spain

来源：

APPLIED ENERGY | 2012年 / 89卷 / 01期

关键词：

Wind rose reconstruction; Synoptic pressure patterns; Evolutionary algorithms; ARTIFICIAL NEURAL-NETWORKS; ENERGY; OPTIMIZATION; MODELS;

D O I：

10.1016/j.apenergy.2011.07.044

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

This paper presents an evolutionary algorithm for wind speed reconstruction from synoptic pressure patterns. The algorithm operates in a search space formed by grids of pressure measures, and must classify the different situations into classes, in such a way that a measure of wind speed in a given point is minimized among patterns assigned to the same class. Then, each class is assigned a mean wind speed and direction, so the wind speed reconstruction is possible for a new grid of synoptic pressures. In this paper we present the problem model and the specific description of the evolutionary algorithm proposed to solve the problem. We also show the good performance of the proposed method in the reconstruction of the average wind speed in six wind towers in Spain. The proposed method is applicable to wind speed reconstruction or reconstruction of wind missing data of wind series, specially when there is no other variable or related measure available. (C) 2011 Elsevier Ltd. All rights reserved.

引用

页码：347 / 354

页数：8

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