Simplified Markov Chain Models for Generation of Synthetic Time Series of Wind Speed and Direction

被引：0
|
作者：
Di Giorgio, V [1 ]
Testa, A. [1 ]
Zou, M. [2 ]
Langella, R. [1 ]
Djokic, S. Z. [2 ]
机构：
[1] Univ Campania Luigi Vanvitelli, Aversa, CE, Italy
[2] Univ Edinburgh, Edinburgh, Midlothian, Scotland
来源：
2022 17TH INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS (PMAPS) | 2022年
关键词：
Non-Homogeneous Markov Chain model; Synthetic time series; Wind Direction; Wind Speed; Simplified Models;
D O I：
10.1109/PMAPS53380.2022.9810593
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：
Simplified non-homogeneous Markov Chain (MC) models for generation of synthetic time series of wind speed (WS) and wind direction (WD) are proposed. The proposed models consider daily, monthly, and seasonal WS and WD characteristics. The accuracy and computational burden of the proposed models are compared with those of a complete model (CM), proposed by the same authors in a previous paper, trough numerical experiments based on field data.
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页数：6
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