气候变化领域集成服务门户(CCPortal): Several Approaches for the Prediction of the Operating Modes of a Wind Turbine

CCPortal

DOI	10.3390/electronics13081504
	Several Approaches for the Prediction of the Operating Modes of a Wind Turbine
	Yun, Hannah; Giurcaneanu, Ciprian Doru; Dobbie, Gillian
发表日期	2024
EISSN	2079-9292
起始页码	13
结束页码	8
卷号	13 期号:8
英文摘要	Growing concern about climate change has intensified efforts to use renewable energy, with wind energy highlighted as a growing source. It is known that wind turbines are characterized by distinct operating modes that reflect production efficiency. In this work, we focus on the forecasting problem for univariate discrete-valued time series of operating modes. We define three prediction strategies to overcome the difficulties associated with missing data. These strategies are evaluated through experiments using five forecasting methods across two real-life datasets. Two of the forecasting methods have been introduced in the statistical literature as extensions of the well-known context algorithm: variable length Markov chains and Bayesian context tree. Additionally, we consider a Bayesian method based on conditional tensor factorization and two different smoothers from the classical tools for time series forecasting. After evaluating each pair prediction strategy/forecasting method in terms of prediction accuracy versus computational complexity, we provide guidance on the methods that are suitable for forecasting the time series of operating modes. The prediction results that we report demonstrate that high accuracy can be achieved with reduced computational resources.
英文关键词	wind turbine; operating mode; discrete time series; prediction; Bayesian context tree; variable length Markov chains; conditional tensor factorization; smoothers
语种	英语
WOS研究方向	Computer Science ; Engineering ; Physics
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Physics, Applied
WOS记录号	WOS:001210056900001
来源期刊	ELECTRONICS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/294159
作者单位	University of Auckland; University of Auckland
推荐引用方式 GB/T 7714	Yun, Hannah,Giurcaneanu, Ciprian Doru,Dobbie, Gillian. Several Approaches for the Prediction of the Operating Modes of a Wind Turbine[J],2024,13(8).
APA	Yun, Hannah,Giurcaneanu, Ciprian Doru,&Dobbie, Gillian.(2024).Several Approaches for the Prediction of the Operating Modes of a Wind Turbine.ELECTRONICS,13(8).
MLA	Yun, Hannah,et al."Several Approaches for the Prediction of the Operating Modes of a Wind Turbine".ELECTRONICS 13.8(2024).