Wind missing data arrangement using wavelet based techniques for getting maximum likelihood-Reference-Cited by-同舟云学术

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Wind missing data arrangement using wavelet based techniques for getting maximum likelihood

Published:2019-04 Issue: Volume:185 Page:552-561
ISSN:0196-8904
Container-title:Energy Conversion and Management
language:en
Short-container-title:Energy Conversion and Management

Author:

Zapata-Sierra Antonio J.,Cama-Pinto Alejandro,Montoya Francisco G.,Alcayde Alfredo,Manzano-Agugliaro Francisco

Funder

Andaluz Institute of Agricultural Research and Training

Ibero-American Postgraduate University Association

Publisher

Elsevier BV

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Reference79 articles.

1. Wind energy research in Mexico;Hernández-Escobedo;Renewable Energy,2018

2. Scientific production of renewable energies worldwide: an overview;Manzano-Agugliaro;Renew Sustain Energy Rev,2013

3. Improved week-ahead predictions of wind speed using simple linear models with wavelet decomposition;Kiplangat;Renewable Energy,2016

4. Fossil fuel and co2 emissions savings on a high renewable electricity system – a single year case study for Ireland;Clancy;Energy Policy,2015

5. How carbon pricing changes the relative competitiveness of low-carbon baseload generating technologies;Nicholson;Energy,2011

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4. A data enhancement-based quadratic imputation framework for consecutive missing values considering spatiotemporal characteristics of dam deformation;Journal of Civil Structural Health Monitoring;2023-11-15

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