Renewable energy prediction: A novel short-term prediction model of photovoltaic output power-Reference-Cited by-同舟云学术

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Renewable energy prediction: A novel short-term prediction model of photovoltaic output power

Published:2019-08 Issue: Volume:228 Page:359-375
ISSN:0959-6526
Container-title:Journal of Cleaner Production
language:en
Short-container-title:Journal of Cleaner Production

Author:

Li Ling-Ling,Wen Shi-Yu,Tseng Ming-Lang,Wang Cheng-Shan

Funder

Natural Science Foundation of Hebei Province

Ministry of Science and Technology, Taiwan

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Strategy and Management,General Environmental Science,Renewable Energy, Sustainability and the Environment

Reference50 articles.

1. Hourly solar irradiance prediction based on support vector machine and its error analysis;Bae;IEEE Trans. Power Syst.,2017

2. A probabilistic competitive ensemble method for short-term photovoltaic power forecasting;Bracale;IEEE Trans. Sustain. Energy,2017

3. Forecasting of power grid investment in China based on support vector machine optimized by differential evolution algorithm and grey wolf optimization algorithm;Dai;Appl. Sci.,2018

4. Day-ahead forecasting of solar photovoltaic output power using multilayer perceptron;Ehsan;Neural Comput. Appl.,2017

5. Photovoltaic output power forecast using artificial neural;ELAMIM;J. Theor. Appl. Inf. Technol.,2018

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