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A new ultra-short-term photovoltaic power prediction model based on ground-based cloud images

  • Published:2018-11 Issue: Volume:200 Page:731-745
  • ISSN:0959-6526
  • Container-title:Journal of Cleaner Production
  • language:en
  • Short-container-title:Journal of Cleaner Production

Author:

Hu Keyong,Cao Shihua,Wang Lidong,Li Wenjuan,Lv Mingqi

Funder

Natural Science Foundation of Zhejiang Province, China

Educational Science Planning in Zhejiang, China

Natural Science Foundation of China

Publisher

Elsevier BV

Subject

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

Reference40 articles.

1. Use of satellite data to improve solar radiation forecasting with bayesian artificial neural networks;Aguiar;Sol. Energy,2015

2. Hybrid algorithm for short-term solar power prediction—sunshine state case study;Asrari;IEEE Trans. Sustain. Energy,2017

3. Very short-term photovoltaic power forecasting with cloud modeling: a review;Barbieri;Renew. Sustain. Energy Rev.,2017

4. Modelling PV clouding effects using a semi-markov process with application to energy storage;Barnes;Ifac Proc. Vol.,2014

5. Wavelet autoregressive forecasting of climatic parameters for photovoltaic systems;Ben Salah,2011

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