Solar irradiance forecasting based on direct explainable neural network-Reference-Cited by-同舟云学术

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Solar irradiance forecasting based on direct explainable neural network

Published:2020-12 Issue: Volume:226 Page:113487
ISSN:0196-8904
Container-title:Energy Conversion and Management
language:en
Short-container-title:Energy Conversion and Management

Author:

Wang Huaizhi,Cai Ren,Zhou Bin,Aziz Saddam,Qin Bin,Voropai Nikolai,Gan Lingxiao,Barakhtenko Evgeny^ORCID

Funder

National Natural Science Foundation of China

Huxiang Young Talents Programme of Hunan Province

Foundations of Shenzhen Science and Technology Innovation Committee

Publisher

Elsevier BV

Subject

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

Reference43 articles.

1. A novel sensor-less current technique for photovoltaic system using DC transformer model based model predictive control;Hussain;Int J Electr Power Energy Syst,2020

2. Exploring key weather factors from analytical modeling toward improved solar power forecasting;Wang;IEEE Trans Smart Grid,2019

3. Variational mode decomposition based low rank robust kernel extreme learning machine for solar irradiation forecasting;Majumder;Energy Convers Manage,2018

4. Forecasting mesoscale distribution of surface solar irradiation using a proposed hybrid approach combining satellite remote sensing and time series models;Doorga;Renew Sustain Energy Rev,2019

5. A solar time based analog ensemble method for regional solar power forecasting;Zhang;IEEE Trans Sustainable Energy,2019

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