Harvesting spatiotemporal correlation from sky image sequence to improve ultra-short-term solar irradiance forecasting-Reference-Cited by-同舟云学术

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Harvesting spatiotemporal correlation from sky image sequence to improve ultra-short-term solar irradiance forecasting

Published:2023-06 Issue: Volume:209 Page:619-631
ISSN:0960-1481
Container-title:Renewable Energy
language:en
Short-container-title:Renewable Energy

Author:

Liu Jingxuan,Zang Haixiang,Ding Tao,Cheng Lilin,Wei Zhinong,Sun Guoqiang

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Renewable Energy, Sustainability and the Environment

Reference55 articles.

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2. A soft actor-critic deep reinforcement learning method for multi-timescale coordinated operation of microgrids;Hu;Prot. Control. Mod. Power. Syst.,2022

3. Novel short-term solar radiation hybrid model: long short-term memory network integrated with robust local mean decomposition;Ngoc-Lan Huynh;Appl. Energy,2021

4. Hybrid renewable energy systems for power generation in stand-alone applications: a review;Bajpai;Renew. Sustain. Energy Rev.,2012

5. Bayesian deep learning for dynamic power system state prediction considering renewable energy uncertainty;Zhang;J. Mod. Power Sys. Clean Energy,2022

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1. Short-term solar irradiance forecasting under data transmission constraints;Renewable Energy;2024-10

2. On the use of sky images for intra-hour solar forecasting benchmarking: Comparison of indirect and direct approaches;Solar Energy;2024-07

3. Multidimensional Feature Extraction Based Minutely Solar Irradiance Forecasting Method Using All-Sky Images;IEEE Transactions on Industry Applications;2024-05

4. Improving ultra-short-term photovoltaic power forecasting using a novel sky-image-based framework considering spatial-temporal feature interaction;Energy;2024-04

5. Research and Analysis of Cloud Distribution Detection Method Based on Single-Photon Lidar;Lecture Notes in Electrical Engineering;2024

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