Net load forecasts for solar-integrated operational grid feeders-Reference-Cited by-同舟云学术

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Net load forecasts for solar-integrated operational grid feeders

Published:2017-12 Issue: Volume:158 Page:236-246
ISSN:0038-092X
Container-title:Solar Energy
language:en
Short-container-title:Solar Energy

Author:

Chu Yinghao,Pedro Hugo T.C.,Kaur Amanpreet,Kleissl Jan,Coimbra Carlos F.M.

Funder

California Solar Initiative (CSI) Research, Development, Demonstration, and Deployment (RD&D)

Publisher

Elsevier BV

Subject

General Materials Science,Renewable Energy, Sustainability and the Environment

Reference46 articles.

1. An ANN-based approach for predicting global radiation in locations with no direct measurement instrumentation;Al-Alawi;Renew. Energy,1998

2. Evolutionary multiobjective optimization of kernel-based very-short-term load forecasting;Alamaniotis;IEEE Trans. Power Syst.,2012

3. Electric load forecasting: literature survey and classification of methods;Alfares;Int. J. Syst. Sci.,2002

4. A prediction interval for a function-valued forecast model: application to load forecasting;Antoniadis;Int. J. Forecast.,2016

5. An integrated artificial neural networks approach for predicting global radiation;Azadeh;Energy Convers. Manage.,2009

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2. Photovoltaic power forecasting: A dual-attention gated recurrent unit framework incorporating weather clustering and transfer learning strategy;Engineering Applications of Artificial Intelligence;2024-04

3. A Deep Learning Framework for Net Load Forecasting With Unsupervised Behind-the-Meter Disaggregated Data;IEEE Access;2024

4. An Overview of Short-Term Load Forecasting for Electricity Systems Operational Planning: Machine Learning Methods and the Brazilian Experience;Energies;2023-11-04

5. Advances in solar forecasting: Computer vision with deep learning;Advances in Applied Energy;2023-09

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