Limitations and Perspectives of Short-Term Renewable Energy Generation Forecasting Methods
Author:
Affiliation:
1. Novosibirsk State Technical University,Industrial Power Supply Systems Department,Novosibirsk,Russia
2. Technical Faculties Novosibirsk State Technical University,Foreign Languages Department,Novosibirsk,Russia
Funder
Russian Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10016894/10016776/10017051.pdf?arnumber=10017051
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1. Improving Daily Peak Flow Forecasts Using Hybrid Fourier-Series Autoregressive Integrated Moving Average and Recurrent Artificial Neural Network Models
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3. Research on a Novel Combination System on the Basis of Deep Learning and Swarm Intelligence Optimization Algorithm for Wind Speed Forecasting
4. Adaptive Residual Compensation Ensemble Models for Improving Solar Energy Generation Forecasting
5. Industry Experience of Developing Day-Ahead Photovoltaic Plant Forecasting System Based on Machine Learning
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