An interpretable probabilistic model for short-term solar power forecasting using natural gradient boosting-Reference-Cited by-同舟云学术

An interpretable probabilistic model for short-term solar power forecasting using natural gradient boosting

Published:2022-03 Issue: Volume:309 Page:118473
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Mitrentsis Georgios^ORCID,Lens Hendrik^ORCID

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference75 articles.

1. A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization;Ahmed;Renew Sustain Energy Rev,2020

2. Stability definitions and characterization of dynamic behavior in systems with high penetration of power electronic interfaced technologies;Hatziargyriou,2020

3. Probabilistic forecasting of solar power, electricity consumption and net load: Investigating the effect of seasons, aggregation and penetration on prediction intervals;Van der Meer;Sol Energy,2018

4. A review of deep learning for renewable energy forecasting;Wang;Energy Convers Manage,2019

5. Forecasting of photovoltaic power generation and model optimization: A review;Das;Renew Sustain Energy Rev,2018

Cited by 44 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Interpretable probabilistic modeling method for runoff prediction: A case study in Yangtze River basin, China;Journal of Hydrology: Regional Studies;2024-04

2. Potential of Explainable Artificial Intelligence in Advancing Renewable Energy: Challenges and Prospects;Energy & Fuels;2024-01-19

3. A new interpretable prediction framework for step-like landslide displacement;Stochastic Environmental Research and Risk Assessment;2024-01-12

4. Integrating prior knowledge to build transformer models;International Journal of Information Technology;2024-01-02

5. Integration of the radial basis functional network and sliding mode control for the sunshine radiation forecast;AIMS Energy;2024