Guest Editorial: Special issue on computational methods and artificial intelligence applications in low‐carbon energy systems-Reference-Cited by-同舟云学术

Guest Editorial: Special issue on computational methods and artificial intelligence applications in low‐carbon energy systems

Published:2024-02 Issue:3 Volume:18 Page:303-305
ISSN:1752-1416
Container-title:IET Renewable Power Generation
language:en
Short-container-title:IET Renewable Power Gen

Author:

Wang Yishen¹^ORCID,Zhou Fei¹,Guerrero Josep M.²,Baker Kyri³,Chen Yize⁴,Wang Hao⁵,Xu Bolun⁶,Xu Qianwen⁷,Zhu Hong⁸,Agwan Utkarsha⁹

Affiliation:

1. State Grid Laboratory of Grid Advanced Computing and Applications State Grid Smart Grid Research Institute Co., Ltd. Beijing China

2. Center for Research on Microgrids (CROM) Department of Energy Technology Aalborg University Aalborg Denmark

3. Department of Civil, Environmental, and Architectural Engineering University of Colorado‐Boulder Boulder Colorado USA

4. Artificial Intelligence Thrust Hong Kong University of Science and Technology (Guangzhou) Guangzhou China

5. Department of Data Science and AI Monash University Clayton Victoria Australia

6. Department of Earth and Environmental Engineering Columbia University New York New York USA

7. Electric Power and Energy Systems Division KTH Royal Institute of Technology Stockholm Sweden

8. State Grid Jiangsu Electric Power Co. Ltd. Nanjing China

9. Department of Electrical Engineering and Computer Sciences University of California ‐ Berkeley Berkeley California USA

Publisher

Institution of Engineering and Technology (IET)

Reference19 articles.

1. Diffusion‐based conditional wind power forecasting via channel attention;Peng H.;IET Renew. Power Gener.,2023

2. Short‐term prediction of behind‐the‐meter PV power based on attention‐LSTM and transfer learning;Zhang J.;IET Renew. Power Gener.,2023

3. Multiple decomposition‐aided Long Short‐term Memory network for enhanced short‐term wind power forecasting;Balci M.;IET Renew. Power Gener.,2023

4. An Integrated Methodology for Significant Wave Height Forecasting based on Multi‐strategy Random Weighted Gray Wolf Optimizer with Swarm Intelligence;Dokur E.;IET Renew. Power Gener.,2023

5. Demand‐side price‐responsive flexibility and baseline estimation through end‐to‐end learning;Shi Y.;IET Renew. Power Gener.,2023