Adaptive Weighted Combination Approach for Wind Power Forecast Based on Deep Deterministic Policy Gradient Method-Reference-Cited by-同舟云学术

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Adaptive Weighted Combination Approach for Wind Power Forecast Based on Deep Deterministic Policy Gradient Method

Published:2023 Issue: Volume: Page:1-13
ISSN:0885-8950
Container-title:IEEE Transactions on Power Systems
language:
Short-container-title:IEEE Trans. Power Syst.

Author:

Li Menglin¹^ORCID,Yang Ming¹^ORCID,Yu Yixiao¹^ORCID,Shahidehpour Mohammad²^ORCID,Wen Fushuan³^ORCID

Affiliation:

1. Key Laboratory of Power System Intelligent Dispatch and Control, Shandong University, Jinan, China

2. Galvin Center for Electricity Innovation, Illinois Institute of Technology, Chicago, IL, USA

3. Hainan Institute, Zhejiang University, Sanya, China

Funder

Key Program of the National Natural Science Foundation of China

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Link

http://xplorestaging.ieee.org/ielx7/59/4374138/10180117.pdf?arnumber=10180117

Cited by 2 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. A novel ensemble deep reinforcement learning model for short‐term load forecasting based on Q‐learning dynamic model selection;The Journal of Engineering;2024-07

2. A short-term power prediction method for wind farm cluster based on the fusion of multi-source spatiotemporal feature information;Energy;2024-05

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