Reinforcement Learning Assisted Deep Learning for Probabilistic Charging Power Forecasting of EVCS

Yuanzheng Li; Yong Zhao; Lei Wu; Zhigang Zeng

doi:10.1007/978-981-99-0799-1_5

Reinforcement Learning Assisted Deep Learning for Probabilistic Charging Power Forecasting of EVCS

Yuanzheng Li
, Yong Zhao
, Lei Wu
, Zhigang Zeng

Department of Electrical and Computer Engineering

Huazhong University of Science and Technology

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

1 Scopus citations

Abstract

As one of the most essential actions, the carbon emission reduction has been adopted to address the problem of climate change.

Original language	English
Title of host publication	Engineering Applications of Computational Methods
Pages	75-100
Number of pages	26
DOIs	https://doi.org/10.1007/978-981-99-0799-1_5
State	Published - 2023

Publication series

Name	Engineering Applications of Computational Methods
Volume	14
ISSN (Print)	2662-3366
ISSN (Electronic)	2662-3374

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 13 Climate Action

Access to Document

10.1007/978-981-99-0799-1_5

Cite this

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title = "Reinforcement Learning Assisted Deep Learning for Probabilistic Charging Power Forecasting of EVCS",

abstract = "As one of the most essential actions, the carbon emission reduction has been adopted to address the problem of climate change.",

author = "Yuanzheng Li and Yong Zhao and Lei Wu and Zhigang Zeng",

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year = "2023",

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