Prospects of Future Research Issues

Yuanzheng Li; Yong Zhao; Lei Wu; Zhigang Zeng

doi:10.1007/978-981-99-0799-1_12

Prospects of Future Research Issues

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

Abstract

We have mentioned the difficulty of smart grid forecast and dispatch mainly lies in the strong uncertainty, curse of dimensionality and the trouble of establishing the accurate model. Fortunately, as one of the model-free approaches, RL is able to deal with the stochastic renewable energy and user power demand through interacting with the environment in the absence of prior knowledge.

Original language	English
Title of host publication	Engineering Applications of Computational Methods
Pages	255-260
Number of pages	6
DOIs	https://doi.org/10.1007/978-981-99-0799-1_12
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 7 Affordable and Clean Energy

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10.1007/978-981-99-0799-1_12

Cite this

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abstract = "We have mentioned the difficulty of smart grid forecast and dispatch mainly lies in the strong uncertainty, curse of dimensionality and the trouble of establishing the accurate model. Fortunately, as one of the model-free approaches, RL is able to deal with the stochastic renewable energy and user power demand through interacting with the environment in the absence of prior knowledge.",

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

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AU - Zhao, Yong

AU - Wu, Lei

AU - Zeng, Zhigang

PY - 2023

Y1 - 2023

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AB - We have mentioned the difficulty of smart grid forecast and dispatch mainly lies in the strong uncertainty, curse of dimensionality and the trouble of establishing the accurate model. Fortunately, as one of the model-free approaches, RL is able to deal with the stochastic renewable energy and user power demand through interacting with the environment in the absence of prior knowledge.

UR - https://www.scopus.com/pages/publications/85159046133

UR - https://www.scopus.com/pages/publications/85159046133#tab=citedBy

U2 - 10.1007/978-981-99-0799-1_12

DO - 10.1007/978-981-99-0799-1_12

M3 - Chapter

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T3 - Engineering Applications of Computational Methods

SP - 255

EP - 260

BT - Engineering Applications of Computational Methods

ER -

Prospects of Future Research Issues

Abstract

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UN SDGs

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