Improved reinforcement learning-based real-time energy scheduling for prosumer with elastic loads in smart grid-Reference-Cited by-同舟云学术

Improved reinforcement learning-based real-time energy scheduling for prosumer with elastic loads in smart grid

Published:2023-11 Issue: Volume:280 Page:111004
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Liu Didi^ORCID,Cheng Pengpeng,Cheng Jun,Liu Junxiu,Lu Meiqu,Jiang Frank

Funder

Guangxi Zhuang Autonomous Region Key Laboratory of Automatic Detecting Technology and Instruments, Guilin University of Electronic Technology

National Natural Science Foundation of China

Guangxi Normal University

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference34 articles.

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3. Prosumers as active market participants: A systematic review of evolution of opportunities, models and challenges;Grani;Renew. Sustain. Energy Rev.,2022

4. Using peer-to-peer energy-trading platforms to incentivize prosumers to form federated power plants;Morstyn;Nat. Energy,2018

5. Modeling and planning of smart buildings energy in power system considering demand response;Dadashi-Rad;Energy,2020

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