Work

SMA-PDPPO: Safe Multiagent Primal-Dual Deep Reinforcement Learning for Industrial Parks Energy Trading

Year: 2024

Type: article

Source: IEEE Transactions on Industrial Informatics

DOI: 10.1109/tii.2024.3514128

Authors: Renzhi Lu, Ning Wu, Tao Yang, Ying Chen, Mingyang Sun, Dong Wang, Xin Peng

Institutions: Huazhong University of Science and Technology, State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Tsinghua University, Peking University, Dalian University of Technology, East China University of Science and Technology, Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education

Language: English

Topic: Smart Grid Energy Management

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: closed

Funders: National Natural Science Foundation of China, Natural Science Foundation of Hubei Province, Key Laboratory of System Control and Information Processing

Awards: G1867760283, G6380561929, G7056022014, G8157764143

OpenAlex ID: W4405717745

FWCI: 1.231

Cites: 35

Cited by: 12

Related to: 10