Multi-Energy Coordination Based on Multi-Agent System in Energy Internet

Liu, Siyuan; Gu, Ying; Wang, Chong; Guo, Fei; Li, Shiqun

doi:10.1109/ei2.2018.8581993

Cited by 7 publications

(1 citation statement)

References 5 publications

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“…In the field of intelligent transportation, Shao et al [20] proposed a data-driven control method for multi-vehicle system coordination based on distributed neighbor selection, where the locally measurable data of each vehicle agent in the network is computed and coordinated in a distributed manner, ultimately improving the efficiency of multi-vehicle system coordination. In the field of smart grid, Liu et al [21] proposed a VPP multi-energy complementary coordination and optimization model considering heat and power supply, which can ultimately relieve the pressure caused by the uncertainty of clean energy generation and load and improve the energy utilization through a multi-agent system composed of device agent, node Agent, and system agent, and then through the interactive coordination between their layers. Other studies such as Wang et al [22] proposed a multi-agent system consistent synchronization control strategy to coordinate multiple manipulators at the same position of the motor agent to achieve synchronization of the manipulator motors.…”

Section: Coordination In Multi-agent Systemmentioning

confidence: 99%

Prominence convergence in the strategy coordination of crowdsourcing workers

Zhang¹,

Jiang²,

Wei³

et al. 2023

Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022)

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With the increasing complexity of tasks in crowdsourcing, researchers begin to employ how a group of workers complete complex tasks collaboratively. In most works, workers often complete tasks independently and the final results are integrated by the requester or the crowdsourcing platform. We observe that the results of workers' task execution may be affected by their social relationships in crowdsourcing platforms; in the process of task execution, workers may adaptively adjust and coordinate their own strategies according to their preferences and the interactions with other workers. Based on the above findings and inspired by the coordination mechanism in multi-agent system, this paper studies the strategy coordination mechanism of crowdsourcing workers, i.e., workers have different social statuses and strategies, and they will change their strategy through the interaction with other workers. This paper firstly defines the synchronization ability of workers and proposes a crowdsourcing worker synchronization network model. Thus, the final strategies of workers are the result of continuous coordination in the synchronization network. By using this model, this paper also explores the phenomenon of workers' prominence strategy, and finally conduct experimental tests in different environments. The experimental results demonstrate the correctness of the model proposed in this paper.

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Section: Coordination In Multi-agent Systemmentioning

confidence: 99%