A Decentralized Energy Flow Control Framework for Regional Energy Internet

Guofeng Wang, Kangli Zhao, Yu Yang, Junjie Lu and Youbing Zhang

Complexity, 2019, vol. 2019, 1-10

Abstract:

As a new form of smart grid, the energy transmission mode of the Energy Internet (EI) has changed from one direction to the interconnected form. Centralized scheduling of traditional power grids has the problems of low communication efficiency and low system resilience, which do not contribute to long-term development in the future. Owing to the fact that it is difficult to achieve an optimal operation for centralized control, we propose a decentralized energy flow control framework for regional Energy Internet. Through optimal scheduling of regional EI, large-scale utilization and sharing of distributed renewable energy can be realized, while taking into consideration the uncertainty of both demand side and supply side. Combing the multiagent system with noncooperative game theory, a novel electricity price mechanism is adopted to maximize the profit of the regional EI. We prove that Nash equilibrium of theoretical noncooperative game can realize consensus in the multiagent system. The numerical results of real-world traces show that the regional EI can better absorb the renewable energy under the optimized control strategy, which proves the feasibility and economy of the proposed decentralized energy flow control framework.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:3928268

DOI: 10.1155/2019/3928268

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