Distributed optimal scheduling for smart building clusters considering peer-to-peer electric energy sharing

被引：0
|
作者：
Zhou J. [1 ]
Li J. [1 ]
Ma H. [2 ]
Jiang D. [3 ]
Zhang H. [1 ]
机构：
[1] Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology, Ministry of Education, Northeast Electric Power University, Jilin
[2] Nanyang Power Supply Company of State Grid Henan Electric Power Company, Nanyang
[3] School of Information and Control Engineering, Jilin Institute of Chemical Technology, Jilin
来源：
Dianli Zidonghua Shebei/Electric Power Automation Equipment | 2021年 / 41卷 / 10期
基金：
中国国家自然科学基金;
关键词：
Distributed optimal scheduling; Fast alternating direction method of multipliers; Ice energy storage; Peer-to-peer electric energy sharing; Smart building clusters;
D O I：
10.16081/j.epae.202110029
中图分类号：
学科分类号：
摘要：
Aiming at smart buildings with both electric energy production and consumption capability, an ener-gy management framework of smart building clusters with P2P(Peer-to-Peer) electric energy sharing as the core is proposed based on the bidirectional flow characteristic of energy and information. The internal resources of smart buildings are quantitatively modeled. At the same time, according to the internal cooling characteristics of the buildings, the ice energy storage system is considered to meet the cooling demand of the buildings. The P2P electric energy sharing mechanism is used to improve the flexibility and economy of system operation, and an optimal day-ahead economic scheduling model of smart building clusters is built. The fast alternating direction method of multipliers is used to solve the model in a distributed way, and the optimal strategy for P2P electric energy sharing of smart building clusters is obtained. Case results show that the proposed model can effectively reduce the dependence of building clusters on external energy, and improve the overall economic benefit of the system and the consumption level of renewable energy while ensuring the comfort of users in the buildings. © 2021, Electric Power Automation Equipment Press. All right reserved.
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页码：113 / 121
页数：8
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