Coordinated Optimal Dispatching Strategy of AC/DC Distribution Network for the Integration of Micro Energy Internet

被引：0
|
作者：
Zheng Z. [1 ,2 ]
Miao S. [1 ,2 ]
Li C. [1 ,2 ]
Zhang D. [1 ,2 ]
Han J. [1 ,2 ]
机构：
[1] State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan
[2] Hubei Electric Power Security and High Efficiency Key Laboratory, Huazhong University of Science and Technology, Wuhan
来源：
Diangong Jishu Xuebao/Transactions of China Electrotechnical Society | 2022年 / 37卷 / 01期
关键词：
AC/DC distribution network; Coordinated optimal scheduling; Dynamic network reconfiguration; Extreme learning machine; Micro energy internet;
D O I：
10.19595/j.cnki.1000-6753.tces.201374
中图分类号：
学科分类号：
摘要：
By connecting distributed generations (DG) to the distribution network through micro-energy-internet (MEI), it can fully utilize the characteristics of the multi-energy coupling and complementation of MEI to promote the consumption of renewable energy. This paper gave full consideration to the technical advantages of AC/DC distribution network and MEI as well as the interaction between them, and studied the optimal dispatching strategy of AC/DC distribution network considering dynamic network reconfiguration and multi-energy collaboration. Firstly, according to the characteristics of the system structure and dispatching model of AC/DC distribution network containing MEI, the coordinated operation mechanism was studied with the locational marginal price of distribution network and the bought/sold power of MEI as interactive variables. Aiming at minimizing operating cost of AC/DC power distribution network and MEI, a coordinated dispatching model of AC/DC power distribution network was established with full consideration of network operation constraints and interaction coupling constraints. Then, based on the derivation of locational marginal price of the mixed integer second order cone programming model, a fast solving method based on the extreme learning machine coupling interaction model was proposed. Finally, an example analysis was carried out on the improved IEEE 33 node AC/DC distribution network containing MEI. The simulation results showed that the scheduling architecture can fully reduce the network operation cost and promote the information interaction between the micro energy grid and AC/DC distribution network. Meanwhile, the solution technology proposed in this paper can greatly improve the solution efficiency on the premise of ensuring the calculation accuracy. © 2022, Electrical Technology Press Co. Ltd. All right reserved.
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页码：192 / 207
页数：15
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