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author:

Fei, Yingyang (Fei, Yingyang.) [1] | Jiang, Yuewen (Jiang, Yuewen.) [2] | Hong, Qiteng (Hong, Qiteng.) [3]

Indexed by:

EI PKU

Abstract:

In this paper, by applying the interval Taylor expansion method to the AC/DC hybrid distribution network and combining it with the augmented rectangular coordinate model, an interval power flow algorithm suitable for solving the intermittent power supply and fluctuating load in the AC/DC hybrid distribution network is proposed. The algorithm considers the influence of the fluctuation of voltage and power in the DC distribution network on the power flow and modulation ratio of the AC distribution network and the voltage source converter under the master-slave control strategy and the peer-to-peer control strategy, which successfully avoids the interval iteration and the nonlinear programming. Based on the augmented rectangular coordinate model, the Jacobian matrix and the Hessen matrix are extremely sparse, which improves the calculation efficiency. Finally, this paper verifies the algorithm in the IEEE33 extended AC/DC hybrid distribution network, and the effectiveness of the algorithm is also proved by comparing the results with those after the Monte Carlo algorithm is run. © 2021, Power System Technology Press. All right reserved.

Keyword:

Electric load flow Iterative methods Jacobian matrices Nonlinear programming Peer to peer networks

Community:

  • [ 1 ] [Fei, Yingyang]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350100, China
  • [ 2 ] [Jiang, Yuewen]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350100, China
  • [ 3 ] [Hong, Qiteng]College of Electronic Information and Engineering, University of Strathclyde, Glasgow; G1 1RD, United Kingdom

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Source :

Power System Technology

ISSN: 1000-3673

Year: 2021

Issue: 7

Volume: 45

Page: 2683-2691

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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