Optimal reconfiguration of distribution network using cycle-break/genetic algorithm

Čađenović, Rade; Jakus, Damir; Sarajčev, Petar; Vasilj, Josip

doi:10.1109/ptc.2017.7980842

Cited by 3 publications

(1 citation statement)

References 15 publications

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“…However, the aforementioned literature does not involve the topology adjustment of the system network and does not fully achieve the purpose of optimizing power flow. For the distribution network reconfiguration problem, its solution usually uses mathematical optimization methods and intelligent algorithms (Mori and Ikegami, 2016) (Mishra and Hota, 2018) (Liu, 2015) (Cadenovic et al, 2017). In Liu et al (2017), a distribution network reconfiguration method considering distributed generation allocation is proposed.…”

Section: Introductionmentioning

confidence: 99%

Economic Dispatch of Distribution Network With Dispersed Wind Power Considering Network Reconfiguration

Lei

Yuan²,

Bai³

et al. 2022

Front. Energy Res.

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With the large-scale development of renewable energy sources such as wind and solar energy, the grid connection of renewable energy sources poses a certain threat to the security and stability of the power system, and also brings a great challenge to the economic dispatch of the distribution network. Traditional and single dispatching methods such as load demand response or network reconfiguration alone cannot meet the needs of a safe and economic operation of the distribution network. This article proposes an economic dispatching method for distribution networks with dispersed wind power considering network reconfiguration, and establishes an economic dispatching model with the objective function of minimizing distribution network operation cost, reconfiguration cost, and total system network loss. Based on the optimal scheduling of energy storage and reactive power compensation devices in the distribution network and the full utilization of demand response, a mixed integer second-order cone programming (MISOCP) method with multi-objective collaborative optimization is proposed. The results of the tests using the IEEE33 node system verify the feasibility and applicability of the proposed method in this article.

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