A Coordination Optimization Method for Load Shedding Considering Distribution Network Reconfiguration

Kai Wang, Lixia Kang () and Songhao Yang ()
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Kai Wang: Department of Chemical Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Lixia Kang: Department of Chemical Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Songhao Yang: Department of Electric Engineering, Xi’an Jiaotong University, Xi’an 710049, China

Energies, 2022, vol. 15, issue 21, 1-18

Abstract: Load shedding control is an emergency control measure to maintain the frequency stability of the power system. Most of the existing load shedding methods use the extensive form of directly cutting off the outlet of the substation, featuring low control accuracy and high control cost. A network reconfiguration technique can adjust the topology of the distribution network and offers more optimization space for load shedding control. Therefore, this paper proposes a reconfiguration–load shedding coordination optimization scheme to reduce the power loss caused by load shedding control. In the proposed method, a load shedding mathematical optimization model based on distribution network reconfiguration is first established. The tie switches and segment switches in the distribution network are used to perform the reconfiguration of the distribution network, and the load switches are adopted to realize the load shedding. To improve the solving efficiency of the model, a solving strategy that combined a minimum spanning tree algorithm with an improved genetic algorithm is trailed to address the nonlinear and nonconvex terms. The application of the proposed method and model are finally verified via the IEEE 33 bus system, and the advantages in reducing the loss cost and the number of outage users are accordingly proven.

Keywords: load shedding; network reconfiguration; minimum spanning tree algorithm; genetic algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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