Repository logo
 

Publication:
An Efficient Mathematical Model for Distribution System Reconfiguration Using AMPL

Loading...
Thumbnail Image

Advisor

Coadvisor

Graduate program

Undergraduate course

Journal Title

Journal ISSN

Volume Title

Publisher

Type

Article

Access right

Abstract

Distribution network is an essential part of electric power system, which however has higher power losses than transmission system. Distribution losses directly affect the operational cost of the system. Therefore, power loss reduction in distribution network is very important for distribution system users and connected customers. One of the commonly used ways for reducing losses is distribution system reconfiguration (DSR). In this process, configuration of distribution network changes by opening and closing sectional and tie switches in order to achieve the lowest level of power losses, while the network has to maintain its radial configuration and nodal voltage limits, and supply all connected loads. The DSR aiming loss reduction is a complex mixed-integer optimization problem with a quadratic term of power losses in the objective function and a set of linear and non-linear constraints. Accordingly, distribution network researchers have dedicated their efforts to developing efficient models and methodologies in order to find optimal solutions for loss reduction via DSR. In this paper, an efficient mathematical model for loss minimization in distribution network reconfiguration considering the system voltage profile is presented. The model can be solved by commercially available solvers. In the paper, the proposed model is applied to several test systems and real distribution networks showing its high efficiency and effectiveness for distribution systems reconfiguration.

Description

Keywords

Efficient mathematical model, electric power distribution systems, loss reduction, network reconfiguration, voltage profile

Language

English

Citation

IEEE Access, v. 9, p. 79961-79993.

Related itens

Sponsors

Units

Departments

Undergraduate courses

Graduate programs