Abstract

We present a directed graph-based method for distribution network reconfiguration considering distributed generation. Two reconfiguration situations are considered: operation mode adjustment with the objective of minimizing active power loss (situation I) and service restoration with the objective of maximizing loads restored (situation II). These two situations are modeled as a mixed integer quadratic programming problem and a mixed integer linear programming problem, respectively. The properties of the distribution network with distributed generation considered are reflected as the structure model and the constraints described by directed graph. More specifically, the concepts of “in-degree” and “out-degree” are presented to ensure the radial structure of the distribution network, and the concepts of “virtual node” and “virtual demand” are developed to ensure the connectivity of charged nodes in every independent power supply area. The validity and effectiveness of the proposed method are verified by test results of an IEEE 33-bus system and a 5-feeder system.

Highlights

  • Distributed generation (DG) is being increasingly deployed into the distribution network, enabling the network to be more flexible in addressing changing market conditions

  • DG is typically defined by small generators of less than 10 MW, which are commonly powered by renewable energy sources that are connected to transmission or distribution systems [1]

  • The results showed that network reconfiguration with DGs reduces active power loss and improves the voltage profile over feeders

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Summary

Introduction

Distributed generation (DG) is being increasingly deployed into the distribution network, enabling the network to be more flexible in addressing changing market conditions. A metaheuristic harmony search algorithm (HSA) was used to reconfigure and identify the optimal placement of DGs. The results showed that the simultaneous network reconfiguration and DG installation method is more effective in reducing power loss and improving the voltage profile. Li et al [7] proposed a service restoration model for reconfiguration in which the minimization of both active power loss and the possible number of switch operations are considered simultaneously, and a new approach based on the tabu search was used to solve this model. In this paper a structural model based on the directed graph and the concepts of ‘‘virtual node’’ and ‘‘virtual demand’’ are developed to solve the reconfiguration problem of the distribution network with DG for two different situations: operation mode adjustment and service restoration.

Structural model of the distribution network
Connectivity constraints
Radial structure constraints
Objective function
Operational constraints
Case studies
A Substation
Conclusions
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