Agent-based power routing in active distribution networks

P.H. Nguyen, W.L. Kling, P.F. Ribeiro

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

12 Citations (Scopus)

Abstract

The expected large-scale implementation of distributed generation (DG) requires a change in the current structure and operation of distribution networks. The future distribution network must be able to manage power flow in a bidirectional way, cope with uncertainties of renewable power generation and adjust to demands of more sophisticated customers. This paper introduces the concept of a power routing function to avoid congestion, minimize the operating cost, and adequately serve the requirements of customers. This function considers the optimal power flow as a problem of minimum cost flow in the graph theory. The Scaling Push-Relabel (SPR) algorithm is used to solve that problem. It will be implemented in a distributed agent environment which is suitable with a design concept of Active Distribution Networks. The performance of the power routing function is tested on a simulation of the medium voltage 32-bus network. Simulation results show the effectiveness and flexibility of the proposed function in dealing with issues of load demand increases and network configuration changes.

Original languageEnglish
Title of host publication2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies, ISGT Europe 2011
DOIs
Publication statusPublished - 1 Dec 2011
Event2nd IEEE (PES) Innovative Smart Grid Technologies Conference Europe (lSGT Europe 2011) - Manchester, United Kingdom
Duration: 5 Dec 20117 Dec 2011
Conference number: 2
http://www.ieee-isgt-2011.eu/

Conference

Conference2nd IEEE (PES) Innovative Smart Grid Technologies Conference Europe (lSGT Europe 2011)
Abbreviated titlelSGT Europe 2011
CountryUnited Kingdom
CityManchester
Period5/12/117/12/11
Internet address

Keywords

  • Active distribution network
  • Graph theory
  • Multi-agent system
  • Optimal power flow

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