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Self-healing reconfiguration scheme for distribution network with distributed generations based on multi-agent systems

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Abstract

More and more distributed generations are connected in the distribution network. Intermittent output and different locations have a significant impact to the distribution network voltage, current, power flow, the traditional forward and backward substitution is unable to solve PV-type node and meshed network, the distributed generations increase the number of network constraints and increase the difficulty of searching the optimal solution. To solve the problem of classic self-healing method failure, based on the multi-agent system, a novel self-healing reconfiguration scheme is proposed for distribution network with distributed generations in this study. Multiple objectives are considered for minimum distributed generation output loss, minimum power loss, load balancing among the feeders and branch current constraint violation, improved forward-backward weep method is used to get power flow solution for different node types of distributed generations, a self-adaptive differential evolution algorithm with improved strategies is proposed to solve problem. The performance of proposed algorithm is analyzed for several case studies on IEEE 33-bus system. The simulation results show that the approach can improve the self-healing reconfiguration performance and adapt to the changes of dynamic conditions.

Keywords

Distribution network Self-healing reconfiguration Multi-agent systems Multi-objective optimization 

Notes

Acknowledgements

The work is supported by the National Natural Science Foundation of China (41101384), a project supported by Scientific and Technological Planning Project of Jilin Province (20140414064GH), Jilin province Development and Reform Commission Projects (2013C040).

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.School of Electrical EngineeringChangchun Institute of TechnologyChangchunChina
  2. 2.College of Computer Sciences and TechnologyJilin UniversityChangchunChina
  3. 3.Department of Electrical EngineeringTexas A&M UniversityCollege StationUSA

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