Prospectives of Day-Ahead Network Reconfiguration for Smart Distribution Systems Considering Load Diversity

In modern smart distribution systems the flow of active and reactive power among distribution feeders is well managed as they are equipped with optimally placed distributed resources such as shunt capacitors, distributed generations and distributed storages, etc. In this context, it is customary to investigate the relevance of conventional Network Reconfiguration (NR) for loss minimization and node voltage profile enhancement. This paper addresses the effectiveness of NR in smart distribution systems while considering intermittency in load and generation among distribution buses. In addition, the load diversity that exists among distribution buses due to load class mix of diverse customers is considered. Proposed method is applied on the benchmark IEEE 33-bus test distribution system to investigate the relevance of conventional NR over day-ahead reconfiguration. The application results reveal that proposed reconfiguration strategy may be more convenient and useful to distribution system operators. 

[1]  M. Kowsalya,et al.  A novel integration technique for optimal network reconfiguration and distributed generation placement in power distribution networks , 2014 .

[2]  A. V. Truong,et al.  A novel method based on adaptive cuckoo search for optimal network reconfiguration and distributed generation allocation in distribution network , 2016 .

[3]  B. Vahidi,et al.  Reconfiguration and Capacitor Placement Simultaneously for Energy Loss Reduction Based on an Improved Reconfiguration Method , 2012, IEEE Transactions on Power Systems.

[4]  Thomas Bäck,et al.  Power Distribution Network Reconfiguration by Evolutionary Integer Programming , 2014, PPSN.

[5]  Hazlie Mokhlis,et al.  Power Losses Reduction via Simultaneous Optimal Distributed Generation Output and Reconfiguration using ABC Optimization , 2014 .

[6]  Roohollah Fadaeinedjad,et al.  Distribution system efficiency improvement using network reconfiguration and capacitor allocation , 2015 .

[7]  Mohamed E. El-Hawary,et al.  The Smart Grid—State-of-the-art and future trends , 2014, 2016 Eighteenth International Middle East Power Systems Conference (MEPCON).

[8]  Mahmoud-Reza Haghifam,et al.  Risk-based reconfiguration of active electric distribution networks , 2016 .

[9]  Yuan-Kang Wu,et al.  Study of Reconfiguration for the Distribution System With Distributed Generators , 2010, IEEE Transactions on Power Delivery.

[10]  Leonardo W. de Oliveira,et al.  Optimal allocation of distributed generation with reconfiguration in electric distribution systems , 2013 .

[11]  Luciane Neves Canha,et al.  Real‐Time Reconfiguration of Distribution Network with Distributed Generation , 2014 .

[12]  Ramesh C. Bansal,et al.  A combined practical approach for distribution system loss reduction , 2015 .

[13]  K. Ravindra,et al.  Power Loss Minimization in Distribution System Using Network Reconfiguration in the Presence of Distributed Generation , 2013, IEEE Transactions on Power Systems.

[14]  A. M. El-Zonkoly,et al.  Optimal placement of multi-distributed generation units including different load models using particle swarm optimization , 2011, Swarm Evol. Comput..