Optimal distribution feeder reconfiguration for integration of electric vehicles

Penetration levels of electric vehicles (EVs) and distributed energy resources (DER) increase as the power distribution grid continues to change. This leads to a significant variation in the distribution system load profile, reduce the voltage quality and create congestion in some nodes of the network. Distribution network reconfiguration (DNR) presents an alternative to reduce the impact of EVs and DER while avoiding requirements of network reinforcement. This work proposes a day-ahead optimal network reconfiguration to mitigate the negative impact caused by the presence of EVs in the distribution system. The distribution network is optimized using genetic algorithm (GA). A sequence of hourly network configuration is proposed to minimize the operating cost resulting from both power losses and switching operation. The cost of power losses is calculated based on the National Electricity Market of Singapore (NEMS)'s electricity hourly price. Simulations results are provided to validate the proposed method.

[1]  Jizhong Zhu,et al.  Optimization of Power System Operation , 2009 .

[2]  Dongyuan Shi,et al.  Multiobjective optimal network reconfiguration considering the charging load of PHEV , 2012, PES 2012.

[3]  Qiuwei Wu,et al.  Optimal Reconfiguration-Based Dynamic Tariff for Congestion Management and Line Loss Reduction in Distribution Networks , 2016, IEEE Transactions on Smart Grid.

[4]  S. Low,et al.  Feeder Reconfiguration in Distribution Networks Based on Convex Relaxation of OPF , 2015, IEEE Transactions on Power Systems.

[5]  Whei-Min Lin,et al.  A new approach for distribution feeder reconfiguration for loss reduction and service restoration , 1998 .

[6]  J. Driesen,et al.  The Impact of Charging Plug-In Hybrid Electric Vehicles on a Residential Distribution Grid , 2010, IEEE Transactions on Power Systems.

[7]  M. Kitagawa,et al.  Implementation of genetic algorithm for distribution systems loss minimum re-configuration , 1992 .

[8]  Gooi Hoay Beng,et al.  Combination of renewable generation and flexible load aggregation for ancillary services provision , 2015, 2015 50th International Universities Power Engineering Conference (UPEC).

[9]  Chia-Hung Lin,et al.  Impact of PV generation to voltage variation and power losses of distribution systems , 2011, 2011 4th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT).

[10]  P. Ravibabu,et al.  Implementation of genetic algorithm for optimal network reconfiguration in distribution systems for load balancing , 2008, 2008 IEEE Region 8 International Conference on Computational Technologies in Electrical and Electronics Engineering.

[11]  Juan Camilo Lopez,et al.  Optimal reconfiguration of electrical distribution systems considering reliability indices improvement , 2016 .

[12]  Qiuwei Wu,et al.  Review of congestion management methods for distribution networks with high penetration of distributed energy resources , 2014, IEEE PES Innovative Smart Grid Technologies, Europe.

[13]  J. J. Grainger,et al.  Distribution feeder reconfiguration for loss reduction , 1988 .

[14]  Ya-Chin Chang,et al.  Loss Minimization of Distribution Systems with Electric Vehicles by Network Reconfiguration , 2012, 2012 International Conference on Control Engineering and Communication Technology.

[15]  Weerakorn Ongsakul,et al.  A multi-objective network reconfiguration of distribution network with solar and wind distributed generation using NSPSO , 2014, 2014 International Conference and Utility Exhibition on Green Energy for Sustainable Development (ICUE).

[16]  Chan-Nan Lu,et al.  Operation of distribution feeders with electric vehicle charging loads , 2012, 2012 IEEE 15th International Conference on Harmonics and Quality of Power.

[17]  J. Teng.  A direct approach for distribution system load flow solutions , 2003 .