Application of TLBO for Distribution Network Planning via Coordination of Distributed Generation and Network Reconfiguration

Abstract This paper proposes an application of Teaching Learning Based Optimization (TLBO) method for optimal integration of Distributed Generations (DGs) in distribution systems to minimize annual energy loss and to maintain a better node voltage profile using penalty factor approach. A piece-wise linear variable load pattern is considered and the distribution network is reconfigured after optimal DG placement. Efforts have been made to scan the search space efficiently in such a way that every node of the system is a candidate node for DG placement with a priority level. The proposed method is applied on IEEE 33-bus test distribution system. The results obtained are promising when compared with other recently established methods.

[1]  Felix F. Wu,et al.  Network reconfiguration in distribution systems for loss reduction and load balancing , 1989 .

[2]  Carlos A. Castro,et al.  Distribution systems operation optimisation through reconfiguration and capacitor allocation by a dedicated genetic algorithm , 2010 .

[3]  R. Venkata Rao,et al.  Multi-objective optimization of two stage thermoelectric cooler using a modified teaching-learning-based optimization algorithm , 2013, Eng. Appl. Artif. Intell..

[4]  A MohamedImran,et al.  Optimal size and siting of multiple distributed generators in distribution system using bacterial foraging optimization , 2014, Swarm Evol. Comput..

[5]  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).

[6]  Srinivasa Rao Rayapudi,et al.  A novel method for optimal placement of distributed generation in distribution systems using HSDO , 2014 .

[7]  Amany El-Zonkoly,et al.  Optimal placement of multi-distributed generation units including different load models using particle swarm optimisation , 2011 .

[8]  Vivekananda Haldar,et al.  Power loss minimization by optimal capacitor placement in radial distribution system using modified cultural algorithm , 2015 .

[9]  Nadarajah Mithulananthan,et al.  AN ANALYTICAL APPROACH FOR DG ALLOCATION IN PRIMARY DISTRIBUTION NETWORK , 2006 .

[10]  Dheeraj Kumar Khatod,et al.  Optimal allocation of combined DG and capacitor for real power loss minimization in distribution networks , 2013 .

[11]  Zahra Moravej,et al.  A novel approach based on cuckoo search for DG allocation in distribution network , 2013 .

[12]  Dheeraj K. Khatod,et al.  Evolutionary programming based optimal placement of renewable distributed generators , 2013, IEEE Transactions on Power Systems.

[13]  M. A. Abido,et al.  Optimal power flow using Teaching-Learning-Based Optimization technique , 2014 .

[14]  R. Venkata Rao,et al.  Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems , 2011, Comput. Aided Des..

[15]  Ruben Romero,et al.  Optimal Capacitor Placement in Radial Distribution Networks , 2001 .

[16]  Debapriya Das,et al.  Optimal placement of capacitors in radial distribution system using a Fuzzy-GA method , 2008 .

[17]  M. E. El-Hawary,et al.  Optimal Distributed Generation Allocation and Sizing in Distribution Systems via Artificial Bee Colony Algorithm , 2011, IEEE Transactions on Power Delivery.

[18]  Suneet Singh,et al.  Optimal Sizing of Distributed Generation Placed on Radial Distribution Systems , 2010 .

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

[20]  Chandan Kumar Chanda,et al.  Placement of wind and solar based DGs in distribution system for power loss minimization and voltage stability improvement , 2013 .

[21]  Vimal J. Savsani,et al.  Comparative Study of Different Metaheuristics for the Trajectory Planning of a Robotic Arm , 2016, IEEE Systems Journal.

[22]  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.

[23]  F. Pilo,et al.  A multiobjective evolutionary algorithm for the sizing and siting of distributed generation , 2005, IEEE Transactions on Power Systems.

[24]  K. Afshar,et al.  Application of IPSO-Monte Carlo for optimal distributed generation allocation and sizing , 2013 .

[25]  Vishal Kumar,et al.  Optimal placement of different type of DG sources in distribution networks , 2013 .

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