Optimal installation of multiple DG units using competitive swarm optimizer (CSO) algorithm

This paper investigates the optimal installation of multiple distributed generation (DG) units in radial distribution network using competitive swarm optimizer (CSO) algorithm. CSO algorithm is basically evolved from PSO algorithm but conceptually it is very different from PSO algorithm. In CSO algorithm, instead of using local best and global best for particle update, a pairwise competition between particles is introduced, so that the particle which fails in the competition will learn from the winner and update its position accordingly. The DG location and sizing problem is solved by the objective of minimizing total real power loss. Results demonstrate the effectiveness of the proposed method in minimizing total real power loss (Pioss) of the system. The dominance of the proposed method is also proved by comparing the simulation results with other optimization techniques.

[1]  Nadarajah Mithulananthan,et al.  Analytical Expressions for DG Allocation in Primary Distribution Networks , 2010, IEEE Transactions on Energy Conversion.

[2]  N. Kumarappan,et al.  Optimal location and sizing of DG and capacitor in distribution network using Weight-Improved Particle Swarm Optimization Algorithm (WIPSO) , 2013, 2013 International Mutli-Conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s).

[3]  N. Kumarappan,et al.  Operation and control of wind/fuel cell based hybrid microgrid in grid connected mode , 2013, 2013 International Mutli-Conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s).

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

[5]  N. Kumarappan,et al.  Sizing and siting of Distribution Generator for different loads using firefly algorithm , 2012, IEEE-International Conference On Advances In Engineering, Science And Management (ICAESM -2012).

[6]  M. M. Aman,et al.  A new approach for optimum simultaneous multi-DG distributed generation Units placement and sizing based on maximization of system loadability using HPSO (hybrid particle swarm optimization) algorithm , 2014 .

[7]  Frede Blaabjerg,et al.  Overview of Control and Grid Synchronization for Distributed Power Generation Systems , 2006, IEEE Transactions on Industrial Electronics.

[8]  D. Shirmohammadi,et al.  A compensation-based power flow method for weakly meshed distribution and transmission networks , 1988 .

[9]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[10]  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.

[11]  Joydeep Mitra,et al.  Analytical approach for placement and sizing of distributed generation on distribution systems , 2014 .

[12]  Ramesh C. Bansal,et al.  Location and Sizing of Distributed Generation Units for Loadabilty Enhancement in Primary Feeder , 2013, IEEE Systems Journal.

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

[14]  Nadarajah Mithulananthan,et al.  Multiple Distributed Generator Placement in Primary Distribution Networks for Loss Reduction , 2013, IEEE Transactions on Industrial Electronics.

[15]  M. Geethanjali,et al.  Application of Modified Bacterial Foraging Optimization algorithm for optimal placement and sizing of Distributed Generation , 2014, Expert Syst. Appl..

[16]  Nikos D. Hatziargyriou,et al.  Integrating distributed generation into electric power systems: A review of drivers, challenges and opportunities , 2007 .

[17]  Satish Kumar Injeti,et al.  A novel approach to identify optimal access point and capacity of multiple DGs in a small, medium and large scale radial distribution systems , 2013 .

[18]  Yaochu Jin,et al.  A Competitive Swarm Optimizer for Large Scale Optimization , 2015, IEEE Transactions on Cybernetics.

[19]  A. A. Abou El-Ela,et al.  Maximal optimal benefits of distributed generation using genetic algorithms , 2010 .

[20]  Lennart Söder,et al.  Distributed generation : a definition , 2001 .