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ISSN:2394-3661 | Crossref DOI | SJIF: 5.138 | PIF: 3.854

International Journal of Engineering and Applied Sciences

(An ISO 9001:2008 Certified Online and Print Journal)

Smart Distribution System by Using Binary Particle Swarm Optimization

( Volume 7 Issue 1,January 2020 ) OPEN ACCESS
Author(s):

Samuel Kefale Melese

Abstract:

The electric Distribution System is subject to many disturbance which results power outage and material damage, and also due to its network topology power delivery to the customer is accompanied with the cost of power loss. Whenever reliability, power loss and resilience is an issue the distribution system must be designed to self healing.  The power coming from the transmission line can be effectively distributed by managing automatically it’s network configuration.  This paper explores effective loss minimization for efficient smart electrical distribution power flow. The  load  on  the  distribution  system  is  a  continuously  changing  entity  and  hence  a configuration which corresponds to a minimum loss at a particular load  will not be so at  a different load. Feeder  reconfiguration  is one  of  the  techniques  for  loss  minimization  in  a nonlinear network  optimization  problem  which  restructures  the  distribution  feeders  by  changing  the  open/closed status of the sectionalizing and tie switches.  and  the  solution  for  the  problem  involves  a  search  over  the  possible configurations with multiple constraints. Binary particle swarm optimization method was applied to find the possible switching-options for loss reduction. Since distribution system is radial configuration backward forward load flow analysis is used. The algorithm is computationally efficient and determines the switching option that gives the maximum loss reduction in the system. For testing the effeteness of the method standard IEEE 33 bus system is used. The proposed algorithm is coded in MATLAB and power world simulator, to check the result obtained by MATLAB. The optimal configuration result shows that large amount of power loss was reduced from the initial configuration. 

DOI DOI :

https://dx.doi.org/10.31873/IJEAS.7.01.02

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