Feeder Reconfiguration of Distribution Systems for Loss Reduction and Emissions Reduction Using MVO Algorithm

Reddy, A. V.; Damodar Reddy, M.; Reddy, Y. V.

Document Type : Review Article

Authors

¹ Department of Electrical and Electronics Engineering, Sri Venkatewara University, Tirupati, India

² Department of Electrical and Electronics Engineering, Sri Venkatewara University, Tirupati, India.

Abstract

This article presents a network reconfiguration in balanced distribution networks using Multi Verse Optimization (MVO) to optimize the total system resistive losses and reduce emissions by means of step by step switching. Reconfiguration is a considerable manner of altering the power flows through the lines from the main substation to load ends, while maintaining radial structure. The main objective of this paper is to solve feeder reconfiguration problem to reduce the total line losses and emission reduction for an open loop distribution system. MVO is a population based method to resolve the network reconfiguration problem. A precise power flow solution is applied and the objective is formulated. A nature inspired Multi Verse Optimization is utilized to restructure the power distribution system and identify the optimal tie switches for lowest line losses in the distribution network. The reduction of resistive losses leads to reduction of emissions. The suggested MVO method has carried out on two standard 16-node and 69-node distribution systems for normal load and overload conditions and results show the performance of the anticipated MVO method. The final outcomes prove that a significant reduction in real power losses and emissions

Keywords

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Majlesi Journal of Electrical Engineering

Feeder Reconfiguration of Distribution Systems for Loss Reduction and Emissions Reduction Using MVO Algorithm

References

References

Volume 12, Issue 2 - Serial Number 2
June 2018
Pages 1-8

Feeder Reconfiguration of Distribution Systems for Loss Reduction and Emissions Reduction Using MVO Algorithm

References

References

Volume 12, Issue 2 - Serial Number 2June 2018Pages 1-8

Volume 12, Issue 2 - Serial Number 2
June 2018
Pages 1-8