Optimal Selection of Capacitors for Radial Distribution Systems to improve Annual Cost Savings and Loss Minimization using Optimization Techniques in Mat Lab Environment

M Surendranatha Reddy*, M. Satish Kumar Reddy**
*-** Assistant Professor, Department of Electrical and Electronics Engineering ,Vaagdevi Institute of Technology & Sciences,Andhra Pradesh, India.
Periodicity:October - December'2013
DOI : https://doi.org/10.26634/jee.7.2.2549

Abstract

The problem of voltage deviation and power loss is mostly addressed in distribution system by growing domestic, industrial and commercial load day by day. To minimize these problems, effective planning of distribution system is required. This effective and reliable planning of distribution system is achieved by optimized placement of control device (capacitor) in distribution networks. The idea for optimal capacitor placement is determined that location of the capacitor is to be installed in the distribution network buses where power losses should be minimum and cost saving should be maximum. This paper presents a new and efficient approach for capacitor placement in radial distribution systems that determine the optimal locations and size of capacitor with an objective of improving the annual cost saving, the voltage profile and reduction of power loss. The solution methodology includes an algorithm that employs Plant Growth Simulation Algorithm (PGSA) and Genetic algorithm to estimate the optimal size of the capacitors at the optimal buses determined. The effectiveness of the proposed method is applied to 33 and 69 bus IEEE radial distribution systems. Result shows that after placement of capacitor in candidate buses the energy loss has been reduced.

Keywords

Radial Distribution System (RDS), Optimal Location, Capacitor Placement, Genetic Algorithm (GA), Objective Function, Power Loss, Plant Growth Simulation Algorithm (PGSA)

How to Cite this Article?

Reddy, M. S., and Reddy, M. S. K., (2013). Optimal Selection of Capacitors for Radial Distribution Systems to Improve Annual Cost Savings and Loss Minimization Using Optimization Techniques in Mat Lab Environment. i-manager’s Journal on Electrical Engineering, 7(2), 8-18. https://doi.org/10.26634/jee.7.2.2549

References

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