scholarly journals Multi-Objective Planning for Optimal Allocation of DG and RPC Units in Radial Distribution System Using Genetic Algorithm

10.29007/bngk ◽  
2018 ◽  
Author(s):  
Jaydeepsinh Sarvaiya ◽  
Mahipalsinh Chudasama

DG penetration is continuously increased across distribution network not only to reduce carbon emission, but also to enhance the performance of the distribution network. In a restructured environment any distribution utility need to address DG placement and sizing problem to find a cost effective solution for the specific investment. Most of the authors have attempted to solve the problem based on real power loss reduction across the network. Some authors consider voltage stability based analysis for increased loadability of network with real power loss. However, optimal reactive power compensation also need to be incorporated for a cost effective solution. In this paper an attempt has been made to address various types of DG and RPC units citing and sizing problem with multi-objectives consists real power loss reduction and VSI improvement. A new approach includes development of cost function to find cost-effective solution for distribution network. Evolutionary based Genetic Algorithm used to optimize the objective function. Proposed algorithm is tested onIEEE-33 bus radial distribution system.

Author(s):  
K. Lenin

In this paper, Enriched Genetic Algorithm (EGA) utilized to solve reactive power optimization problem. In the proposed algorithm Stochastic Universal Selection (SS) is utilized to improve the selection procedure. The selection method in Genetic algorithm (GA) plays a significant role in the runtime to get the optimized solution as well as in the superiority of the solution. In this work, an enriched selection technique is presented which uphold both fast runtime and elevated quality solution. Proposed EGA algorithm has been tested in standard IEEE 118 & practical 191 bus test systems and simulation results show clearly the advanced performance of the proposed algorithm in reducing the real power loss.


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