Optimal placement and sizing of distributed generations using shuffled bat algorithm with future load enhancement

In this paper, a new and efficient hybrid optimization algorithm is proposed for optimal placement and sizing of the distributed generations (DGs). Bus voltage profile improvement, line flow capacity, and active and reactive power loss minimization are considered as multi-objectives to optimize under-distribution load enhancement. The addition of multi-DGs to the distribution system, which is already having DGs, is studied under increased load demand. Renewable energy resources such as wind, solar, fuel cell, and micro turbines are considered in power system modeling for finding the optimal placement and sizing. Current injection-based distribution load is considered in DGs modeling in power systems. Active and reactive losses and voltage profiles are studied for all combinations of DGs. To optimize the objective function, a new optimization technique called shuffled bat algorithm is proposed. The proposed methodology is tested on 38-bus and 69-bus radial distribution systems with 100% and 120% of base load conditions to demonstrate its performance and effectiveness. Results show that the planned methodology is superior to existing strategies in terms of multi-objectives considered.