Serial Exponential Elk Herd Optimizer for optimal power planning with distribution generation

This study presents a novel approach for optimal PDP in Medium Voltage (MV) networks with Distributed Generation (DG) integration, using a new optimization technique called Serial Exponential Elk Herd Optimizer (SeEHO). SeEHO combines Exponential Weighted Moving Average (EWMA) technique with Elk Herd Optimizer (EHO) to enhance the algorithm's ability to handle dynamic fluctuations in grid and improve convergence speed. The primary objective is to optimize placement, size, and type of DG units to minimize power losses, reduce the cost of DG installation, and improve network reliability. The results of this study may be employed to elevate the stability of MV distribution network optimization procedures, especially with regard to minimizing power losses in the network. Empirical results demonstrate that proposed SeEHO outperforms traditional methods by significantly reducing both active and reactive power loss, improving convergence speed and decreasing the cost of DG.