Numerical Efficient Probabilistic Three-Phase Load Flow Based on GALHS With WGs Uncertainties Including VDL Loads and Correlation

The shift to a horizontally integrated from a vertically integrated structure in the power system leads to heightened uncertainty across multiple levels. The incorporation of uncertain behaviour is required in power system analysis due to the new power system topology. For unbalanced and balanced scenarios, three-phase load flow analysis has been widely utilized for studying power systems. This paper presents a novel and efficient approach called Genetic Algorithm based Latin Hypercube sampling (GALHS) for solving the three phase probabilistic load flow (PLF) problem. The GALHS based PLF method is designed to accurately quantify uncertainties and determine the distribution probability of different parameters, while minimizing the computational workload. The proposed technique has undergone testing utilizing the IEEE-118 bus test system for various scenarios.