Maximum Area Aggregation Approach For Cumulant-Based Probabilistic Optimal Power Flow studies

Abstract

The paper introduces a Maximum Area Aggregation (MAA) approach for Cumulant-Based Probabilistic Optimal Power Flow (P-OPF) studies. The Maximum Area Aggregation (MAA) approach relies on the Cumulant Method (CM) to produce Probability Density Functions (PDFs) in the limited and the original cases, and then combines these PDFs to generate the final PDF for all system variables. The probabilities that system variables reach their limits are computed and the maximum probability is extracted and used to find the final PDF by aggregating the PDFs (the original PDFs and the limited ones). The proposed approach is verified against Monte-Carlo Simulation (MCS) consisting of 10,000 samples and compared with the original Cumulant Method (CM). The results of MAA approach demonstrate significant improvements when compared with traditional CM results.