Probabilistic load flow: A business park analysis, utilizing real world meter data

Abstract

With the introduction of higher levels of renewables and demand response programs, traditional deterministic power system tools fall short of expectation. Probabilistic load flow takes into account the uncertainty, formed by inconsistent or unknown loads and generation, in the fundamental load flow analysis. Previous works have assumed the input variables to independent. This paper applies real world meter data into the probabilistic load flow simulation, making it no longer valid to just assume independence or total correlation between the inputs without further analysis. Meter data, in 5 or 15 minute intervals, of a typical southeastern United States business park are utilized for the analysis. Since the data are incomplete, several assumptions are made for the input variables. Two different load correlation scenarios are analyzed and the probabilistic load flow results are validated by comparison of available power flow and voltage meter data. The real world data test case further confirms the validity of the proposed probabilistic load flow technique which provides an accurate and practical way for finding the solution to stochastic problems occurring in power distribution systems.