Probabilistic Power Flow Using Point Estimate Methods In Mesh And Radial Power Networks

Present trend in power system steady state analysis is to account for the existing uncertainties in the system parameters. With the increased installations of renewable energy resources, robust analysis methodologies and techniques are needed to counter the power system operation and planning challenges. Probabilistic power flow (PPF) has been identified as an efficient tool for power system analysis under uncertainty. This paper commemorates the PPF using point estimate methods (PEM). Two schemes of PEM (2m and 3m) are presented and their performance in solving PPF is evaluated by comparing it to the Monte-Carlo based PPF. PEM-PPF has been tested in both meshed transmission system (30-Bus) and radial distribution system (33-Bus) for its performance. Results have been discussed and PEM is shown to be better performing for radial networks. A new probability density function (PDF) recovery method of Johnson distribution system is used to approximate the PDF of output random variables.