Probabilistic Analysis of Electric Energy Systems

Code 103
Semester Fall
Class Hours - Lab Hours 3 - 0
Lecturers Aris Dimeas , Nikolaos Hatziargyriou


Stochastic processes: Basic principles, Markov and Poisson processes, renewal processes, Kalman filters. Monte-Carlo simulation: Basic principles, random numbers, numerical methods, application in energy systems, reliability analysis of power systems. Preventive maintenance, control and renewal: General, unrevealed failures, criteria for maintenance procedures, minimization of maintenance cost, maximization of availability, optimization of control periods, various types of maintenance procedures, calculation of system availability considering unrevealed failures, examples. Probabilistic Load Flow: general, deterministic load flow equations, probabilistic modeling of input variables, probabilistic load flow algorithms, D.C. load flow, A.C. load flow formulations, decoupled load flow equations, stochastic load flow, probabilistic load flow in distribution systems with dispersed energy resources, practical applications.