ABSTRACT
Probabilistic methods are mathematical techniques to formally consider the impact of uncertainty in models, parameters, or data. Typical uncertainties include the future value of loading conditions, fuel prices, weather, and the status of equipment. Methods to consider all possible values of uncertain data or parameters include such techniques as interval analysis, minimum/maximum analysis, and fuzzy mathematics. In many cases, these techniques will produce conservative results because they do not necessarily incorporate the “likelihood” of each value of a parameter in an expected range, or they might be intentionally designed to compute “worse case” scenarios. ese techniques are not discussed further here. Instead, this chapter presents two techniques that have been successfully applied to power system planning and operational analysis as noted by the “Application of Probability Methods” subcommittee of the IEEE Power Engineering Society in Rau et al. (1994). ey are
• Monte Carlo simulation: analysis in which the system to be studied is subjected to pseudorandom operating conditions, and the results of many analyses are recorded and subsequently statistically studied. e advantage is that no specialized forms or simplišcations of the system model are needed.
