Availability and Reliability have become a major concern for operating companies; especially for those where unscheduled outages due to purchased power agreements may be highly penalized. On the other hand, high revenues by the sale of electricity can be achieved if the power generating set performs according to its demand.
Economic calculations demonstrate that the bottom line between profit and loss lies within the high 90th% of availability. This paper summarizes the results of an analysis based on the regulations in France with its so-called EJP days (Effacement Jour Pointe). Any loss of highly penalized EJP days is quantified based on known RAM (Reliability, Availability, Maintainability) values of the equipment, as these are the Mean Time Between Failures MTBF’s and the Mean Times To Repair MTTR’s of the overall equipment as well as its subassemblies. In formulating the demand, the past 12 years of assigned EJP days by the Electricité de France, EdF, was analyzed to derive probability ratings of seasonal distributions, weekly distributions and day block distributions.
The mathematics of this simulation model are based on well proven statistical procedures (i.e. the Monte Carlo Method). By performing parameter variations, the model can also quantitatively predict how much the Mean Time Between Failures of a heavy duty gas turbine must usually be better for this application when compared to an aeroderivative gas turbine. This is because it normally takes longer to repair or replace a heavy duty gas turbine versus an aeroderivative unit in case of a major unscheduled or forced outage.
Life Cycle Cost versus Life Cycle Investment – A new Approach