OPTIMIZING LIFETIME CONSUMPTION AND INCREASING FLEXIBILITY USING ENHANCED LIFETIME ASSESSMENT METHODS WITH AUTOMATED STRESS CALCULATION FROM LONG-TERM OPERATION DATA

摘要

In the past most of the steam turbines were designed as base load machines. Due to new market requirements based on the effect of renewable energies, power plant operators are forced to operate with more frequent start-up events and load changes, resulting in a fundamental higher low cycle fatigue (LCF) lifetime consumption. Traditional methods of lifetime assessment often use representative start-ups, for the calculation of LCF damage, which can provide very conservative results with reasonable safety margins. For a high number of starts these safety margins may result in an overestimation of the LCF damage. At Alstom, an enhanced method for lifetime assessment has been developed, that evaluates the actual lifetime consumption from real operation data in an automated manner and provides much more realistic results. The operation data is used to calculate the transient temperature distribution and heat transfer coefficients along the rotor for each start-stop cycle. The corresponding stress distribution in the rotor is evaluated by means of a Finite-Element-method analysis. Finally the number of remaining cycles is extracted for the most critical locations using material data. In combination with the creep damage the lifetime consumption is evaluated. The entire process is highly automated, but also facilitates easy monitoring through the lifetime engineer by graphic presentation of calculation results. Using this enhanced method of lifetime assessment, the computed lifetime consumption is closer to the actual value, supporting the planning of overhauls and component replacements and minimizing the risk of failure or forced outages. The utilization of remaining lifetime can be optimized in favour of a more flexible mode of operation (e.g. low load operation and fast start-up) or extension of operational lifetime for conventional and combined cycle power plants.