Effect of start and stop cycles on hydropower plants: modelling the deterioration of the equipment to evaluate the cycling cost
Résumé
Abstract With the high energy demand, renewable energies emerged and the deregulation of the energy market appeared in the late ’90. These types of energies are intermittent and can produce high fluctuations in the power grid because they are connected only in certain weather conditions (for example: solar energy can be produced only by day and wind energy only when it is windy). Hydropower energy is recognized for its flexibility in responding to the demands of the network in order to maintain a constant level of energy and to guarantee the security of the electrical network. Nowadays, the hydropower plants are the main provider of energy adjustments thanks to a high number of start and stop cycles (which can sometimes be around 6 per day), the fast variations in load and the use of PSH (pumped-storage hydropower). But these rapid changes in the production conditions of hydroelectric power plants lead to high stresses on the components and consequently to faster degradation (mechanical, electrical, thermal, hydraulic, etc.). This work focuses on the design of a methodology that relies on auditable methods to estimate the cost of start and stop cycles and presents three complementary, representative (by equipment), reproductible (can be applied by different operators) methods based on explicit assumptions and validated by experts and in function of the available data in order to estimate the degradation of the main components of the hydropower plant (shut-off valve, runner, generator, transformer and circuit-breaker). These methods are based on the main degradation phenomena. The first method uses on-site measurements to study the fatigue on runners, the second method uses a reliability law to estimate the lifetime of generators and a predictive model using online temperature measurements and the last method uses expert judgement due to the lack of measurements on the equipment.
Domaines
Sciences de l'ingénieur [physics]
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Savin_2023_IOP_Conf._Ser. _Earth_Environ._Sci._1136_012057.pdf (1.03 Mo)
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