Alexander Ni

Ignition Delay Time Modulation as a Contribution to Thermo-Acoustic Instability in Sequential Combustion

Pressure pulsations due to combustion instabilities have been encountered in a premixed sequential gas turbine combustor. Measured noise spectra display one or several distinct peaks at Strouhal numbers significantly larger than unity. Height and location of the peaks depend in a sensitve manner on fuel type and/or operating conditions.The paper identifies a possible mechanism of the observed combustion instability and presents a mathematical model of acoustic self-excitation. The mechanism of self-excitation comprises interactions between the acoustic field in the fuel injector / burner with the ignition delay time of the fuel-air mixture and the heat release intensity:• pressure drop in the fuel injector nozzle changes with variations of the acoustic pressure in the burner,• variations of pressure drop and air flow velocity modulate the fuel concentration,• acoustic perturbations in the pre-flame region influence the delay time for self-ignition and consequently lead to fluctuations of flame velocity and -position.• fluctuations of flame velocity influence the refracation of acoustic waves at the flame front.• fuel inhomogeneities modulate the heat release rate and consequently the rate of volume production by the flame.Based on this structure of a self-excitation mechanism, an analytical model has been developed and used to compute eigenfrequencies and growth rates of instabilities. Some characteristics of the suggested self-excitated instabilities as they are predicted by the model match well with empirical information.Copyright

Advanced Bottoming Cycle Optimisation for Large Alstom CCPP

This paper presents the fundamentals of an evolutionary, thermo-economic plant design methodology, which enables an improved and customer-focused optimization of the bottoming cycle of a large Combined Cycle Power Plant. The new methodology focuses on the conceptual design of the CCPP applicable to the product development and the pre-acquisition phase. After the definition of the overall plant configuration such as the number of gas turbines used, the type of main cooling system and the related fix investment cost, the CCPP is optimized towards any criteria available in the process model (e.g. lowest COE, maximum NPV/IRR, highest net efficiency). In view of the fact that the optimization is performed on a global plant level with a simultaneous hot- and cold- end optimization, the results clearly show the dependency of the HRSG steam parameters and the related steam turbine configuration on the definition of the cold end (Air Cooled Condenser instead of Direct Cooling). Furthermore, competing methods for feedwater preheating (HRSG recirculation, condensate preheating or pegging steam), different HRSG heat exchanger arrangements as well as applicable portfolio components are automatically evaluated and finally selected. The developed process model is based on a fixed superstructure and copes with the full complexity of today’s bottoming cycle configurations as well with any constraints and design rules existing in practice. It includes a variety of component modules that are prescribed with their performance characteristics, design limitations and individual cost. More than 100 parameters are used to directly calculate the overall plant performance and related investment cost. Further definitions on payment schedule, construction time, operation regime and consumable cost results in a full economic life cycle calculation of the CCPP. For the overall optimization the process model is coupled to an evolutionary optimizer, whereas around 60 design parameters are used within predefined bounds. Within a single optimization run more than 100’000 bottoming cycle configurations are calculated in order to find the targeted optimum and thanks to today’s massive parallel computing resources, the solution can be found over night. Due to the direct formulation of the process model, the best cycle configuration is a result provided by the optimizer and can be based on a single-, dual or triple pressure system using non-reheat, reheat or double reheat configuration. This methodology enables to analyze also existing limitations and characteristics of the key components in the process model and assists to initiate new developments in order to constantly increase the value for power plant customers.Copyright