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This paper proposes a dynamic simplified approach to model a Heat Recovery Steam Generator of a Gas Turbine Combined Cycle (GTCC) and its validation against field data. The adopted framework begins with some physical considerations on global HRSG structure, and then focuses on a specific application for a real plant, i.e. a 390 MW multi-shaft combined cycle based on the AEN94.3 A4 frame. Moreover the model embodies some parameters, which are easily derived from historical data to enhance the forecasting capabilities of the software, resulting in a hybrid model which covers a high range of working conditions. The whole model is designed to run in Excel/Visual Basic environment to allow for extended use by people who have limited experience in advanced modelling software. The model so created has been handled through a training process based on 10 days of experimental data, in order to create the basis for true system flexibility. Therefore, the feasibility of this approach has been verified using a Gas Turbine (GT) load profile accomplished in everyday working operations and validating the results against field data.

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As distributed systems arise as the dominate approach in energy production, new and time-effective methods to study global configuration of small scale generation systems have to be discovered. This work proposes a comparison between two disparate approaches to microturbine modelling. The target system is a modified Turbec T100 microturbine coupled with an external vessel, which aims to simulate the dynamic global behavior of a fuel cell gas turbine hybrid system generator. The first model is based on first principles with ordinary differential equations to capture the dynamic performance of the turbine and it is developed with Matlab/Simulink environment. The second model is based on a simplified-physics time constant approach and it is developed with Excel/Visual Basic software, thus aiming at a viable tool for distributed applications, despite any lose in accuracy. Both models have been verified against the experimental data of the microturbine test rig, and compared in terms of computational efforts, modelling flexibility, prediction accuracy.

This paper presents the development, implementation and validation of a simplified dynamic modeling approach to describe SOFC/GT hybrid systems in three real emulator test-rigs installed at University of Genoa (UNIGE, Italy), German Aerospace Center (DLR, Germany) and National Energy Technology Laboratory (NETL, USA), respectively. The proposed modeling approach is based on an experience-based simplification of the physical problem to reduce model computational efforts with minimal expense of accuracy. Traditional high fidelity dynamic modelling requires specialized skills and significant computational resources. This innovative approach, on the other hand, can be easily adapted to different plant configurations, predicting the most relevant dynamic phenomena with a reduced number of states: such a feature will allow, in the near future, the model deployment for monitoring purposes or advanced control scheme applications (e.g. model predictive control). The three target systems are briefly introduced and dynamic situations analyzed for model tuning, first, and validation, then. Relevance is given to peculiar transients where the model shows its reliability and its weakness. Assumptions introduced during model definition for the three different test-rigs are discussed and compared. The model captured significant dynamic behavior in all analyzed systems (in particular those regarding the GT) and showed influence of signal noise on some of the SOFC computed outputs.

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In the panorama of gas turbines for energy production, a great relevance is given to performance impact of the ambient conditions. Under the influence of ambient temperature, humidity and other factors, the engine performance is subject to consistent variations. This is true for large power plants as well as small engines. In Combined Cycle configuration, variation in performance are mitigated by the HRSG and the bottoming steam cycle. In a small scale system, such as a micro gas turbine, the influence on the electric and thermal power productions is strong as well, and is not mitigated by a bottoming cycle. This work focuses on the Turbec T100 micro gas turbine and its performance through a series of operations with different ambient temperatures. The goal is to characterize the engine performance deriving simple correlations for the influence of ambient temperature on performance, at different electrical loads. The newly obtained experimental data are compared with previous performance curves on a modified machine, to capture the differences due to hardware degradation in time. An active management of the compressor inlet temperature may be developed in the future, basing on the analysis reported here.