Hardware-in-the-loop simulation Transients Transfer function a b s t r a c t Direct-fired fuel cell gas turbine hybrid power system responses to open-loop transients were evaluated using a hardware-based simulation of an integrated solid oxide fuel cell gas turbine (SOFC/GT) hybrid system, implemented through the Hybrid Performance (Hyper) facility at the U.S. Department of Energy, National Energy Technology Laboratory (NETL). A disturbance in the cathode inlet air mass flow was performed by manipulating a hot-air bypass valve implemented in the hardware component. Two tests were performed; the fuel cell stack subsystem numerical simulation model was both decoupled and fully coupled with the gas turbine hardware component. The dynamic responses of the entire SOFC/GT hybrid system were studied in this paper. The reduction of cathode airflow resulted in a sharp decrease and partial recovery of the fuel cell thermal effluent in 10 s. In contrast, the turbine rotational speed did not exhibit a similar trend. The transfer functions of several important variables in the fuel cell stack subsystem and gas turbine subsystem were developed to be used in the future control method development. The importance of the cathode airflow regulation was quantified through transfer functions. The management of cathode airflow was also suggested to be a potential strategy to increase the life of fuel cells by reducing the thermal impact of operational transients on the fuel cell subsystem.ScienceDirect j o urn al h om epa ge: www.elsev ier.com/locate/he i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y 4 0 ( 2 0 1 5 ) 1 9 6 7 e1 9 7 9 http://dx.

A new emergency shutdown procedure for a direct-flred fuel cell turbine hybrid power system was evaluated using a hardware-based simulation of an integrated gasiflerlfuel celllturhine hybrid cycle (IGFC), implemented through the Hybrid Performance (Hyper) project at the National Energy Technology Laboratory, U.S. Department of Energy (NETL). The Hyper facility is designed to explore dynamic operation vf hyhrid systems and quantitatively characterize such transient hehavior. It is possihle to model, test, and evaluate the effects of different parameters on the design and operation of a gasiflerlfuel celllgas turbine hyhrid system and provide a means of quantifying risk mitigation strategies. An open-loop system analysis regarding the dynamic effect of bleed air, cold air bypass, and load hank is presented in order to evaluate the comhination of these three main actuators during emergency shutdown. In the previous Hyhrid control system architecture, catastrophic compressor failures were ohserved when the fuel and load hank were cut off during emergency shutdown strategy. Improvements were achieved using a nonlinear fuel valve ramp down when the load bank was not operating. Experiments in load hank operation show compressor surge and stall after emergency shutdown activation. The difficulties inflnding an optimal compressor and cathode mass flow for mitigation of surge and stall using these actuators are illustrated.

Energy based Cyber-physical systems (CPS) find their greatest popularity in smart grid applications, where a complex computational algorithm imparts “intelligence” to a supervisory control and data acquisition (SCADA) system used for balancing load distributions. In contrast to this static application of CPS technology, research conducted jointly by U.S. Department of Energy’s, National Energy Technology Laboratory (NETL) and Ames Laboratory proposes a new paradigm in which CPS is used as a core technology in energy system development, design, and deployment. The goal is to speed up the development and deployment of advanced concept power plants, reduce the cost and thereby encouraging private and public investment, and substantially reduce the risk of failure. The current technology development paradigm generally starts with models and bench-scale tests, leading to a pilot plant demonstration of the technology before construction of a commercial system. The concept proposed by NETL and Ames incorporates CPS before and during the construction of a pilot plant — arguably the highest risk part of implementing new energy technologies — and then extends the cyber physical infrastructure to the full-scale plant creating a fully functional and coupled digital twin. The creation of a cyber-physical platform as a part of the advanced energy system design and deployment has the potential to enable the “customization” of energy systems to meet local needs and resources. This will reduce cost and environmental impact of energy production and use. Examples of how the technology development process can be changed in the energy sector will be discussed using fuel cell turbine hybrids as an example.

A pressure drop analysis for a direct-fired fuel cell turbine hybrid power system was evaluated using a hardware-based simulation of an integrated gasifier/fuel cell/turbine hybrid cycle, implemented through the hybrid performance (Hyper) project at the National Energy Technology Laboratory, U.S. Department of Energy (NETL). The Hyper facility is designed to explore dynamic operation of hybrid systems and quantitatively characterize such transient behavior. It is possible to model, test, and evaluate the effects of different parameters on the design and operation of a gasifier/fuel cell/gas turbine hybrid system and provide means of evaluating risk mitigation strategies. The cold-air bypass in the Hyper facility directs compressor discharge flow to the turbine inlet duct, bypassing the fuel cell, and exhaust gas recuperators in the system. This valve reduces turbine inlet temperature while reducing cathode airflow, but significantly improves compressor surge margin. Regardless of the reduced turbine inlet temperature as the valve opens, a peak in turbine efficiency is observed during characterization of the valve at the middle of the operating range. A detailed experimental analysis shows the unusual behavior during steady state and transient operation, which is considered a key point for future control strategies in terms of turbine efficiency optimization and cathode airflow control.

Clean energy has become an increasingly important consideration in today’s power systems. As the push for clean energy continues, many coal-fired power plants are being decommissioned in favor of renewable power sources such as wind and solar. However, the intermittent nature of renewables means that dynamic load following traditional power systems is crucial to grid stability. With high flexibility and fast response at a wide range of operating conditions, gas turbine systems are poised to become the main load following component in the power grid. Yet, rapid changes in load can lead to fluid flow instabilities in gas turbine power systems. These instabilities often lead to compressor surge and stall, which are some of the most critical problems facing the safe and efficient operation of compressors in turbomachinery today. Although the topic of compressor surge and stall has been extensively researched, no methods for early prediction have been proven effective. This study explores the utilization of machine learning tools to predict compressor stall. The long short-term memory (LSTM) model, a form of recurrent neural network (RNN), was trained using real compressor stall datasets from a 100 kW recuperated gas turbine power system designed for hybrid configuration. Two variations of the LSTM model, classification and regression, were tested to determine optimal performance. The regression scheme was determined to be the most accurate approach, and a tool for predicting compressor stall was developed using this configuration. Results show that the tool is capable of predicting stalls 5–20 ms before they occur. With a high-speed controller capable of 5 ms time-steps, mitigating action could be taken to prevent compressor stall before it occurs.