Micro gas turbines (MGT) provide a highly efficient, low-pollutant way to generate power and heat on-site. MGTs have also proven to be a versatile technology platform for recent developments like utilization of fuels with low specific heating values and solar thermal electricity generation. Moreover, they are the foundation to build novel cycles like the inverted Brayton cycle or fuel cell hybrid power plants.
Numerical simulations of steady operation points are beneficial in various phases of MGT cycle development. They are used to determine and analyze the future potentials of innovative cycles for example by predicting the electrical efficiency and they support the thermodynamic design process (by providing mass flow, pressure and temperature data). Numerical Simulation allows to approximate off-design performance of known cycles e.g. power output at different ambient conditions. Additionally, numerical simulation is used to support cycle optimization efforts by analyzing the sensitivity of component performance on cycle performance. Numerical models of the MGT components have to be tuned and validated based on experimental data from MGT test rigs.
At DLR institute of combustion technology a MGT steady-state cycle simulation tool has been used to analyze a variety of cycles and has been revised for several years. In this paper, the validation process is discussed in detail. Comparing simulation data with measurement data from the DLR Turbec T100 test rig has led to extensions of the numeric models, on the one hand, and to modifications of the test rig on the other. Newly implemented numerical models account for the generator heat release to the inlet air and the power electronic limitations. The test rig was modified to improve the temperature measurement at positions with uneven spatial temperature distribution such as the turbine outlet. Analyzing these temperature distributions also yields a possible explanation for the apparent strong recuperator efficiency drop at high load levels, which was also observed by other T100 users before.
The transformation of our energy system toward zero net CO2 emissions correlates with a stronger use of low energy density renewable energy sources (RES), such as photovoltaic (PV) energy. As a source of flexibility, distributed PV systems, in particular, are oftentimes installed in combination with battery storage systems. These storage systems are dispatchable, i.e., controllable by the operating owners, who can thereby take over an active market role as energy prosumers. The particular battery operation modes are based on the individual prosumer decisions, which, in turn, are strongly affected by the regulatory framework in place. Regulatory frameworks differ from country to country, but almost all regulatory frameworks feature a network charge mechanism, which allocates network infrastructure and operating costs to the end customers. This raises the question of the extent to which different network charges lead to different prosumer decisions, i.e., battery operation modes, and thus different energy system configurations (system costs). In order to evaluate this question we apply (a) a fundamental linear optimization model of the energy wholesale market, which we stringently link to (b) an analysis of peak-coincident network capacity utilization as well as (c) an evaluation of the complete costs of energy for prosumers and consumers. This stringent cycle of analysis is applied to two prototypical network allocation schemes. We demonstrate that network allocation schemes that are orientated to peak-coincident network capacity utilization could both better incentivize a distribution network-oriented behaviour and better share financial burdens between prosuming and purely consuming households than would be the case for volumetric network charge designs. This paper further demonstrates that network-oriented battery operation does not, per se, result in optimal RES integration at the wholesale market level and CO2 emissions reduction. To identify effects from increasing sector integration, an analysis is both performed for a setting without and with consideration of widespread e-mobility. As a broader conclusion, our results demonstrate that future regulatory frameworks should have a stronger focus on prosumer integration by means, among other things, of an adequate network charge design reflecting the increasingly distributed nature of our future energy system.
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