FG Thermische Energietechnik
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- CCS (2)
- CCS; Flexibility; Post combustion capture; Oxyfuel; Solvent storage; Pipeline (1)
- District heating systems (1)
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- Dynamic thermo-hydraulic modeling and simulation (1)
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- Oxy-fuel; Pulverized coal combustion; Flame pattern; Stability limits (1)
- Power plant flexibility, Isothermal oxidation, Cyclic oxidation, High temperature corrosion, Superheaters (1)
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As power generation from variable renewable energy sources such as wind and solar power continues to increase in the future, fewer baseload power plants will be needed. As a result, high operational flexibility is becoming a vital requirement for conventional power plants to allow for the smooth integration of the variable renewable energy sources (v-RES) into the grid. To understand the impact of high operational flexibility (increased cycling) for coal-fired power plant materials, five commercial coal boiler superheater and reheater materials were investigated under isothermal and cyclic conditions for 1000 h each. The candidate alloys investigated were: T91, VM12-SHC, TP347-HFG, DMV304 HCu and DMV310 N. The results (weight change kinetics and metallographic analysis) after exposure at a metal surface temperature of 650 °C clearly showed the impact of increased flexibility on the corrosion and oxidation of the materials. Oxide growth (weight gain), metal loss, oxide spallation, and grain boundary attack were found to be more severe under cyclic conditions than under isothermal conditions.
District heating dynamic models arise as an alternative approach to in-situ experimental investigations. The main advantage of dynamic modeling and simulation is the possibility to avoid technical and operational risks that might occur during in-situ experimental investigations (e.g. heat demand is not met, damages in the energy systems etc.). Within this study, the authors present two models for an existing district heating system in Cottbus, Germany. One model is developed using the tool EBSILON Professional, while the other one is developed using the Simscape toolbox for physical modeling in Matlab/Simulink. The models were experimentally validated against measured data from the considered district heating system. The results show that the Simscape model has a better fit and better response than the EBSILON model. Yet, some discrepancies were found between the measured and the simulated data and, therefore, the uncertainties of the models were addressed. A comparative study between both tools is presented. The EBSILON models permit only unidirectional flow, whereas the Simscape toolbox permits reverse flow. Nevertheless, the EBSILON model outperforms the Simscape model in computation time. In addition, this study presents an approach for dynamic thermo-hydraulic modeling of district heating networks. This approach is utilized to examine the role of district heating networks as heat storage as an optimization configuration. The numerical results show less start-ups for additional heat sources. Yet, higher heat losses from the network are observed due to the installation of unburied pipelines.
Renewable energy sources are becoming a greater component of the electrical mix, while being significantly more volatile than conventional energy sources. As a result, net stability and availability pose significant challenges. Energy-intensive processes, such as chlor-alkali electrolysis, can potentially adjust their consumption to the available power, which is known as demand side management or demand response. In this study, a dynamic model of a chlor-alkali membrane cell is developed to assess the flexible potential of the membrane cell. Several improvements to previously published models were made, making the model more representative of state-of-the-art CA plants. By coupling the model with a wind power profile, the current and potential level over the course of a day was simulated. The simulation results show that the required ramp rates are within the regular operating possibilities of the plant for most of the time and that the electrolyte concentrations in the cell can be kept at the right level by varying inlet flows and concentrations. This means that a CA plant can indeed be flexibly operated in the future energy system.
Load forecasting is an essential part of the operational management of combined heat and electrical power units, since a reliable hour- and day-ahead estimation of their thermal and electrical load can significantly improve their technical and economic performance, as well as their reliability. Among different types of prediction techniques, data-driven machine learning methods appear to be more suitable for load estimation in operational systems, compared to the classical forward approach. Research so far has been concentrated mainly on the magnitude of buildings with single load types. It has only been extended to a limited degree on the level of a district heating network where several end users with different characteristics merge into one bigger scale heat consumer (city or group of communities). In this study, artificial neural networks are utilized, to develop a load prediction model for district heating networks. A segmented analytical multi-phase approach is employed, to gradually optimize the predictor by varying the characteristics of the input variables and the structure of the neural network. The comparison against the load prediction time series generated by a local communal energy supplier using a commercial software reveals that, although the latter is enhanced by manual human corrections, the optimized fully automatic predictors developed in the present study generate a more reliable load forecast.
Electrochemical energy conversion technologies play a crucial role in space missions, for example, in the Environmental Control and Life Support System (ECLSS) on the International Space Station (ISS). They are also vitally important for future long-term space travel for oxygen, fuel and chemical production, where a re-supply of resources from Earth is not possible. Here, we provide an overview of currently existing electrolytic energy conversion technologies for space applications such as proton exchange membrane (PEM) and alkaline electrolyzer systems. We discuss the governing interfacial processes in these devices influenced by reduced gravitation and provide an outlook on future applications of electrolysis systems in, e.g., in-situ resource utilization (ISRU) technologies. A perspective of computational modelling to predict the impact of the reduced gravitational environment on governing electrochemical processes is also discussed and experimental suggestions to better understand efficiency-impacting processes such as gas bubble formation and detachment in reduced gravitational environments are outlined.