Competitive Bidding by Surrogate Modeling of Steam Parameter Influence on the Attainable Start Numbers of Turbine Casings

2020 ◽  
Author(s):  
Marcel Seiler ◽  
Vitali Züch ◽  
Peter Dumstorff ◽  
Henning Almstedt
Keyword(s):  
Wall Temperature ◽  
Surrogate Model ◽  
Power Plants ◽  
Fe Model ◽  
Steam Turbines ◽  
Require Time ◽  
Steam Parameters ◽  
Fast Prediction ◽  
Main Steam ◽  
Flexible Operation

Abstract The continued expansion of fluctuating energy sources such as wind turbines and solar systems will increase the demand for more flexible operation modes of power plants. Especially steam turbines with all their components will have to sustain a higher amount of start-stop cycles in order to compensate for variations in wind and solar radiation. Besides the rotor, inner casings are an example for main steam turbine components which are strongly loaded by thermal cycles at each start and shut down procedure. A precise prediction of the attainable number of start-stop cycles enables a more flexible operation within the guaranteed lifetime. However, this would require time-consuming FE calculations for each power plant due to their specific steam parameters. In this paper, a physics based surrogate model is discussed for a fast prediction of permissible start-stop cycles at plant specific steam parameters. The correlation between the physical properties from the surrogate model (wall temperature difference and the resulting stresses) and the attainable number of start-stop cycles from the FE model is determined. A validation with a different inner casing design within a usual wall temperature range confirms the high accuracy level of the surrogate model compared to uncertainties like material scatter or casting tolerances. With the provided approach typically a higher number of starts can be efficiently calculated in the bidding phase compared to assuming only one conservative value for each turbine type or size. Furthermore, the steam parameters can be optimized for increasing the number of starts to the required value without additional and time-consuming FE calculations.

Efficient Multi-Objective Optimization of Labyrinth Seal Leakage in Steam Turbines Based on Hybrid Surrogate Models

2016 ◽  
Author(s):  
Kevin Cremanns ◽  
Dirk Roos ◽  
Simon Hecker ◽  
Peter Dumstorff ◽  
Henning Almstedt ◽  
...  
Keyword(s):  
Steam Turbine ◽  
Surrogate Model ◽  
Power Plants ◽  
Polynomial Regression ◽  
Renewable Energy Sources ◽  
Surrogate Models ◽  
Future Market ◽  
Steam Turbines ◽  
Model Calculations ◽  
Highly Efficient

The demand for energy is increasingly covered through renewable energy sources. As a consequence, conventional power plants need to respond to power fluctuations in the grid much more frequently than in the past. Additionally, steam turbine components are expected to deal with high loads due to this new kind of energy management. Changes in steam temperature caused by rapid load changes or fast starts lead to high levels of thermal stress in the turbine components. Therefore, todays energy market requires highly efficient power plants which can be operated under flexible conditions. In order to meet the current and future market requirements, turbine components are optimized with respect to multi-dimensional target functions. The development of steam turbine components is a complex process involving different engineering disciplines and time-consuming calculations. Currently, optimization is used most frequently for subtasks within the individual discipline. For a holistic approach, highly efficient calculation methods, which are able to deal with high dimensional and multidisciplinary systems, are needed. One approach to solve this problem is the usage of surrogate models using mathematical methods e.g. polynomial regression or the more sophisticated Kriging. With proper training, these methods can deliver results which are nearly as accurate as the full model calculations themselves in a fraction of time. Surrogate models have to face different requirements: the underlying outputs can be, for example, highly non-linear, noisy or discontinuous. In addition, the surrogate models need to be constructed out of a large number of variables, where often only a few parameters are important. In order to achieve good prognosis quality only the most important parameters should be used to create the surrogate models. Unimportant parameters do not improve the prognosis quality but generate additional noise to the approximation result. Another challenge is to achieve good results with as little design information as possible. This is important because in practice the necessary information is usually only obtained by very time-consuming simulations. This paper presents an efficient optimization procedure using a self-developed hybrid surrogate model consisting of moving least squares and anisotropic Kriging. With its maximized prognosis quality, it is capable of handling the challenges mentioned above. This enables time-efficient optimization. Additionally, a preceding sensitivity analysis identifies the most important parameters regarding the objectives. This leads to a fast convergence of the optimization and a more accurate surrogate model. An example of this method is shown for the optimization of a labyrinth shaft seal used in steam turbines. Within the optimization the opposed objectives of minimizing leakage mass flow and decreasing total enthalpy increase due to friction are considered.

Thermo-Economic Optimization of the Dual-Pressure Condenser for 700 °C Ultra-Supercritical Coal-Fired Power Plants

2020 ◽  
Author(s):  
Yue Fu ◽  
Ming Liu ◽  
Liyuan Wang ◽  
Junjie Yan
Keyword(s):  
Heat Transfer ◽  
High Pressure ◽  
Mass Flow ◽  
Power Plants ◽  
Low Pressure ◽  
Heat Transfer Area ◽  
Economic Optimization ◽  
Steam Parameters ◽  
Main Steam ◽  
The Cost

Abstract Pulverized coal power is one of major contributor in power production, whose efficiency can be enhanced by increasing the main steam parameters and adjusting the cold end system parameters. The thermo-economic optimization of the cold end system for 700 °C ultra-supercritical coal-fired power plants were carried out in this study. The condenser pressure was thermo-economically optimized for the single-pressure condenser systems. Then, with the same heat transfer area of the optimized single-pressure condenser, the dual-pressure condenser system was thermo-economically optimized. The distributions of heat transfer area and exhaust steam mass flow between the high-pressure and low-pressure chambers in the dual-pressure condenser system were optimized. The results show that the optimal vacuum pressure of the single-pressure condenser is 3 kPa and the optimal heat transfer area is 27 km2. For the dual-pressure condenser system, the cost of dual-pressure condenser is reduced to the minimum value 1.3 million CNY/year. The power plant efficiency is increased by the maximum value 0.1% when the heat transfer area and exhaust steam mass flow rate are distributed equally between two chambers, compared with that of the single-pressure condenser system. The optimal values of the low-pressure and high-pressure chamber are 2.4 kPa and 3.2 kPa, respectively. This paper provides the reference for the design optimization of cold end system for high parameter power units.

Thermal Modeling of a Solar Steam Turbine With a Focus on Start-Up Time Reduction

2011 ◽  
Author(s):  
James Spelling ◽  
Markus Jo¨cker ◽  
Andrew Martin
Keyword(s):  
Steam Turbine ◽  
Power Plants ◽  
Thermal Power ◽  
The Body ◽  
Average Error ◽  
Steam Turbines ◽  
Effective Measure ◽  
Start Up ◽  
Turbine Casing ◽  
Main Steam

Steam turbines in solar thermal power plants experience a much greater number of starts than those operating in base-load plants. In order to preserve the lifetime of the turbine whilst still allowing fast starts, it is of great interest to find ways to maintain the turbine temperature during idle periods. A dynamic model of a solar steam turbine has been elaborated, simulating both the heat conduction within the body and the heat exchange with the gland steam, main steam and the environment, allowing prediction of the temperatures within the turbine during off-design operation and standby. The model has been validated against 96h of measured data from the Andasol 1 power plant, giving an average error of 1.2% for key temperature measurements. The validated model was then used to evaluate a number of modifications that can be made to maintain the turbine temperature during idle periods. Heat blankets were shown to be the most effective measure for keeping the turbine casing warm, whereas increasing the gland steam temperature was most effective in maintaining the temperature of the rotor. By applying a combination of these measures the dispatchability of the turbine can be improved significantly: electrical output can be increased by up to 9.5% after a long cool-down and up to 9.8% after a short cool-down.

Economic Analysis for Steam-Driven Induced Draft Fans and Application Characteristics of Different Units

2014 ◽  
Vol 889-890 ◽  
pp. 1574-1577
Author(s):  
Qi Sheng Xu ◽  
Gui Cai Liu ◽  
Jie Wu ◽  
Xiao Qian Ma ◽  
Yue Xi Yu ◽  
...  
Keyword(s):  
Economic Analysis ◽  
Economic Benefit ◽  
Power Plants ◽  
Application Characteristics ◽  
Steam Parameters ◽  
Main Steam ◽  
Induced Draft Fan

Concerning the steam-driven induced draft fan renovation tendency in large coal-fired power plants, the economic analysis of steam-driven way is proposed. And based on the 600MW unit of different capacity, the application characteristics are analyzed. As the result, the economic benefit of 600MW subcritical, supercritical and ultra-supercritical units are 6.93×106, 5.14×106 and 3.81×106 RMB, respectively. The lower main steam parameters, the larger economic benefit.

Thermal Characterization of a Steam Turbine Casing Including Measuring of Adiabatic Wall Temperatures Using Proprietary Sensors

2021 ◽  
Author(s):  
Bernhard Valerian Weigel ◽  
Stefan Odenbach ◽  
Wieland Uffrecht ◽  
Thomas Polklas
Keyword(s):  
Steam Turbine ◽  
Measurement Data ◽  
Thermal Characterization ◽  
Steam Turbines ◽  
Adiabatic Wall ◽  
Cfd Validation ◽  
Thermally Induced ◽  
Steam Parameters ◽  
Cold Starts ◽  
Flexible Operation

Abstract Modern steam turbines must increasingly be designed for flexible operation. However an increasing amount of cold starts and load changes have a massive impact on fatigue resistance of the material. So the monitoring of thermal parameters of the casing is significant for checking thermally induced stresses and furthermore lifetime calculation. Additionally the measurement data is helpful for CFD validation reasons. This paper presents a new proprietary developed sensor setup and measurement results. The sensors are flush mounted into a steam turbine at different axial and circumferential locations in the recirculation area between the intermediate and the lower pressure turbine. Hence it is possible to detect temperatures, temperature gradients and heat flux in the part of the wall near the fluid. Moreover the field of temperature within the sensor can be modulated by powering an installed heater. So the adiabatic wall temperature can be identified. For measuring the temperature gradient, seven equidistant spaced thermocouples were used in difference circuit. Therefore two different types of thermocouples were applied. Both types have better transfer characteristics compared to a thermocouple of type K. High amplification enables monitoring of small differences in temperature. The temperature measures an integrated resistor thermometer. The sensors are applied on a real 12 MW industrial steam turbine with maximal live steam parameters of 400 °C and 30 bar. The measurements show various operation points and load changes.

Investigation of Steam Turbine Warm-Keeping by Use of Air

2019 ◽  
Author(s):  
Dennis Toebben ◽  
Piotr Luczynski ◽  
Manfred Wirsum ◽  
Wolfgang F. D. Mohr ◽  
Klaus Helbig
Keyword(s):  
Heat Transfer ◽  
Steam Turbine ◽  
Power Plants ◽  
Calculation Model ◽  
Heat Radiation ◽  
Technical Solution ◽  
Fe Model ◽  
Steam Turbines ◽  
Data Set ◽  
Start Up

Abstract The changing energy landscape leads to a rising demand of more flexible power generation. A system for steam turbines warm-keeping provides the ability to shutdown conventional power plants during periods with a high share of renewable power. Simultaneously, these power plants are ready for grid stabilization on demand without an excessive consumption of lifetime during the start-up. One technical solution to keep a steam turbine warm is the use of hot air which is passed through the turbine. In addition, the air supply prevents corrosion during standstill and also enables the pre-warming after maintenance or long outages. This paper investigates the warm-keeping process of an intermediate pressure steam turbine (double shell configuration) through the use of dynamic numerical Finite-Elements (FE) simulations. As a representative test-case, warm-keeping calculations during a weekend shutdown (60h) are conducted to investigate the temperatures, their distribution and gradients within the rotor and the casing. For this purpose an improved numerical calculation model is developed. This detailed 3D FE model (including blades and vanes) uses heat transfer correlations conceived for warm-keeping with low air mass flows in gear mode operation. These analytical correlations take heat radiation, convection and contact heat transfer at the blade roots into account. The thermal boundary conditions at the outer walls of rotor and casing are determined by use of experimental natural cool-down data. The calculation model is finally compared and verified with this data set. The results offer valuable information about the thermal condition of the steam turbine for a subsequent start-up procedure. The warm-keeping operation with air is able to preserve hot start conditions for any time period. Most of the heat is transferred close to the steam inlet of the turbine, which is caused by similar flow directions of air and steam. Thus, temperatures in the last stages and in the casing stay well below material limits. This allows higher temperatures at the first blade groove of the turbine, which are highly loaded during a turbine startup and thus crucial to the lifetime.

scholarly journals Optimization of Integrated Gasification Combined-Cycle Power Plant for Polygeneration of Power and Chemicals

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7285
Author(s):  
Ammar Bany Ata ◽  
Peter Maximilian Seufert ◽  
Christian Heinze ◽  
Falah Alobaid ◽  
Bernd Epple
Keyword(s):  
Power Plants ◽  
Combined Cycle ◽  
Integrated Gasification Combined Cycle ◽  
Steam Power ◽  
Optimized Model ◽  
Overall Performance ◽  
Mass Flows ◽  
Integrated Gasification ◽  
Steam Parameters ◽  
Flexible Operation

Efficient and flexible operation is essential for competitiveness in the energy market. However, the CO2 emissions of conventional power plants have become an increasingly significant environmental dilemma. In this study, the optimization of a steam power process of an IGCC was carried out, which improved the overall performance of the plant. CCPP with a subcritical HRSG was modelled using EBSILON Professional. The numerical results of the model were validated by measurements for three different load cases (100, 80, and 60%). The results are in agreement with the measured data, with deviations of less than 5% for each case. Based on the model validation, the model was modified for the use of syngas as feed and the integration of heat into an IGCC process. The integration was optimized with respect to the performance of the CCPP by varying the extraction points, adjusting the steam parameters of the extractions and modifying the steam cycle. For the 100% load case, a steam turbine power achieved increase of +34.2%. Finally, the optimized model was subjected to a sensitivity analysis to investigate the effects of varying the extraction mass flows on the output.

scholarly journals Some design characteristics of micro steam turbines for agricultural biomass energy conversion

2020 ◽  
Vol 180 ◽  
pp. 01017
Author(s):  
Gabriel-Paul Negreanu ◽  
Ion Oprea ◽  
Viorel Berbece
Keyword(s):  
Energy Content ◽  
Agricultural Waste ◽  
Appropriate Technology ◽  
Hot Water ◽  
Biomass Energy ◽  
Flow Section ◽  
Steam Turbines ◽  
Agricultural Biomass ◽  
Steam Parameters ◽  
Main Steam

The paper continues the study of reconversion of a 400 kW hot water boiler in a steam generator suitable to valorise the energy content of briquettes and pellets of agricultural biomass. After steam parameters selection (pressure, temperature, mass-flow rate), an overview of main steam machines types (axial, radial, screw, piston engine) is done. Further, a parallel design of most wide-spread ones (Laval, Curtis and radial) were performed, at different rotation speeds, in order to find the best configuration in respect with the flow section dimensions, internal efficiency and power (electrical and thermal) output. The results of the paper could be very useful for the investors in agricultural “waste-toenergy” projects in order to select appropriate technology and equipment.

Thermal Modeling of a Solar Steam Turbine With a Focus on Start-Up Time Reduction

2011 ◽  
Vol 134 (1) ◽  
Author(s):  
James Spelling ◽  
Markus Jöcker ◽  
Andrew Martin
Keyword(s):  
Steam Turbine ◽  
Power Plants ◽  
Thermal Power ◽  
The Body ◽  
Average Error ◽  
Steam Turbines ◽  
Effective Measure ◽  
Start Up ◽  
Turbine Casing ◽  
Main Steam

Steam turbines in solar thermal power plants experience a much greater number of starts than those operating in baseload plants. In order to preserve the lifetime of the turbine while still allowing fast starts, it is of great interest to find ways to maintain the turbine temperature during idle periods. A dynamic model of a solar steam turbine has been elaborated, simulating both the heat conduction within the body and the heat exchange with the gland steam, main steam and the environment, allowing prediction of the temperatures within the turbine during off-design operation and standby. The model has been validated against 96 h of measured data from the Andasol 1 power plant, giving an average error of 1.2% for key temperature measurements. The validated model was then used to evaluate a number of modifications that can be made to maintain the turbine temperature during idle periods. Heat blankets were shown to be the most effective measure for keeping the turbine casing warm, whereas increasing the gland steam temperature was most effective in maintaining the temperature of the rotor. By applying a combination of these measures the dispatchability of the turbine can be improved significantly: electrical output can be increased by up to 9.5% after a long cooldown and up to 9.8% after a short cooldown.

Off Design Performance Prediction of Steam Turbines

2007 ◽  
Author(s):  
R. Senthil Murugan ◽  
P. M. V. Subbarao
Keyword(s):  
Power Plants ◽  
Calculated Data ◽  
Operating Conditions ◽  
Steam Turbines ◽  
Design Data ◽  
Technical Data ◽  
Design Performance ◽  
Design Variables ◽  
Steam Parameters ◽  
Time Specific

Steam turbines in coal fired power plants are designed for some fixed operating conditions. When operated at those fixed conditions, the turbines are supposed to give maximum cycle efficiency. But off-design conditions occur several times due to condenser variation, environmental change, plant aging, etc. Performance at those off-design conditions affects economy of operation. Hence prediction of performance at off-design conditions is necessary. In this work a 210 MW steam turbine is designed using available design data. Calculated data matched available data quite satisfactorily. Design condition heat cycle data and other available technical data were used for design. Three off-design conditions, varying steam flow rate, varying condenser pressure, and varying inlet steam parameters were considered for study of off-design performance. These effects were suitably incorporated to recalculate performance of the same turbine at these conditions. Performance characteristics are obtained by varying one off-design condition at a time. Specific examples also are solved by simultaneously considering all three mentioned off-design variables using actual field data. Off-design performance predictions were found to be satisfactory.

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