Rotor-Blade Interaction During Blade Resonance Drive-Through

2021 ◽  
Author(s):  
Roland Grein ◽  
Ulrich Ehehalt ◽  
Christian Siewert ◽  
Norbert Kill
Keyword(s):  
Power Plants ◽  
Renewable Energy Sources ◽  
Cyclic Fatigue ◽  
Combined Cycle ◽  
Plant Design ◽  
Steam Turbines ◽  
Rotating Speed ◽  
Start Up ◽  
Blade Vibrations ◽  
Fast Start

Abstract In the future energy landscape, combined cycle power plants will increasingly take the role of providing balancing power for fluctuating renewable energy sources due to their high availability and fast start-up times. This implies more frequent cycling, a larger number of speed cycles and thus new challenges for plant design and operation. One of these challenges is a potential increase of cyclic fatigue incurred by last-stage blades during start-up and coast-down. Blade vibrations might be induced by synchronous shaft vibrations when the blade resonance is excited by lateral shaft vibrations. In this paper, we report measurement results of shaft and blade vibrations observed at some Siemens Energy steam turbines. Apart from the expected increase of blade vibrations when the double rotating speed crosses the blade resonance, a distinctive dip of shaft vibrations at the low-pressure turbine bearings is observed. We argue that this phenomenon is likely related to the aforementioned interaction between blade and shaft vibrations and present a theoretical framework to describe this interaction and the observed effect.

Coordinated Control of Gas and Steam Turbines for Efficient Fast Start-Up of Combined Cycle Power Plants

2016 ◽  
Vol 139 (2) ◽  
Author(s):  
Yasuhiro Yoshida ◽  
Kazunori Yamanaka ◽  
Atsushi Yamashita ◽  
Norihiro Iyanaga ◽  
Takuya Yoshida
Keyword(s):  
Thermal Stress ◽  
Steam Turbine ◽  
Gas Turbines ◽  
Power Plants ◽  
Thermal Stresses ◽  
Control Method ◽  
Coordinated Control ◽  
Combined Cycle ◽  
Steam Turbines ◽  
Start Up

In the fast start-up for combined cycle power plants (CCPP), the thermal stresses of the steam turbine rotor are generally controlled by the steam temperatures or flow rates by using gas turbines (GTs), steam turbines, and desuperheaters to avoid exceeding the thermal stress limits. However, this thermal stress sensitivity to steam temperatures and flow rates depends on the start-up sequence due to the relatively large time constants of the heat transfer response in the plant components. In this paper, a coordinated control method of gas turbines and steam turbine is proposed for thermal stress control, which takes into account the large time constants of the heat transfer response. The start-up processes are simulated in order to assess the effect of the coordinated control method. The simulation results of the plant start-ups after several different cool-down times show that the thermal stresses are stably controlled without exceeding the limits. In addition, the steam turbine start-up times are reduced by 22–28% compared with those of the cases where only steam turbine control is applied.

Optimizing Lifetime Consumption and Increasing Flexibility Using Enhanced Lifetime Assessment Methods With Automated Stress Calculation From Long-Term Operation Data

2013 ◽  
Author(s):  
Jan Vogt ◽  
Thomas Schaaf ◽  
Klaus Helbig
Keyword(s):  
Power Plants ◽  
Low Cycle Fatigue ◽  
Combined Cycle ◽  
Transient Temperature ◽  
Steam Turbines ◽  
Transfer Coefficients ◽  
Term Operation ◽  
Flexible Mode ◽  
Start Up ◽  
Safety Margins

In the past most of the steam turbines were designed as base load machines. Due to new market requirements based on the effect of renewable energies, power plant operators are forced to operate with more frequent start-up events and load changes, resulting in a fundamental higher low cycle fatigue (LCF) lifetime consumption. Traditional methods of lifetime assessment often use representative start-ups, for the calculation of LCF damage, which can provide very conservative results with reasonable safety margins. For a high number of starts these safety margins may result in an overestimation of the LCF damage. At Alstom, an enhanced method for lifetime assessment has been developed, that evaluates the actual lifetime consumption from real operation data in an automated manner and provides much more realistic results. The operation data is used to calculate the transient temperature distribution and heat transfer coefficients along the rotor for each start-stop cycle. The corresponding stress distribution in the rotor is evaluated by means of a Finite-Element-method analysis. Finally the number of remaining cycles is extracted for the most critical locations using material data. In combination with the creep damage the lifetime consumption is evaluated. The entire process is highly automated, but also facilitates easy monitoring through the lifetime engineer by graphic presentation of calculation results. Using this enhanced method of lifetime assessment, the computed lifetime consumption is closer to the actual value, supporting the planning of overhauls and component replacements and minimizing the risk of failure or forced outages. The utilization of remaining lifetime can be optimized in favour of a more flexible mode of operation (e.g. low load operation and fast start-up) or extension of operational lifetime for conventional and combined cycle power plants.

State of the Art Steam Turbine Automation for Optimum Transient Operation Performance

2007 ◽  
Author(s):  
Rainer Quinkertz ◽  
Edwin Gobrecht
Keyword(s):  
Steam Turbine ◽  
Power Plants ◽  
Combined Cycle ◽  
Steam Turbines ◽  
Operation Performance ◽  
Control Functions ◽  
Steam Power Plants ◽  
Start Up ◽  
Full Speed ◽  
Startup Performance

The growing share of renewable energies in the power industry coupled with increased deregulation has led to the need for additional operating flexibility of steam turbine units in both Combined Cycle and Steam Power Plants. Siemens steam turbine engineering and controls presently have several solutions to address various operating requirements: - Use of an automatic step program to perform startups allows operating comfort and repeatability. - 3 start-up modes give the operator the flexibility to start quickly to meet demand or slowly to conserve turbine life. - Several options for lifetime management are available. These options range from a basic counter of equivalent operating hours to a detailed fatigue calculation. - Restarting capabilities have been improved to allow a faster response following a trip or shutdown. - In addition to control of speed, load and pressure, special control functions provide alternative work split modes during transient conditions. - Optimum steam temperatures are calculated by the steam turbine control system to achieve optimum startup performance. - Siemens steam turbines are also capable of load rejection to house load, some even to operation at full speed, no load. Several plants are already equipped with these solutions and have provided data showing they are operating with shorter start-up times and improved load rejection capabilities. Finally Siemens of course continues to pursue future development.

Repowering and Retrofitting

2002 ◽  
Author(s):  
Andreas Pickard
Keyword(s):  
Steam Turbine ◽  
Power Plants ◽  
Free Market ◽  
Leading Edge ◽  
Project Planning ◽  
Combined Cycle ◽  
Steam Turbines ◽  
Planning Stage ◽  
Reheat Steam ◽  
Plant Optimization

At the start of this new century, environmental regulations and free-market economics are becoming the key drivers for the electricity generating industry. Advances in Gas Turbine (GT) technology, allied with integration and refinement of Heat Recovery Steam Generators (HRSG) and Steam Turbine (ST) plant, have made Combined Cycle installations the most efficient of the new power station types. This potential can also be realized, to equal effect, by adding GT’s and HRSG’s to existing conventional steam power plants in a so-called ‘repowering’ process. This paper presents the economical and environmental considerations of retrofitting the steam turbine within repowering schemes. Changing the thermal cycle parameters of the plant, for example by deletion of the feed heating steambleeds or by modified live and reheat steam conditions to suit the combined cycle process, can result in off-design operation of the existing steam turbine. Retrofitting the steam turbine to match the combined cycle unit can significantly increase the overall cycle efficiency compared to repowering without the ST upgrade. The paper illustrates that repowering, including ST retrofitting, when considered as a whole at the project planning stage, has the potential for greater gain by allowing proper plant optimization. Much of the repowering in the past has been carried out without due regard to the benefits of re-matching the steam turbine. Retrospective ST upgrade of such cases can still give benefit to the plant owner, especially when it is realized that most repowering to date has retained an unmodified steam turbine (that first went into operation some decades before). The old equipment will have suffered deterioration due to aging and the steam path will be to an archaic design of poor efficiency. Retrofitting older generation plant with modern leading-edge steam-path technology has the potential for realizing those substantial advances made over the last 20 to 30 years. Some examples, given in the paper, of successfully retrofitted steam turbines applied in repowered plants will show, by specific solution, the optimization of the economics and benefit to the environment of the converted plant as a whole.

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.

Combined-Cycle Start-Up Procedures: Dynamic Simulation and Measurement

2016 ◽  
Author(s):  
Nicolas J. Mertens ◽  
Falah Alobaid ◽  
Bernd Epple ◽  
Hyun-Gee Kim
Keyword(s):  
Power Plant ◽  
Dynamic Simulation ◽  
Steam Generator ◽  
Heat Recovery ◽  
Thermal Stresses ◽  
Measurement Data ◽  
Combined Cycle ◽  
Heat Recovery Steam Generator ◽  
Start Up ◽  
Fast Start

The daily operation of combined-cycle power plants is increasingly characterized by frequent start-up and shutdown procedures. In addition to the basic requirement of high efficiency at design load, plant operators therefore acknowledge the relevance of enhanced flexibility in operation — in particular, fast start-ups — for plant competitiveness under changing market conditions. The load ramps during start-up procedure are typically limited by thermal stresses in the heat recovery steam generator (HRSG) due to thick-walled components in the high pressure circuit. Whereas conventional HRSG design is largely based on simple steady-state models, detailed modelling and dynamic simulation of the relevant systems are necessary in order to optimize HRSG design with respect to fast start-up capability. This study investigates the capability of a comprehensive process simulation model to accurately predict the dynamic response of a triple-pressure heat recovery steam generator with reheater from warm and hot initial conditions to the start-up procedure of a heavy-duty gas turbine. The commercial combined-cycle power plant (350 MWel) was modelled with the thermal-hydraulic code Apros. Development of the plant model is based on geometry data, system descriptions and heat transfer calculations established in the original HRSG design. The numerical model is validated with two independent sets of measurement data recorded at the real power plant, showing good agreement.

scholarly journals Solid Oxide Fuel Cell Combined Cycles

1996 ◽  
Author(s):  
Frank P. Bevc ◽  
Wayne L. Lundberg ◽  
Dennis M. Bachovchin
Keyword(s):  
Fuel Cell ◽  
Solid Oxide Fuel Cell ◽  
Power Plants ◽  
Combined Cycle ◽  
Solid Oxide ◽  
Plant Performance ◽  
Gaseous Emissions ◽  
Oxide Fuel ◽  
Plant Design ◽  
Combined Cycles

The integration of the solid oxide fuel cell (SOFC) and combustion turbine technologies can result in combined-cycle power plants, fueled with natural gas. that have high efficiencies and clean gaseous emissions. Results of a study are presented in which conceptual designs were developed for three power plants based upon such an integration, and ranging in rating from 3 to 10 MW net ac. The plant cycles are described, and characteristics of key components are summarized. In addition, plant design-point efficiency estimates are presented, as well as values of other plant performance parameters.

Challenges in Designing and Building a 700 MW All-Air-Cooled Steam Electric Power Plant

2011 ◽  
Author(s):  
John T. Langaker ◽  
Christopher Hamker ◽  
Ralph Wyndrum
Keyword(s):  
Power Plant ◽  
Electric Power ◽  
Power Plants ◽  
Combined Cycle ◽  
Air Cooling ◽  
Plant Design ◽  
Auxiliary Equipment ◽  
Turbine Generator ◽  
Plant Equipment ◽  
Dry Cooling

Large natural gas fired combined cycle electric power plants, while being an increasingly efficient and cost effective technology, are traditionally large consumers of water resources, while also discharging cooling tower blowdown at a similar rate. Water use is mostly attributed to the heat rejection needs of the gas turbine generator, the steam turbine generator, and the steam cycle condenser. Cooling with air, i.e. dry cooling, instead of water can virtually eliminate the environmental impact associated with water usage. Commissioned in the fall of 2010 with this in mind, the Halton Hills Generating Station located in the Greater Toronto West Area, Ontario, Canada, is a nominally-rated 700 Megawatt combined cycle electric generating station that is 100 percent cooled using various air-cooled heat exchangers. The resulting water consumption and wastewater discharge of this power plant is significantly less than comparably sized electric generating plants that derive cooling from wet methods (i.e, evaporative cooling towers). To incorporate dry cooling into such a power plant, it is necessary to consider several factors that play important roles both during plant design as well as construction and commissioning of the plant equipment, including the dry cooling systems. From the beginning a power plant general arrangement and space must account for dry cooling’s increase plot area requirements; constraints therein may render air cooling an impossible solution. Second, air cooling dictates specific parameters of major and auxiliary equipment operation that must be understood and coordinated upon purchase of such equipment. Until recently traditional wet cooling has driven standard designs, which now, in light of dry cooling’s increase in use, must be re-evaluated in full prior to purchase. Lastly, the construction and commissioning of air-cooling plant equipment is a significant effort which demands good planning and execution.

Modeless Start-Up Control for Operational Flexibility of Combined Cycle Power Plants

2020 ◽  
Vol 53 (10) ◽  
pp. 636-645
Author(s):  
Yasuhiro Yoshida ◽  
Yuya Tokuda ◽  
Takuya Yoshida ◽  
Yuki Enomoto ◽  
Nobuhiro Osaki ◽  
...  
Keyword(s):  
Power Plants ◽  
Combined Cycle ◽  
Operational Flexibility ◽  
Start Up
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