Challenges in Advanced-USC Steam Turbine Design for 1300°F / 700°C

2012 ◽  
Author(s):  
N. Lückemeyer ◽  
H. Kirchner ◽  
H. Almstedt
Keyword(s):  
Steam Turbine ◽  
Gas Turbine ◽  
Power Plants ◽  
The European Union ◽  
Steam Turbines ◽  
Major Step ◽  
Basic Product ◽  
Application Range ◽  
Cr Steels ◽  
Nickel Base

With global warming being one of mankind’s greatest challenges together with, an increasing demand for electricity world-wide, and studies showing that fossil resources like coal and gas will remain a major source for electricity for the next couple of decades, research into the development of highest efficiency fossil power plants has become a top priority. Calculations for coal fired power plants have shown that by increasing the live steam parameters to 700°C and 350bar CO2 emissions can be reduced by as much as 8% compared to the current state-of-the-art. This is equivalent to a reduction of 24% compared to the current steam power plant fleet within the European Union. To achieve the desired operating hours at this temperature the application of nickel (Ni) based alloys for the main steam turbine components such as rotors, inner casings and valves is necessary. The use of Nickel base alloys for selected gas turbine components is common practice. But with steam turbine rotors being solid, 1000mm in diameter and casings with wall thicknesses >100mm the gas turbine application range and experience for nickel base alloys are well exceeded. This paper discusses a basic product design concept in order to identify the core challenges in developing Ni based steam turbine components. These include casting, forging, non-destructive testing and welding. The material property requirements for such components (steam-oxidation resistance, creep and fatigue resistance) are also identified. Based on these challenges and requirements a number of research projects have been carried out in Europe which have selected Alloy617 as being most suitable for forged components and Alloy625 for cast components. Further projects are currently being initiated. The last major step in steam turbine development for high temperatures was to switch from low alloyed chromium (Cr) steels to high alloyed Cr steels. The identified challenges in using Nickel base alloys for large steam turbines are compared to this last material switch to characterize the level of complexity and difficulty of the development of the 700°C steam turbine technology.

scholarly journals Prediction of the windage heating effect in steam turbine labyrinth seals

2017 ◽  
Vol 1 ◽  
pp. ETJLRM
Author(s):  
Simon Hecker ◽  
Andreas Penkner ◽  
Jens Pfeiffer ◽  
Stefan Glos ◽  
Christian Musch
Keyword(s):  
Steam Turbine ◽  
Power Plants ◽  
Thermal Stresses ◽  
Heating Effect ◽  
Steam Turbines ◽  
Labyrinth Seals ◽  
Cfd Simulations ◽  
Application Range ◽  
Operation Conditions ◽  
The Impact

Abstract Today’s steam turbine power plants are designed for highest steam inlet temperatures up to 620°C to maximize thermal efficiency. This leads to elevated thermal stresses in rotors and casings of the turbines. Hence, temperature distributions of the components have to be predicted with highest accuracy at various load points in the design process to assure reliable operation and long life time. This paper describes the windage heating effect in full labyrinth seals used in steam turbines. An analytical approach is presented, based on CFD simulations, to predict the resulting steam temperatures. A broad application range from very low to highest Reynolds numbers representing different turbine operation conditions from partial to full load is addressed. The effect of varying Reynolds number on the flow friction behaviour is captured by using an analogy to the flow over a flat plate. Additionally, the impact of different labyrinth geometries on the friction coefficient is evaluated with the help of more than 100 CFD simulations. A meta-model is derived from the numerical results. Finally, the analytical windage heating model is validated against measurements. The presented approach is a fast and reliable method to find the best performing labyrinth geometries with lowest windage effects, i.e. lowest steam temperatures.

Fault diagnosis method of peak-load-regulation steam turbine based on improved PCA-HKNN artificial neural network

2021 ◽  
pp. 1748006X2110105
Author(s):  
Yifan Wu ◽  
Wei Li ◽  
Deren Sheng ◽  
Jianhong Chen ◽  
Zitao Yu
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Steam Turbine ◽  
Power Plants ◽  
Peak Load ◽  
Clean Energy ◽  
Steam Turbines ◽  
Peak Shaving ◽  
Diagnosis Method ◽  
Load Regulation

Clean energy is now developing rapidly, especially in the United States, China, the Britain and the European Union. To ensure the stability of power production and consumption, and to give higher priority to clean energy, it is essential for large power plants to implement peak shaving operation, which means that even the 1000 MW steam turbines in large plants will undertake peak shaving tasks for a long period of time. However, with the peak load regulation, the steam turbines operating in low capacity may be much more likely to cause faults. In this paper, aiming at peak load shaving, a fault diagnosis method of steam turbine vibration has been presented. The major models, namely hierarchy-KNN model on the basis of improved principal component analysis (Improved PCA-HKNN) has been discussed in detail. Additionally, a new fault diagnosis method has been proposed. By applying the PCA improved by information entropy, the vibration and thermal original data are decomposed and classified into a finite number of characteristic parameters and factor matrices. For the peak shaving power plants, the peak load shaving state involving their methods of operation and results of vibration would be elaborated further. Combined with the data and the operation state, the HKNN model is established to carry out the fault diagnosis. Finally, the efficiency and reliability of the improved PCA-HKNN model is discussed. It’s indicated that compared with the traditional method, especially handling the large data, this model enhances the convergence speed and the anti-interference ability of the neural network, reduces the training time and diagnosis time by more than 50%, improving the reliability of the diagnosis from 76% to 97%.

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.

scholarly journals Reheat and Regenerative Gas Turbines for Feed Water Repowering of Steam Power Plant

1995 ◽  
Author(s):  
G. Negri di Montenegro ◽  
M. Gambini ◽  
A. Peretto
Keyword(s):  
Steam Turbine ◽  
Gas Turbine ◽  
Flow Rate ◽  
Gas Turbines ◽  
Power Plants ◽  
Feed Water ◽  
Brayton Cycle ◽  
Energy Integration ◽  
Steam Power ◽  
Steam Power Plants

This study is concerned with the repowering of existing steam power plants (SPP) by gas turbine (GT) units. The energy integration between SPP and GT is analyzed taking into particular account the employment of simple and complex cycle gas turbines. With regard to this, three different gas turbine has been considered: simple Brayton cycle, regenerative cycle and reheat cycle. Each of these cycles has been considered for feed water repowering of three different existing steam power plants. Moreover, the energy integration between the above plants has been analyzed taking into account three different assumptions for the SPP off-design conditions. In particular it has been established to keep the nominal value for steam turbine power output or for steam flow-rate at the steam turbine inlet or, finally, for steam flow-rate in the condenser. The numerical analysis has been carried out by the employment of numerical models regarding SPP and GT, developed by the authors. These models have been here properly connected to evaluate the performance of the repowered plants. The results of the investigation have revealed the interest of considering the use of complex cycle gas turbines, especially reheat cycles, for the feed water repowering of steam power plants. It should be taken into account that these energy advantages are determined by a repowering solution, i.e. feed water repowering which, although it is attractive for its simplicity, do not generally allows, with Brayton cycle, a better exploitation of the energy system integration in comparison with other repowering solutions. Besides these energy considerations, an analysis on the effects induced by repowering in the working parameters of existing components is also explained.

Steam Injected Gas Turbine (STIG) for Load Flexible CHP: Aspects of Dynamic Behaviour, Control and Water Recovery

2019 ◽  
Author(s):  
Thorsten Lutsch ◽  
Uwe Gampe ◽  
Guntram Buchheim
Keyword(s):  
Steam Turbine ◽  
Gas Turbine ◽  
Power Plants ◽  
Operating Cost ◽  
Combined Cycle ◽  
System Response ◽  
Water Recovery ◽  
Operating Range ◽  
Demand Fluctuations ◽  
Wide Operating

Abstract Industrial combined heat and power (CHP) plants are often faced with highly variable demand of heat and power. Demand fluctuations up to 50% of nominal load are not uncommonly. The cost and revenue situation in the energy market represents a challenge, also for cogeneration of heat and power (CHP). More frequent and rapid load changes and a wide operating range are required for economic operation of industrial power plants. Maintaining pressure in steam network is commonly done directly by a condensation steam turbine in a combined cycle or indirectly by load changes of the gas turbine in a gas turbine and heat recovery steam generator arrangement. Both result in a change of the electric output of the plant. However, operating cost of a steam turbine are higher than a single gas turbine. The steam injected gas turbine (STIG) cycle with water recovery is a beneficial alternative. It provides an equivalent degree of freedom of power and heat generation. High process efficiency is achieved over a wide operating range. Although STIG is a proven technology, it is not yet widespread. The emphasis of this paper is placed on modeling the system behavior, process control and experiences in water recovery. A dynamic simulation model, based on OpenModelica, has been developed. It provides relevant information on system response for fluctuating steam injection and helps to optimize instrumentation and control. Considerable experience has been gained on water recovery with respect to condensate quality, optimum water treatment architecture and water recovery rate, which is also presented.

Lifetime Assessments of an Old Westinghouse-Design Steam Chest

2012 ◽  
Author(s):  
Sazzadur Rahman ◽  
Waheed Abbasi ◽  
Thomas W. Joyce
Keyword(s):  
Steam Turbine ◽  
Material Properties ◽  
Power Plants ◽  
Real Life ◽  
Cyclic Stress ◽  
Steam Turbines ◽  
Reliable Operation ◽  
Steady State Operation ◽  
Different Temperatures ◽  
Transient Events

Fossil steam turbines were designed for approximately thirty years of reliable operation based on a normal duty cycle. During operation, highly stressed components of steam turbine power plants undergo a change in material properties due to cyclic stress and exposure to different temperatures. Among all the components of a steam turbine, the steam chest is affected the most as it experiences a wide variation of stresses and loads during transient events and steady-state operation. These factors can strongly influence the metallurgical condition and overall reliable life of steam chests. In this paper, Siemens’ overall approach for lifetime assessments will be discussed with a real life example on a 40 year old Westinghouse-design steam chest. The methodology and the findings from the assessment are also discussed.

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.

Effects of Steam Reheat in Advanced Steam Injected Gas Turbine Cycles

1998 ◽  
Author(s):  
A. Hofstädter ◽  
H. U. Frutschi ◽  
H. Haselbacher
Keyword(s):  
Steam Turbine ◽  
Gas Turbine ◽  
Power Plants ◽  
Steam Injection ◽  
Combined Cycle ◽  
Back Pressure ◽  
Turbine Efficiency ◽  
Pressure Steam ◽  
Additional Improvement ◽  
Gas Turbine Exhaust

Steam injection is a well-known principle for increasing gas turbine efficiency by taking advantage of the relatively high gas turbine exhaust temperatures. Unfortunately, performance is not sufficiently improved compared with alternative bottoming cycles. However, previously investigated supplements to the STIG-principle — such as sequential combustion and consideration of a back pressure steam turbine — led to a remarkable increase in efficiency. The cycle presented in this paper includes a further improvement: The steam, which exits from the back pressure steam turbine at a rather low temperature, is no longer led directly into the combustion chamber. Instead, it reenters the boiler to be further superheated. This modification yields additional improvement of the thermal efficiency due to a significant reduction of fuel consumption. Taking into account the simpler design compared with combined-cycle power plants, the described type of an advanced STIG-cycle (A-STIG) could represent an interesting alternative regarding peak and medium load power plants.

Predictive Emissions Monitoring Using a Continuously Updating Neural Network

2010 ◽  
Author(s):  
Evert Vanderhaegen ◽  
Michae¨l Deneve ◽  
Hannes Laget ◽  
Nathalie Faniel ◽  
Jan Mertens
Keyword(s):  
Neural Network ◽  
Quality Assurance ◽  
Gas Turbine ◽  
Power Plants ◽  
The United States ◽  
Gaseous Emissions ◽  
The European Union ◽  
Actual Measurement ◽  
Long Time ◽  
Operational Data

In the European Union, power plants of more than 50 MW (thermal energy) need to comply with the Large Combustion Plant Directive (LCPD, 2001) implying that flue gas emissions need to be measured continuously. Traditionally, emissions from power plants are measured using Automated Measuring Systems (AMS). The LCPD states that no more than 10 days of emission data may be lost within one year including days needed for maintenance. This is the reason why more and more power plants are currently installing a second, back-up AMS since they have problems with the availability of their AMS. Since early 1990’s, Predictive Emissions Monitoring Systems (PEMS) are being developed and accepted by some local authorities within Europe and the United States. PEMS are in contrast to AMS based on the prediction of gaseous emissions (most commonly NOx and CO) using plant operational data (eg. fuel properties, pressure, temperature, excess air, …) rather than the actual measurement of these emissions. The goal of this study is to develop a robust PEMS that can accurately predict the NOx and CO emissions across the entire normal working range of a gas turbine. Furthermore, the PEMS should require as little maintenance as possible. The study does not intend to replace the AMS by a PEMS but rather to use the PEMS as a backup for the AMS. Operational data of a gas turbine, acquired over a long period, was used to identify inputs with a high influence on the NOx and CO formation. Consequently, simulations were done testing different model structures and calibration methodologies. The study shows that a static model failed to predict the emissions accurately over long time periods. In contrast, a dynamic or self-adapting algorithm proved to be most efficient in predicting the emissions over a long time period with a minimum of required intervention and maintenance. The self-adapting algorithm uses measured AMS data to continuously update the neural network. Since the PEMS is developed as a backup for the AMS, these data are readily available. The study shows that in case of a failing AMS, the developed model could accurately predict the NOx emissions for a duration of several weeks. Although not discussed in detail in this study, a quality assurance system of the PEMS is also developed since the PEMS needs to comply to the EN14181 (as does any AMS). The PEMS as a backup of the AMS instead of a second AMS is cost and time saving. Not only is the purchase of a second AMS avoided (between 40 and 100 k€) but equally important and of the same order of magnitude are the cost and time savings with respect to the Quality Assurance of the second AMS.

Sign in / Sign up

Export Citation Format

Share Document