Steam Turbine System Research Articles

Gross error detection in steam turbine measurements based on data reconciliation of inequality constraints

Maintaining the online calculation accuracy of isentropic efficiency of a steam turbine stage is challenging due to widely existing gross errors in steam turbine measurements. They invalidate modelling results and hinder model-based monitoring and optimization. Data reconciliation is a mathematical method for gross error detection and has been applied in various industrial systems. In power plant systems, previous studies focus on gross error detection of flow rate measurements in regenerative systems based on equality constraints, which is insufficient for gross error detection of steam turbine systems. We propose a data reconciliation model adding inequality constraints to solve the problem. Statistical test is used to detect gross errors in steam turbine systems. Then an in-service 660 MW ultra-supercritical double reheat power plant is selected as a case study. Gross errors of flow rate measurements are detected and eliminated firstly. Then nonlinear inequality constraints, entropy increase of each stage, are added for further detection. Results show that the proposed model effectively detects gross errors in the steam turbine system and further improve the thermal calculation accuracy by 3.1–5.7%. It provides quantitative guidance for the calibration and maintenance of measurement instruments and facilitates performance monitoring and operation optimization in in-service power plants.

Study on the Model and Simulation of Single-Unit Isolated Grid Operation Using APROS

In order to solve the problem of imperfect control strategy and unstable control for steam turbine rotating speed of isolated grid operation in distributed generation system, based on APROS simulation support platform, the isolated grid system is divided into steam turbine system, energy-consuming system and throttle system to construct the model of single-unit isolated grid operation. The simulation results verify the accuracy of the steady-state model. The turbine energy-consuming system model can characterize the operating characteristics of the isolated grid, and the operating characteristics of the energy-consuming system will significantly affect the speed regulation of the turbine system. The establishment of the overall model lays foundation for the design and optimization of the control scheme of the single-unit isolated grid system.

Techno-economic analysis of e-waste based chemical looping reformer as hydrogen generator with co-generation of metals, electricity and syngas

Chemical looping reforming (CLR) is an efficient technology to convert hydrocarbon fuels into CO 2 and H 2 using metal oxide based oxygen carriers. The novelty of the present study is to utilize electronic waste such as printed circuit board (PCB) to generate high quality syngas and metallic components for the CLR process. A portion of the syngas generated during e-waste pyrolysis is used with coal and polypropylene for effective combustion. A techno-economic analysis is performed for the production of hydrogen and electricity in the CLR method. The levelized costs for electricity (LCOE), hydrogen (LCOH), syngas (LCOS), and metal (LCOM) production using e-wastes are estimated as 92.28 $/MWh, 3.67 $/kg, 0.0034 $/kWh, and 24.32 $/ton, respectively. The LCOH is found to be the least of 2.90 $/kg under the co-feed conditions of PCB syngas-PP. The integration of the e-waste based CLR with a steam turbine system achieved a net efficiency of 50%. • E-waste based chemical looping reformer (CLR) is proposed for hydrogen generation. • Mixture of PCB based syngas, coal, and polypropylene (PP) is used as feedstock. • Techno-economic analysis is conducted for CLR integrated steam turbine system. • Levelized costs for hydrogen, electricity, syngas and metal oxides are assessed. • PCB syngas with coal and PP produced a net efficiency of 48.8% with LCOH of 3 $/kg.

Techno-Environmental Evaluation of a Liquefied Natural Gas-Fuelled Combined Gas Turbine with Steam Cycles for Large Container Ship Propulsion Systems

Restrictions on emissions are being imposed by regional and international shipping organisations, which raise the question of which marine fuel and technology can most effectively replace heavy fuel oil and diesel engines. The aim of this study is to find appropriate advanced combined gas and steam turbine cycles for marine propulsion systems in a large container ship with respect to the evolving maritime environmental regulations. The selection criteria are the thermodynamic performance, emissions, size, and weight of advanced combined gas and steam turbine cycles in a large container ship. Two baselines are used: a diesel engine using marine diesel oil and a combined gas and steam turbine system using liquefied natural gas and marine diesel oil. Then, liquefied natural gas cycles are examined based on fuel replacement and enhanced to assess the benefits of liquefied natural gas over marine diesel oil. The results show that the enhanced liquefied natural gas combined gas and steam turbine cycles are the most efficient, at up to 1.6% higher than the other cycles. Regarding the size and weight, the combined gas and steam turbine propulsion system is approximately 24.7% lighter than the original diesel engine propulsion system.

Modified LPP based on Riemannian metric for feature extraction and fault detection

Dimensionality reduction methods based on manifold learning are widely adopted for industrial process monitoring. However, in many situations, these methods fail to preserve manifold intrinsic features in low-dimensional space, resulting in reduced process monitoring efficacy. To overcome this problem, a modified locality preserving projection (MLPP) based on the Riemannian metric is put forward. First, the Riemannian metric, which embodies a manifold’s geometric information, is estimated from process data. Then, the low dimensional embedding coordinates obtained from LPP are supplemented with an estimate of the Riemannian metric. Finally, a process monitoring model is developed, and kernel density estimation is utilized to approximate confidence bounds for T2 and SPE statistics. The proposed MLPP method is applied to the feature extraction of Twin-Peaks dataset, fault detection of hot strip mill, steam turbine system and Tennessee Eastman processes. The effectiveness of MLPP method is compared with both the manifold learning and deep learning approaches. In addition, the proposed method is evaluated under various noisy conditions. The average fault detection rate of 98.9%, 99.6% and 84.4% in hot strip mill, steam turbine system and Tennessee Eastman processes, respectively, are higher than the existing methods. Quantitative results indicate the superiority of the proposed MLPP method.

The application of modified thermodynamic system correction method to secondary reheat steam turbine

In order to calculation the enthalpy of wet steam in the secondary reheat turbine thermal system the thermodynamic system of the secondary reheat steam turbine based on the isentropic ideal expansion process line was corrected, This method simplifies the correction calculation step and increases the accuracy of the correction result. Analysis of the rationality of the improved method shows that: Compared with the existing secondary reheat steam turbine thermal system correction method, the maximum error of the improved thermal system correction method is 0.14%. Therefore, this method can better meet the test accuracy requirements.

Energy Assessment and Comparison of the Use of a Conventional Steam Turbine System in a Lng Carrier Propulsion with the Use of a Coges System

Energy Assessment and Comparison of the Use of a Conventional Steam Turbine System in a Lng Carrier Propulsion with the Use of a Coges System

Study on current characteristic detection method of hydraulic solenoid valve in nuclear power plant

In this paper, a set of electromagnetic valve current characteristic test system is designed to improve the reliability of the trip solenoid valve in the field steam turbine system of nuclear power plant. The test system starts from the field requirements, working principle of solenoid valve, software control and other aspects to complete the pressure suppression function of the hydraulic test system and the functions of data acquisition, storage, display, playback and so on. The test system is composed of a hydraulic system and an electrical control system. The system verifies the reliability of the tested object by detecting the important parameters of the solenoid valve, calibrating the current characteristic points, calculating the characteristic parameters, and judging whether the test is qualified. The test results show that the system has been successfully applied in nuclear power field, meets the needs of the site, and works well.

A Novel Control Strategy on Stable Operation of Fuel Gas Supply System and Re-Liquefaction System for LNG Carriers

Liquefied natural gas has attracted attention through an explosive increase in demands and environmental requirements. During this period, the Energy Efficiency Design Index (EEDI), which was adopted by the International Maritime Organization, expecting to significantly reduce CO2 from ships, has become an important key. It has triggered a change in use from steam turbine systems and dual fuel diesel electrics to high-efficiency main engines such as ME-GI engines to meet the EEDI requirements. However, since the ME-GI engines use 300 bar of fuel gas pressure, it is necessary to resolve problems of the pressure controllability and to prevent the reductions of the re-liquefaction amount caused by clogging of the lubricant mixed with the fuel gas during the compression. The purpose of this study is to propose a novel control strategy with a newly developed configuration for controlling the pressure so as not to trip the BOG compressors when the ME-GI engines are tripped, and for preventing a reduction on re-liquefaction amount. Unlike the typical configuration used in the current vessels, this proposal separately provides the fuel gas at 150 bar without lubricants to the re-liquefaction. In addition, three control strategies are proposed, depending upon the application of multi-controllers and the location of the pressure transmitters. A simulation was conducted to verify the efficacy of the proposed method, focusing on the controllability of the pressure and the re-liquefaction amount, in comparison with the typical configuration. As results of the simulation, the proposal showed excellent controllability without trips of the BOG compressors even in abnormal conditions and confirmed the great re-liquefaction performance.

Multivariate State Estimation Technique Combined with Modified Information Entropy Weight Method for Steam Turbine Energy Efficiency Monitoring Study

An energy efficiency monitoring method of the steam turbine system is studied in this paper. Multivariate state estimation technique (MSET) is utilized to compare the actual monitoring parameters and the healthy data of the equipment in normal working condition with a multi parameter estimation model. Due to the limitation of a single heat rate index in evaluating energy efficiency variation, the energy efficiency deviation degree combined with improved information entropy weight is proposed to judge the steam turbine’s operation condition levels. The index value in the modified weight method has been searched for more steady weight values calculated by information entropy values with small variation. Taking a 600 MW unit as an example, the energy efficiency levels of the unit under a 550 MW normal working condition are clustered into four groups, testifying the MSET model correctness and calculating the deviation degree value. Then, the energy efficiency status monitoring model is utilized to record residuals of actual data and estimated data during abnormal energy efficiency period. The residuals over deviation degree are then marked and judged as related with the abnormal data. The results show that the MSET model can timely and accurately judge the change of unit operation state, and the deviation degree calculated by the modified information entropy weight method can provide earlier warnings for the abnormal energy efficiency working conditions.

Exploration on Problems and Measures of Energy Saving and Environmental Protection of Boiler and Steam Turbine System in Thermal Power Plant

Exploration on Problems and Measures of Energy Saving and Environmental Protection of Boiler and Steam Turbine System in Thermal Power Plant

Artificial intelligence based operational strategy development and implementation for vibration reduction of a supercritical steam turbine shaft bearing

The vibrations of bearings holding the high-speed shaft of a steam turbine are critically controlled for the safe and reliable power generation at the power plants. In this paper, two artificial intelligence (AI) process models, i.e., artificial neural network (ANN) and support vector machine (SVM) based relative vibration modeling of a steam turbine shaft bearing of a 660 MW supercritical steam turbine system is presented. After extensive data processing and machine learning based visualization tests performed on the raw operational data, ANN and SVM models are trained, validated and compared by external validation tests. ANN has outperformed SVM in terms of better prediction capability and is, therefore, deployed for simulating the constructed operating scenarios. ANN process model is tested for the complete load range of power plant, i.e., from 353 MW to 662 MW and 4.07% reduction in the relative vibration of the bearing is predicted by the network. Further, various vibration reduction operating strategies are developed and tested on the validated and robust ANN process model. A selected operating strategy which has predicted a promising reduction in the relative vibration of bearing is selected. In order to confirm the effectiveness of the prediction of the ANN process model, the selected operating strategy is implemented on the actual operation of the power plant. The resulting reduction in the relative vibrations of the turbine’s bearing, which is less than the alarm limit, are confirmed. This cements the role of ANN process model to be used as an operational excellence tool resulting in vibration reduction of high-speed rotating equipment.

Development of integrated technology for waste heat recovery from humid flue gas of hot water boiler

For coal-fired hot water boilers, we developed a comprehensive waste heat recovery system coupled with a packed tower, industrial steam turbine, and absorption heat pump, which can directly reduce the auxiliary power consumption, realize energy cascade utilization, and waste heat recovery. The ASPEN Plus software was used to simulate the packed tower, absorption heat pump, and industrial steam turbine system. The design parameters of the system were obtained and the operation characteristics of the system under load rates of 25%, 50%, 75%, and 100% were investigated, the feasibility of steam subsystem transformation was also analyzed. Taking a 140 MW coal-fired boiler as an example, in the range of 25%~100% load rate, the direct energy saving can reach 118 to 523 kW∙h, the waste heat recovery power is 2.7 to 11.4 MW, and the coal saving can reach 374 to 1605 kg/h, resulting in energy and resource consumption reduction effect, the system also has CO2 and pollutant emission reduction effect. The RadFrac model can be used in packed tower design, the system can work well under variable load conditions.

A Comprehensive Heat Transfer Study Inside a Steam Turbine Valve: Experiment, Numerical Simulation, and Simplified Model

Abstract In a steam turbine system, one of the main factors limiting the operational flexibility is the thermal stress associated with a high-temperature gradient within the control valves, which often leads to structural damage during frequent startup and shutdown cycles. One possible solution is to utilize an electric heating system with appropriate insulation to decrease the warm-up time. Here, an experiment and a numerical simulation were performed using a scaled turbine valve equipped with an electric heating system to understand the heat transfer process. The experiment, which was conducted at Shanghai Jiao Tong University, had a duration of 100 h and included three heating–cooling cycles and two heat preservation states. The results showed that the temperature distribution of the scaled valve was uniform, which is due to the high thermal conductivity of the valve body and the low conductivity of the insulation layer. The simulation, which used the commercial software ansysfluent 2019 R1, was performed to model the experimental heat transfer process and showed less than 10% deviation from the measured temperatures. A sensitivity study revealed that the valve temperature is very insensitive to the heat transfer coefficient of the outer surface of the insulation layer, which is attributed to the negative feedback regulation of radiation heat transfer. To further improve the computing efficiency, a simplified model based on the lumped parameter method and the quasi-steady-state assumption was proposed and validated. This model can predict the 100 h valve temperature history in less than 1 min and showed good agreement for all of the studied cases. The ability of the simplified model to simulate the valve heating–cooling cycles at a high efficiency could accelerate the thermal design process to improve the operational flexibility of steam turbines in the future.

Small-Scale Solar–Bio-Hybrid Power Generation Using Brayton and Rankine Cycles

This study conducted a detailed technical analysis of small-scale solar–bio-hybrid power generation systems using Rankine (steam turbine) and Brayton (gas turbine) cycles. Thermodynamic models were developed to characterize the state of working fluid and select the most suitable solar collection technology for individual power generation systems. Net capacity factor of power generation and utilization efficiencies of solar and biogas energy were used as parameters to evaluate energy generation and conclude the preferred system configuration. The analysis concluded that the steam turbine system has better global efficiency (67.7%) than the gas turbine system (55.7%), while the gas turbine system has better electricity generation efficiency (27.0%) than that (5.6%) of the steam turbine system. The effects of different climates on the selection of suitable hybrid systems were also investigated to delineate suitability and feasibility of different hybrid systems. In addition, the method used in this study can also be applied to investigate and optimize other small-scale hybrid renewable energy generation systems.

Fault Propagation Inference Based on a Graph Neural Network for Steam Turbine Systems

A fault propagates along physical paths until it reaches the boundary of the equipment or system, which shows as a functional failure. Hence, inferring the fault propagation helps to ensure the normal operation of the industrial system. To infer the fault propagation in the steam turbine system, a graph model is developed. Firstly, a process graph topology is constructed according to the system mechanism, whose nodes and edges represent the equipment and mutual relationships. Meanwhile, a fault graph topology is built, in which nodes indicate potential faults and edges are inferred propagation paths. Then, the representations of fault nodes are realized through a graph neural network. Lastly, link prediction methods based on nodes’ representations are conducted, along with the paths inference results. Consequently, the accuracy of fault propagation inference for the steam turbine system is over 86%.

State of the Art and Trends in the Design and Operation of High- and Low-Pressure Heaters for Steam Turbines at Thermal and Nuclear Power Plants in Russia and Abroad: Part 1. Heater Types and Designs

The modern state in design, calculation, and operation of heaters used in the steam-turbine regeneration systems in Russia and abroad is reviewed and analyzed. The first part of the article gives a list of companies producing steam-turbine feedwater heaters and the market shares occupied by the countries producing these apparatuses. The ranges of operating parameters for the feedwater heaters of Russian and foreign steam turbines are indicated. The article gives the types of heat exchangers included in the regenerative feedwater heating system and serving as high- and low-pressure heaters that are adopted in Russia and abroad, including contact apparatuses and plate-type heaters. Specific examples of arranging such apparatuses at power plants in different countries are given. Advantages and drawbacks associated with the use of contact and plate-type apparatuses as turbine unit feedwater heaters are discussed. Different designs of shell-and-tube high- and low-pressure feedwater heaters adopted in the United States, Europe, and Russia are presented. The designs of particular high- and low-pressure heaters characteristic of different domestic and foreign producers are described. Methods for arrangement and structural makeup of different functional areas of the heater’s heat-transfer surface are shown. The advantages and drawbacks of header-and-helical coil-type high-pressure heaters and tubular apparatuses for the similar purpose, including chamber-type apparatuses, are discussed in terms of thermal efficiency, reliability, and repairability. It follows from the presented data that there is no commonly accepted approach to designing the considered apparatuses, and that there is mutual influence of manufacturing experience, design trends, and heater manufacturing traditions in different countries.

Model of thermal power plant considering water spray desuperheater for power system analysis

It is of great significance to build a model of the water spray temperature reduction system that is more suitable for electrical simulation, and apply it to the existing thermal power plant model for the simulation analysis of today’s complex thermal power plants. Based on reasonable thermodynamic assumptions, the law of conservation of energy and the law of conservation of mass, a transfer function model of a water-jet cooling system suitable for the simulation of a thermal power plant is established by using mechanism modeling. The relationship between these variables and the effect of each variable on the output variables verified the correctness of the model. A steam turbine system considering the influence of the boiler was further established, and a simulation analysis of the operating characteristics was performed, which verified that the influence of the boiler on the dynamic response of the unit is necessary in the long-term stability analysis. Finally, combined with the model established in this paper, a dynamic model of thermal power unit with water spray temperature reduction device was established. The model is simulated with the step disturbance of velocity, the disturbance of cooling water flow and the disturbance of opening door. Based on the simulation results, the action response characteristics in the process are analyzed. It is verified that the model can accurately describe the main steam parameters and power regulation when applied to large-scale power grid transient simulation.

Information entropy theory for steam turbine system monitoring study

AbstractA steam turbine is one of the components in a power plant. Considered as a strong coupling system, steam turbines may possess correlation information among the operation parameters. In this article, a correlation extraction method based on mutual information theory is proposed for performance monitoring. First, five functions between two variables including linear and nonlinear relationships are tested to validate the proposed method. In the first industrial case study, a sensor fault detection based on the governing stage pressure is conducted on the abnormal fluctuation mutual entropy values calculated by operation data. The results show the proposed method may effectively be used to detect sensor errors and locate the first error sample. Furthermore, uncertainty analysis on the heat rate is studied to sort the importance degree of the relative parameters. The mutual information entropy difference values are then calculated to quantify the sensitivity degree of the operation parameters to the heat rate index. The results in this case study are in accordance with the sequences by the Guide to the Expression of Uncertainty Measurement (GUM) and Monte Carlo (MC) methods. In conclusion, mutual information entropy may hence be used as a new solution for turbine monitoring, combined with information theory.

4E Analysis of a Fuel Cell and Gas Turbine Hybrid Energy System

Exergy analysis of the expansion turbine hybrid cycle of integrated molten carbonate fuel cells is presented in this study. The proposed cycle was used as a sustainable energy curriculum to provide a small hybrid power plant with high energy efficiency. To generate electricity with the system mentioned above, and externally repaired fusion carbon fuel cell was used located at the top of the combined cycle. Moreover, the turbine and steam turbine systems are considered as complementary and bottom layers for co-generation, respectively. The results showed that the proposed system could reach net energy of up to 1125 kilowatts, while the total exergy efficiency (including electricity and heat) for this system is more than 68%. Moreover, the energy supplied and exergy efficiency derived from the proposed cycle are stable versus changes in ambient temperatures. Besides, the effect of increasing the current density on the cell voltage and the total exergy destruction was considered. Also, the new approaches of the exergoeconomics and exergoenvironmental analysis are implemented in this system. The results show that the hybrid system can decrease the exergy destruction costs more than 16%, and the environmental footprint of the system more than 23.4%.