Turbine Equipment Research Articles

Study on Condition Monitoring and Evaluation of Auxiliary Engine of Steam Turbine Based on Matter-element Theory

As an important equipment in thermal production process of thermal power unit, auxiliary equipment of steam turbine, such as feed-water pump, whether it can operate safely and economically is very important for normal operation of thermal power plant. Considering that the auxiliary machine on the side of the steam turbine of a power plant has the characteristics of high failure rate, a state monitoring and evaluation method based on the matter-element theory is proposed. Based on the establishment of the monitoring index and evaluation model of the auxiliary engine on the side of the steam turbine, the correlation degree between the main operating parameters of the auxiliary engine and the monitoring model is determined. According to the value of correlation degree, the operating condition of auxiliary machine is judged to be excellent, good, qualified or malfunction. Finally, a 300MW steam feed pump is taken as an example to prove that this method has certain engineering application value.

Structural reliability analysis and uncertainties‐based collaborative design and optimization of turbine blades using surrogate model

Abstract In power and energy systems, both the aerodynamic performance and the structure reliability of turbine equipment are affected by utilized blades. In general, the design process of blade is high dimensional and nonlinear. Different coupled disciplines are also involved during this process. Moreover, unavoidable uncertainties are transported and accumulated between these coupled disciplines, which may cause turbine equipment to be unsafe. In this study, a saddlepoint approximation reliability analysis method is introduced and combined with collaborative optimization method to address the above challenge. During the above reliability analysis and design optimization process, surrogate models are utilized to alleviate the computational burden for uncertainties‐based multidisciplinary design and optimization problems. Smooth response surfaces of the performance of turbine blades are constructed instead of expensively time‐consuming simulations. A turbine blade design problem is solved here to validate the effectiveness and show the utilization of the given approach.

Accumulation of Corrosion-Fatigue Damage by Hydro Turbine Equipment Elements

Questions are considered for evaluating material damage and substantiation of life on the basis of corrosion-fatigue crack development kinetics. Linear fracture mechanics are used for this approach suitable for large and small cracks, which makes it possible to include a nominal initial crack l0 among basic material properties. Calculated curves for fatigue in an aqueous medium based on 1010 cycles, and the curves for fatigue damage accumulation corresponding to 106 and 1010 cycles are provided for specimens with a cross section of 180X200 mm of steel 06Kh12N3D in rolled and cast conditions. Results are provided for evaluation of the life of during action of two-stage loading and repeated overloading.

Examination of informativeness of diagnoses expressed with multiple-valued logic

This paper presents the essence of an examination of informativeness in the diagnostic information outputs expressed with multiple-valued logic. The diagnostic test required for the examination was completed on wind turbine equipment. The examination included a constant set of determined diagnostic output values. The DIAG 2 diagnostic system was used for the examination and the diagnostic test. DIAG 2 is a smart diagnostic system capable of any inference k of the set {k = 2, 3, 4}. The examination results were expressed in an Object State Table, separately for each k-valued logic of inference tested. Keywords: technical diagnostics, diagnostic inference, multiple-valued logic, artificial intelligence

Determination of optimal wind turbine alignment into the wind and detection of alignment changes with SCADA data

Abstract. Upwind horizontal axis wind turbines need to be aligned with the main wind direction to maximize energy yield. Attempts have been made to improve the yaw alignment with advanced measurement equipment but most of these techniques introduce additional costs and rely on alignment tolerances with the rotor axis or the true north. Turbines that are well aligned after commissioning may suffer an alignment degradation during their operational lifetime. Such changes need to be detected as soon as possible to minimize power losses. The objective of this paper is to propose a three-step methodology to improve turbine alignment and detect changes during operational lifetime with standard nacelle metrology (met) mast instruments (here: two cup anemometer and one wind vane). In step one, a reference turbine and an external undisturbed reference wind signal, e.g., met mast or lidar are used to determine flow corrections for the nacelle wind direction instruments to obtain a turbine alignment with optimal power production. Secondly a nacelle wind speed correction enables the application of the previous step without additional external measurement equipment. Step three is a monitoring application and allows the detection of alignment changes on the wind direction measurement device by means of a flow equilibrium between the two anemometers behind the rotor. The three steps are demonstrated at two 2 MW turbines together with a ground-based lidar. A first-order multilinear regression model gives sufficient correction of the flow distortion behind the rotor for our purposes and two wind vane alignment changes are detected with an accuracy of ±1.4∘ within 3 days of operation after the change is introduced. We show that standard turbine equipment is able to align a turbine with sufficient accuracy and changes to its alignment can be detected in a reasonably short time, which helps to minimize power losses.

Diagnosing of a complex technical object in four-valued logic

This paper presents the essence of an investigation of a complex technical object with the use of four-valued logic. To this end, an intelligent diagnostic system (DIAG 2) is described. A special feature of this system was its capability of inferring k at {k = 4, 3, 2}, in which case the logic {k = 4} is applied. An important part of this work was to present the theoretical foundations describing the essence of inference in the four-valued logic contemplated. It was also pointed out that the basis for classification of states in the multiple-valued logic of the diagnostic system (DIAG 2) was the permissible interval of changes in the values of diagnostic signal features. Four-valued logic testing was applied to a system of wind turbine equipment. Keywords: technical diagnostics, diagnostic inference, multiple-valued logic, artificial intelligence

Design and Manufacturing of Composite Tower Structure for Wind Turbine Equipment

This study proposes the composite tower design process for large wind turbine equipment. In this work, structural design of tower and analysis using finite element method was performed. After structural design, prototype blade manufacturing and test was performed. The used material is a glass fiber and epoxy resin composite. And also, sand was used in the middle part. The optimized structural design and analysis was performed. The parameter for optimized structural design is weight reduction and safety of structure. Finally, structure of tower will be confirmed by structural test.

Development of a risk management model for power tunnels design process

In this study, an innovative risk management model for the design process of power tunnels projects is presented. Experts who have experience in mega dam projects and working in owner administration or consultant companies were interviewed, and their responses were analyzed and ranked. Impacts of the identified risks on cost and time of the project are separately determined. These separations are of the novelty of this current study. This leads to identify disagreements between the two parties, remove bias from the study, and also render a better perspective for impact types of the risks. Based on the opinions of consultant-experienced experts, the risk “delays due to making new decisions by owners” and the risk “poor documentation” were identified as the most critical risks affecting time and cost of the projects, respectively. On the other hand, owner-experienced experts found the risk “change of design due to inaccessibility of proper turbine sets” as the most important risk. The results showed that the most critical risks can be mitigated and/or avoided through resolving the bureaucracy to receive permission to purchase appropriate turbine sets and equipment for power plants and establishing systematic documentation units in both owner and consultant administrations.

Synthesis of the equipment health management system of the turbine units' of thermal power stations

The aim of the research is the development of technical diagnostics subsystem with the possibility of its further integration into the automated system of equipment health management, which will improve the efficiency of data ware, hardware and software. Synthesis of intellectual diagnostic models was produced a by using the Matlab graphical agents. At the same time, there were synthesized models of three types: fuzzy, neural-network and model built by planning the full factorial experimental method. Was proposed the concept of the three-stage procedure of the diagnosis of the thermal power station's turbine unit, instead of the creation of diagnosis mathematical models and failure models of objects, immediately begin to develop an algorithm of diagnosis using advanced intelligent technologies. The technique of creating a sub-line diagnostics status of the turbine unit, which includes three main stages: identification of diagnostic features based on expert method; the synthesis of diagnostic model of the facility technical condition; research models on the stability, sensitivity and uniqueness, was proposed. The main diagnostic features of assessing the state of turbine equipment, which, in accordance with the concept developed, allow forming a matrix of planning a full factorial experiment. The proposed techniques and concepts were subjected to experimental verification. The intellectual diagnostic model of turbine unit equipment health was proposed, synthesized and investigated. It was found that the best model is the model, built using neuro-fuzzy algorithms. The simulation was provided for neuro-fuzzy algorithms and confirmed their effectiveness and compliance with the laws of the physical functioning of the HPC. The results of this research have been used in the development of Almaty CHP-2 turbine equipment health management subsystems, allow the further development of the theoretical foundations of intellectual systems, and demonstrate the possibility of using modern concepts to solve important technical problems. Subsystem of operative diagnosis and the following software implementation in a complex of automated technological process of thermal power control system allows one to make an early diagnosis of the equipment health. This significantly reduces the maintenance costs, improves reliability and security, as well as the effectiveness of the control system. In this regard, the results of this study provide further development of the theoretical foundations of the intellectual systems and demonstrate the possibility of modern concepts usage to determinate the important technical problems.

Experience in Operating the Condenser Ball-Cleaning System of the T-250/300-240 Power Generating Unit at the Minsk CHP-4

During its operation, the Minsk CHP-4 branch of Minskenergo RUE implemented many different measures to improve the technical and economic performance indicators and to increase the efficiency of both the installed turbine and boiler equipment and the plant as a whole. The device being used for cleaning condenser tubes by porous rubber balls is a preventive ecologically friendly means for maintaining a clean cooling surface of the condenser tube systems.

Hybrid power source based on heat and wind power plants

The technology of use of electric power of the wind power plants for direct replacement of fuel in the thermal cycles of the heat power plants is offered in the paper. The technology avoids solving the problems of ensuring the quality of electricity and the operational redundancy of the wind power in the power systems, as well as permits combining the achievements of traditional (gas turbine and steam and gas technologies, combined-cycle technologies and heating) and non-traditional renewable energy. The energy and environmental effects from the application of the proposed technology are shown, the technological advantages of the proposed schemes are considered, providing them with a wide scope of practical use both in local and in large power systems. The implementation and development of the proposed technology will allow extending and expanding business for manufacturers of steam turbine and gas turbine equipment, including the transition to the hydrogen power. The proposed technologies are protected by the patent.

The Ways to Improve the Efficiency of Binary Cogeneration Plant Operation by Use Additional of the Exit-Gas Heat Behind the Recovery Boiler

The exit-gas temperature behind the recovery boiler depends on the location, climate conditions, operation modes of the gas and steam turbine equipment at the combined-cycle cogeneration plant and can be slightly higher than the minimum admissible value. It leads to emergence of additional of exit-gas heat behind the recovery boiler. However the high-grade heat of the steam turbine extraction not only for own flows needs but also system water is used for heating. It reduces profitability of work of all power plants. The ways of use of the additional of the exit-gas heat behind the recovery boiler system water heating and chemically treated water of district heating makeup heating are offered. It leads to production the extra power by steam turbine and to improve the efficiency of binary combined-cycle cogeneration plant operation.

Ejectors of power plants turbine units efficiency and reliability increasing

The functioning of steam turbines condensation systems influence on the efficiency and reliability of a power plant a lot. At the same time, the condensation system operating is provided by basic ejectors, which maintain the vacuum level in the condenser. Development of methods of efficiency and reliability increasing for ejector functioning is an actual problem of up-to-date power engineering.In the paper there is presented statistical analysis of ejector breakdowns, revealed during repairing processes, the influence of such damages on the steam turbine operating reliability. It is determined, that 3% of steam turbine equipment breakdowns are the ejector breakdowns. At the same time, about 7% of turbine breakdowns are caused by different ejector malfunctions. Developed and approved design solutions, which can increase the ejector functioning indexes, are presented. Intercoolers are designed in separated cases, so the air-steam mixture can’t move from the high-pressure zones to the low-pressure zones and the maintainability of the apparatuses is increased. By U-type tubes application, the thermal expansion effect of intercooler tubes is compensated and the heat-transfer area is increased. By the applied nozzle fixing construction, it is possible to change the distance between a nozzle and a mixing chamber (nozzle exit position) for operating performance optimization.In operating conditions there are provided experimental researches of more than 30 serial ejectors and also high-efficient 3-staged ejector EPO-3-80, designed by authors. The measurement scheme of the designed ejector includes 21 indicator. The results of experimental tests with different nozzle exit positions of the ejector EPO-3-80 stream devices are presented. The pressure of primary stream (water steam) is optimized. Experimental data are well-approved by the calculation results.

Optimization of the operating conditions of gas-turbine power stations considering the effect of equipment deterioration

In recent years in most power systems all over the world, a trend towards the growing nonuniformity of energy consumption and generation schedules has been observed. The increase in the portion of renewable energy sources is one of the important challenges for many countries. The ill-predictable character of such energy sources necessitates a search for practical solutions. Presently, the most efficient method for compensating for nonuniform generation of the electric power by the renewable energy sources—predominantly by the wind and solar energy—is generation of power at conventional fossil-fuel-fired power stations. In Russia, this problem is caused by the increasing portion in the generating capacity structure of the nuclear power stations, which are most efficient when operating under basic conditions. Introduction of hydropower and pumped storage hydroelectric power plants and other energy-storage technologies does not cover the demand for load-following power capacities. Owing to a simple design, low construction costs, and a sufficiently high economic efficiency, gas turbine plants (GTPs) prove to be the most suitable for covering the nonuniform electric-demand schedules. However, when the gas turbines are operated under varying duty conditions, the lifetime of the primary thermostressed components is considerably reduced and, consequently, the repair costs increase. A method is proposed for determination of the total operating costs considering the deterioration of the gas turbine equipment under varying duty and start–stop conditions. A methodology for optimization of the loading modes for the gas turbine equipment is developed. The consideration of the lifetime component allows varying the optimal operating conditions and, in some cases, rejecting short-time stops of the gas turbine plants. The calculations performed in a wide range of varying fuel prices and capital investments per gas turbine equipment unit show that the economic effectiveness can be increased by 5–15% by varying the operating conditions and switching to the optimal operating modes. Consequently, irrespective of the fuel price, the application of the proposed method results in selection of the most beneficial operating conditions. Consideration of the lifetime expenditure included in the optimization criterion enables enhancement of the operating efficiency.

Application of synthetic fire-resistant oils in oil systems of turbine equipment for NPPs

Results of the investigation of the synthetic fire-resistant turbine oil Fyrquel-L state in oil systems of turbosets under their operation in the equipment and oil supply facilities of nuclear power plants (NPPs) are presented. On the basis of the analysis of the operating experience, it is established that, for reliable and safe operation of the turbine equipment, at which oil systems synthetic fire-resistant oils on the phosphoric acid esters basis are used, special attention should be paid to two main factors, namely, both the guarantee of the normalized oil water content under the operation and storage and temperature regime of the operation. Methods of the acid number maintenance and reduction are shown. Results of the analysis and investigation of influence of temperature and of the variation of the qualitative state of the synthetic fair-resistant oil on its water content are reported. It is shown that the fire-resistant turbine oils are characterized by high hydrophilicity, and, in distinction to the mineral turbine oils, are capable to contain a significant amount of dissolved water, which is not extracted under the use of separation technologies. It is shown that the more degradation products are contained in oil and higher acid number, the more amount of dissolved water it is capable to retain. It is demonstrated that the organization of chemical control of the total water content of fireresistant oils with the use of the coulometric method is an important element to support the reliable operation of oil systems. It is recommended to use automatic controls of water content for organization of daily monitoring of oil state in the oil system. Recommendations and measures for improvement of oil operation on the NPP, the water content control, the use of oil cleaning plants, and the oil transfer for storage during repair works are developed.

Mathema' cal model of varia' on of output opera' onal characteris' cs of steam turbines of thermal power plants

In this article we have studied the statistic materials for failures and malfunctions that aff ect the performance of heat power installations. This is a qualitative analysis and quantitative assessment of indicators of reliability of different turbine types. In the paper, there is presented a mathematical model of variation for output characteristics of a turbine depending on the number of failures observed in the course of operation. The mathematical model is based on methods of mathematical statistics, the probability theory and methods of matrix calculus. The novelty of this model lies in the fact that it allows predicting variation of control parameters and the output characteristic in an explicit form. The parameters that can be assumed as such characteristics are: average load, heat generation and electric power generation, running time, amount of time spent on emergency repair, number of staff participating in repair, cost of repair, income from sales of thermal and electric energy, availability quotient, probability of no-failure operation, etc. Based on the statistical data obtained at operation of steam turbines, quality and quantitative assessments of reliability indicators has been presented. Specific measures are suggested for elimination of causes of failures of components of turbines and turbine equipment. These are the failures of turbine blades caused by exhaustion of service life and extreme fatigue of metal that are accounted for the largest number of cases of damage and failure of turbines. Statistics of failures of bearings are affected by both internal and external factors of technical and operational nature. Damage of bearings and parts of rotors most often leads to unscheduled shutdown and repair of the turbine. The most common failures are those of the main oil pump and oil pipelines. According to statistical data, it is possible to develop appropriate measures for improvement of output characteristics. This is a so-called a model of management of output characteristic. For the purpose of management of the output characteristic, a probabilistic model taking into account the operating influences in an explicit form has been offered. A specific example of variation of turbines' output characteristics over a long-term period of operation has been given.

Принятие решений в условиях применения автоматизированных информационно-измерительных систем на ТЭС: опыт Челябинской ТЭЦ-2

We consider the problem of phased implementation of automated information-measuring systems at thermal power plants, economic efficiency of which is determined by their reliability, cost, volume, automated, errors of measurement, number of measuring channels, level of qualification and number of staff, as well as the impact on the performance of automated control systems and power equipment. The article formulates principles for decision-making in the application of automated information-measuring systems for thermal power plants based on the analysis of experience. In the first part of the review describes the experience of using workstations for electricity metering and registering of vibration condition of equipment and emergency situations. There are recommendations for the transition to the next stage of automation. In the second part of the review describes the experience of implementing a second stage of automation to account for the power and energy, technical diagnostics of turbine equipment and registration of emergency events. In the third part of the review we consider the problem of searching for invalid the loss of energy and technical diagnostics of measuring channels of automated information-measuring systems, as well as recommendations for the conduct of personnel policy. The recommendation is focused mainly on thermal power plants not equipped with full-scale automated control systems of technological processes.

Thermal Tests of LMS100 Gas-Turbine Units at the Dzhubga Thermal Power Plant

Test results at different loads and ambient temperatures for LMS100 PB gas-turbine units at the Dzhubga thermal power plant are discussed. The performance indicators for these gas turbine units and their turbine equipment, combustion chambers, and air cooling systems are determined. The gas-turbine units produce the design power (normally about 90 MW, and up to 95 – 99 MW when necessary) with a gross efficiency of 42.3 – 42.7% with moderate (no more than 20 – 35 mg/m3) atmospheric emissions of nitrogen oxides (under normal conditions). The differences in the performance of individual components of the gas-turbine units are within the limits of error in the measurements.

Monitoring wind farms occupying grasslands based on remote-sensing data from China’s GF-2 HD satellite—A case study of Jiuquan city, Gansu province, China

Monitoring wind farms occupying grasslands based on remote-sensing data from China’s GF-2 HD satellite—A case study of Jiuquan city, Gansu province, China

Representational Learning for Fault Diagnosis of Wind Turbine Equipment: A Multi-Layered Extreme Learning Machines Approach

Reliable and quick response fault diagnosis is crucial for the wind turbine generator system (WTGS) to avoid unplanned interruption and to reduce the maintenance cost. However, the conditional data generated from WTGS operating in a tough environment is always dynamical and high-dimensional. To address these challenges, we propose a new fault diagnosis scheme which is composed of multiple extreme learning machines (ELM) in a hierarchical structure, where a forwarding list of ELM layers is concatenated and each of them is processed independently for its corresponding role. The framework enables both representational feature learning and fault classification. The multi-layered ELM based representational learning covers functions including data preprocessing, feature extraction and dimension reduction. An ELM based autoencoder is trained to generate a hidden layer output weight matrix, which is then used to transform the input dataset into a new feature representation. Compared with the traditional feature extraction methods which may empirically wipe off some “insignificant’ feature information that in fact conveys certain undiscovered important knowledge, the introduced representational learning method could overcome the loss of information content. The computed output weight matrix projects the high dimensional input vector into a compressed and orthogonally weighted distribution. The last single layer of ELM is applied for fault classification. Unlike the greedy layer wise learning method adopted in back propagation based deep learning (DL), the proposed framework does not need iterative fine-tuning of parameters. To evaluate its experimental performance, comparison tests are carried out on a wind turbine generator simulator. The results show that the proposed diagnostic framework achieves the best performance among the compared approaches in terms of accuracy and efficiency in multiple faults detection of wind turbines.