thermal Power Plant

Abstract: The present paper deals with the opportunities for the modeling of flue gas and air system of a thermal power plant by making the performance evaluation using probabilistic approach. The present system of thermal plant under study consists of four subsystems with three possible states: full working, reduced capacity working and failed. Failure and repair rates for all the subsystems are assumed to be constant. Formulation of the problem is carried out using Markov Birth-Death process using probabilistic approach and a transition diagram represents the operational behavior of the system. Interrelationship among the full working and reduced working states has been developed. A probabilistic model has been developed, considering some assumptions. Data in feasible range are selected from a survey of thermal plant and the effect of each subsystem on the system availability is tabulated in the form of availability matrices, which provides various performance/availability levels for different combinations of failure and repair rates of all subsystems. Based upon various availability values obtained in availability matrices and graphs of failure/repair rates of different subsystems, performance and optimum values of failure/repair rates for maximum availability, of each subsystem is analyzed and then maintenance priorities are decided for all subsystems.

As a new control method, internal mode control(IMC) was formally proposed by Garica and Morariin[1] in 1982. Rivera[2] first introduced the idea of IMC into the design of PID controller, and established the relationship between the filter parameters and PID controller parameters. Then more and more scholars tried to design PID controller using IMC principle[3][4][5].Compared with classical PID control[6], the structure of the IMC-PID controller was simple, and there was only one setting parameter. With the continuous development and improvement of IMC, the conventional IMC method has been developed to the intelligent control method. Many scholars combined IMC with adaptive control[7][8], fuzzy control[9], neural network[10] and so on, which had certain advantages in the control of complex process. Truong Nquyen Luan Vu and Le Hien Giang[11] had proved that IMC-PID controller can be applied to first-order and time-delay process, and it had certain robustness.Liang Wei-Ping,Ge Xiao-Jing[12] studied a fuzzy algorithm control system based on IMC, which can adjust the proportional coefficient of IMC-PID controller online.in order to improve the system robustness and control performance, Zhi-cheng Zhao[13]andYing -ming Li[14] both presented an adaptive IMC-PID control scheme based on neural network, through neural network self-learning to adjust the parameters of the IMC - PID controller, . In reference[15], the design of a fractional order proportional integral differential controller was proposed. Although satisfactory results were obtained, the output was still undamped and there were many parameters need to be optimized. Bayu Jayawardhana,Hartmut Logemann and Eugene P.Ryan[16] presented a kind of PID control of second-order systems with hysteresis for constant reference signal asymptotic tracking and constant interference signal suppression.But the satisfactory robustness can not be obtained.Zhao and Wang[17] presented that use IMC-PID to control the superheated steam pressure.PID controller is still the most widely used controller in thermal power plant.Alberto Leva[18] introduced the performance and robustness improvement in the IMC-PID tuning method.In addition, the IMC-PID controller can be designed based on different algorithms,such as NPSO algorithm[19],LMI algorithm[20],Novel Bat algorithm[21] and so on.In summary, the IMC-PID

For conservation of fuel it is required to carry out energy audit of thermal power plant otherwise scarcity of fuel in future occurs. Pains taking task work with rMany people’s had done the works on performance of thermal power plant according to the equipment based. But system based work hadn’t found for auditing the thermal power plant. There is potential of energy conservation on the basis of system based audit. The thermal power plant mainly consists of following systems

This paper discusses safety performance rating by quantitative monitoring in the thermal power plant during previous seven years, from 1st April 2007 to 31st March 2014. Safety performance measurement is a crucial part of achieving efficiency in continuous improvement, with the help of this quantitative monitoring method we have calculated frequency rate, severity rate, incident rate, disabling rate, safe activity rate and also calculated safe T score for 2007-08 (-0.70010),2008-09(1.364),2009-10(- 0.2665),2010-11(10.358), 2011-12( 3.9086), 2012-13(- 1.20609) and 2013-14(-0.6855). After calculation of all this safety performance status is cleared, because when we got the negative value of Safe-T-Score (Less than -2) that time the record is improved as compared to with the past. In the year of 2007-08 and 2009-10 the safety performance record is improved than it was in the past. Something better things have happened. So with help of this quantitative monitoring we can say the safety performance was good but management should try to make safety measures status better or improved. In the safety monitoring various elements are there like safety rating, safety policy, safety organization, safety committee, planning and implementation, safety audit, safety sampling, safety survey etc.They are helpful in minimizing the work place hazards, control the accident, and occupational diseases. Including the quantitative safety monitoring in industry many accidents, hazards and occupational diseases are reduced, it can provide information to each and every worker about the various hazards in the workplace and provide the good solutions for controlling those hazards. Providing proper training and motivation to the every employer to identify and control hazards and there may be a provision for punishment for wrong work.

Gas turbine power plant performance is affected by several factors. These factors could be environmental (ambient temperature, humidity); internal (poor maintenance, load type); or external factors (gas supply, labour strikes, acts of terrorism or war, acts of nature, grid/substation failure). All these factors together affect the output from a generating plant. The plant management only has control over the internal factors while the environmental and external factors are outside the control of plant management. In improving a system, there must first be a way to measure its current performance, compare it with the expected performance level, and then recommend it for improvement either in part or wholly if it is found to be performing below the expected output. In evaluating the performance of Alaoji thermal power plant, the following standard performance indices will be adopted: Capacity Factor (CF), Load factor (LF), Availability Factor (AF) and Plant Use Factor (PUF).

All good engineering design starts with a clear understanding of the project’s needs, budgetary constraints, material constraints, performance tolerances, and criteria for judging the effectiveness and success of the final product. Once all of these design specifications are clearly understood, the process of actually designing the product may begin. (Note that in the “real world” any or all of these specifications usually change many times throughout the design process. For Design of Solar Thermal power plant we will clearly define but are likely to change during we work on the project.) One possible approach to producing a solar power plant would be to design and build an actual power plant prototype, within the limits of the design criteria.

Caspian Sea, in the north of Iran with total power generation capacity of 2170 MW. The power plant capacity was enhanced and expanded in 2000s with dual gas modern gas turbines with capacity of 270 MW. Also the plant is benefited by a combined cycle unit, combination of gas and steam turbine cycles for electric power generation with highest efficiency and capacity of 140 MW. This thermal power plant consists of 4 thermal units, each has power generation capacity of 440 MW, with 4 concrete type stack gas chimney of 134 m height. The major combustion fuels are dark fuel oil (Fuel no. 6 and Mazout) and natural gas. The standard heat of combustion for the fuel oil is known as heating value of the fuel that is about 39700 Btu/kg and for natural gas 42500 Btu/m 3 [23]. Since there is shortage of natural gas in cold season, the plant may depend mostly on fossil fuel. The number 6 fuel oil is a complex blend of hydrocarbons derived from various refinery streams, usually residues, and can contain small amount of hydrogen sulfide. Typical streams include atmospheric tower bottoms, vacuum tower bottoms, catalytically cracked gas oil, slurry oil and acid soluble oil. The composition is complex and varies with the source of crude oil. This kind fuel is combustible at high temperature with auto- ignition temperature of 315.59°C (600.1°F), Flash point of higher than 60°C (140°F). The products of combustion are carbon oxides (CO, CO 2 ), nitrogen

As the large change of the grid load, many large capacity units of our country had to change the load in order to meet the gird need. When a thermal power plant receives a given load instruction from the grid, it is necessary to set an opti- mal steam pressure to maintain the high efficiency of the plant. In the past optimization methods, during the process of calculation, the output of the turbine often changed, it was hard to maintain the output constant. Therefore, in combina- tion with the theory of variable condition of turbine, calculation of governing stage and the matrix equation of thermal power system, an optimization method were put forward and an optimal solution was got in a given load.

Abstract— Noise is defined as any unwanted sound that you do not need or want to hear. Loud noise can also create physical and psychological stress, reduce productivity, interfere with communication and concentration, and contribute to workplace accidents and injuries by making it difficult to hear warning signals. There are number of locations in every old Thermal Power Plant who is responsible to create noise. Different Coal based Thermal Power Plants were selected from the decade 1980 to 2011. In thermal power plant, most of the section can create high decibel noise i.e. 90 dB to 95 dB and it is hazardous to human health. Sound becomes undesirable when it disturbs the normal activities such as working, sleeping, and during conversations it can also cause memory loss, severe depression, and panic attacks. ISO 1999 standard describes a model for the prediction of the distribution of the hearing loss at a given frequency, in a population of a given age, after a certain number of years of exposure to a LEX, 8h level. Use of a three Level risk scale provides guidance for the assessment of the Level of risk. Level 1- Daily noise exposure level definitely below 80 dB (A), which has a minimal risk of noise induced hearing loss.

The study included monitoring of pilot Project installed at NTPC Simhadri Visakhapatnam thermal power plant. The detail of SCR model installed at selected power plant where continuous monitoring for 15 days was performed are mentioned in different sections of this research paper. From the experiment the maximum efficiency and the minimum efficiency are depicted in the work also the efficiencies with respect to the temperature fields were also recorded and it was found that the complete setup experiment did not have any effect on sulphur oxides and only the oxide of nitrogen was calibrated hence other techniques can also be further implemented other than SCR technique.

Energy auditing of a thermal power plant involves the study of boiler system, electrical system, pumping system, air compressor system, cooling towers, auxiliaries power con- sumption etc. This project analyses the performance assess- ment of Boiler system, cooling tower of a 500MW KO- THAGUDEM thermal power plant.

V Milind S. Mankar et, al describes a systematic approach to predict of nitrogen oxides emission from 270 MW coal fired thermal power plant with the help of artificial neural network. The NO formation mechanism and NOx emission control techniques also describe. The oxygen concentration in flue gas, coal properties coal flow, boiler load, air distribution scheme, flue gas outlet, temperature and nozzle tilt were investigated through field experiment. The predicted values of ANN model for different load condition were verified with the actual values. These parameters help us to ensure to complete combustion and less emission with increased boiler life.[12]

ABSTRACT: Now a day’s one of the critical issues in a thermal power plant is to improve the efficiency of individual equipment. The various works found in literature shows that efficiency and availability depends on high reliability and maintainability of the equipments. But in present scenario with the concept of e– maintenance reduces the overall maintenance cost. The use of intelligent fault detection systems plays an important role for fault diagnosis and supervision in process control. Artificial intelligent applications in process control helps in timely detection, diagnosis and correction of abnormal operating condition in the thermal power plants. When the plant is in operating condition and within controllable region, detection and diagnosis of process faults at very early stage improves overall efficiency of operation.

Site selection is a vital issue that must be analyzed deeply in order to have efficient power Generation from technical and economic point of view without damaging environment and Society. Selection of unsuitable location for power plant will lead to increased costs, waste of energy and resources, and increased environmental pollution, which has a tremendous negative impact on society. Therefore, it is required to analyze any location before the installation of power plant. So, this paper tries highlighting the main factors which helps in the Selecting the location of Thermal Power Plant.

Monetary value of the non-Structural equipments located on the industrial buildings is usually much higher than the value of the structure itself, specially, if the performance criteria is for the immediate occupancy of the plant. In this project, seismic Vulnerability of the non -structural equipments Located on the main control buildings of Hamedan thermal power plant was investigated by the qualitative and quantitative methods. Hamedan thermal power plant is located in a region with high seismic risk on the North-west of Iran. This power plant with a generation capacity of 1000 megawatts plays an important role in the power generation network of the nation. Its construction began at 1991 and official date of operation has been since 1997. This plant includes several parts namely; boilers, turbine halls, stack, control buildings, water treatment

The circulation of water and steam is carried out with the help of the pump11. The working substance exits out of the gas chamber of the steam boiler through the pipeline 23 and is being conveyed onto the input of the gas heater 24. In such a way the primary heat circuit , in which argon circulates, is being closed. The turbo unit of thermal power plant consists of a turbogenerator 12 on one side of which (on shaft) a gas turbine and on the other side a steam turbine 2 are located, in much the same way how it was carried out by firm „Siemens” and is shown at Fig. 1. It shall be noted that the heat schema of power plant consists out of components, which are being widely used nowadays in industrial energetics. The new components are MHD AC generator 25 and the gas heater 24.

This paper analyzes main legal requirements for thermal power plants in China, which is intended to save energy and reduce discharge by restricting coal consumption for power generation. However, based on our four cases of the selec- tion of thermal power plant construction proposals, which provide the ideal contrast of two different regulation circum- stances, we find that state-owned firms, which strictly follow the regulations, cannot realize the efficient use of energy and capital. In contrast, private firms, which are more able to follow the principle of profit maximization and dare to breach the regulation policy, can realize the efficient use of energy and capital. Then using the fixed-ratio production function, this paper suggests regulation not only results in energy and capital waste, but also employment opportunity loss. Expanding this conclusion, this paper proposes that the more regulation, the more employment opportunity loss. Therefore, if the government can deregulate the regulated sectors, more labor can be combined with the capital of new entrants, and the income distribution will be more equitable.

electricity produced throughout the world is from steam power plants. Therefore, it is very important to ensure that the plants are working with maximum efficiency. Thermodynamic analysis of the thermal power plant has been undertaken to enhance the efficiency and reliability of steam power plants. Most of the power plants are designed by the energetic performance criteria based on first law of thermodynamics only. The real useful energy loss cannot be justified by the fist law of thermodynamics, because it does not differentiate between the quality and quantity of energy. The present work deals with the comparison of energy and exergy analysis of thermal power plant stimulated by coal. Generally, it is predicted that even a small improvement in any part of the plant will result in a significant improvement in the plant efficiency. Factors affecting efficiency of the Thermal Power Plant have been identified and analyzed for improved working of thermal power plant.

Abstract: A nonlinear gain scheduling control strategy is proposed for a concentrated solar thermal power plant. The strategy involves the identification of local linear time-invariant state space models around a family of operating points, the design of corresponding local linear dual mode model-based predictive controllers and the selection of an appropriate scheduling variable to govern the switching. The local models are estimated directly from input-output data using a subspace identification method while taking into account the frequency response of the plant. Input-output data are obtained from a nonlinear simulation model of the plant rather than the plant itself. The effectiveness of the proposed control strategy in terms of tracking and disturbance rejection is evaluated through two different scenarios created in a nonlinear simulation environment.

Sub cooling would increase the heat input in the steam generator, and on the other hand, the introduction of steam into the pump would cause poor performance. The properties of the pump inlet or condenser exit (state 3 in Figure 3) therefore, may be obtained directly from the saturated-liquid curve at the (usually) known condenser pressure. The properties for an isentropic pump discharge at state 4 could be obtained from a sub cooled-water property table at the known inlet entropy and the throttle pressure. However, such tables are not widely available. The enthalpy of a sub cooled state is commonly approximated by the enthalpy of the saturated-liquid evaluated at the temperature of the sub cooled liquid. This is usually quite accurate because the enthalpy of a liquid is almost independent of pressure as the Rankine cycle based thermal power plant works at atmospheric pressure.