scholarly journals Investigation on Slagging Fouling Potential in Coal Blending for PLTU with PC Boiler with Droptube Furnace Method

2021 ◽  
Vol 2 ◽  
pp. 28-40
Author(s):  
Hariana Hariana ◽  
Fairuz Milkiy Kuswa ◽  
Dani Rudiana ◽  
Lan Marakkup Tua Naingolan
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
Xrd Analysis ◽  
Drop Tube ◽  
Acceptable Risk ◽  
Drop Tube Furnace ◽  
Design Specifications ◽  
Initial Design ◽  
Direct Testing ◽  
Coal Blending

The majority of power plants in Indonesia are Coal-Fired Power Plants (PLTU) which using coal as the main fuel. The coal used in the PLTU is coal that has been adjusted to the existing PLTU design. However, coal availability according to the initial design of the PLTU is running low and even almost non-existent. If the coal does not meet the PLTU design specifications is forced to be used as fuel, various problems will arise regarding to the capability and reliability of the power plant itself. Therefore, looking for coal alternatives that have similar specifications to the PLTU design is very important, to get these alternatives can be done by Blending coal from various specifications. The Blending product must be evaluated from various aspects, one of which is slagging and fouling. This research will focus on the aspects of slagging fouling resulting from the Blending of two different coals in terms of characteristics and specifications. Evaluation is carried out by taking samples and tested to make predictions based on AAS and AFT, burning in the Drop Tube Furnace (DTF), and performing SEM and XRD analysis of two coal Blending products. The results obtained are that the A and B Blending products are in an acceptable risk for direct testing on a larger scale (PLTU) or boiler simulator. However, Blending A has a greater potential for further research than Blending product B.

scholarly journals Ash Evaluation of Indonesian Coal Blending for Pulverized Coal-Fired Boilers

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Hariana ◽  
Adi Prismantoko ◽  
Ganda Arif Ahmadi ◽  
Arif Darmawan
Keyword(s):  
Power Plants ◽  
Calorific Value ◽  
Pulverized Coal ◽  
Tube Furnace ◽  
Low Rank ◽  
Drop Tube ◽  
Chemical Additives ◽  
X Ray ◽  
Drop Tube Furnace ◽  
Coal Blending

Coal calorific value is one of the main considerations for using coal as a power plant fuel. In addition, the requirements for indications of slagging and fouling are also important to maintain combustion efficiency. However, coal power plants often experience problems in boiler operations due to the use of certain types of coal, even though they have a relatively high calorific value. This research investigates the effect of coal blending on ash fouling and slagging in an experimental investigation using a drop tube furnace with or without additives. Five different types of coal from different locations have been used in this study. Pulverized low-rank coal samples are burned in a drop tube furnace at 1,175°C with probe temperatures of 550°C and 600°C, corresponding to the combustion chamber of 600 MW power plants, including superheater and reheater areas. The ash particles’ characteristics and material composition were also analyzed using scanning electron microscopy with energy-dispersive X-ray (SEM-EDX) and X-ray diffraction (XRD), respectively. All coal mixture combinations demonstrated potential as a fuel for power plants that use pulverized coal-fired boilers. Because of its capacity to reduce slagging and fouling potentials, combining coal blending with the use of chemical additives yielded the greatest results.

Effects of Mineral Transformations on the Reduction of PM2.5 during the Combustion of Coal Blends

2011 ◽  
Vol 356-360 ◽  
pp. 1306-1314 ◽  
Author(s):  
Ming Jun Ji ◽  
Yoshihiko Ninomiya ◽  
Zhong Bing Dong ◽  
Qun Ying Wang
Keyword(s):  
Electron Microscopy ◽  
Power Plants ◽  
Chemical Species ◽  
Drop Tube ◽  
Transmission Electron ◽  
Coal Blending ◽  
Mineral Compositions ◽  
Parent Coal ◽  
Mineral Transformations

Two chinese bituminous coals used in coal-fired power plants are combusted under air conditions in a lab-scale drop tube furnace. The effects of minerals transformation on the formation of PM 2.5 are investigated during the combustion of coal blends. The collected PM were subjected to Computer controlled scanning electron microscopy (CCSEM) and High-resolution transmission electron microscopy(HRTEM) coupled with energy dispersive X-ray spectroscopy (EDX) analysis for determination of chemical species within them. The results show that PM 2.5 emissions are not linearly related to the wt.% of the parent coal or coal blends. Transformations of fine Si-Al mineral grains provided by the minerals in coal XQ into coarse particles (>2.5 μm in diameter) are responsible for the reduction of PM1-2.5 during the combustion of coal blending. The transformed fine Si-Al particles are captured by the coarse Ca-Mg-Al-Si provided by the minerals in coal HT to form larger Ca-Mg-Al-Si particles (>2.5 μm in diameter). Increasing Ca and Mg concentration in coal blends enhances the liquid concentration produced during combustion and hence affects the emissions of PM1 and PM1-2.5.Through adjusting the mineral compositions in coal blends, the reduction of PM1 and PM1-2.5 emissions can be achieved during combustion.

Study and Application of Two-Level Optimization of Coal Blending for Power Plant Based on On-Line Coal Identification

2011 ◽  
Author(s):  
Ji Xia ◽  
Peng Peng ◽  
Cheng Zhang ◽  
Tao Yang ◽  
Gang Chen
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
Thermal Power ◽  
Time Lag ◽  
Utilization Rate ◽  
Coal Blending ◽  
Sensing Model ◽  
On Line ◽  
Blended Coals ◽  
The Heat Balance

In china, many thermal power plants have to burn blended coals forced by the complexity of coal type and market tension and transportation pressure of coal purchasing. As a engineering implementation method of coal blending, “different coals grinding in different mills and then mixed burning in the furnace” has many advantages such as low investment, easy to control milling system parameters and can be optimized online, etc, compared with traditional coal blending methods. But it is limited by the number of mills and cannot achieve high-precision ratio of blending. To remedy this shortcoming, a model of two-level optimization of coal blending for the thermal power plant with direct blowing pulverizing system was established in this paper. The tradional coal blending was regarded as first step of optimization. The secondary optimization was implemented by adjusting the outputs of different mills, then the blend was changed to accurate ratio. Furthermore, since the existence of coal bunker, it made a time lag from coal discharge to combustion, meanwhile, the real-time load was unpredictable and the coal utilization rate was inconsistent of each bunker. The three reasons make it uncertain of the current coal of bunker. To identify each coal in the mill(equivalent to bunker) correctly was the basis of achieving the second blending optimization. Therefore, a soft-sensing model of coal moisture based on the heat balance equation was used to take this work. At last, a intelligent coal blending system by the two-level optimization model was developed for a power plant and achieved good results.

scholarly journals Coal blending selection for CFPP fuel with slagging fouling prediction and procurement cost calculation

2021 ◽  
Vol 882 (1) ◽  
pp. 012030
Author(s):  
Hariana ◽  
H P Putra ◽  
A A Raksodewanto ◽  
Enjang ◽  
F M Kuswa ◽  
...  
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
Low Rank ◽  
Cost Calculation ◽  
Technical Requirement ◽  
Operation Condition ◽  
Technical Aspects ◽  
Blending Method ◽  
Coal Blending ◽  
Procurement Cost

Abstract Most coal-fired power plants in Indonesia use medium and low-rank coal due to coal availability in the domestic coal market. Because of technical and economic reasons, single coal as fuel is rarely used in coal-fired power plants. Therefore the coal blending method is used. Here, the most dominant technical requirement of a coal-fired power plant is the calorific value and potential of slagging and fouling. For this reason, a selection method that involves the technical aspect of coal and coal procurement cost is carried out. This study found that from 42 types of alternative coal blend made, 18 types fulfill the potential of slagging and fouling criteria. 12 type coal blends could be prioritized as the main alternative because they fulfilled all technical aspects and coal procurement costs. The conclusion obtained from this study is the completion of the search for alternative coal blends based on technical aspects, especially slagging and fouling and procurement cost, to effectively obtain blending priority. This method can be developed for different coal-fired power plant technology and operation condition.

Influence of Coal Blending Methods on Unburned Carbon and NO Emissions in a Drop-Tube Furnace

2011 ◽  
Vol 25 (11) ◽  
pp. 5055-5062 ◽  
Author(s):  
Byoung-hwa Lee ◽  
Seoung-gon Kim ◽  
Ju-hun Song ◽  
Young-june Chang ◽  
Chung-hwan Jeon
Keyword(s):  
Tube Furnace ◽  
Unburned Carbon ◽  
Drop Tube ◽  
Drop Tube Furnace ◽  
Coal Blending ◽  
No Emissions

A New Method for Determining Pulverized Coal Economic Fineness

2013 ◽  
Vol 441 ◽  
pp. 1072-1076
Author(s):  
Xiao Bin Huang ◽  
Pei Chao Zhang ◽  
Long Fei Liang
Keyword(s):  
Power Plant ◽  
Ignition Temperature ◽  
Power Plants ◽  
Thermal Power ◽  
Combustion Efficiency ◽  
Pulverized Coal ◽  
New Method ◽  
Thermal Power Plants ◽  
Coal Blending ◽  
The Relationship

Coal blending technology is commonly used in coal-fired thermal power plant in recent years to ease cost pressures. But thermal power plants still use empirical formula to determine the economic fineness of pulverized coal. This approach cannot change economic fineness of pulverized coal based on the proportion of blending coal timely and accurately, resulting in increasing carbon content of fly-ash and reduced combustion efficiency of boiler. In this paper, a new method for determining pulverized coal economic fineness is proposed. Dry ash-free basis volatile, coal uniformity index, ignition temperature, proportion of blending coal are considered as parameters. According to the relationship between these parameters, the best coal fineness can be obtained in real-time. Influences of coal blending technology are reduced greatly and the accuracy of the economic fineness is improved.

Fuzzy multi-objective decision making approach for nuclear power plant installation

2020 ◽  
Vol 39 (5) ◽  
pp. 6339-6350
Author(s):  
Esra Çakır ◽  
Ziya Ulukan
Keyword(s):  
Linear Programming ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Energy Supply ◽  
Energy Demand ◽  
Nuclear Power ◽  
Power Plants ◽  
Total Duration ◽  
Objective Functions ◽  
Multi Objective

Due to the increase in energy demand, many countries suffer from energy poverty because of insufficient and expensive energy supply. Plans to use alternative power like nuclear power for electricity generation are being revived among developing countries. Decisions for installation of power plants need to be based on careful assessment of future energy supply and demand, economic and financial implications and requirements for technology transfer. Since the problem involves many vague parameters, a fuzzy model should be an appropriate approach for dealing with this problem. This study develops a Fuzzy Multi-Objective Linear Programming (FMOLP) model for solving the nuclear power plant installation problem in fuzzy environment. FMOLP approach is recommended for cases where the objective functions are imprecise and can only be stated within a certain threshold level. The proposed model attempts to minimize total duration time, total cost and maximize the total crash time of the installation project. By using FMOLP, the weighted additive technique can also be applied in order to transform the model into Fuzzy Multiple Weighted-Objective Linear Programming (FMWOLP) to control the objective values such that all decision makers target on each criterion can be met. The optimum solution with the achievement level for both of the models (FMOLP and FMWOLP) are compared with each other. FMWOLP results in better performance as the overall degree of satisfaction depends on the weight given to the objective functions. A numerical example demonstrates the feasibility of applying the proposed models to nuclear power plant installation problem.

Human reliability in non-destructive inspections of nuclear power plant components: modeling and analysis

2019 ◽  
Vol 7 (2B) ◽  
Author(s):  
Vanderley Vasconcelos ◽  
Wellington Antonio Soares ◽  
Raissa Oliveira Marques ◽  
Silvério Ferreira Silva Jr ◽  
Amanda Laureano Raso
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Human Factors ◽  
Nuclear Power ◽  
Power Plants ◽  
Failure Modes ◽  
Cooling System ◽  
Human Reliability ◽  
Non Destructive ◽  
Plant Components

Non-destructive inspection (NDI) is one of the key elements in ensuring quality of engineering systems and their safe use. This inspection is a very complex task, during which the inspectors have to rely on their sensory, perceptual, cognitive, and motor skills. It requires high vigilance once it is often carried out on large components, over a long period of time, and in hostile environments and restriction of workplace. A successful NDI requires careful planning, choice of appropriate NDI methods and inspection procedures, as well as qualified and trained inspection personnel. A failure of NDI to detect critical defects in safety-related components of nuclear power plants, for instance, may lead to catastrophic consequences for workers, public and environment. Therefore, ensuring that NDI is reliable and capable of detecting all critical defects is of utmost importance. Despite increased use of automation in NDI, human inspectors, and thus human factors, still play an important role in NDI reliability. Human reliability is the probability of humans conducting specific tasks with satisfactory performance. Many techniques are suitable for modeling and analyzing human reliability in NDI of nuclear power plant components, such as FMEA (Failure Modes and Effects Analysis) and THERP (Technique for Human Error Rate Prediction). An example by using qualitative and quantitative assessesments with these two techniques to improve typical NDI of pipe segments of a core cooling system of a nuclear power plant, through acting on human factors issues, is presented.

Nonlinear Trend Analysis of Mill Fan System Vibrations for Predictive Maintenance and Diagnostics

2012 ◽  
Vol 58 (4) ◽  
pp. 351-356
Author(s):  
Mincho B. Hadjiski ◽  
Lyubka A. Doukovska ◽  
Stefan L. Kojnov
Keyword(s):  
Power Plant ◽  
Trend Analysis ◽  
Thermal Power Plant ◽  
Power Plants ◽  
Thermal Power ◽  
Balkan Peninsula ◽  
Predictive Maintenance ◽  
Nonlinear Trend ◽  
The Subject ◽  
The Given

Abstract Present paper considers nonlinear trend analysis for diagnostics and predictive maintenance. The subject is a device from Maritsa East 2 thermal power plant a mill fan. The choice of the given power plant is not occasional. This is the largest thermal power plant on the Balkan Peninsula. Mill fans are main part of the fuel preparation in the coal fired power plants. The possibility to predict eventual damages or wear out without switching off the device is significant for providing faultless and reliable work avoiding the losses caused by planned maintenance. This paper addresses the needs of the Maritsa East 2 Complex aiming to improve the ecological parameters of the electro energy production process.

Visualization of Aviation Fluid Droplets At High Temperatures In A Drop Tube Furnace

2013 ◽  
Author(s):  
Vignesh Venkatasubramanian ◽  
Jingran Duan ◽  
Stephen A. Giles ◽  
Steve R. Duke ◽  
Ruel Overfelt
Keyword(s):  
High Temperatures ◽  
Tube Furnace ◽  
Drop Tube ◽  
Drop Tube Furnace
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