Comparing Boiler Efficiency Calculation Methods

2011 ◽  
Author(s):  
David A. T. Rodgers ◽  
Timothy Golightly ◽  
Marc E. Lemmons ◽  
William C. Stenzel ◽  
Fred D. Lang
Keyword(s):  
Energy Balance ◽  
Test Data ◽  
Test Methods ◽  
Calculation Methods ◽  
Energy Balance Method ◽  
Efficiency Calculation ◽  
Boiler Efficiency ◽  
Calculation Methodology ◽  
Loss Method ◽  
San Rafael

This paper compares two methods for calculating boiler efficiency using test data obtained from the Boardman Coal Plant. The two test methods are ASME PTC 4’s Energy Balance Method as evaluated by Sargent & Lundy LLC, Chicago, IL, and the Input/Loss Method as evaluated by its owner, Exergetic System Inc., San Rafael, CA. The differences in methods are fundamental: varying in basic definitions of boiler efficiency and calculation methodology.

Determination of Fuel Input for a Coal Fired Plant Performance Test

2009 ◽  
Author(s):  
H. Jin
Keyword(s):  
Energy Balance ◽  
Heat Loss ◽  
Steam Generator ◽  
Heat Input ◽  
Short Form ◽  
Fuel Efficiency ◽  
Balance Method ◽  
Plant Performance ◽  
Energy Balance Method ◽  
Loss Method

In applying ASME PTC 46 “Overall Plant Performance” to a coal-fired steam plant, it is mandated that the heat input to the plant is determined by the product of heat input to the steam and the inverse of the steam generator fuel efficiency. Steam generator fuel efficiency is to be determined, per PTC 46, by the energy balance method as detailed in ASME PTC 4 “Fired Steam Generators”. ASME PTC 4 (1998) superseded an earlier Code, ASME PTC 4.1, which is no longer an ANSI standard or an ASME Code (as this paper was being written, PTC 4- 2008 has been published as a revision of PTC 4-1998). PTC 4.1 made use of a simplified “short form” to determine efficiency by what was known as the heat loss method, used by the industry for many years due to its ease of use. The energy balance method is fundamentally different from the heat loss method even in terms of the definition of efficiency and heat input. This paper explores the major differences between the two PTC’s (the defunct PTC 4.1 and PTC 4). Without knowing these differences, a direct comparison of PTC 4 and PTC 4.1 results is meaningless and could lead to false conclusions.

scholarly journals THERMAL LOSSES EVALUATION IN 660 MW COAL-FIRED POWER PLANT USING INDIRECT EFFICIENCY METHOD

2021 ◽  
Vol 19 (01) ◽  
Author(s):  
Muhammad Rizaldi Zaman ◽  
Nazaruddin Sinaga
Keyword(s):  
Energy Balance ◽  
Power Plant ◽  
Heat Loss ◽  
Performance Testing ◽  
Standard Test ◽  
Performance Evaluations ◽  
Efficiency Evaluation ◽  
Performance Tests ◽  
Energy Balance Method ◽  
Boiler Efficiency

Boilers are one of the main equipment in the PLTU apart from turbines and generators. Each year there must be a difference in the actual boiler efficiency value with the conditions during commissioning. Periodically, boiler performance evaluations are carried out in order to identify losses from several factors. In this study, the method used for evaluation is the energy balance method. During the experiment, the standard test guide (ASME PTC - 4) was used. The boiler under test has a capacity of 660 MW. Evaluation is done by comparing the boiler efficiency value at the time of commissioning with the latest performance tests. From the results of performance testing, it is known that the decrease in boiler efficiency when compared with the commissioning results from 86.92% to 82.625%. The reduction in boiler efficiency is due to an increase in heat loss due to dry gas, hydrogen content in coal, and incomplete combustion.Keywords: boiler, efficiency, evaluation, reduction, performance

Dynamics research of Fangzhu’s nanoscale surface

2021 ◽  
pp. 146134842110527
Author(s):  
Pinxia Wu ◽  
Weiwei Ling ◽  
Xiumei Li ◽  
Xichun He ◽  
Liangjin Xie
Keyword(s):  
Energy Balance ◽  
Analytical Solutions ◽  
Numerical Experiments ◽  
Fractal Model ◽  
Balance Method ◽  
Transform Method ◽  
Energy Balance Method ◽  
Collection Rate ◽  
Fractal Derivative ◽  
Approximate Analytical Solutions

In this paper, we mainly focus on a fractal model of Fangzhu’s nanoscale surface for water collection which is established through He’s fractal derivative. Based on the fractal two-scale transform method, the approximate analytical solutions are obtained by the energy balance method and He’s frequency–amplitude formulation method with average residuals. Some specific numerical experiments of the model show that these two methods are simple and effective and can be adopted to other nonlinear fractal oscillators. In addition, these properties of the obtained solution reveal how to enhance the collection rate of Fangzhu by adjusting the smoothness of its surfaces.

scholarly journals Analisa Keseimbangan Energi PLTU Takalar (Punagaya) Unit 2 Berdasarkan Perubahan Beban

2021 ◽  
Vol 18 (2) ◽  
pp. 257
Author(s):  
Makmur Saini ◽  
Nur Hamzah ◽  
Devi Prasetyo Utomo
Keyword(s):  
Energy Balance ◽  
Energy Loss ◽  
Heat Rate ◽  
Electrical Energy ◽  
Optimal Operation ◽  
Steam Power ◽  
Energy Balance Method ◽  
Full Load ◽  
Operation Pattern ◽  
Operating Target

This study aims to calculate the efficiency and heat rate of the unit 2 PLTU Takalar (Punagaya) system with the energy balance calculation method, calculate the NPHR value of PLTU Takalar (Punagaya) unit 2 when the unit is operating, and also to determine the energy loss from the conversion energy results at PLTU Takalar (Punagaya) unit 2 when the unit operates. The PLTU's Net Plant Heat Rate (NPHR) value is a very important role as an indicator of the performance of a steam power plant. The real-time NPHR value calculation using the energy balance method can be used as an evaluation material to control the operation pattern of the generator in order to obtain optimal operation. The method used in this research is to collect direct and indirect data to calculate the energy balance and NPHR of PLTU Takalar (Punagaya) unit 2 during the reliability run period. The calculations carried out include the calculation of the energy balance in the boiler, the energy balance in the steam cycle, the balance of electrical energy, the efficiency of the PLTU and NPHR systems. Based on the results of calculations that have been carried out the efficiency and NPHR of PLTU Takalar (Punagaya) unit 2 is the best during the reliability run of 32.76% and 2801.93 kcal / kWh at full load conditions with an energy loss value of 220.60 MW. The performance of PLTU Takalar (Punagaya) unit 2 during the reliability run is very good where the unit operates continuously and the NPHR value when full load fulfills the contract warranty and the maximum operating target. 

scholarly journals Gas System for the ATLAS NSW Micromegas Detectors: Design Aspects and Advanced Validation Methods for their QA/QC

2019 ◽  
Vol 24 ◽  
pp. 23 ◽  
Author(s):  
T. Alexopoulos ◽  
E. Gazis ◽  
S. Maltezos ◽  
A. Antoniou ◽  
V. Gika ◽  
...  
Keyword(s):  
Distribution System ◽  
Gas Flow ◽  
Test Methods ◽  
Gas Leak ◽  
Gas System ◽  
Medical Needles ◽  
Flow Pressure ◽  
Loss Method ◽  
Lock In ◽  
Rate Loss

In this work we present the design aspects of the Gas Distribution System of NSW Micromegas detectors, simulation results and gas flow / pressure uniformity. We also describe the appropriate gas leak test methods, a conventional and an alternative one, being used in the Quality Assurance and Quality Control of the detectors. For the performance studies we used emulated leak branches based on medical needles. We also describe proposed upgrade stages combining the proposed competitive Flow Rate Loss method with the Lock-in Amplifier technique. Further, we describe the baseline setup for the Gas Tightness Station at BB5/CERN.

scholarly journals A distributed snowmelt prediction model in mountain areas based on an energy balance method

1994 ◽  
Vol 19 ◽  
pp. 107-113 ◽  
Author(s):  
Takeshi Ohta
Keyword(s):  
Energy Balance ◽  
Prediction Model ◽  
Deciduous Forest ◽  
Balance Method ◽  
Evergreen Forest ◽  
Snowmelt Runoff ◽  
Mountain Areas ◽  
Mountain Area ◽  
Energy Balance Method ◽  
Surface Cover

A distributed snowmelt prediction model was developed for a mountain area. Topography of the study area was represented by a digital map. Cells On the map were divided into three surface-cover types; deciduous forest, evergreen forest and deforested area. Snowmelt rates for each cell were calculated by an energy balance method. Meteorological elements were estimated separately in each cell according to topographical characteristics and surface-cover type. Distributions of water equivalent of snow cover were estimated by the model. Snowmelt runoff in the watershed was also simulated by snowmelt rates calculated by the model. The model showed thai the snowmelt period and snowmelt runoff after timber harvests would be about two weeks earlier than under the forest-covered condition.

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