In coal fired power plants coal is a main fuel for combustion purpose. Before use of coal different tests are to be carried out to analysis the constituent elements and some undesirable contamination in the coal. Discuss the analysis procedures of the coal.
The analysis of coal is as follows C=82%, H=6%,O2=4% and remaining is ash. Determine the amount of theoretical air required for complete combustion. If the actual air supplied is 40% in excess and 80% of given carbon is burnt to CO2 and remaining is CO. Conduct the volumetric analysis of dry products of combustion.
In coal fired power plants coal is a main fuel for combustion purpose. Before use of coal different tests are to be carried out to analysis the constituent elements and some undesirable contamination in the coal. Discuss the analysis procedures of the coal.
The analysis of coal is as follows C=82%, H=6%,O2=4% and remaining is ash. Determine the amount of theoretical air required for complete combustion. If the actual air supplied is 40% in excess and 80% of given carbon is burnt to CO2 and remaining is CO. Conduct the volumetric analysis of dry products of combustion.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
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Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
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Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
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And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
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Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
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PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
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Mission to Decommission: Importance of Decommissioning Products to Increase E...
Coal
1. Adhunik Power & Natural Resources Ltd.
Impact of Coal Quality on PlantImpact of Coal Quality on Plant
Life & PerformanceLife & Performance
2. After the liberalization of Import, most of the Power Stations are attracted
towards using Imported Coal due to:
1)Higher Calorific Value
2)Low Ash Content
3)Low Price per Unit of Energy.
Boilers in India are designed for high ash content Coal, which has lead to:
1)Large scale erosion of components leading to high Maintenance Cost
2)Low Availability
3)Lower PLF in due course of time.
Use of Imported coal has lead to Severe Operation Problems & Outages
because of basic Design features particularly in PF & FBC Boilers.
Coal has basically two components:
1)Marcels (Organic Matter) - Responsible for Heat Value
2)Mineral Matter (Inorganic Matter) - Responsible for Ash Components
Distribution of qualities of these two components effect the Coal Combustion &
thereby Boiler designs in Principle.
3. COAL COMBUSTIONCOAL COMBUSTION
COAL ParticleCOAL Particle
HeatingHeating
Formation of CharFormation of Char
Burning of VolatilesBurning of Volatiles
Release of VolatilesRelease of Volatiles
Burning of CharBurning of Char
Ash FormationAsh Formation
Each process has its own time
depending on Characteristic,
distribution & size of Marcels &
Mineral Matter.
Different Analysis is used to Assess
the Coal Combustion Characteristic.
Previously well known analysis were:
1.Proximate Analysis.
(Rank of Coal)
2.Ultimate Analysis
(Elemental Chemical Composition)
4. NEW METHODS FOR ANALYSIS OF MARCELS
1. Differential
thermogravimetic
Analysis (DTG)
Burning profile
Observation
Profile extends to
higher temp. Range
High Wt. loss at
low Temp.
High Peak at low
Temp
High Peak at
higher temp
High Burn out
temperature
Effects
Slow Burning
Coals
Good Burning
Good flame
stability
Increase furnace
temp.
Require
Large furnace
Leading to high S/H
temp.
Consequently tube
failure
No problem
Problem in water wall
higher unburned
carbon
5. 2. Modified Bomb
calorimeter (ISO
Periobol Bomb
Calorimeter)
3. Petro graphic
Analysis
Observation
Heat Release rate
Reactivity
Effects
Faster heat
Release initially &
slow towards end.
Slow rate
initially faster
afterwards
Virtinite >62.7%
Virtinite ≤62.7%
Exinites
Intertinite
Require
Requires high
absorption surface in
furnace zone.
High furnace vol.
Rise in temp of S/H,
Eco, etc & low Boiler
Efficiency.
Difficult to burn Good
Burning char highly
reactive.
Less reactive
High unburned
carbon
NEW METHODS FOR ANALYSIS OF MARCELS
contd…..
6. MINERAL MATTER
Three aspects of mineral matter influences the ash formation
1.Nature of mineral matter (Included/Excluded).
2.Particle size distribution.
3. Form of mineral matter
Ash contains SiO2, Al203, Fe2O3, CaO, MgO, Na2O K2O, TiO2 & SO3
Ash fusion temperature depends upon the quality & quantity of these
oxides.
7. ASH CHARACTERISTICS
Ash Analysis High Iron Content Clinker formation & furnace temp. limitation
Iron > 19%
10-12%
4-8%
Furnace Temp.< 1200⁰C
< 1300⁰C
Max. 1400-1450⁰C
Slagging Index
< 0.6
0.6-2.0
2-2.6
> 2.6
Boiler Slagging (Deposits of Ash on waterwall)
Low
Medium
High
Severe
Fouling Potential
<0.2
0.2-0.5
0.5-1.0
>1.0
Fouling Potential (Deposits of Ash in S/H)
Low
Medium
High
Severe
Ash Fusion Temp. Higher Ash Fusion
Temp.
>1100⁰C
<1100⁰C
No clinkering tendency.
High clinkering tendency.
Erosion Index
<1.0
>1.0
Erosion of Boiler & Mill Internals
Low
High
8. ENVIRONMENTAL RESTRICTION
Most of the Imported coals have high sulpher content
compared to Indian coal. The design of ESP & stacks are
based upon the low sulpher content of Indian coal. In
Europe & other place desulphurization units are mandatory
parts of the boiler system which are absent in India.
Blend rations are to be decided upon keeping in mind the
Pollution norms in India, otherwise Desulphurization
Equipments or increase in the height of stack is must.
9. COAL BLENDING
Keeping in mind the design features & others, we can operate Indian boilers
with blended coal i.e. a mixture of Imported coal & Indian coal, limited to the
blend ratio, which is most nearest to their design. Inspite of best of blending
each particle of coal burns as per their own characteristic. The blend Ratio
can be decided by
1.Full Scale trails on Boiler- Costly and time consuming.
2.Analyzing Burning Profile of Blended coal at laboratory level.
A study of burning Profile of various mix of Indian coal & South African coal
is represented graphically for typical PF boiler. From it is quite clear that a
30% blend Ratio of Imported to Indian coal has nearly similar burning
profile with similar peaking temperature which is a vital parameter of
furnace design. Similar study can be made for available imported coals &
blend ratios can be fixed for all the boilers in our group scientifically
without inviting costly full scale trials.
10. BLENDING METHODS
Proper blending of coal is always a difficult task. Lower the particle size
better is the blending but limited to feeding of size requirement in boiler.
Difficulties:
1.Stoker fired boiler-Improper mix due large size of feed requirement
2.Large area requirement if blending is done in yard.
3.Difficulty in measurement of accurate blends ratio.
Following are the basic guidelines for better blending:
1.Giving feed from two different sources to common pint on conveyor.
2.Proper mixing by tilting at number of transfer pints before crushing.
3.Common crushing, so that further mixing takes place during crushing.
11. EXECUTIVE SUMMARY
INDONESIAN COAL
PROXIMATE ANALYSIS
ASH
%
MOISTURE
%
VOLATILE
MATTER
%
FIXED
CARBON
%
GCV
Kcal/kg
16.41 6.80 36.25 40.54 5696
1. Trail on FBC Boiler i.e. EC4 for 100% blend, gains were Rs. 40,000 per day.
2. Blend ratio to be limited to 30% due to SO2 norms.
3. Gain at 30% Blend Ratio approx. 15000/day in EC4.
4. Gain for EC1 & EC2 to be calculated after trails.
5. Gain will be available for 8-9 months only, i.e. excluding Monsoon Period.
12. PROXIMATE ANALYSIS
ASH
%
MOISTURE
%
VOLATILE
MATTER
%
FIXED
CARBON
%
GCV
Kcal/kg
17.36 3.33 22.23 57.08 5998
SOUTH AFRICAN COAL
1. Loss in Boiler Efficiency due to high unburned carbon.
2. Net Gain Rs. 60,000 per day for 400 TDP steam.
3. Blend ratio to be limited to 25-30% due to SO2 norms & problems of
clinkering & high flue gas temp in PF boilers of EC1.
4. Expected gain on continuous basis shall be approximately 50000-55000/day.
5. Gain will be available for 8-9 months only, i.e. excluding Monsoon Period.
13. COST IMPACT OF MOISTURE ON
C.V.Cost including Freight (Cif) value at 6500 Kcal = Rs. 1160/ton
Landed Cost = Rs. 2145/ton
An increase in 1% Moisture has a reduction of Rs. 11.60/ton as per weight basis.
Whereas for a Reduction in Gross Calorific value because of high moisture by 1%, the
corresponding loss is about 64 kcal.
Conversion factor at 2.5% moisture = (100-{2.5+1})/(100-2.5)
= 6433 kcal
Difference in C.V. = 6500-6433
= 64 kcal
Cost/kcal = 2145/6500
= Rs. 0.33/kcal
= Rs. 33/100 Kcal
Equivalent Cost for 67 Kcal = 33/100 x 67
= Rs. 22
Total Loss = Rs. 22- Rs. 11.60
approx. Rs. 11
14. Unit Stroker Fired Boilers Fluidized Bed
Boilers
Pulveriz
ed Fuel
Boilers
Under Grate Spreader Chain/
Travelling
Gate
Bed
Super
Heater
Convective
Super
Heater
Stationary Moving
Proximate Analysis
Moisture % 0-10 0-10 0-25 0.20 5-10 8-15 5-10
Volatile
Matter
% 30-40 30-40 18-30 30-40 20-40 20-40 15-25
Fixed
Carbon
% 40-50 40-50 50-65 40-50 30-40 30-40 30-50
ASH % 5-10 5-10 5-15 10-20 >25 >25 >20
FC/VM % 1-1.25 1-1.25 1-1.25 1-1.25 1.4-1.6 <1.5 <2.0
C.V. Kcal
/kg
6500-
7500
6500-
7500
5000-
6000
4500-
5500
3000-
4000
5000-
6000
Rank Semi Anthracite Sub Bituminous
Free
Swelling
Index
5 Max 7 Max NA 5Max NA NA NA
HGI NA NA NA NA NA NA 50-70
SPECIFICATION OF COAL
15. Unit Stroker Fired Boilers Fluidized Bed
Boilers
Pulveriz
ed Fuel
Boilers
Under Grate Spreader Chain/
Travelling
Gate
Bed
Super
Heater
Convectiv
e Super
Heater
Stationary Moving
Statutory Req.
Sulphur ^
<0.5 <0.5 <0.5 <0.5 <0.7 <0.7 <0.5
Moisture % 0-10 0-10 0-25 0.20 5-10 8-15 5-10
Ash Characteristics
Erosion
Index (EI)
NA NA NA NA <1.0 <1.0 <1.0
Ash
softening
Temp
⁰C 13501400 1350-
1400
1050-
1100
1125-1175 >1200 >1150 >1100
Slagging
Index
NA NA NA NA <0.6 <0.6 0.6-2.0
Fouling
Indes
NA NA NA NA <0.2 <0.2 0.2-1.0
Origin
16. GRASIM NAGDA
Analysis & Summary of 100% Imported Coal Use in EC4
(INDONESIAN COAL)
SNo Particulars Unit EC4 Remarks
1. Furnace Temperature ⁰C 782 Improved Norm
2. Bed Temperature ⁰C 922 Within Norms
3. Stack Temperature ⁰C 119 No Dev. From SECL Coal
4. Main Steam Flow TPH 89
5. Main Steam- SECL TPH 81
6. Main Steam Flow-Parta TPH 85
7. Coal Consumption
a. Imported
b. 100% SECL
c. Parta
TPD
TPD
TPD
294
313
331
8. Blend Ratio % 100
9. Calorific Value
a. Imported
b. 100% SECL
c. Parta
d. Gain/loss from SECL
Kcal/kg
Kcal/kg
Kcal/kg
Kcal/kg
5700
4807
4833
893
17. Sr. No. Particulars Unit EC4 Remarks
10 Boiler Efficiency
a.Direct Method
b.Loss Method
c.Average
d.SECL
e.Gain/loss from SECL
%
%
%
%
%
81.87
84.58
83.20
83.78
-0.58
11 Cost of Coal
a.Imported
b.SECL
c.Parta
d.Gain/Loss from SECL
Rs./T
Rs./T
Rs./T
Rs./T
2115
1905
1988
-210
Rs 1959 at 4944 kcal
At 4833 kcal, April 99 Parta
12 Coal Cost/100 Kcal
a.Imported
b.SECL
c.Parta
d.Gain/Loss from SECL
Rs T/1000 Kcal
Rs T/1000 Kcal
Rs T/1000 Kcal
Rs T/1000 Kcal
371
396
411
25
13 Cost of steam
a.Imported
b.SECL
c.Parta
d.Gain/Loss from SECL
Rs./T
Rs./T
Rs./T
Rs./T
286
305
324
19
14 Gain/loss From SECL Rs/Day 40570 At 89 TPH Steam
15 Gain /loss from SECL at Parta Steam Rs/Day 38619 At 85 TPH steam
18. Grasim Nagda (SOUTH AFRICAN COAL)
Analysis & Summary of Blending Imported Coal with SECL Coal From 03/07/99-05/07/99
S.N. Particulars Unit EC1 EC2 EC4 TOTAL/Wt
d
Remarks
1 Furnace Temp. ⁰ C 857 643 722 748 Increasing Trend in EC1
2 Bed Temp ⁰ C 891 922 910 Within norms
3 Stack Temp ⁰ C 171 155 119 146 No dev. From SECL Coal
4 Main Steam Flow TPH 141 104 166 411
5 Main Steam- SECL TPH 141 101 158 400
6 Main Steam Flow-Parta TPH 135 105 158 398
7 Coal Consumption
a.Imported
b.SECL
c.Total
d.100% SECL
e.Parta
TDP
TDP
TDP
TDP
TDP
137
342
479
487
491
141
277
418
419
410
166
367
533
533
596
444
986
1430
1439
1497
8 Blend Ratio % 29 34 31 31
9 Calorific Value
a. Imported
b. Blended
c. SECL Blended
d. 100% SECL
e. Parta
f. Gain/loss from SECL
Kcal/kg
Kcal/kg
Kcal/kg
Kcal/kg
Kcal/kg
Kcal/kg
5998
5229
4921
4779
4833
308
5998
5273
4904
4677
4833
369
5998
5194
4830
5025
4833
364
5998
5229
4882
4840
4833
346
As fired basis-10% moisture
Derived Value
20. OUR RECOMMENDATIONS
1. Use of Indonesian Coal at 25-30% Blend Ratio.
2. If possible use of South African coal to be avoided because of
clinking nature of coal.