consolidated report on the activities and achievements indo

Consolidated Report on the Activities and Achievements

Power Plant Optimization Component

Indo- German Energy Programme (IGEN) Phase-II

(2009-2015)

Ministry of PowerGovernment of India

Implemented by

Consolidated Report on the Activities and Achievements

Power Plant Optimization Component

Indo- German Energy Programme (IGEN) Phase-II

(2009-2015)

FOREWORD

In order to achieve the goal of the Government of India to make power available to all at

affordable price it is necessary to enhance efficiency in generation, transmission and

distribution of the electricity apart from promoting demand side management of electricity

conservation.

GIZ Germany and Central Electricity Authority (CEA) are implementing Indo-German Energy

Programme (IGEN) with the objective of improving efficiency of coal-fired generation in the

country and has taken up various activities in this direction such as providing Ebsilon

diagnostic software to 15 power utilities, training their engineers for using this software for

analysing and improving the performance of their thermal units effectively, demonstration of

energy savings achieved by implementing measures identified through mapping of

operating units and capacity building of power utility engineers by conducting study cum

familiarisation tour to Germany for sharing the best O&M practices being followed in Thermal

generation and state of the art technology used in German plants.

It is very heartening to know that the outcome of these activities has not only resulted in

energy /fuel saving but also helped in reducing CO2 emissions from the power sector. The

best part is that the plant engineers are now feeling more confident about their

understanding of gaps in performance of their stations and also have adequate knowledge

to take up appropriate measures to enhance efficiency of plant.

A brief report covering activities and achievements of IGEN programme, has been brought

out in the form of this book with an aim of dissemination of knowledge and experience

gained during the course of the implementation of this programme by the engineers of power

utilities.

I appreciate the efforts of the CEA and GIZ engineers for summarising entire activities of

IGEN in this book which would provide valuable information to various utilities and to

stakeholders in power sector.

New Delhi Major Singh

June 2015 Chairperson

Major Singh Chairperson

Central Electricity Authority

FOREWORD

India has been growing at a very fast pace of industrialization. This demands additional electricity - more than 1 GW of power generation capacity is currently being added every month. Out of this capacity, coal still rules as the largest contributor. However, just capacity addition cannot be the solution in the long run as resources and emission budgets are limited. One answer to this challenge is the increased energy efficiency by which fuel and emissions can be reduced significantly.

Therefore one focus of the Indo-German Energy Programme (IGEN) was on the generation side, especially on coal fired power plants. All the activities were jointly implemented with the Central Electricity Authority. Aim was to reduce fuel and emissions, based on trainings for plant engineers, knowledge exchanges and dissemination of software tools as well as continuous consultancies.

It gives me immense pleasure to value the high success of this programme. Savings of 1.2 Million tons of coal and 1.6 Million tons of CO2 each year are remarkable and more than expected. For me most important is that the plant engineers became self-sufficient in the analysis of gaps as well as in the identification and implementation of saving measures. Therefore I have full confidence that the huge savings will remain also in future. This consolidated summary report takes us to the beginning of our activities, reflecting the efforts which the IGEN team along with CEA and the consultant STEAG has taken the last six years and whom I thank a lot for their efforts. I like to share these experiences and wish you a good time with reading.

New Delhi Dr. Winfried Damm June 2015 Director

Dr. Winfried Damm Director

Indo-German Energy Programme

GIZ-India

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Contents

Executive Summary ............................................................................................................................................. 1

1. Introduction................................................................................................................................................... 3

1.1. Indian Power Sector ........................................................................................................................... 3

1.2. Low Carbon Growth Strategy for Generation Planning in India .................................................. 5

2. Indo-German Energy Programme (IGEN) ............................................................................................... 6

3. Training and capacity development of plants engineers with diagnostic software and study tours 7

3.1. Training of 101 engineers with adequate supply of diagnostic tool, Ebsilon® Professional ... 7

3.2. Human Resource Development to improve knowledge on critical areas................................... 8

4. Feasibility studies to identify savings measures for 17 plant units with the support of consultant

“case studies” ....................................................................................................................................................... 9

4.1. Findings of case Study .................................................................................................................... 10

4.2. Reasons for high operating gross heat rates ............................................................................... 11

4.3. Recommendations as proposed in the Case Studies ................................................................. 12

4.4. Impact of Case Studies ................................................................................................................... 12

5. Feasibility studies to identify savings measures for 30 further plant units “mapping reports” ....... 14

5.1. Findings of Mapping Reports .......................................................................................................... 15

5.2. Reasons for high operating gross heat rate ................................................................................. 16

5.3. Recommendations for Improving Energy Efficiency ................................................................... 19

5.4. Impact of Mapping Reports ............................................................................................................. 19

6. Implementation of exemplary saving measures in three selected plants (Model Power Plants) .. 21

6.1. Approach ........................................................................................................................................... 21

6.2. Identified gaps in Energy Efficiency area ...................................................................................... 21

5.3. Measures Recommended ............................................................................................................... 23

5.4. Conclusion and Findings ................................................................................................................. 24

7. Implementation of a demonstration boiler performance optimization system (BPOS) ............... 25

7.1. Approach ........................................................................................................................................... 25

7.2. BPOS System Description .............................................................................................................. 25

7.3. Conclusion and Benefits .................................................................................................................. 27

Abbreviations ...................................................................................................................................................... 30

Annexures ........................................................................................................................................................... 31

Annexure 1: 85 Units Mapped under IGEN Phase I ................................................................................ 31

Annexure 2: Formulae and Calculations .................................................................................................... 33

References .......................................................................................................................................................... 33

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Executive Summary

As per the growing energy demand of electricity in India, the generation has to be in kept at

same pace. This tremendous pressure urges for efficient electricity generation techniques.

Under Power Plant optimization Component, IGEN Phase-II, an average improvement in

heat rate of 3.5% was achieved for 27 units with a total capacity of 6.6 GW.. This refers to an

efficiency improvement of 1.2 % points and a CO2 emission reduction of 1.6 million tonnes

per year.

This was done with the training of 101 engineers on the use of Ebsilon® Professional

software and supply of 40 licenses to them. These trainings and distributions were catered to

15 thermal generating utilities.

Ebsilon® Professional is a diagnostic tool that helps the power plant operators to identify the

deviation of parameters against their design values. Ebsilon® Professional also helps to

undertake the “what if” scenarios of the thermodynamically cycle. Distribution of the software

was also accompanied with dedicated trainings and handholding exercise on use of same.

Utilities prepared 17 case studies, with the support of consultant and 30 mapping reports, by

their own, with the use of Ebsilon® Professional.

Apart from these four plants were identified for implementation of prioritised

recommendations to develop them as showcased model power plants. One of the units was

equipped with state of the art Boiler Performance Optimization System (BPOS).

All these activities resulted in a significant savings which has been discussed in various

chapters in the report. The summaries of quantified savings for each activity are shown in

the table and chart below.

S.No.

Activity Name Capacity

Improvement in Heat Rate from operating (%)

Improvement in Efficiency from operating (% points)

Coal Savings (kt/year)

CO2

Savings (kt/ year)

Monetary Savings (Cr. Rs/ year)

Monetary Savings (Million Euro/ year)

1 Impact of case studies (8 units) 1925 3.7 1.2 378 506 151 21.6

2 Impact of mapping reports (15 units) 3470 3.8 1.3 706 945 282 40.4

3 Impact of model power plants and BPOS (4 units)

1170 2.2 0.7 122 180 49 7.0

Total 6565 3.5%

(Weighted Average)

1.2 % (Weighted Average)

1206 1631 483 68.9

From the table above, it can be observed that the activities on coal fired power plants under

IGEN Phase-II resulted in an increase in average efficiency by 1.2 % points. This is

equivalent to a savings of 1.6 million tonnes of CO2 per year or 1.2 tonnes of coal per year. It

means an annual savings of 483 crore INR or 68.9 million Euro.

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Breakdown of annual 1.6 Million tons of CO2 savings in coal fired power plants with a capacity of 6.8 Gigawatt and an annual electricity production of 47000 GWh

The plants have become more prepared with the tool and knowledge to identify deviations in

operating conditions. It was also reported that some of the utilities are also practicing sharing

of knowledge from IGEN activities among other plants in their utility. This is creating a

cascading effect which was the long term objective of IGEN.

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0

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100000

150000

200000

250000

1940 1960 1980 2000 2020Year

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)

0100200300400500600700800900

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1940 1960 1980 2000 2020Year

Per

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(kW

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1. Introduction

1.1. Indian Power Sector

India is the fourth largest producer of electricity (European Union included) in the world. Since independence, there has been a significant capacity addition in every decade. However, since the last decade the capacity addition has increased colossally. This change can be attributed to the privatization of licensing policy of Indian power sector. The capacity addition to Indian power sector has been more than 196 times since independence, 1947.

Figure 1: Installed capacity in the Indian power sector

The per capita power consumption of India has also increased from a mere 16.3 kWh to 957 kWh (2013-14) since independence. This is a growth of over 58 times since then. On one hand where the Indian power sector is ageing with its coal based capacities, on the other hand it is quite young at the non-conventional generating sources. The growing demand of electricity is placing tremendous pressure on the power sector and coal being the largest in terms of capacity, also shares the largest segment of this burden. The demand for electricity is likely to continue to grow by about 8-9% per year to keep the pace of economic development in line with Government of India’s targets. The government has already announced its commitment to uninterrupted 24x7 hours electricity supply to consumers.

Figure 2: Per capita electricity consumption

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The power sector in India has witnessed drastic changes in the past few decades. The Electricity Act, 2003 paved way for the advent of reforms and competition in the power sector. The competition in power sector has brought “energy efficiency” at the central stage in supply and demand side management of power. India’s national and international commitment concerning environment is another important driver for energy efficiency in power generation. The power industry in India has registered significant progress since the inception of the economic planning process in 1951. Installed capacity grew from about 1362 MW in 1947 to about 2, 67,637 MW by 31st March, 2015, including over 31,692 MW (11.84 %) from renewables. The installed capacity as on 31-03-2015 is given in table below.

Table 1: Installed capacity as on 31.03.2015 (Figures in MW)

It is observant from the table above that out of 267 GW installed capacity; thermal alone is responsible for approximately 70% share. Also, of this 70%, coal based thermal power plants alone contributes 87 %. The share of each generating source towards Indian power sector is shown in figure below.

From the above figure it is evident that the coal shares the largest chunk of 60% followed by hydro 15%, renewable energy sources (R.E.S.)12%, gas based plants 8%, and the remaining is shared by diesel and nuclear. Though in past, Coal Plants were the major area of interest, now the renewable energy sources are gaining much popularity due to low CO2 approach. It has hence, become necessary for the existing Coal based Power Plants to reduce CO2 emission by enhancing efficiency. This is also backed by the PAT scheme of Govt. of India which mandates all power plants to reduce their heat rate or in other words increase efficiency by a target.

61.51% 8.62%

0.45%

2.16%

15.42%

11.84%

Coal

Gas

Diesel

Nuclear

Hydro

RES

Sector Hydro Thermal Nuclear R.E.S

Grand

Total

Coal Gas Diesel Total

State 11091.43 48130.00 7519.73 0.00 55649.73 5780.00 0.00 72521.16

Private 27482.00 58100.50 6974.42 602.61 65677.53 0.00 3803.67 96963.20

Central 2694.00 58405.38 8568.00 597.14 67570.52 0.00 27888.47 98152.99

Total 41267.43 164635.88 23062.15 1199.75 188897.78 5780.00 31692.14 267637.35

% 15.42 61.51 8.62 0.45 70.58 2.16 11.84 100

Figure 3: Contribution of generation sources towards total capacity

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52%

10%

5%

2%

10%

9%

12%

0% 0% Electricity

Transport

Residential

Other Energy Activities

Cement

iron and Steel

Other manufacturing Industries

Agriculture

Waste

1.2. Low Carbon Growth Strategy for Generation Planning in India

India is one of the lowest emitters of greenhouse gases (GHGs) in the world on per capita

basis. The per capita CO2 emission of India is 1.4 tCO2, which is less than one third of the

world’s average of 4.5 tCO2. Towards providing cleaner fuel and superior technology, and to

reduce India’s dependence on coal, a low carbon growth strategy is being adopted by the

Government for generation capacity addition during 12th Plan (2012- 2017) and future

plans. Accordingly, the Plan takes into account the development of projects based on

renewable energy sources as well as other measures and technologies promoting

sustainable development of the country. Two of the important steps of this Sustainable

Integrated approach are Efficiency Improvement of existing stations and Energy

Conservation in generation and at consumer end. India has already projected the estimated

capacity addition by Solar to be 100GW and by wind energy to be 60GW by the year 2022.

India has also prepared a national action plan for climate change and said that it will reduce

the emission intensity of its GDP by 20 to 25 percent, over 2005 levels, by 2020.

Approximately 11 Million tons of Coal per annum can be saved by increase of 1% in

efficiency of thermal power plants. Since the fuel cost amounts to approximately 3/4th of the

total average production cost, even a marginal improvement in efficiency results into huge

amount of saving of money. Thus, twin benefits of energy efficiency are – cost effectiveness

and reduction in greenhouse gas emissions.

According to a survey, coal based power plants have the maximum stake in CO2 production

in India, followed by transport and others. It can be observed from the above figure that

electricity production alone shares more than 50% for total CO2 production. Hence,

improvement of efficiency of thermal power plants will create a huge impact.

.

Figure 4: Share of emission of CO2 from each Sector

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2. Indo-German Energy Programme (IGEN)

The Indo-German Energy Programme (IGEN) deals with various projects/ components in

conventional and non-conventional generation techniques, demand side and consumer side

energy efficiency, etc. The Indo-German technical cooperation in the field of Energy

Conservation commenced when the first Indo-German Energy Efficiency Project was

launched in May 1995 by the Energy Management Centre, a predecessor organization to

the Bureau of Energy Efficiency (BEE). With the success of the project and looking into the

need of promoting Energy Efficiency in the country, a full-fledged Indo-German Energy

Program (IGEN) was launched in October 2003. IGEN was launched in the context of

enactment of Energy Conservation Act 2001 and establishment of Bureau of Energy

Efficiency. Out of the two components – Energy Efficiency component and Power Plant

Optimization component, the later, being implemented by Central Electricity Authority (CEA)

and GIZ, aims at improvements in energy efficiency of power plants.

The 1st Indo-German Energy Programme was executed from 2006 to 2009. It aimed at

potential studies of thermal power generating units and performance optimization of thermal

power stations. Under this, GIZ provided support to CEA for creating data base of the older

thermal power plants in India. The scope of the work primarily covered the analysis of 85

coal fired power generating units using Ebsilon® Professional. (Ref. Annexure-1).

While analyzing the efficiency of conventional power plants, one has to remember that fuel

cost amounts to approximately 75% of the total average production costs. This fact clearly

highlights the necessity of operating the plant at optimum efficiency. Along with cost

effectiveness, the reduction in the emission of air pollutants is also required. The

degradation of the plant efficiency is a normal process, but a permanent challenge to

minimize the degradation by measuring performance parameters and taking the corrective

action through the O&M exists. The studies from IGEN Phase-I, reflected a saving potential

of coal to the tune of 6.92 million tonnes per year. As per Indian quality of coal, the savings

would lead to a CO2 emissions reduction up to 10 million tonnes per year. This reconfirmed

the possibility of huge potential in Green House Gas mitigation. Mapping exercise

introduced power plants to the versatility of Ebsilon® Professional as a diagnostic tool and

enabler for planning for Energy Efficiency measures in Thermal Power Plants.

To make the energy efficiency efforts sustainable in the long run, phase II (Power Plant

Component) was launched to build on the achievements of phase I. The power plant

optimization component aims at capacity development and exchange of best practices. The

result oriented parameters for PPOC Phase-II were,

a) Training and capacity development of plants engineers with diagnostic software

and study tours

b) Feasibility studies to identify savings measures in plant.

c) Implementation of exemplary saving measures in three selected plants

d) Implementation of a demonstration boiler performance optimization system (BPOS)

The list of activities was designed accordingly to achieve the above mentioned results.

Steag Energy Service, were appointed as the consultant for the technical support for plant

engineers. Adelphi consult GmbH, was appointed the consultant for the study cum

familiarization tour to Germany.

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3. Training and capacity development of plants engineers with diagnostic

software and study tours

The capacity development was divided in two activities namely, a) training of 101 engineers

with adequate supply of diagnostic tool, Ebsilon® Professional, and b) human resource

development to improve knowledge on critical areas. The objective was to make the plant

operators self-sustainable in analyzing the gaps in their plant. To assist this, the gap

analysis software, Ebsilon® Professional and trainings were given. Also, to make them more

aware on critical areas, a study cum familiarization tour was organized.

3.1. Training of 101 engineers with adequate supply of diagnostic tool, Ebsilon® Professional

A total of 101 participants were trained on the use of Ebsilon® Professional preceded by

distribution of 40 Ebsilon® Professional licenses. Among the trainees, 97 were from thermal

generating utilities and 4 from CEA. The resource personnel from Steag Energy Services for

each two week training consisted of 8 specialists from India and one expert from Germany.

These distribution and trainings were done in batches, under main programme and its

extension phase. The distribution of Ebsilon® Professional licenses were accompanied by

distribution of laptops as well. The utilities signed a memorandum of understanding with GIZ

in presence of CEA. The list of beneficiary utilities is given in the table below.

S.No. Utility Number of Licenses in PPOC Phase-II

Number of Licenses under PPOC extension

Total Number of Licenses

Number of Laptops

1 APGENCO 1 3 4 4

2 CSPGCL 1 2 3 3

3 DVC 1 2 3 3

4 GIPCL 1 0 1 1

5 GSECL 1 2 3 3

6 HPGCL 1 2 3 3

7 MPPGCL 1 2 3 3

8 MAHAGENCO 1 2 3 3

9 NLCL 1 2 3 3

10 OPGCL 1 0 1 1

11 PSPCL 1 2 3 3

12 RRVUNL 1 2 3 3

13 TANGEDCO 1 2 3 3

14 TVNL 1 0 1 1

15 UPRVUNL 1 2 3 3

TOTAL 40 40 Table 2: List of Beneficiaries of Ebsilon® Professional

The trainings were held for 2 weeks per batch in New Delhi. This was followed by special

handholding exercises to make plant specific models at each plant site. This helped the

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plant professional to map their unit and carry out the gap analysis themselves. Many plant

prepared operating models for various conditions which helped them to understand the

behaviour of system in a better way.

3.2. Human Resource Development to improve knowledge on critical areas

Under this subcomponent, two weeks study tour to Germany was conducted. The key

features were visit to eleven power plants, power plant equipment manufacturers, power

plant associates, think tanks and universities. The focus was modernization and retrofitting

of power plants, online and offline monitoring programs, coal blending technologies and best

operation and maintenance practices.

During all the tour, German experts shared their knowledge and expertise by presenting best

practice examples, case studies and state of art technologies to the delegation. Furthermore

the tour was useful for exchanging knowledge between the participants.

A total of 53 participants were divided into three batches. Each batch had a visit for two

weeks. The composite list consisted of 41 engineers from state thermal generating utilities,

seven representatives from Central Electricity Authority (CEA), and two representatives from

Ministry of Power (MoP) participated in the tours. Additionally, experts from GIZ also

attended the first study cum familiarization tour. The study tours were conducted in oct-2011,

and sept-oct-2011.

The two week training visits provided contacts to relevant institutions and companies for

further cooperation and to develop public private partnership initiatives. During the tour, the

participants visited different coal and lignite fired power plants, one gas fired power plant and

one geothermal power plant. The tour proved quite useful in dissemination of knowledge and

best practice exchange.

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4. Feasibility studies to identify savings measures for 17 plant units with

the support of consultant “case studies”

Case studies were primarily done by the plant with full onsite and offsite of consultant.

These studies were done on 17 units with capacities adding up to 3.6GW. These were the

base for implementation of energy efficiency measures. The monitoring on this activity for 8

units with a total of 1.9 GW capacities, revealed an efficiency improvement of 3.7 % (1.2%

points). This meant 0.5 million tonnes of CO2 emission savings per year or 0.38 million

tonnes of coal savings per year.

Model analysis was carried out to determine the degradation of performance of important

equipment which can affect the overall plant performance and efficiency. Enthalpy drop

values were obtained from the HS (Mollier) diagrams. The model enabled assessment of

impact of changes in some parameters over other parameters. Such changes included

deviations in coal quality as well. Deviations have been determined with the help of the

model taking into account the impact of external factors and current operating conditions of

the plant. Some of the important parameters analyzed are:

Turbine and Gross heat rate

Boiler efficiency & unit efficiency

Efficiency of turbines (HP, IP, LP)

Regenerative heater performance

Condenser performance

Excess O2

The list of units that undertook case study is mentioned below

Sl No State Board/ Electricity Gen. Company

Power Station Unit size MW

Unit No

1 APGENCO Kothagudem Thermal Power Plant 120 6

2 GSECL Sikka Thermal Power Plant 120 1

3 GIPCL Surat Lignite 125 3

4 OPGC IB Valley Thermal Power Plant 210 2

5 HPGCL Panipat Thermal Power Plant 210 6

6 MAHAGENCO Khaperkheda Thermal Power Plant 210 3

7 GSECL Gandhinagar Thermal Power Plant 210 5

8 GSECL Wankbori Thermal Power Plant 210 2

9 NLCL Neyveli lignite 210 2

10 NLCL Neyveli lignite 210 7

11 TANGEDCO Tuticorin Thermal Power Plant 210 2

12 TANGEDCO Tuticorin Thermal Power Plant 210 4

13 PSPCL GHTPP, Lehra Mohabbat TPS 210 1

14 TVNL Thenughat Thermal Power Plant 210 2

15 DVC Durgapur Thermal Power Station 210 4

16 RRVUNL Suratgarh Thermal Power Plant 250 3

17 UPRVUNL Anpara Thermal Power Plant 500 4

Total Capacity 3635 Table 3: list of units that prepared case study reports

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4.1. Findings of case Study

The studies revealed that most of the units are being operated under various constraints like

poor quality of coal, insufficient attention to proper maintenance of boiler, turbine and other

equipment, operating parameters different from the rated values and obsolete

instrumentation. These have resulted in high heat rates and unreliable plant operations. The

savings potential from these 17 case study reports have been listed in table below.

Parameters 120 MW (2)

125 MW (1)

210 MW (12)

250 MW (1)

500 MW (1)

Total (toe)

Short Term Potential ( 117365.47 toe)

MS pressure 361.30 0 3663.11 0 52.12 4076.53

MS Temp 34.44 0 1351.69 735.84 0 2121.97

RH Temp 319.35 0 2339.79 153.30 723.58 3536.02

Condenser Vacuum

691.69 1273.07

40922.94 3766.13 46653.83

UBC in Fly Ash 559.24 0 13521.06 0 14080.30

UBC in bottom ash

342.17 0 5430.96 333.43 298.94 6405.49

Makeup 0 0 15494.69 0 2057.29 17551.98

Excess air 2977.11 688.22 18547.02 0 727.01 22939.35

Long Term Potential (347881.32 toe)

RH Spray 0 515.21 5902.90 0 1282.20 7700.31

SH Spray 8.65 15.59 286.49 0 77.26 388.00

Exit Gas Temp 2472.42 1728.24

26512.61 0 3679.20 34392.47

Change in FW temp

1279.99 0 4008.67 0 5365.50 10654.17

HPT Efficiency 2305.49 3612.85

22362.29 4849.65 3633.21 36763.48

IPT Efficiency 3070.22 569.26 20195.44 617.19 5274.13 29726.24

LPT Efficiency 4160.73 0 163036.17

6169.10 17004.04 190370.04

HPH TTD 3116.58 0 18124.09 700.89 1926.06 23867.62

HPH DCA 0 5.73 1712.99 80.48 0 1799.20

LPH TTD 83.44 0 8963.30 938.20 253.86 10238.81

LPH DCA 0 0 631.95 0 1349.04 1980.99

Total 465246.78

Table 4: Savings Potential from 17 Case Study reports

It can be observed that from these 17 case study reports, a saving potential worth 0.46

million tonnes of oil equivalent was revealed. The calculations of indices were done

considering 70% PLF.

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4076.53 2121.97

3536.02

46653.83

14080.30

6405.49

17551.98

22939.35

Total Short term Saving Potential (117365.47 toe)

MS pressure (kg/cm2) MS Temp (ᴼC)

RH Temp (ᴼC) Condenser Vacuum (mmHg)

UBC in Fly Ash (%) UBC in bottom ash (%)

Makeup (%) Excess air (%)

7700.31 388.00

34392.47

10654.17

36763.48

29726.24 190370.04

23867.62

1799.20

10238.81 1980.99

Total Long term Saving potential (347881.32 toe)

RH Spray (t/h) SH Spray (t/h)

Exit Gas Temp (ᴼC) Change in FW temp (ᴼC)

HPT Efficiency (%) IPT Efficiency (%)

LPT Efficiency (%) HPH TTD (K)

HPH DCA (K) LPH TTD (K)

LPH DCA (K)

Capacity range of units (MW)

No. of units

Average Deviation of Boiler Efficiency (%)

Average Deviation of Turbine Heat Rate(%)

Average Deviation of Gross Heat Rate (%)

120 2 5.41 5.42 11.91

125 1 0.62 1.15 1.01

210 12 3.11 5.94 10

250 1 0.9 5.71 6.74

500 1 1.95 7.92 10.08

Table 5: Major variation (%) among important parameters from case Study reports

Table above shows the average deviation of TG Heat rate, Boiler Efficiency and Unit Heat

rate among various ranges of capacities.

The total saving potential for 17 units (3635MW) works out to be 465246.78 toe per year

(Short term117365.47 and long term 347881.32 toe per year) as shown in fig below.

Figure 5: Short term and Long Term Savings potential with Factors considering 70%PLF

On analysis of fig above, it is observed that the maximum contributing factor towards short

term savings is condenser vacuum and for long term savings is turbine efficiency. Other

major contributing factors are main steam (MS) temperature, unburnt carbon, and excess air

4.2. Reasons for high operating gross heat rates

Based on observations during site visit and discussions with the site engineers on the

operation and maintenance aspects of the power plants, some areas commonly observed to

be responsible for high operating gross heat rate are listed below. These observations are

not applicable to all the units but are representative of the type of problems encountered.

For specific sites, the individual reports may be referred.

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Analysis of observations for different power plants indicates that the major reasons for the

high operating gross heat rate are:

Un-optimized boiler combustion

Low turbine cylinder efficiency

Low condenser vacuum.

Heater performance

High air ingress in the boiler/air heater

Inefficient operation of air pre-heaters

High super heater and re-heater spray

Make Up flow

Coal quality not conforming to design coal

Inefficient soot blowing of the boiler tubes

4.3. Recommendations as proposed in the Case Studies

Recommendations to improve the performance and efficiency of the plant have been made

for each of the units covering maintenance and, operational aspects. These

recommendations take into account the observations at site, available information with

project engineers and deviations in operating parameters determined by Ebsilon®

Professional model. The recommendations have been divided into two categories namely:

Short term and Long Term

The short term recommendations are those which mostly relates to operating practices, can

be implemented immediately at lesser cost, permitting picking up of low hanging fruits.

The long term recommendations cover overhauling and retrofit in the plant. The

recommendations cover energy audit of air flue gas path, replacement of APH blocks,

providing oxygen analyser at APH outlet, steam path audit for turbines and checking the

blade profile, checking and rectification of heater baffle arrangement, burner management

system, auto controls, turbine, ESP controls and ID fan control improvement. These

recommendations, however, will need further detailed studies which could be taken up at the

stage of next annual overhauling or at the time of Residual Life Assessment studies.

4.4. Impact of Case Studies

The activities were aimed at development of self-reliability among the plant engineers to

identify gaps and bridge them. All together 17 thermal generating units prepared case

studies of their operating condition to find out the deviation from their design parameters.

Accordingly recommendations were also made on short and long term basis. This entire

activity was closely supported by the experts from Steag. The activity was designed till the

recommendation against the gaps identified and the implementation of measures were to be

done by the plant based on the recommendations. The plants did their part in the most

promising way they could. In the conclave held in Jan-2014, the plants presented their work

of implementation and other works with the use of Ebsilon® Professional. These works led

to a betterment of heat rate. Some of the plant even quantified their savings. The quantified

savings and their analysis on other parameters are shown in the table below.

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S.No.

Plant name Utility Name

Capacity


Improvement in Efficiency from operating (%)


1 Suratgarh TPS RVUN 250 4.01 4.18 44.3

2 Tenughat TPS TVNL 210 6.45 6.90 69.7

3 Anpara TPS UPRVUNL 500 0.68 0.69 22.6

4 Surat Lignite TPS

GIPCL 125 1.10 1.11 9.1

5 Tuticorin TPS TANGEDCO

210 8.98 9.87 123.5

6 IB Valley TPS OPGC 210 2.19 2.24 26.2

7 Gandhinagar TPS

GSECL 210 4.33 4.52 38.3

8 Neyveli Lignite TPS

NLC 210 3.11 3.21 44.6

Table 6: Achievements of units that prepared case study reports

The above mentioned savings leads to a CO2 emission reduction of 0.5 million tonnes per

year with an equivalent monetary savings of 151 Crore INR. This is a huge savings and the

biggest achievement is that the plants have done this on their own part. It can also be said

that from a capacity of 1925 MW (sum of capacities mentioned in table above), a savings

worth 0.5 million tonnes of CO2 emission reduction was achieved.

14 | P a g e

5. Feasibility studies to identify savings measures for 30 further plant

units “mapping reports”

The focus was to develop in house capabilities amongst identified thermal power plants to

use Ebsilon® Professional and undertake mapping exercise to plan for interventions needed

to restrict controllable losses. Power plant efficiency engineers were extensively trained in

application of Ebsilon® Professional and were provided handholding by consultant in the

entire process of the project leading to mapping of further 30 units. The methodology was

kept same as that in the case study reports. Where in the case study reports, it was more

with the stronger support of Steag Energy Services India, in Mapping Reports the emphasis

was on plant’s own efforts. The list of different size of units, state generating utility wise

mapped are shown in the table below

Sl No State Board/ Electricity Gen. Company


Unit No

1. PSPCL Guru Nanak Dev Thermal Power Station 110 1

2. HPGCL Panipat Thermal Power Station 120* 1

3. GIPCL Surat Lignite Thermal Power Station 125 1

4. GIPCL Surat Lignite Thermal Power Station 125 4

5. DVC Mejia Thermal Power Station 210 3

6. GSECL Gandhinagar Thermal Power Station 210 4

7. HPGCL Panipat Thermal Power Station 210 6

8. NLCL Neyveli Second Thermal Power Station 210 4

9. NLCL Neyveli Second Thermal Power Station 210 6

10. OPGC IB Thermal Power Station 210 1

11. MPPGCL Sanjay Gandhi Thermal Power Station 210 4

12. TVNL Tenughat Thermal Power Station 210 1

13. MAHAGENCO Nasik Thermal Power Station 210 5

14. CSPGCL Hasdeo Thermal Power Station 210 1

15. TANGEDCO Tuticorin Thermal Power Station 210 3

16. TANGEDCO Tuticorin Thermal Power Station 210 5

17. TANGEDCO Mettur Thermal Power Station-1 210 4

18. DVC Chandrapura Thermal Power Station 250 7

19. DVC Chandrapura Thermal Power Station 250 8

20. MPPGCL Satpura Thermal Power Station 250 10

21. UPRVUNL Harduaganj Thermal Power Station 250 8

22. PSPCL Guru Hargobind Thermal Plant 250 3

23. MAHAGENCO New Parli Thermal Power Station 250 6

24. CSPGCL DSPM Thermal Power Station 250 2

25. RRVUNL Suratgarh Super Thermal Power Station 250 1

26. RRVUNL Suratgarh Super Thermal Power Station 250 4

27. UPRVUNL Anpara Thermal Power Station 500 5

28. DVC Durgapur Steel Thermal Power Station 500 1

29. DVC Mejia Thermal Power Station 500 7

30. APGENCO Vijayawada Thermal Power Station 500 7

Total MW of Units Mapped 7460

Table 7: Details of Units Mapped

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5.1. Findings of Mapping Reports The studies revealed that most of the units are being operated at differed conditions than

the design parameters. These were mainly due to poor quality of coal, insufficient attention

to proper maintenance of boiler, turbine and other equipment, operating parameters different

from the rated values and obsolete instrumentation. One major factor which was affecting

most of the units was the backing down due to grid restriction. The units are forced to run on

a lower loading due to restrictions from grid. These have resulted in high heat rates and

unreliable plant operations. The savings potential from these 30 mapping reports have been

listed in table below.

Parameters 110-120 MW

125 MW 210 MW

250 MW

500 MW

Total (toe/yr)

No. of units in category

2 2 13 9 4

Short Term Potential ( 380578 toe)

MS pressure 2350 46 20363 3242 73 26073

MS Temp 860 43 4420 5078 2707 13106

RH Temp 1767 398 5584 3568 2573 13890

Condenser Vacuum

8365 409 55394 53027 15395 132591

UBC in Fly Ash 6934 0 37675 8742 5212 58562

UBC in bottom ash

1943 0 34247 8927 2345 47462

Makeup 0 0 21375 21257 7197 49829

Excess air 543 5414 1221 11696 20191 39065

Long Term Potential ( 782140 toe)

RH Spray 0 324 7612 2992 733 11660

SH Spray 42 23 4299 234 730 5328

Exit Gas Temp 1018 1494 50802 19625 9829 82768

Change in FW temp

359 2183 9768 8313 7306 27930

HPT Efficiency 5433 0 131322 23050 50203 210007

IPT Efficiency 108 0 23632 37332 40998 102069

LPT Efficiency 0 12295 80653 24697 73817 191463

HPH TTD 2604 0 27693 15060 77348 122705

HPH DCA 0 0 2879 1040 2523 6442

LPH TTD 5416 0 8253 0 4054 17723

LPH DCA 0 0 221 0 270 491

Coal Moisture 0 1382 1446 726 3554

Total 1162718

Table 8: Savings potential from 30 Mapping Reports

It can be observed that from these 30 mapping reports, a saving potential worth 1.16 million

tonnes of oil equivalent was revealed. The calculations of indices were done considering

85% PLF.

16 | P a g e

Capacity range of units (MW)

No. of units

Average Deviation of Boiler Efficiency(%)

Average Deviation of Turbine Heat Rate (%)

Average Deviation of Gross Heat Rate (%)

110-120 2 4.69 7.75 12.92

125 2 0.69 0.87 1.56

210 13 2.97 6.48 9.64

250 9 0.93 5.81 7

500 4 0.26 7.1 6.08

Table 9: Major variation (%) among important parameters from mapping reports

5.2. Reasons for high operating gross heat rate The heat rate improvement opportunities for existing units include reductions in heat rate

due to process optimization, more aggressive maintenance practice and equipment design

modifications. Opportunities exist in the boiler, turbine cycle and in the heat rejection

system. The overall level of heat rate improvement which can be achieved varies with unit

design, maintenance condition, operating conditions and type of coal.

Major reasons for the high operating gross heat rate are:

Load factor: The heat rate of a coal-fired power plant represents the amount of heat,

typically in kcal/kg, needed to generate 1 kilowatt-hour (kWh) of electricity. Accordingly,

typical units for heat rate are kcal/kWh. For a given power plant, heat rate depends on the

plant’s design, its operating conditions, and its level of electric power output. Loading factor

decides the upper limit of heat rate once the unit is in operation. For a selected design set of

parameters a unit gives power at different heat rates at different loads. The loading factor is

so important that a supercritical unit operating at 70 % loading factor will be no better than a

subcritical power plant operating at 100% loading factor.

In case of 30 units mapped, the average operating loading of 110-120 MW,125MW, 210

MW, 250 MW and 500 MW plants are 89.8%,100%, 94.48%, 98.67 % and 100%

respectively. Thus it is evident from the above that in the case of units mapped, the low load

factor was least responsible for deterioration in heat rate.

Boiler combustion optimization: The boiler is an important system to be looked for

improvement in heat rate. The operating conditions in a typical pulverized coal fired boiler

can be controlled by adjusting the fuel-air ratio, mixing patterns of coal, flow of combustion

air and adjustment of O2 level. Adjusting these parameters affects combustion efficiency,

steam temperatures, slagging and fouling patterns and furnace heat absorption, which in

many boilers in turn have significant effects on unit heat rate and emission level.

In case of 30 units mapped, the boiler efficiency ranged from 82 % to 86 %. Around 19.6 %

energy loss are accounted due to deteriorated boiler performance.

Sootblowing optimization: Slagging and fouling deposits on the heating surfaces strongly

affect heat absorption pattern in pressure parts, steam and flue gas temperature and unit

17 | P a g e

heat rate. Sootblowing optimization helps in improving the optimum sootblowing strategies

which prevent built up of soot and slag deposits and improve the heat rate.

In most of the mapped soot blowing is done on fixed periodicity and also LRSBs are not in

operation. Thus sootblowers should be used on need basis in every shift in furnace zone

and the LRSBs should be operated as required.

Degradation in Turbine Performance: The performance of turbine deteriorates over time

due to nozzle and blade erosion, seal leakage and periodic turbine outages. One of the

techniques used to prevent excessively high steam temperatures for HPT and IPT is to

spray water into the steam. Water for spray are taken from the turbine cycle and result in an

increase in heat rate. Consequently, attemperation spray flow rates should be the minimized

to the design limit to control steam temperatures.

Turbine efficiency is deteriorated a considerable amount compared to design, in respect of

units mapped around 43.3 % energy losses is attributable to this account.

Low condenser vacuum: As the steam temperature in the condenser increases above

design limit, the back pressure increases, which results in reduction in MW generation and

leads to increase in cycle and unit heat rate. Units where heat is rejected to river water,

condenser pressure can increase due to increase in river water temperature and/or

condenser fouling. Units having cooling towers, the back pressure can increase due to facts

such as condenser fouling, cooling tower performance deterioration, and increases in

ambient temperature and humidity.

In case of 30 units mapped, approximately 11.4 % losses are accounted from the deviation

of condenser vacuum.

Feedwater Heater performance: Thermal performance losses occur in feedwater heaters.

These controllable losses frequently occur because of poor performing level controls. The

problems can range from something as simple as inaccurate or fluctuating readings across

several instruments that leave the real level in question to those that justify taking a

feedwater heater out of service. Regardless of the severity, poor feedwater heater level

control effects overall boiler and turbine cycle efficiency (i.e. increase in unit or turbine cycle

heat rate). The higher the feedwater temperature, the lesser fuel is required to produce the

steam used to produce electricity in the steam turbine. However, steam is extracted from

different locations from the steam turbine for feedwater heating, which increases the plant

heat rate. The net effect of feedwater heating using extraction steam is a reduction in the

plant heat rate.

The energy loss calculated to be around 12.67 %, on account of feed heater performance of

30 units mapped.

Air heater Performance: Poorly maintained air heater degrades the heat rate. As a unit

ages, the percentage of air leaking past the seals increases, which lowers the plant

efficiency due to the increase of air flow sent through the FD fans to maintain sufficient O2

levels in the boiler. Worn-out/choked heating elements, improper seal clearances, damaged

sector plates and side sealing plates, air ingress due to damaged expansion bellows,

improper sealing of inspection holes results in the poor air preheater performance. Thus

18 | P a g e

increase in flue gas pressure drop, reducing the air heater leakage can decrease the plant

heat rate.

In case of 30 units mapped APH leakage varies from 4 % to 20 % and the energy loss due

to change in exit gas temperature is found to be 7.12%.

Makeup flow: Makeup is the quantity of water that is lost from the cycle during operation.

Losses bsetween 0% to 3% are normally acceptable for a cycle make up to offset cycle

losses which may be on account of various leakages in the system; boiler blow down, soot

blowing and valve passing. The additional make up flow result in higher feed water thermal

duties which causes additional extraction flows and higher pump duty requirement, in turn

increase the heat rate.

The heat rate deviation for make-up is an approximation, as the location in the cycle of each

loss is not known, therefore, the exact heat rate deviation is not known. The energy loss due

to make up water consumption works out to be 4.29 % in case of 30 units mapped.

High Moisture Coal and Reduced Stack Temperature: High moisture levels in coals have

several adverse impacts on the operation of a pulverized coal generating unit, for they can

result in fuel handling problems and they affect heat rate, stack emissions and maintenance

costs. By using the waste heat to reduce coal moisture before pulverizing the coal can

provide heat rate benefits. The degree to which performance improves depends strongly on

the degree of drying. Opportunities also exist to condense moisture from flue gas by

reducing flue gas exit temperature. Captured sensible and latent heat can be used to

improve unit heat rate through efficiency improvements both in the boiler and turbine cycle.

It is found that the moisture percentage is closer to design limit in almost all the plants, so

this factor cannot be attributed to energy loss in case of 30 units mapped.

Fig 6: Gap analysis for major heat loss areas

11%

20%

43%

13%

13% Condenser

Boiler

Turbine (HPT+IPT+LPT)

Heater

Minor losses

19 | P a g e

Deterioration in turbine and heater performance, degradation in condenser vacuum and

boiler performance contributed major energy losses as shown in figure above. The minor

loss area consists of main steam and reheats parameters, make-up water, superheater and

reheater spray, and feedwater temperature. The analysis made in Figure 4.1 should be

taken as guiding factor while making investment/ expenditure planning for energy efficiency

interventions.

5.3. Recommendations for Improving Energy Efficiency

Since each plant has its own operational features and design parameters, recommendations

to improve the performance and energy efficiency of the plant have been made for each of

the units. The recommendations made cover maintenance and operational aspects. The

inputs for arriving at recommendations are (i) observations at site, (ii) available information

with project engineers including plant’s operation and maintenance history and (iii)

deviations in operating parameters determined by Ebsilon® Professional model depicting

component behavior with change in boundary conditions relating to important operation

parameters. The recommendations have been divided into two categories namely: Short

term and Long Term

The short term recommendations are those which mostly relate to operating practices and

minor maintenance intervention, can be implemented immediately at lesser cost, permitting

picking up of low hanging fruits. The long term recommendations are those which can be

implemented during overhaul/ forced outage etc. and would require higher quantity of

resources.

Emerging out from experience of mapping of 30 units, it can be concluded that instead of

following ad-hoc approach in energy efficiency in thermal power plants, adoption of Systems

Approach for Efficiency Management is the need of hour. It would call for focus on systems

& procedures for good Operation & Maintenance practices. The following need to be

institutionalized for continual improvement in energy efficiency:

Energy Efficiency Management System

Advanced tools, technologies & systems

Skill development and training

Documentation and guidelines & awareness program

Maintenance Management System

Outage Management and Planning system

IGEN Phase- II has provided opportunities to State Generating companies to attain

sustainability in application of analytical tools for planning and providing inputs and

interventions to minimize controllable losses in thermal power plants leading to achievement

of targeted energy efficiency level.

5.4. Impact of Mapping Reports

Similar to the case studies, 30 units also mapped their units as a part of IGEN activity and

prepared reports. The difference between the case study and the mapping reports are that

where the former was done with full support of consultant Steag, the later was done by the

plant on their own. The plants identified the gaps in their units and made recommendations

20 | P a g e

accordingly. They even implemented some of the measures they identified and achieved

savings. These savings quantified in terms of various decision parameters are mentioned in

the table below.

S.No.

Plant name Utility Name

Capacity


Improvement in Efficiency from operating (%)


1 Chandrapura CTPS

DVC 250 3.98 4.14 49.6

2 Chandrapura CTPS

DVC 250 4.05 4.22 38.5

3 Korba HTPS west

CSPGCL 210 11.12 12.51 134.3

4 Korba DSPM TPS

CSPGCL 250 0.51 0.51 6.8

5 NLC NLC 210 0.71 0.72 12.3

6 NLC NLC 210 5.64 5.97 99.3

7 Tuticorin TANGEDCO

210 1.90 1.94 23.6

8 GHTP PSPCL 250 0.81 0.81 7.6

9 Anpara TPS UPRVUNL 500 4.75 4.99 139.1

10 IB Valley OPGCL 210 1.79 1.82 23.2

11 Gandhinagar TPS

GSECL 210 2.68 2.76 17.1

12 Satpura MPPGCL 250 5.35 5.65 64.3

13 SGTPS MPPGCL 210 5.31 5.61 63.2

14 Surat Lignite GIPCL 125 2.42 2.48 16.0

15 Surat Lignite GIPCL 125 1.38 1.40 11.4 Table 10: Achievements of units that prepared case study reports

The above mentioned savings leads to a CO2 emission reduction of 0.945 million tonnes per

year with an equivalent monetary savings of 282 Crore INR. This is a huge savings and the

biggest achievement is that the plants have done this on their own part. It can also be said

that from a capacity of 3470 MW (sum of capacities mentioned in table above), a savings

worth 0.945 million tonnes of CO2 emission reduction was achieved.

21 | P a g e

6. Implementation of exemplary saving measures in three selected plants

(Model Power Plants)

To make the recommendations of case study and mapping reports viable and practical, the

Model Power plant activity was conceived. The aim of Model Power plant was to

demonstrate the recommendations by implementing the mainly short and medium term

measures. These measures basically consisted of better operation and maintenance

practices and energy efficiency measures. The activities of Model Power plant resulted in an

average efficiency increase of 2.7% (0.9% points). This means an annual savings of 0.18

million tonnes of CO2 or 0.12 million tonnes of coal. This analysis was done from 3 units with

a total capacity of 920 MW.

Moving forward with the concept, four thermal power units were identified in close steering

with CEA, for model power plant activity. These were:

1) Bhusawal TPS, Unit #3, 210 MW

2) Mettur TPS, Unit#1, 210 MW

3) Durgapur Steel TPS, Unit 1, 500MW

4) Giral Lignite TPS, Unit#1, 125 MW

6.1. Approach

Steps taken to identify energy efficiency improvements areas and measures and

quantifiable energy saving on account of implementation of select recommendations

Gap identification and analysis based on:

Assessment of unit based on data/documents collected from the plant, hot walk

down survey and comparing different conditions or modes of operation

Assessment of the impact of individual equipment performance’s variation on

overall plant working/performance.

Thermodynamic analysis of the unit with the help of Ebsilon® Professional

Identification of potential areas of improvement and detailing out recommended

measures for energy efficiency improvement.

Assistance to the plant in implementation of agreed energy efficiency measures.

6.2. Identified gaps in Energy Efficiency area Most of the gaps identified were somewhat common for all plants. Additionally, some plants

had their typical area of improvement. Some of gaps common to all plants are listed below:

Partial load operation: This was prevalent in almost all the plants. The units had to run on

lower loading due to external reasons, mainly restriction from the grid. However, at some

plants, it was also due to their internal factors like low vacuum, unavailability of fuel, etc..

This affects the heat rate significantly.

Coal: In most of the plants the availability and quality of coal is the biggest issue. The

designed coal is not available and the coal sourced from other places doesn’t meet design

requirement. This not only leads to a higher heat rate but also deteriorates equipment in

22 | P a g e

long run. A higher ash content in coal leads to problem in ash handling system. Also, as the

availability of coal became a problem in near past, the coal sourced from other/ far sources

increased the generation cost.

Low Vacuum: This was mainly due to deposits in the condenser. Also the performance of

cooling tower was affecting this. At some plants the cooling water pump was also

responsible for low vacuum.

Air fans: The primary, secondary and induced draught fans were operating at their maximum

margins. This was due to many reasons, such as, leakages in the ducts, air preheater, high

ash content in coal (leading to high erosion in ID fan impeller and deterioration of

performance),

Boiler combustion: In almost all the plants, the problem of combustion appeared. The fuel-

air ratio, mixing patterns of coal, flow of combustion air and adjustment of O2 level, were not

optimum. This affected the combustion efficiency, steam temperatures, slagging and fouling

patterns and furnace heat absorption.

Unburnt Carbon: Due to improper combustion, poor milling performance, inadequate fuel air

ratio, coal quality, the unburnt in fly ash as well as bottom ash was on higher side. This

resulted in waste of energy ultimately leading to higher heat rate.

Soot blowing optimization: Deposits on the heating surfaces was found in the boiler. This

strongly affected heat absorption pattern and led to improper temperature distribution in

pressure parts, steam and flue gas temperature.

Air heater performance: Air leakages in seals were observed which lowers the plant

efficiency due to the increase of air flow sent through the FD fans to maintain sufficient O2

levels in the boiler. Worn-out/choked heating elements, soot deposit, improper seal

clearances, damaged sector plates and side sealing plates, air ingress due to damaged

expansion bellows, improper sealing of inspection holes were also observed.

Degradation in turbine performance: Deterioration of turbine performance and hence higher

heat rates were observed. While the exact influence on turbine can be determined when it is

opened, the inference from the operating parameters and the Ebsilon® Professional model,

was that there might be chances of nozzle/ blade erosion and seal leakages. The last

stages of LP rotor might also be having deposits.

Feedwater heater performance: Variation in the effectiveness of feedwater heaters from the

design was observed. This was due to improper extraction parameters, leakages in internals

of heaters. At some plants, the drip was not maintaining and the heaters were getting

bypasses. Also, some were avoiding the use of heaters in the circuit. These all resulted in

thermal loss.

Makeup water: Makeup water was observed high in plants. It was mainly due to various

leakages in the system; boiler blow down, soot blowing and valve passing. The additional

make up flow resulted in higher feed water thermal duties which cause additional extraction

flows and higher pump duty requirement, in turn increasing the heat rate.

23 | P a g e

Superheater and reheater spray: the spray was observed on higher side. This caused higher

make up water requirement. Also, it contributed to a significant heat loss.

Insulation and cladding: In some plants, insulation was also one of the reasons of heat loss.

Damaged insulation in some of the locations such as ducts, steam pipes, etc. resulted in

higher heat loss and also results in poor performance of certain equipment.

5.3. Measures Recommended

Based on the gap analysis in each plant, recommendations were made. These

recommendations were presented before the plant management and an action plan was

agreed upon. They were mainly divided into two categories, namely short term and long term

recommendations. The short term recommendations are those which mostly relates to

operating practices, can be implemented immediately at lesser cost, permitting picking up of

low hanging fruits. The long term recommendations cover overhauling and retrofit in the

plant. Some of the recommendations are mentioned below

Partial load operation: Partial load due to internal reasons can be controlled by proper

maintenance of equipment reducing breakdowns, and increasing individual equipment

efficiency.

Coal: To improve coal quality coal blending should be practiced- a) internal blending and b)

external blending. Use of blended coal in proper ratio can improve combustion efficiency.

This will also average the generation cost by decreasing heat rates. Proper selection of mills

in case of internal blend will also improve performance parameters. Mill load biasing to be

done based on GCV of imported coal to avoid clinkering and slagging.

Low Vacuum: Condenser cleaning needs to be done in most cases. Condenser vacuum can

be improved by high pressure jet cleaning and scale removal. Online tube cleaning system

can be installed to have regular cleaning. Tube leakages can be attended. Performance of

individual cooling tower cell to be restored by taking necessary repair work one by one in the

running unit.

Boiler combustion: Mill combination to be checked and control the fuel air damper and aux

air damper to maintain furnace left-right uniform temperature and avoid high variation in

furnace temperature.

Soot blowing optimization: Soot blowing to be made a regular practice. Usages of LR soot

blowers to be adopted to ensure adequate cleaning of Ist and 2nd pass. LRSB’s to be

operated once a week.

Air heater performance: Improved monitoring of combustion regime and APH performance

shall reduce flue gas temperature leaving air heater and reduce boiler losses. For improving

APH’s performance APH soot blowing to be done regularly. Additional zirconia probes can

be installed at inlet of each APH to get better insight into excess air at which optimum boiler

operation is being achieved. Air ingress across seals to be controlled. APH baskets to be

checked and replaced during overhaul.

24 | P a g e

Degradation in turbine performance: To improve HP and IP turbine efficiency complete

overhauling of turbine is desirable. Turbine first stage pressure was high in some units which

indicate salt deposits. To rectify this, overhauling of complete turbine is recommended.

Feedwater heater performance: The terminal temperature difference of HP heaters in some

plants was observed to be negative, which is impossible. This is due to faulty measuring

instruments and needs calibration during shutdown.

Makeup flow: Makeup water consumption to be monitored periodically using deaerator drop

test. Isolation checklist to be developed for periodic checking to eliminate passing of drains,

control valves and isolation valves, thereby minimizing heat rate loss.

Superheater and reheater spray: SADC operation should be modulated to achieve better

control of furnace exit temperature and to reduce spray

Insulation and cladding: Insulation to be restored during running /opportunity shutdown as

may be possible to reduce heat loss.

5.4. Conclusion and Findings As a result of implementation of measures, there was a significant improvement in heat rate

thereby leading to improvements in efficiency. The table below gives an overview of

improvements in parameters.

ITEM Unit Initiated by IGEN

Due to change in Coal Quality

Unaccounted Overall

Heat Rate Improvement (from operating) %

2.77 1.55 0.42 4.74

Efficiency Improvement (from operating) %

2.86 1.58 0.57 5.01

Energy toe/year 40002.06 21332.45 6234.62 67569.13

Coal Savings t/year 119757.15 65026.52 18156.78 202940.45

CO2 Savings t/year 176530.85 91910.70 27698.03 296139.58

Monetary Savings Cr Rs./Year 40.62 21.66 6.28 68.56

Monetary Savings Mio Euro/year

5.80 3.09 0.90 9.79

Table 11: Achievements of model power plant

It can be observed from the table above that with the activities on these plants, 296

thousand tonnes of CO2 emission reduction per year was achieved. This meant a savings of

Rs. 68.5 Crores per year.

Apart from the direct improvement in heat rates and savings, an improved O&M practices

have been developed in regard to, heat rate deviation monitoring, mill performance

monitoring & testing, coal blending process, air ingress survey across flue gas path,

strengthening on line measurement scheme across air heaters, soot blowing, condenser

tube cleaning, strengthening on line measurement across regenerative feed water heaters,

combustion stability.

25 | P a g e

7. Implementation of a demonstration boiler performance optimization

system (BPOS)

Apart from the model power plants, one unit of Suratgarh super thermal power plant was

undertaken for implementation of state of art Boiler performance optimization system

(BPOS) as pilot project. BPOS is an intelligent soot blowing software which optimizes the

entire process of soot blowing. This leads to an improvement in boiler efficiency thereby

leading to a better heat unit rate and efficiency.

The main objective was to demonstrate and assess the technical viability and financial

attractiveness for retrofitting Indian power plants with online BPOS in closed loop mode for

reducing the environmental pollution and greenhouse gases and document the lessons

learned. The system was implemented in 250 MW Unit#6 of Suratgarh Super Thermal

Power Station (SSTPS) of Rajasthan Rajya Vidyut Utpadan Nigam Ltd (RVUN).

Duration of the project was 9 months. Project was started in December 2013 with kick off

meeting at site and site acceptance test was carried out successfully in August 2014. The

commissioning of the system and necessary modification of DCS has been done during

operation of the unit without any unit shutdown.

In a coal-fired boiler, the deposition of ash and soot on the boiler tubes can lead to a

reduction in boiler efficiency. Thus, cleaning of heating surfaces is one of the most important

boiler auxiliary operations for boiler efficiency optimization. BPOS has first principle based

thermodynamic boiler model which calculates efficiency of the heating surfaces. The

cleaning of the furnace is done automatically based on these calculated results and not on

time basis.

7.1. Approach

Prior to this project the control and instrumentation related to soot blowing were usually

treated as isolated systems and performance of the boiler was calculated manually. The

following stems were undertaken for installation and commissioning of this demonstrational

project of BPOS under IGEN Phase-II.

i) Plant basis data collection and analysis

ii) System installation and data acquisition.

iii) Preparation of thermodynamically boiler model and installation on site

iv) Commissioning in open loop

v) Commissioning in closed loop.

The activities were started with the signing of MoU between GIZ and RVUN at CEA’s office

and handing over of license. At various stages the OEM was also involved and several

discussions were held. The demonstrational project was completed with the successful

commissioning and site acceptance test.

7.2. BPOS System Description

Boiler performance Optimization System is an online performance monitoring and

optimization system for the Boiler operation.

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The main modules covered under BPOS system is given below:

Data Management System (SRx) with Data Visualizer (SRxVIS)

Data Validation System (SRv)

Boiler Performance Monitoring System (SR::BPOS)

Soot Blowing Optimization System (SR::BCM)

Boiler Offline What-If Analysis (SR::What if)

Excel Reports

Ebsilon® Professional Thermodynamic Boiler calculation

For the evaluation of boiler operation a detailed thermodynamic model of the relevant boiler

components has been built by powerful software program Ebsilon® Professional.

Ebsilon® Professional runs in the background and interfaces with SRx to get the

measurement values and writes the results. All relevant model results are available in

process screens of BPOS.

Within Ebsilon® Professional the model has been configured graphically (Fig. 6 & 7) during

its implementation. Boiler has been constructed from the main components available in

Ebsilon® Professional like heating surfaces, injections, combustion chamber as well as the

connecting pipes.

System Modules

The Figure below shows the basic, optimization and performance analysis modules of

BPOS. All the modules interface with central Data Management System to take data and

write back the results. The sequence of operation is following.

Data from DCS is collected in Data Management System. Collected data is validated by

Data validation module. Validate data is taken by boiler model, boiler efficiency and other

performance parameters are calculated by boiler performance monitoring module. The

results are presented in excel reports. Soot blowing optimizer uses these results to generate

soot blowing recommendation. Boiler What-if Analysis module is an offline tool which is used

on used demand.

Figure 7: BPOS Modules

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Hardware Description

The figure below shows the system configuration of BPOS at Suratgarh.

Figure 8: BPOS Hardware

There is one BPOS server connected to DCS network through a Firewall and total three

numbers of BPOS clients are connected to BPOS sever. BPOS server and one client is

located in engineering room while two BPOS client have been installed in control room.

RVUN has provided a broadband connection which has been also connected to BPOS

server through firewall.

7.3. Conclusion and Benefits

Monitoring

After the successful completion of BPOS the results were compared. Two time periods have

been selected for analysis of the data. The first time period is from 6th to 17th June which is

the time period before commissioning of BPOS. The second time period is from 20th to 30th

August which is the time period after commissioning of BPOS. The selection of both periods

was made to ensure that the boiler has been operated under similar conditions in respect to

load, ambient temperature and the coal GCV. Additionally both periods should have the

same duration. Report was generated from BPOS system for the above mentioned periods.

28 | P a g e

Screenshots of the two reports is shown here as Fig. 14 & 15. Transient state data has not

been taken into consideration for comparison of above periods. The average values of unit

load and boiler efficiency shown in the below table has been taken from generated BPOS

reports.

For the comparison of boiler efficiency the actual value of efficiency in the period after BPOS

has been corrected to take into account the different conditions.

Benefits

a) Boiler Efficiency Improvement - Suratgarh Unit-6 already operates with high boiler

efficiency which is even better than the design. Despite of this the improvement in

efficiency by 0.18% has been achieved by use of BPOS.

b) Heat rate Improvement - the improvement of unit heat rate due to improvement of boiler

efficiency by 0.18 % amounts to 4.54kcal/kWh in case of this unit.

c) Monetary savings - The improvement of efficiency leads to reduction of coal needed for

the generation of same amount of power. Considering that the coal burnt in Unit No. 6

cost Rs. 5000/ton, an efficiency improvement of 0.18 percent means decrease in coal

consumption by 1989.46 tons/year for a savings of Rs. 99.47 Lac per year.

d) Environmental Savings - The improvement in the boiler efficiency has the positive

impact on environment as well. The reduction of coal consumption for the same

generated output leads to reduction of environmental pollution and greenhouse gases.

Given that the saving of coal per year is 1989.46 tons/ year and carbon percentage in

coal used in Suratgarh is 47.2 %, the saving of CO2 emission amounts to 3441 tons per

year.

e) Improving Operational Practices - The installation of BPOS improved the operational

practices. The cleaning of furnace is now carried out automatically based on requirement

from thermo dynamical point of view.

f) Automatic Efficiency Reporting by Email – Reports with all relevant boiler parameters

are automatically generated and sent by email to plant officials on daily basis. Thus the

information is readily available at the user desk.

g) Offline What-If Analysis – Plant engineers can examine now the impact of different

operational scenarios on efficiency before their implementation during the real operation.

h) Thermodynamic transparency of the boiler – BPOS calculates online parameters

such as efficiency of the heating surfaces, temperature profile on the flue gas side and

air ingress to furnace. These parameters are not available in the DCS systems and

cannot be obtained without a boiler model.

29 | P a g e

i) Measurements validation – BPOS provides the information about the quality of the

measurements and provide replacement values for bad sensors so that calculations are

done with high accuracy and availability.

j) Lifetime Storage of Data - BPOS is capable of storing the data for the lifetime of the

power plant and data can visualized very quickly. Thus analysing of boiler operation from

overhaul to overhaul can be done very easily.

Conclusion

It is known that if the boiler is kept clean, its efficiency will increase on account of better heat

transfer. Where, practicing soot blowing daily or once in a shift increases the steam

consumption, avoiding soot blowing will invite depositions on boiler tubes ultimately leading

to improper heat transfer. Hence, it becomes utmost important to use the soot blowing

operation when and where it is needed the most.

The above result clearly shows this advantage of BPOS over conventional practice of soot

blowing.

The situation before BPOS differed a lot in terms of practice. The soot blowing operation was

done manually. Wall blowing was done selectively depending on the availability of wall

blowers and frequency varied from weekly to fortnightly. If lower mills are in operation, wall

blowing is avoided so that reheat temperature does not go down further. Frequency of soot

blowing in LRSB varied from fortnightly to monthly.

The situation after BPOS became more optimised where the soot blowing was controlled in

close loop of BPOS. The system generated commands of soot blowing depending upon the

need in specific areas. This optimised the steam and time consumption. Also, it avoided the

depositions in boiler and resulted in higher boiler efficiency.

30 | P a g e

Abbreviations

APH Air preheater TTD Terminal temperature

difference

AUX Auxiliary UBC Un-burnt carbon

BFP Boiler feed pump WW Water wall

BA Bottom ash WB Wind box

CEP Condensate extraction pump WBT Wet bulb temperature

CHP Coal handling plant GHG Greenhouse gas

CO

COH

Carbon monoxide

Capital overhaul

PPOC Power Plant Optimization

Component

CO2 Carbon dioxide IGEN Indo German Energy

Programme

CW Cooling water CEA Central Electricity Authority

DCS Distributed control system SB Soot blower

DCA Drain cooler approach toe Tonnes of oil equivalent

DM Demineralised

ESP Electro-static precipitator

EA Excess air

FA Fly ash

FD Forced draft

FG Flue gas

FW Feed Water

GCV Gross calorific value

HBD Heat balance diagram

HGI Hard groove index

HPH High pressure heater

HPT High pressure turbine

ID Induced draft

IGV Inlet guide vane

IPT Intermediate pressure turbine

KVA Kilo volt ampere

LPH Low pressure heater

LPT Low pressure turbine

LTSH Low temperature super heater

LMTD Log mean temperature difference

mmHg Millimetre of mercury

mmwc Millimetre of water column

MS Pressure Main steam pressure

MS Temperature Main steam temperature

MU Million unit

PA Primary air

PLF Plant load factor

PPD Predicted performance data

R&M Renovation and Modernization

RH Reheater

RPM Revolution per minute

RW Raw water

31 | P a g e

Annexures

Annexure 1: 85 Units Mapped under IGEN Phase I

Sl No. State Board/ Electricity Gen. Company


Unit No

1 PSEB Gurunanak Dev. Thermal Power Plant, Bathinda

110 2

2 MAHAGENCO Khapar Kheda Thermal Power Plant 210 1

3 WBPDCL Kolaghat Thermal Power Plant 210 3

4 TNEB Mettur Thermal Power Plant 210 1

5 MAHAGENCO Nasik Thermal Power Plant 210 3


7 OPGLC IB Valley Thermal Power Plant 210 1

8 PSEB Guru Hargobind Thermal Power Plant 210 1

9 NLCL Neyveli Lignite Corporation 210 3

10 NLCL Neyveli Lignite Corporation 210 7

11 MBEB Satpura Thermal Power Plant 210 7

12 RSEB Suratgarh Thermal Power Plant 250 1

13 TNEB Tuticorn Thermal Power Plant 210 1

14 MAHAGENCO Chanderpur Thermal Power Plant 500 6


16 MAHAGENCO Koradi Thermal Power Plant 200 5

17 WBPDCL Bandel Thermal Power Plant 210 5

18 MAHAGENCO Bhusawal Thermal Power Plant 210 3

19 CSEB Korba Thermal Power Plant 210 4

20 PSEB Guru Gobind Singh Thermal Power Plant 210 6

21 GSECL Ukai Thermal Power Plant 210 5

22 TNEB North Chennai Thermal Power Plant 210 1



25 DVC Bokaro Thermal Power Plant 210 1

26 GSCEL Wanakbori Thermal Power Plant 210 4

27 GSCEL Wanakbori Thermal Power Plant 210 3

28 DVC Durgapur Thermal Power Plant 210 5

29 DVC Meja Thermal Power Plant 210 4

30 APGENCO Vijayawada Thermal Power Plant 210 1


32 CSEB Korba East Thermal Power Plant 120 6



35 UPRVUNL Obra Thermal Power Plant 200 13



38 APGENCO Rayalseema Thermal Power Plant 210 1

39 WBPDCL Bakreshwar Thermal Power Plant 210 2

40 MAHAGENCO Parli Thermal Power Plant 210 3

41 KPCL Raichur Thermal Power Plant 210 3

42 KPCL Raichur Thermal Power Plant 210 4



32 | P a g e

Sl No. State Board/ Electricity Gen. Company


Unit No


46 UPRVUNL Paricha Thermal Power Plant 210 3


48 GSECL Dhuvaran Thermal Power Plant 140 5

49 GEB Gandhinagar Thermal Power Plant 120 2

50 GSECL Wanakbori Thermal Power Plant 210 1

51 TVNL Tanughat Thermal Power Plant 110 2



54 GIPCL Surat Lignite 125 2

55 GSECL Sikka Thermal Power Plant 120 1

56 DVC Chandarapura Thermal Power Plant 140 3

57 MPPGCL Sanjay Gandhi Thermal Power Plant 210 1

58 MPPGCL Amarkantak 120 3

59 WBPDCL Santaldhi Thermal Power Plant 120 1

60 DVC Durgapur 140 3


62 APGENCO Rayalseema Thermal Power Plant 210 3

63 OPGCL IB Valley Thermal Power Plant 210 2


65 UPRVUNL Panki Thermal Power Station 105 4

66 RVUNL Kota Thermal Power Plant 110 2

67 RVUNL Kota Thermal Power Plant 210 4


69 TNEB North Chennai Thermal Power Plant 210 4

70 TNEB Mettur Thermal Power Plant 210 4

71 TNEB Ennore Thermal Power Plant 110 5

72 MAHAGENCO Chandarpura Thermal Power Plant 500 7

73 MAHAGENCO Koradi Thermal Power Plant 210 6

74 PSEB Bathinda Thermal Power Plant 110 1


76 CSEB Korba Thermal Power Plant 210 2

77 PSEB Ropar Thermal Power Plant 210 2

78 PSEB Ropar Thermal Power Plant 210 3

79 MAHAGENCO Kapar Kheda Thermal Power Plant 210 2



82 RUVNL Kota Thermal Power Plant 195 6


84 RSEB Suratgarh Thermal Power Plant 250 2


Total 14285

33 | P a g e

Annexure 2: Formulae and Calculations Gross generation = G kW Reduction in TG heat rate = A kcal/kWh (From Model Analysis) Boiler efficiency = B % (From Model Analysis) Gross calorific value =GCV kcal/kg Cost of fuel = Cf Rs/tons Reduction in heat Input to boiler (HinBoil) = (G*365*24*PLF*A) / B Reduction in fuel consumption (Fcon) = HinBoil / GCV (kg) = HinBoil / GCV /1000 (tons) Monetary saving = Fcon* Cf/10000000 Crores of Rs. = (Fcon* Cf /70)/1000000 million € C + O2 = CO2

Carbon in Coal = XC 1 kg of fuel = (44/12)* XC of CO2 Total CO2 savings (tonnes/ year) = (44/12)* XC *coal savings per year Coal savings (tonnes/ year) = (ΔHR/ coal GCV) *load* 8760 * PLF Tonnes of oil equivalent (toe) per year = (ΔHR/ oil GCV) *load* 8760 * PLF Average coal GCV = (coal GCV before + coal GCV after)/2 Average carbon % in coal = (carbon % before + carbon % after)/2

References

1. http://en.wikipedia.org/wiki/List_of_countries_by_electricity_production 2. CEA- Growth of Electricity Sector in India from 1947-2013

http://www.cea.nic.in/reports/planning/dmlf/growth.pdf 3. CEA- Executive Summary Feb-2015

http://www.cea.nic.in/reports/monthly/executive_rep/feb15.pdf 4. CEA- Executive Summary Mar-2015

http://www.cea.nic.in/reports/monthly/executive_rep/mar15.pdf 5. The Final Report of the Expert Group on Low Carbon Strategies for Inclusive Growth

http://planningcommission.nic.in/reports/genrep/rep_carbon2005.pdf 6. Model Power Plant Reports IGEN Phase-II_ Durgapur TPS 7. Model Power Plant Reports IGEN Phase-II_ Bhusawal TPS 8. Model Power Plant Reports IGEN Phase-II_ Mettur TPS 9. Model Power Plant Reports IGEN Phase-II_ Giral TPS 10. Report on Introduction of Measures for improved PLF and availability 11. Case Study Reports IGEN Phase-II 12. Compendium of Case Studies IGEN Phase-II 13. Mapping Reports IGEN Phase-II 14. Summary of mapping Reports IGEN Phase-II 15. Feedback templates from utilities 16. Presentations of utilities from IGEN Conclave, January 2014

http://en.wikipedia.org/wiki/List_of_countries_by_electricity_production

http://www.cea.nic.in/reports/planning/dmlf/growth.pdf

http://www.cea.nic.in/reports/monthly/executive_rep/feb15.pdf

http://www.cea.nic.in/reports/monthly/executive_rep/mar15.pdf

http://planningcommission.nic.in/reports/genrep/rep_carbon2005.pdf

34 | P a g e

Imprint

The findings and conclusions expressed in this document do not

necessarily represent the views of the GIZ or BMZ.

The information provided is without warranty of any kind.

Published by

Deutsche Gesellschaft für

Internationale Zusammenarbeit (GIZ) GmbH

Indo German Energy Programme (IGEN)

Power Plant Optimisation Component

Registered offices: Bonn and Eschborn, Germany

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