Performance enhancement of old thermal power stations using software tools

Transcription

1 EEC Workshop - 29th August, New Delhi Performance enhancement of old thermal power stations using software tools Dr. J T Verghese Managing Director STEAG Energy Services, India

2 STEAG Energy Services India Business Lines Textmasterformate durch Klicken bearbeiten Zweite Ebene Dritte Ebene Vierte Ebene Fünfte Ebene STEAG Energy Services India offers services in the field of: Engineering Consulting Services Diagnostic Study and Testing Energy Audit Renovation & Modernization Consultancy Operation and Maintenance Information Technology for Power Plants New Technologies for Power Plants Advisory 2

3 STEAG Energy Services India Offices / O & M Sites Bathinda New Delhi Noida Ahmedabad Hazira Jharsuguda Haldia Hyderabad Corporate & Registered Offices of STEAG India Bangalore Chennai Regional Offices of STEAG India O & M Sites of STEAG India 3

4 Major Clients Many 4 more

5 O & M Projects S. No. Type Capacity Location Owner Scope Duration From To 1. CCPP 156 MW Hazira GSEG O & M CCPP 30 MW Gandhar ONGC O & M X 600 MW Coal Based Power Plant at Jharsuguda, Orrisa - India 3. CCPP 116 MW Haldia HPL O & M WHRP 30 MW Goa Videocon O & M Advisory Coal 4 X 600 MW Jharsuguda 6. CCPP 507 MW (156 MW MW) Sterlite Energy O & M Hazira GSEG O & M CCPP 165 MW Bathinda HMEL O & M CCPP Hazira, Gujarat - India 5

6 R & M and LE Mapping using Ebsilon Software to check the potential for efficiency improvement RLA Studies & Performance Evaluation Tests R&M Measures should include online software tools to optimize efficiency Techno-economic Analysis of R&M Measures Tendering and award of contract for R&M Preparation of technical and commercial specification for R&M 6

7 How to Improve Efficiency First Step: low hanging fruits Improve efficiency by improving operation and maintenance by the normal methods: Maintenance Planning Training Standard Operating Procedures Improve maintenance methods 7

8 How to Improve Efficiency Next Steps Audit or map the plant using offline modeling tool to detect causes for sub-optimal operations Provide online systems for optimization of resources fault detection and prediction lifetime monitoring for better planning of inspections and maintenance and calculation of life-time consumption Provide customized systems for maintenance planning 8

9 Audit or map the plant using off line modelling Summary of the mapping exercise conducted jointly by CEA and Steag under the Indo German Efficiency Program 9

10 Mapping of 85 power plants - EBSILON Design Model Performance as per design documents Analysis 1. Output 210 MW 2. Gross Heat Rate kcal/kwh 3. Coal Consumption 110 t/h 4. Boiler Efficiency Turbine Cycle Heat Rate kcal/kwh 6. Unit Efficiency 37.3% 10

11 EBSILON Running Model Analysis Simulated Performance as per operating GCV 1. Output 210 MW 2. Gross Heat Rate kcal/kwh 3. Coal Consumption 166 t/h 4. Boiler Efficiency 79.6% 5. Turbine Cycle Heat Rate kcal/kwh 6. Unit Efficiency 32.3% 11

12 85 Units Mapped Size-wise Capacity (MW) Number of Units Total 85 12

13 Analysis of 16 Units Under 16 Years of Age with Reaction Type Turbine Including Indicative Saving of Coal Analysis of 16 units under 16 years of age with reaction type turbine Indicative saving of coal 1200 th tons of consumed coal potentially per year conserved coal best If all the units would have the same gross heat rate as the most efficient unit, 8.6% of the coal, altogether 1,256,650 tons, approx. Rs crores would be saved by the 15 less efficient units each year. Assumptions: all the units work at a PLF of 80%, use coal with 4000 kcal/kg calorific value and 1ton coal costs Rs

14 Analysis of 16 Units Under 16 Years of Age with Reaction Type Turbine Analysis of 16 units under 16 years of age with reaction type turbine Indicative additional capacity million units 1200per year additional capacity million units/ year If all the units would have the same capacity as the unit with the highest capacity, the overall output would be by 9.7% or 2,173 million units higher each year. Assumption: all the units work at a PLF of 80%

15 Analysis of 16 Units Above 16 Years of Age with Reaction Type Turbine Analysis of 16 units above 15 years of age with reaction type turbine Indicative saving of coal 1,200 th tons of consumed coal potentially per yearconserved coal best 1, If all the units would have the same gross heat rate as the most efficient unit, 7.3% of the coal, 1,122,600 tons, approx. Rs 101 crore would be saved by the 15 less efficient units each year. Assumptions: all the units work at a PLF of 80%, use coal with 4000 kcal/kg calorific value and 1ton coal costs Rs U1 U2 U3 U4 U5 U6 U7 U8 U9 U10 U11 U12 U13 U14 U15 U16 15

16 Analysis of 16 Units Above 15 Years of Age with Reaction Type Turbine Analysis of 16 units above 15 years of age with reaction type turbine Indicative additional capacity million units 1200per year If all the units would have the same capacity as the unit with the highest capacity, the overall output would be by 8.1% or 1,807 million units higher each year. Assumption: all the units work at a PLF of 80% additional capacity million units/ year

17 Analysis of 17 Units Above 15 Years of Age with Impulse Type Turbine Analysis of 17 units above 15 years of age with impulse type turbine Indicative saving of coal 1,200 th tons of consumed coal per potentially year conserved coal best If all the units would have the same gross heat rate as the most efficient unit, 7.3% 1,000 of the coal, 1,122,600 tons, approx. Rs crore would be saved by the 15 less efficient units each year Assumptions: all the units work at a PLF of 80%, use coal with 4000 kcal/kg calorific value and If all the units would have the same gross heat rate as 1ton coal costs Rs the most efficient unit, 7.3% of the coal, 1,122,600 tons, approx. Rs crore would be saved by the 15 less efficient units each year Assumptions: all the units work at a PLF of 80%, use coal with kcal/kg calorific value and 1ton coal costs Rs U1 U2 U3 U4 U5 U6 U7 U8 U9 U10 U11 U12 U13 U14 U15 U16 U17 17

18 Analysis of 17 Units Above 15 Years of Age with Impulsive Type Turbine Analysis of 17 units above 15 years of age with impulse type turbine Indicative additional capacity million units 1200 per year If all the units would have the same capacity as the unit with the highest capacity, the overall output would be by 7.1% or 1,655 million units higher each year. Assumption: all the units work at a PLF of 80% additional capacity real U1 U2 U3 U4 U5 U6 U7 U8 U9 U10 U11 U12 U13 U14 U15 U16 U17 18

19 Auxiliary Consumption of 210 MW Capacity Units Auxiliary Consumption of 210 MW capacity units (%) 13 Auxiliary consumption (%)

20 Generally Observed Problems Systems Maintenance planning and management Observations Needs to be upgraded Online monitoring DCS Not provided Only some units have been provided Documentation Operating instruction and manual Needs improvement Needs to be updated 20

21 Online systems Provide Online systems for: optimization of processes fault detection and prediction system life time monitoring for better planning of inspections and maintenance and calculation of life time consumption. 21

22 Why to use the software tools? DCS has the information needed to do the calculation of efficiencies and heat rates it gives performance calculation, trending and values of parameters But what are the limitations? 1.DCS does not give the system wise efficiencies so you do not know where the losses occur 2.Data from I/O points e.g. Temperature, pressure mass flow could be wrong because of sensor errors, bad connectors etc. That makes calculation erroneous. 3.DCS does not give advice what to do 22

23 Online Tool: Optimization Sequence 1. All relevant data from DCS which goes into calculation need to be validated i.e. all implausible values have to be replaced by plausible values 2. All calculations must be done every 5 minutes (not only once a day) since the quality of coal and combustion process is changing. Threfore the state of heating surfaces must be monitored constantly. 3. Results are presented in a user friendly manner: Status of the subsystems is indicated by green, yellow, red and losses expressed in money terms. 23

24 PADO Screens 24/09/2008 ES- Page 24

25 PADO Screens Textmasterformate durch Klicken bearbeiten Zweite Ebene Dritte Ebene Vierte Ebene Fünfte Ebene 24/09/2008 ES- Page 25

26 PADO Controllable Losses (1) 26

27 PADO Set Point Optimization (1) 27

28 Modules of the On Line systems 28

29 Advantages of the Online Tool Improving the quality of measurements by data validation Evaluation of boiler, turbines, condenser and other components Optimization of unit operation (sootblowing, setpoints) Calculation of what-if scenarios Generation of daily and monthly reports Enhance the efficiency of the power plant! 29

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