Proceedings of 2000 International Joint Power Generation Conference Proceedings of Insert Conference Abbreviation: Miami Beach,Insert Florida, July 23-26, 2000 Conference Name Insert Conference Date and Location

IJPGC2000-15031

Paper Number Here

Combined Cycle Heat Recovery Optimization W. Stenzel- EPRIsolutions

A. Ragland, Vogt-NEM

ABSTRACT The US electrical power industry has changed from a regulated business where utilities were virtually guaranteed a rate of retum to an unregulated business where the market sets the price. As with any unregulated business, the price of a service or supply is determined by supply and demand, and the seller must be competitive in order to meet its desired revenue target. Profitability will largely be determined by the business' overall operating efficiency. As the electricity supply business becomes more competitive, it becomes more important to optimize fuel selection and plant design to achieve competitive electricity prices while providing a satisfactory financial return for owners and other participants. Plant designs need to be adjusted to the specific project parameters to achieve optimum results. Fuel costs, yearly plant outputs, interest rates and other factors need to be considered when establishing plant designs. Four plant designs are compared using natural gas in this paper. This paper will present a view of the cost benefits achieved through heat recovery steam generator (HRSG) optimization. The many possible business and technology scenarios, and site specific nature of each project makes it difficult, time consuming and costly to effectively optimize fuel selection, generating unit selection, efficiency, capital cost, and return on investment. Using computer tools is very important to properly handle these complex analyses. The use of the SOAPP Combustion Turbine Software as an analysis/decision support tool for optimizing combined cycle plants is described herein. INTRODUCTION Achieving financial improvements requires proper analysis of many requirements and parameters. Changing one input design parameter often results in modifications to other parameters. For example, changing the HRSG design changes efficiency, fuel cost, capital cost, debt financing, and emission rates. Often it is important to assess the impact of a range of inputs in the analysis. Combustion turbine performance has the primary impact on combined cycle plant efficiency. The next most important piece of equipment that impacts efficiency is the heat recovery steam generator. The HRSG parameters to optimize include steam pressures, temperatures, flows, pinch points, approach temperatures, and HRSG exit gas temperatures. HRSG BASIC DESIGN CONCEPTS Figure 1 is a typical cycle for a single pressure HRSG. Multiple pressure HRSGs with duct firing and other capabilities can become much more complicated. This diagram shows the main gas, steam, and condensate flows, and the typical HRSG surfaces and steam drums. Flue gas from the combustion turbine enters the HRSG and is reduced in temperature by the superheater, reheater, dram evaporative surfaces, and economizer before it enters the stack. Condensate from the combined cycle condenser enters the deaerator, and flows through the economizer to the drum. Steam from the drum flows to the superheater and then to the high pressure turbine. Steam from the high pressure steam turbine flows through the reheater and then to the intermediate pressure turbine. Pinch points and approach temperatures are important HRSG design parameters. Reducing these temperatures will increase cycle efficiency. However, optimization involves fairly complicated heat transfer calculations and steam cycle heat balances to avoid operational problems. Figure 2 provides a simple diagram showing pinch and approach temperatures:

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BASIC

DESIGN

CONCEPTS

The HRSG design first begins with the combined cycle systems engineer employed by the either the owner or the EPC. The systems engineer begins with a desire to meet the plant's required net electrical output (MW) and heat rate (BTUs/MW). The first decision to be made is the choice of gas turbine size. As a general guideline, the gas turbine will represent 66% of the plant's electrical output assuming that the HRSG does not employ a duct burner. The remaining output will be supplied by the steam turbine. For example, if the plant's requirement is 250 MW, then 165 MW would be supplied from the gas turbine and 85 MW would be supplied by the steam turbine. 60 Hz gas turbines currently available in the 165 MW class range are the GE's Frame 7FA, Siemens Westinghouse's 501F, Siemens' V84.3A, and ABB's GT24. If it is desired that the steam turbine supply an additional percentage of the plant's output, this can be increased up to 50% if a duct bumer is added• A steam turbine that supplies 50% of the output to a combined cycle plant using one of the aforementioned gas turbines would increase the plant's overall output from 250 MW to 335 MW. With the plant's size and gas turbine choice made, the combined cycle systems engineer proceeds next to determine the plant's heat rate. This becomes a tradeoff between capital cost and efficiency. The lowest cost option would be a one pressure level, non reheat HRSG resulting in relatively poor heat rate. To obtain better heat rates with associated higher costs the following ranking should be used:

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Costs

HRSG Type

Heat Rate

Low

1 Pressure Level, non reheat

High

Low to medium

2 Pressure Levels, non reheat

Med./High

Medium

3 Pressure Levels, non reheat

Medium

Medium to high

3 Pressure Levels, reheat

Med./low

High

3 Pressure Levels, reheat

Low

Optimizing pinch point and approach temperatures follows the selection of the pressure level. Decreasing the pinch point and approach temperature results in higher efficiency, but higher capital cost.

OPTIMIZATION METHODOLOGY Most combined cycle optimizations should follow the steps summarized below: •

• • • •

Determine the plant goals; e.g., the amount and value of the power, emission limits, fuel availability and costs, transmission requirements and/or limitations, forecasted generation load schedules, target electricity market price and/or other requirements and goals. Identify new plant requirements for meeting the generation goals. Develop the initial design, operation parameters, capital costs, schedules and economics. Obtain the necessary equipment and construction bids. Select the best option(s) based on economics and other factors.

Determining the generation and business goals is the most important first step because this will usually lead to the identification of the most competitive plant configuration. Often, there is a tendency to begin these studies with a previous unit or a manufacturer's design to keep engineering costs low, or because of short schedules. However, this can lead to over looking the best options for optimized efficiency and plant costs, which leads to higher financial returns.

OPTIMIZATION EXAMPLE The combined cycle plant options addressed in this paper are typical process steam supply and electrical generation cases. The selection of the performance, fuel cost, plant cost and economic parameters are based on a conservative approach. Actual project values will probably differ considerably. Four cases are developed. Table 1 shows the common design inputs for the selected 4 cases. Table 1. Common Design Input UI' Model Number

GE PG7241(FA)-60Hz

Number ot CT's Perf P0mt Dry Bulb "l'emp - F

66

PerI-Pomt Wet Bulb Temp - F

57

Capacgy Factor - %

85

Book Lile

20

i'ax Lile

20

Commercial Operating Year

2002

Base Year

1999

Capital Costs Esc Rate - %/yr o & M Costs Esc Rate - %/yr

3.0 ..........

3.0

Steam Price Esc Rate - %/yr

3.5

Prunary Fuel Type / Cost

Natural Gas / $2.8 US/MBtu

Secondary Puel Type / Cost

No. 2 Fuel Oil / $3.5 US/MBtu

Primary / Secondary Fuel Esc R a t e ' %/yr

2.5

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The following Table 2 shows the selected design cases with different pinch and approach points. Table 2. Plant Performance Design Cases HP Steam Pressure - psm HP Pinch Point - F IP Pinch Point - F LP Pinch Point L F HP Evap Approach - F IP Evap A p p r o a c h - F LP Evap A p p r o a c h - F Net Plant Output - kW Stack Exhaust temp - F

2 1400

3 1800

16

10

t6

10

16

12

16

12 14

1 1400

4 1800

16

14

16

24

10

24

10

24

12

24

12

24

14

499,966

Net Plant Heat Rate (HHV) at 100% L o a d Btu/kWh

•

24

501,800

14

501,360

503,230

212

203

213

204

6,980

6,955

6,961

6,935

Capital costs for these 4 cases were shown in the following table. Note these costs are for a high labor site area. Table 3. Capital Costs (x $1000) Design Cases

1

Combustion Turbines & Accessories

83,497

HRS(J's, S(SR & Accessories Balance o f Plant

29,704

Total Process Capital Total Investment, includes land, taxes, engrg., escalation, startup, etc.

2 .......

:.

3

4

83,497'

83,497

83,497

34,588

29,938

35,107

85,372

85,752

85,672

86,002

198,573

203,837

199,107

204,606

242,778

249,121

243,421

250,047

Table 4 shows operating costs for Cases ! through 4 Table 4. Operating Cost (Year 2000 x $1000) Design Cases 1 Fuel Fixed Operatmg Expenses Variable Operating E x p e n s e s

2

.3

4

3,958

73,958

73,958

9,856

9,973

9,860

73,958

9,982

73,958

73,958

73,958

73,958

The resulting Internal Rate o f Return (IRR) for 4 design cases are shown below: Capacity payments are $ 9 4 / k w - y r , and energy payments are $25.50/MWh for the first year o f operation with escalation rate o f 3%/yr for subsequent_years. Table 5. IRR value for different scenarios Scenario No.

1

F f i e l P n c e , year 2000 $US/Mbtu with 2.5% annual escalation Capacity Vactor ' %

2.8

Design Case 1 Design C a s e 2 Design Case 3

IRR

Design C a s e 4

•

2 2.8

85

45

18.34

18.97

18.79

18.88

18.63

19.11

19.03

18.98

SUMMARY Based on the parameters selected the IRR results show that the best return is obtained with the more efficient cycles and that the IRR is best at a somewhat lower efficiency when the capacity is dropped from 85% to 45%.

SOAPP SOFTWARE

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To compete in today's global market, project planners must be able to move quickly, accurately, and cost-effectively to address the unique requirements of each project opportunity. To accomplish this, departure from the cumbersome process of preparing separate performance and cost estimates, based on information provided by multiple sets of vendors, and feeding that information into a spreadsheet environment to execute a detailed financial analysis is needed. The Electric Power Research Institute and Sargent & Lundy developed an easy to use personal computer SOAPP ® (State-of-the-Art Power Plant) software for integrated plant analysis and optimization of plants for electricity and steam supply. The currently available SOAPP software for plant design and evaluation capabilities~ includes large combustion turbine combined cycle, small combustion turbine cogeneration, repowering, and pulverized coal plants~ natural gas cofiring and rebuming~ and some pulverized coal plant major systems and equipment. The SOAPP WorkStation allows the user to define multiple sites, economic scenarios, unit configurations, and fuel types. Any combination of input data groups can be selected to form a conceptual plant design. Once selected and associated together as a conceptual design, the performance, cost, and financial analyses are fully automated (Figure 3).

Figure 3: SOAPP WorkStation Operation The Unit Data group allows the user to input specific key design attributes of the unit. For the SOAPP CT/CC WorkStation, the user starts with the selection of the combustion turbine (CT) model, selecting from a data base of more than 45 commercially available 50 and 60 Hz models, ranging in size from 20 MW to 220 MW. Simple cycle, combined cycle, and cogeneration cycles can be configured. Based on the CT selected, a default configuration is available if desired; otherwis% the user can configure each major equipment item and select process design conditions separately. The Site Data Input group consists of ambient conditions (temperature, elevation, etc.), environmental criteria (emissions limits), site conditions (seismic zone, cooling water conditions, etc.), and certain site-specific cost and economic inputs. The Fuel Data group defines the available fuels and fuel usage. Primary and secondary fuels are defined, along with a secondary fuel usage factor. The Economic Data group contains the information required to perform the capital and operation and maintenance (O&M) cost estimates, and the financial analyses. The WorkStation integrates performance, cost, and financial analysis capabilities into one product, combining them with a flexible data input structure. This allows the user to optimize the plant design to technical and financial criteria, and assess it against project and market uncertainties. Because so many project-specific site and financial variables interact with the design, no one parameter can be used to judge the optimum solution for any particular project. "What if" scenarios provide an invaluable tool for evaluating the impacts of key design decisions on overall project performance. The combination providing the optimal project financial performance will emerge from this investigation.

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The user has a wide variety of deliverables from which to choose (Figure 4).

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Re;ults Summaries "~gs ce Diagram eros Flow Diagram e r o s Piping Diagram / Condensale Flow Diagram / Condensate Pip~ Diagam Waker System Flow Diagram Water System Piping Diagram n s F 1 o ~ Diagram ns Piping Diaglam ~eGa~. and SCR Flow Diagram ~eGas and SCR Pipi~:j Diagram Av,d~lblO I~ommmeal .r~-. ~., 21---~, ..... , .

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Figure 4." SOAPP CT/CC WorkStation Deliverables

Optimization analyses, such as the process described for Figure 3, should be performed or updated at each of the major stages of the project based on the latest design and cost information; including the Initial Screening, Preliminary Design and Cost Estimating, Bid Preparation, Bid Evaluation, Contract Award, and Design stages. SUMMARY

To compete in today's global market, it is very important to optimize new combined cycle plant designs to achieve the best financial return and competitive electricity pricing. Using the SOAPP software allows project planners to quickly, accurately, and cost-effectively produce proposals that address each project's unique requirements• SOAPP Is a registered trademark of the Electric Power Research Institute, Inc.

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