Heat Rate Calc based on CEMS Data April 12, 2016 Kevin Harris, ColumbiaGrid Paul Deaver, CEC

Overview Big Picture Data Source: CEMS Data Filtering Data Station Service Review IO Curves Calc Generic IO Curve Adjusting Full Load HR Processing GT Issues/Lesson Learned

Big Picture Purpose: To develop heat rate curve for PCM Data Used: EPA CEMS data Procedure: Filter EPA CEMS data Calculate IO Curve: 2nd order polynomial Take into account station service by scale CEMS heat points to modeled heat points Calc Avg Heat Rate: 𝐹𝑢𝑒𝑙 𝑖𝑛𝑝𝑢𝑡 𝑎𝑡 𝐶𝐸𝑀𝑆 𝐻𝑒𝑎𝑡 𝑃𝑜𝑖𝑛𝑡𝑠 𝑀𝑜𝑑𝑒𝑙𝑒𝑑 𝐻𝑒𝑎𝑡 𝑃𝑜𝑖𝑛𝑡𝑠 Error Check Results

CEMS Data EPA Continuous Emission Monitoring System (CEMS) Track flue gas to provide information on compliance with emission standards Processed hourly data from 2010-2014 (~43,824 data points/unit) Processed data for 287 units: 71 ST-Coal, 64 ST-NG, 83 GT and 69 CC EPA CEMS Data can be found at: ftp://ftp.epa.gov/dmdnload/emissions/smoke/ ftp://ftp.epa.gov/dmdnload/emissions/hourly/monthly/

Review both the IO Curve and Histogram when making filter decisions Filtering Data Why filter data: Noise/unreasonable operating points Filtering is a multi pass process: Pass 1: Used only whole hours of operation Pass 2: X-Axis Gross Capacity Max operating limit: Based on EIA-860 rating + station service + buffer In some cases physical data did not exceed EIA-860 rating Min operating limit: Based on observed lower operating limit in histogram Pass 3: Y-Axis Fuel Burn Iteration 1: Filter based on +/- IO Curve from Pass 2 Iteration 2: Based on calc IO Curve from Pass 3, iteration 1 Review both the IO Curve and Histogram when making filter decisions

Station Service There are no generic rules when determining station service Station Service was based on WECC 2015 power flow Case 25HS1a as follows: ST-Coal: Individual units station service was used ST-NG: Most of the ST-NG unit are retired by 2026. Value from WECC 2014 power flow Case 14LSa1e was used. The average of 12 units is 1 MW/unit. Used Zero GT: For all practical purpose zero CC: Values were all over the place for F-Frame CC with the following stats Avg: 5.74 MW, Min: 0, Max 20.4 StDev 4.55 [StDev is 80% of Avg]). Calc generic Station Service for F-Frame CC has little impact on CEMS calc full load HR. Used generic IO Curve for CC with CC 260 MW CC w/station service 265.74 and a full load HR of 7.00. This resulted in a HR increase of 0.049%. To be conservative use a 0.1% increase.

X-Axis (Filter, IO and Heat Points) On the X-axis we have three primary components Filter Points: Upper and lower point to filter CEMS data IO Curve Points: Points on the X-axis to calculate fuel burn for the IO Curve Heat Points: Modeled heat points Max rating is based on the EIA-860 Sum/Win rating. The user selects Sum, Win or Avg(Sum/Win) rating based on available CEMS data Station Service: IO Curve Point(Max) – Heat Point (Max) Heat Points are scaled IO Curve Points based on ratio of: Heat Point(Max)/IO Curve Point(Max) Typically the following relationship exist: Max Rating: Filter Points >= IO Curve Points >= Heat Points Min Rating: Filter Points <= IO Curve Points <= Heat Points The Y-axis filter excludes data outside the given +/- range around the previous Polynomial IO Curve Given this filter will change the IO Curve this is iterated a minimum of twice to minimize any potential issues.

Example Filter: San Juan 4 San Juan 4 – ST-Coal New Mexico Sum/Win/Min Rating: 507/507/150 Filter Points: 275 - 550 IO Curve Points: 275 – 550 Heat Points: 253.5 – 507 Implied Station Service 43 MW X-Axis Filter: 275 – 550 Y-Axis Filter: +/- 550 from Poly

A separate spreadsheet contains additional examples with charts Example Heat Rate Calc A separate spreadsheet contains additional examples with charts 2016_0419_HR_Examples_v01.xlsx

Example: Fort St Vrain GT Fort Saint Vrain - GT in Colorado EIA Sum/Win/Min Rating: 145/160/73 IO Curve Points = Heat Points implies no station service Note: X-Axis Filter, clear IO trend to winter rating. Winter rating 160 is used over summer rating of 145 X-Axis Filter: 65 – 162 Y-Axis Filter: +/- 75 from Poly

Example: Magnolia CC Magnolia – CC in LADWP – 9/2005 EIA Sum/Win CT Rating: 161/165 EIA Sum/Win CC Rating: 301/305 Rule of Thumb: CT are 2/3 of CC implying CC should be 241.5/247.5 Assume EIA reported CC is CC+DB Used CC Sum/Win Rating 242/248 Assume DB > 241.5 MW X-Axis Filter: 175 – 242 Y-Axis Filter: +/- 50 from poly

Example: Gila River CC 1a Gila River 1a – CC @ PV – 7/2003 EIA Sum/Win CC Rating: 257.5/276.5 EIA Sum/Win CT Rating: 146/163 Heat Points: 170.0 – 257.5 Implied Station Service 0 MW Assume CC+DB: 295 DB X-Axis Filter: 170 – 259 Y-Axis Filter: +/- 220/100 from poly DB?

Error Check If one of the following conditions is True the generic heat rate shape is used with calc full load Heat Rate Incremental hear rates are always monotonically increasing: iHR(2) < iHR(3) < iHR(4) Heat Rate (1) is greater than Heat Rate (Full Load): aHR(1) > aHR(Full Load)

Generic Steam IO Curve Unitize calculation for generic Steam Heat Rate Criteria for selecting Steam units: four heat point without errors y:= 0.07879+0.85196𝑥+0.068195 𝑥 2 𝑅 2 =0.9984

Generic CC IO Curve Unitize calculated for generic CC heat rate Criteria for selecting CC units: four heat point without errors

Adjustment to Full Load Heat Rate Full load hear rate were reviewed and adjusted if needed Aligned or average sister units to same HR Example Align: N Valmy unit 1 had a 9.4 HR while unit 2 10.1, changed unit 1 to 10.1 Example Avg: El Segundo 1a and 1b have a wide spread between the two full load HR but operating hours are about the same. Modeled HR were the avg of unit 1a and 1b. For CC maintained a spread between technology (E-Frame, F-Frame, G-Frame, and H-Frame)

Processing GT In general CEMS data for most GT was thin Processed CEMS data to obtain: Full load heat rate Operating range Exception: NV Energy Clark GT were either on or off Assume min rating is 55% of max Model with two heat points and flat heat rate shape

Issues/Lessons Learned A 3rd order polynomial resulted in additional error, therefore use a 2nd order Additional filtering may be needed for 3rd order polynomial What’s station service? This is still an open question Units with a GT splitting out CEMS data by season improve IO Curve. Duct Burner heat rate need improvement