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Kevin Harris, ColumbiaGrid TEPPC\Model Work Group - Chair

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Presentation on theme: "Kevin Harris, ColumbiaGrid TEPPC\Model Work Group - Chair"— Presentation transcript:

1 Kevin Harris, ColumbiaGrid TEPPC\Model Work Group - Chair
MWG Identified Area of Model Improvement to TAS Salt Lake City - January 30, 2017 Kevin Harris, ColumbiaGrid TEPPC\Model Work Group - Chair

2 Overview Hydro Operation Modeling CC as 1x1 Heat rate review
Dispatch PLF to Load – Solar –Wind The use of fixed hourly shape Modeling of the Core Columbia River Hydro Dispatch to Multi Regions Modeling CC as 1x1 Heat rate review Non-Dispatchable Supply Maintenance Other Items What do we Model?

3 Hydro Issues

4 Hydro Dispatch: Load – Solar - Wind
Currently: Hydro is dispatch against load Problem: Load – Solar shapes results in radical shift in daily load pattern which dispatchable Hydro is not responding to Shift CA Hydro to respond to net load (Load – Solar) Hydro supporting afternoon ramp instead of contributing to the problem Recommendation: Solar Coefficient Factor:= 1 (100%) Wind Coefficient Factor:= Northwest:=0; other area?

5 Hydro Dispatch: Hourly Shape
Currently: Many Hydro units in California are modeled with a fixed hourly shape Problem: They are capable of shifting generation to correspond to load - solar Switch these plants from “Hourly Shape” to “Load Following” (PLF only) allows them to respond to the net Load - Solar

6 Hydro Dispatch: Hourly Shape
Example Modeled Hydro gen (WAPA): Judge F Carr, Spring Creek, & Folsom If op flexibility still exist peaking capability by increase. Example: Shifting 8 hrs of peaking into 6 hrs results in a 33% increase in peaking capability Fixed hourly shapes peak mid-day New daily peak On average this change would support 200 MW of the afternoon ramp

7 Modeling Core Columbia River
Currently: The Core Columbia River is modeled as PLF with some HTC Problem: HTC increase in operational flexibility by shifting generation from the morning to the afternoon ramp Recommend switch modeling of Columbia River with PLF only

8 Hydro Dispatch: Multi Regions
Currently: Some Hydro is dispatch to multi regionals Problem: Currently procedure in GridView makes it difficult to calc the appropriate K Factor Minimize the use of this feature or iterate on solving appropriate K Factor

9 Modeling of Combine Cycle
Currently: CC are modeled as whole plants, i.e. 2x1 Redhawk CC modeled as 482 MW Problem: Commitment is preformed by CT Switching modeling to 1x1 configuration allow additional operational flexibility in meeting California duck curve Switching modeling to 1x1 configuration allow additional operational flexibility in meeting California duck curve

10 Full Load Heat Rate Review
Problem: Continue to find units with heat rate issues Example: Carlsbad LMS full load heat rate v1.5: 10.7 MMBtu/MWh V1.7: 6.1 MMBtu/MWh LMS Generic: 8.8 MMBtu/MWh Carlsbad min generation Min rating 20% Gas turbines cannot operate below load and be NOx compliant Las Vegas CG 2&3 full load heat rate: 6.65 MMBtu/MWh LM6000 base CC ~ 7.9 GT/CC with 5-6 heat point blocks

11 Non-Dispatchable Supply

12 Non-Dispatchable Supply
Non-Dispatchable supply is not limited to just wind and solar Other types of Non-Dispatchable supply: Geothermal, Cogeneration, Biomass, Land Fill Gas,.. Currently: These units are modeled as dispatchable supply: heat rate curve, fuel cost, dispatch range (min-max rating) Problem: This result in non-dispatchable supply responding to price signals in the whole sale electric market

13 Non-Dispatchable v1.5: Geysers
Average annual generation (aMW) Modeled: 907 Historic 5 yr avg: 534 Diff in gen: 373 (+70%) Hourly generation profile shows a significant amount dispatchability Note: Modeled capacity is close to nameplate

14 Non-Dispatchable v1.7: Geysers
Average annual generation (aMW) Modeled: 572 Historic 5 yr avg: 534 Diff in gen: 38 aMW (7%) Hourly generation profile does not reflect historic operation

15 Non-Dispatchable v1.50: Sycamore CG
Average annual generation (aMW) Modeled: 277 Historic 5 yr avg: 159 Diff in gen: 118 (+74%) Hourly generation profile shows a significant amount of dump energy

16 Non-Dispatchable v1.70: Sycamore CG
Average annual generation (aMW) Modeled: 73 Historic 5 yr avg: 159 Diff in Gen: -86 (-54%) Hourly generation profile shows a significant amount of dump energy

17 Non-Dispatchable Economic of non-dispatchable supply is independent of the whole sale electric market Making it dispatchable makes it difficult to control Small changes in fuel cost changes how the units dispatches

18 Re-evaluate Maintenance
With load minus solar and wind changes when maintenance can be preformed Example: Intermountain 1 & 2 ran an avg of 0.9 units between 3/13 to 6/17 (Sched maint in fall) Given little op in spring should maint be shifted to spring? Other Issue Annual CF 39% but min fuel take ~50-70% Should fix cost be taken out of modeled coal cost? Two weeks maintenance per year?

19 Other Items Pancake wheeling cost
Impedes exchange of power on the market Modeling of CAISO CO2 tax with asset controlled supply Explore an hourly method to implement PAR’s operation Problem: Consistently appear as a binding path in WECC analyst If PAR is properly operated the path is not binding

20 An efficient market vs a power market?
What do we Model? An efficient market vs a power market? Do we model An efficient single owner market? A wholesale power market with 38 balance areas? Problem: We pick and choose modeling assumption independent of a clear understanding of what market we are modeling Solution: We need a clear definition of what type of market we model in the Base Case

21 Cycling of CC Outside of CA
CC outside of CA are starting mid-day in response to duck curve Est cost of start outside of CA (SW + NW) $172M/year $471k/day Start are the difference between Max(HE 17-22) – Min(HE 12-16)

22 What do we Do? Do we apply constraints to minimize mid-day start of CC outside of California? Do we model an efficient market If so, what rules do we enforce and ignore in the base case? When market issues are found what do we do?

23 Kevin Harris (503)

24 Based on 2026CC modeled loads and solar from 2026CC v1.5
Impact of CA Duct Curve ~25,000 MW of solar modeled in CA Avg daily min shifts from Off-Peak to mid-day Solar only reduces peak demand May-Sep No change to peak demand during fall/winter (Oct-Apr) Based on 2026CC modeled loads and solar from 2026CC v1.5

25 CAISO Duck Curve Impact on Ramp Rate
Modeled CAISO load avg daily ramp rate 4,000 MW ramp in 3 hrs in 11 months 12,000 MW ramp in 7 hrs is 4 months Modeled CAISO Load–Solar avg daily ramp rate 12,000 MW ramp in 3 hrs in 11 months 18,000 MW ramp in 7 hrs in 10 months

26 Cycling of CC for CA Duct Curve
Average daily committed start by hour by month CA: Minor mid-day dip in committed CC SW: Clear mid-day dip with afternoon spike in committed of CC

27 Suggested Intertie Charts
Propose 3 types of charts to review flow on interties Flow duration: Determine peak flow issues Avg monthly flow: Compare modeled flow with historic flow

28 Suggested Intertie Charts
Average hourly flow by month. Intra-day relationships are change with the CA duck curve. Understanding then this occurs and it magnitude results in improved understanding of transmission issues


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