System Analysis Advisory Committee. March 27, 2015

Transcription

1 System Analysis Advisory Committee March 27, 2015

2 Current SAAC Members Clint Kalich, AVISTA Mike McCoy, BECKER CAPITAL Marty Howard, BMH3 (CONSULTANT) Ehud Abadi, BPA Robert J Petty, BPA John Scott, EPIS Sibyl Geiselman, EWEB Kevin Nordt, GCPUD Rick Sterling, IDAHO PUC Mark Stokes, IDAHO POWER Jim Litchfield, LITCHFIELD CONSULTING (CONSULTANT) Fred Huette, NW ENERGY COALITION Diane Broad, ODOE Mike Hoffman, PNL Michael Deen, PPC Dick Adams, PNUCC Sima Beitinjaneh, PORTLAND GENERAL ELECTRIC Villamor B Gamponia, PSE Phillip. Popoff, PSE Mark Dyson, ROCKY MOUNTAIN INSTITUE Tom Chisholm, USACE 2

3 RPM Thermal Dispatch Decision S1n Market Price VOM S2n Fuel Cost + CO2 Cost Then S1n S2n = $ per MW earned by dispatch So max(s1n S2n, 0) determines how much money a generator would make when added over each period 3

4 Within Period Variation Market price within a period has a distribution and gas price within a period has a distribution The probability of the two distributions overlapping requires the computation of the location, range and correlation 4

5 Model Thermal Dispatch Logic Location Correlation Range 5

6 RPM NPV Calculation Collection of costs and offsetting benefits Market price in RPM covers more than the region Exports are common, so what is the cost to the region? 6

7 On Average Generation Exceeds Loads 30,000 25,000 20,000 15,000 10,000 5, , Simulation Year Load, Generation, Imports (MWa) Load Total Generation + Conservation Net Imports 7

8 General Concept Formulation can be a bit strange, e.g. note considering the value of a MWh Value of Dispatched Generation = Market Price Variable Costs Market Price Value of Dispatched Generation = Market Price (Market Price Variable Costs) = Variable Costs So the formulation uses Market Price Value of Dispatched Generation as a proxy 8

9 NPV Cost and Benefits Costs in the NPV formulation Cost of serving load at market price Cost of acquiring new resources Cost of generation curtailment and load shedding Cost of fixed O&M for existing resources Resource Adequacy Penalties Offsetting benefits Value of generation Value of conservation REC Values 9

10 NPV End Effects Calculation uses a discount rate and adjusts for perpetuity Tracking impacts on NPV in the RPM can help in understanding the formulation 10

11 Perpetuity Formulation If you miss geometric series recall: i 1 x = = 1 x i 0 So discounting out into infinity from the start of the perpetuity period gives: 1 1 (1 + d E S 1) where E is the end of the study in periods (80) and S is the start of the perpetuity period (73) ( ) 11

12 RPM Web Interface See it at Data were updated relatively recently, Scenario 1B data will be posted after final data sets are collected Does not perform optimization, i.e. creating an efficient frontier 12

13 RPM Conservation Supply Curves and Logic 13

14 Updates Since the Sixth Plan Substantially updated inputs and logic for conservation Added concept of program year Ramp rates can change by bin and program year All cost effective bins are purchased Lost opportunity conservation is available based on program cycle 14

15 Measure Combination Conservation workbooks are posted with measure level data at plan/7/technical#conservation Conservation workbook bundler at WBExtract/releases creates input supply curves 15

16 Study Supply Input Max energy and capacity by price bucket for the study for Lost Opportunity and Discretionary Conservation 16

17 Program Year Supply Max energy per program year for Lost Opportunity and Discretionary Conservation 17

18 Program Year Ramp Shows the percentage of the max that can be purchased in each program year Program Year Conservation Bucket

19 Program Year Moves ramps based on when programs in a bin become cost effective E.g if for bin 5 the first program year allows 3% of the max conservation to be purchased and the second program year allows 7% of the max conservation to be purchased, whenever the bin becomes cost effective, the first year 3% is purchased the second year, if it remains cost effective, 7% is purchased 19

20 Effective Program Year Example Bins 1 through 4 are always cost effective thus the program year always increments Time Bin 5 is cost effective at first but becomes too expensive Conservation Bucket When bin 5 becomes cost effective again then it picks back up with the next ramp in the supply curve inputs 20

21 Combined Conservation Limits Each year/period the ramp is multiplied by the max energy for the program year/period which is multiplied by a factor accounting for load differences between futures to determine the supply of conservation When the cumulative purchases reach the study maximum, no more can be purchased 21

22 Conservation Acquisition Ramps and supply limit purchases Once the study max is reached no more purchases are made Time Conservation Bucket

23 Cost Effective Logic Exponentially smoothed price (one game): Pt where ( e P ) = Pt t 1 t 1 Pt is expected price at time t e is the equilibrium electric price at time t t Market Adjustment (Conservation Adder) Avoided Cost Credit 23

24 Example Game Price Smoothing Smooth price is more stable for purchasing decisions Time Compare Expected Elec Prices ($/MWh) Equilibrium Elec Prices Expected Equil Elec Price 24

25 Compared to Conservation Cost Conservation is cost effective if 1.1P + a c where P a t is expected price at time t is t the conservation adder c is the cost of conservation bin Note, the 1.1 represents the Power Act credit for conservation 25

26 Average Cumulative Conservation This shows total purchased costeffective conservation Time Conservation Type Lost Opportunity Discretionary 26

27 Into the RPM 27

28 RPS Logic 28

29 REC Calculations Starting REC bank balances Existing resource annual contribution to REC banks New resources optioned for adequacy or economics are allocated to REC banks based on proportion of RPS requirement Resources built for RPS are allocated based on REC bank balance approaching zero Expiring RECs based on First In First Out approximation 29

30 RPS Requirement Changes in RPS reflected 1200 in an increase in requirements Requirements based on regional load allocated to each state Time State MT OR WA ID 30

31 Starting allocation based on Existing Resources Renewable Resources Allocation Time State MT OR WA ID Resources built for RPS are assigned to the state requiring the RECs when added 31

32 REC Bank Balance Example REC banking delays construction of renewables Time State MT OR WA ID 32

33 RPS Build Example Builds are triggered when banks get close to zero Time NewResources UT Scale Solar PV ID Wind COL Basin Wind MT EX TRNS Ut Scale Solar PV ID B2H 33

34 No Renewable Build Example In some futures, builds may not be required for the duration of the study Time State MT OR WA ID 34

35 Into the RPM again 35

36 Scenario 1B - Disclaimer Data inputs for the Draft Plan are still being finalized Some of the model logic is still being vetted Resource strategies are shown for illustrative purposes and are likely not optimal model solutions All results shown with 80 games rather than 800 for time consideration 36

37 Scenario 1B No carbon regulation No RPS changes Only known retirements Includes 800 futures 37

38 Why not Negative Conservation Adders 38

39 Why not Negative Conservation Adders Model spent over 70% of the time exploring extremely expensive and risky resource strategies NPV arithmetic in effect guarentees negative adders will not result in optimal results RPM allows for real-time scenario examination that will make it easy to compare to strategies with negative adders when questions arise 39

40 Resource Strategies Option nothing zero conservation adder Option nothing mid-range conservation adder Option nothing extreme conservation adder Option DR Bin 1 and Recips mid-range conservation adder Option everything zero conservation adder Option everything mid-range conservation adder 40

41 2,000 1,800 1,600 1,400 1,200 1, No Options Average Resource Build RPS Resources still must be built, regardless of options selected YearSubAnnBlock NewResources UT Scale Solar PV ID Wind COL Basin Wind MT EX TRNS Wind MT New 230kV Line Wind MT Path8 Upgrade Ut Scale Solar PV ID B2H 41

42 Zero Conservation Adder Average Conservation Minimal conservation by end of Time Conservation Type Lost Opportunity Discretionary 42

43 No Options Zero Adder Costs Hydro Generation Value Must Run Generation Value Dispatchable Generation Value Conservation Value Backstop/Curtailment Cost New Resource Costs (Construction, FOM) Costs driven by not meeting RAAC adequacy standards Fixed O&M of Existing Resources Resource Adequacy Penalties Net Cost to Serve Load -150, ,000-50, , , , , ,0 NPV by Cost/Value Type ($ Million) 43

44 NPV Zero Conservation Adder 7u 6u 5u 4u Mean NPV $107 Billion TailVar 90 $204 Billion NPVs include substantial penalties 3u 2u 1u 0-100,000-50, , , , , , , , ,0 NPV of Cost to Serve ($ Million) 44

45 Zero Supply Conservation No Options Sets all supply curves to zero so no conservation can be bought No load shed in the 80 games run Minimal generation curtailment Market depth same as Sixth Plan, i.e MW Demonstrates that Resource Adequacy Penalties have a much higher impact than curtailment/load shed penalties 45

46 Maximum Load Shed Time Zero Load Shed for the 80 games run Off or On Peak OffPeak OnPeak 46

47 Maximum Generation Curtailment Minimal Curtailment Time Off or On Peak OffPeak OnPeak 47

48 No Options Zero Conservation 4.5u Adder NPV Distribution 4u 3.5u 3u 2.5u Mean NPV $242 Billion TailVar 90 $380 Billion Both primarily driven by penalities 2u 1.5u 1u 500n 0-100, , , , , , ,0 NPV of Cost to Serve ($ Million) 48

49 No Options $75 Conservation 20u Adder NPV Distribution 18u 16u 14u 12u 10u 8u 6u 4u 2u Mean NPV $76 Billion TailVar 90 $135 Billion Still $9 Billion on average in Adequacy Penalties* * - This doesn t indicate the mean would be $67 Billion without penalties, these numbers should not be added together 0-25, ,000 50,000 75, , , , , , ,0 NPV of Cost to Serve ($ Million) 49

50 No Options $150 Conservation 22.5u Adder NPV Distribution 20u 17.5u 15u Mean NPV $78 Billion TailVar 90 $129 Billion 12.5u 10u 7.5u 5u 2.5u , ,000 NPV of Cost to Serve ($ Million) 50

51 No Options $150 Conservation Adder Average Conservation Conservation adder of $150 leads to around 1150 amw combined conservation by end of Time Conservation Type Lost Opportunity Discretionary 51

52 DR Bin 1 and Recip Option Average Resource Build 2,500 2,000 Recips are added likely for adequacy requirements 1,500 1, YearSubAnnBlock NewResources Demand Response Price Bin 1 RECIP ENG West TD UT Scale Solar PV ID Wind COL Basin Wind MT EX TRNS Ut Scale Solar PV ID B2H 52

53 DR Bin 1 and Recip Option 25u NPV Distribution 22.5u 20u 17.5u 15u 12.5u Mean NPV $71 Billion TailVar 90 $107 Billion Down to $4 Billion in adequacy penalties * 10u 7.5u 5u 2.5u 0 20,000 40,000 60,000 80, , , , , ,0 NPV of Cost to Serve ($ Million) 53

54 Option Everything $0 Adder Resource Build 5,000 4,500 4,000 3,500 3,000 2,500 2,000 1,500 1, YearSubAnnBlock NewResources Demand Response Price Bin 1 Demand Response Price Bin 2 Demand Response Price Bin 3 CCCT Adv1 Wet Cool CCCT Adv2 Dry Cool RECIP ENG West TD RECIP ENG East UT Scale Solar PV ID Wind COL Basin Wind MT EX TRNS Wind MT New 230kV Line Ut Scale Solar PV ID B2H 54

55 Option Everything $0 Adder NPV Distribution 10u 9u 8u 7u Mean NPV $111 Billion TailVar 90 $184 Billion 6u 5u 4u 3u 2u 1u 0-50, , , , , , ,0 NPV of Cost to Serve ($ Million) 55

56 Option Everything $75 Adder Resource Build 3,000 2,500 2,000 1,500 1, YearSubAnnBlock NewResources Demand Response Price Bin 1 Demand Response Price Bin 2 Demand Response Price Bin 3 CCCT Adv1 Wet Cool CCCT Adv2 Dry Cool RECIP ENG West TD UT Scale Solar PV ID Wind COL Basin Wind MT EX TRNS Ut Scale Solar PV ID B2H 56

57 Option Everything $75 Adder NPV Distribution 22.5u 20u 17.5u 15u Mean NPV $92 Billion TailVar 90 $133 Billion 12.5u 10u 7.5u 5u 2.5u 0 20,000 40,000 60,000 80, , , , , , ,0 NPV of Cost to Serve ($ Million) 57

58 What do you want to see? Explore outputs from points in 1B? Try other inputs? Any results you would expect given different inputs? Note: most real-time analysis will be done with 80 games to allow for results in a timely manner 58

59 Communicating Results What would you advise for communicating results from the model effectively? Are the graphs from the model you feel are helpful or misleading? What policy questions would you recommend we take forward based on the outputs you have seen today? 59