VGS StudyVGS StudyBenefits of Leveraging Diversity across the Benefits of Leveraging Diversity across the

Western InterconnectionWestern Interconnection

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Presented at

WECC VGS Subcommittee Meeting

Salt Lake City, Utah October 27, 2010

Project team

N. Samaan, R. Guttromson, Y. V. Makarov, T. Nguyen, C. Jin, M. Elizondo, and X. Guo

Pacific Northwest National Laboratory (PNNL)

M. Milligan, and K. OrwigNational Renewable Energy Laboratory (NREL)

B. Nickel, M. Mizumori, M. Hunsaker, and H. Pacini

Western Electricity Coordinating Council (WECC)

Study ObjectivesStudy Objectives

To determine the saving in operating costs (production and balancing costs) due to WECC BAs consolidation as an upper bound for BAs cooperation benefits

To examine the effect of congestion on potential benefits

To evaluate the benefits of intra-hour (10-min) scheduling

The analysis will be performed for three different scenarios of VG penetration 15%, 20%, and 30% as percentage of WECC energy demand for one year

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Study ScenariosStudy Scenarios

Scenario 1: BA structure like today’s: BAs are separate, congestion exists

Scenario 2: Full consolidation, copper sheet no congestion

Scenario 3: Full consolidation, congestion exists

Scenario 4: Separate BAs with 10-min intra hour scheduling

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Base Simulation CaseBase Simulation CaseTEPPC 2020 Case will be the base case for the study

The case will be in PROMOD format with the full WECC nodal model

The 2006 load shapes are scaled up to represent 2020 estimated values

Wind and Solar production time series will be generated based on 2006 weatherHydro production is based on an average year (which is representative for hydro production in 2006)

Proportional Load Following (PLF) model

Hydro Thermal Coordination (HTC) (used for 21 hydro plants in the model )

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Progress in the Study

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WECC provided 2009 1-minute resolution load and net interchange data for each BAPNNL combined the intra-hour variability characteristics of 2009 load data with 2006 1-hour average load to create a representative 1-min time series for 2006 loadWECC provided 1-hour resolution aggregated wind profiles NREL provided 1-hour resolution solar profilesPNNL performed trial simulations for scenarios 1, 2 and 3 using TEPPC 2019 case

Progress in the Study (2)

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PNNL developed a forecast simulation model to generate load, wind and solar forecast errors at different time frames taking into consideration the correlation between the errorsWork is in progress to put assumptions for AGC capabilities of generating units in the model Flow gates were added to PRMOD model to monitor hourly interchanged power between individual BAsAnalysis is in progress to better understand hydro-scheduling in PRMOD

Data Processing-Original DataData Processing-Original Data2009 1-min resolution load of WECC 32 BAs (no load for the 5 generation-only BAs)Outliers & missing data

0 1 2 3 4 5 6

x 105

0

5000

10000AESO

0 1 2 3 4 5 6

x 105

-1000

0

1000

2000

3000WALC

Outlier

Missing Data

Data Processing-First StepData Processing-First Step

Load should be highly persistent locally in time around a changing mean

We highlight deviations by modeling this changing mean and observing the magnitude of deviations from the mean

For robustness, mean is modeled using a 15-minute running medianWe set rules for anomalous values and also inspect visuallyOur rule was to flag values greater than 6 standard deviations from the mean

For visual inspection, it is impossible to view the entire year with 1-minute resolution data, so we look at the data on a daily basis

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Data Processing-First Step (2)Data Processing-First Step (2)

Data Processing-First StepData Processing-First Step

Gray dots are the load values, black line is the running median, red dots are flagged as anomalousShould the jump before 8:00 be deemed as anomalous by visual inspection?

Data Processing-Second StepData Processing-Second Step

Replace missing data by the data in previous week plus random noise To identify outliers, a threshold is set at 3 standard deviations from the mean

Mean is obtained by dividing a yearly data set into 10 smaller sets

Use spline interpolation to correct outlying data based on prior and subsequent “good” data pointsFurther correct data that deviates more than ±5% of the mean value in 1min by changing the current value to the previous value ±5%

Data Processing-Second StepData Processing-Second Step

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5

x 105

0

2

4

6x 10

4 APS Original 2009 Load Data

Time (min)

Po

we

r (M

W)

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5

x 105

0

5000

10000Step 1 Cleaning

Time (min)

Po

we

r (M

W)

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5

x 105

0

5000

10000Step 2 Cleaning

Time (min)

Po

we

r (M

W)

Combined the intra-hour variability characteristics of 2009 load data with 2006 1-hour average load

1. Compute hourly average load data for all BAs in 2009

2. Apply nonlinear interpolation method to smooth the step hourly change

3. Calculate the difference between actual and interpolated values

4. Scale these differences based on the maximum load level during the whole year

5. Take the hourly load data in 2006 and interpolate these data to obtain interpolated load data

6. Apply the 2009 differences to the interpolated 2006 load and obtain the final load curves in 2006, with 1 minute resolution

ExampleExample

Error= Generated-Interpolated Erro

r sca

led

base

d on

max

imum

load

Generated Load Curve for CAISO in 2006

Generated 2006 Load Curves with 1-minute Generated 2006 Load Curves with 1-minute resolution for all BAs resolution for all BAs

Trial Simulations with TEPPC 2019 case to determine Pools and BAs Structure for each

Scenario

Current TEPPC model has 7 pools. Each pool has a set of consolidated BAs (Scenario 0)

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The objective of the first scenario of the study is to model current situation as realistic as possible but in 2020

http://www.nerc.com/fileUploads/File/AboutNERC/maps/NERC_Regions_BA.jpg

Scenario 0-TEPPC 2019 Structure 39 areas, 7 pools

Full transmissionHydro is scheduled to benefit poolsResults summary

Steam (GWh) 551715

Nuclear (GWh) 79993

Turbine (GWh) 78069

Hydro (GWh) 181523

Dump Energy (GWh) 57

Emergency Energy (GWh) 0

Total thermal cost (k$) 22,576,212.00

Scenario 1A -25 Areas, 25 Pools 25 is the maximum number of Pools allowed in PROMODFull transmissionHydro is scheduled to benefit pool where the unit belongsResults summary

Steam (GWh) 540583.8Nuclear (GWh) 67797.6Turbine (GWh) 111128.5Hydro (GWh) 181574.5Dump Energy (GWh) 47517.5Emergency Energy (GWh) 42126.2Total thermal cost (k$) 28,441,966.00

Huge dump and emergency energy because

The optimization is done over poolsSome pools don’t have enough capacity while the others have too much to serve their own load.

PACE

IPC

Scenario 1B: 20 pools, 20 areasFull transmissionHydro is scheduled to benefit area where the unit belongsResults summary

Steam (GWh) 542389Nuclear (GWh) 75471Turbine (GWh) 95540Hydro (GWh) 181547Dump Energy (GWh) 6330Emergency Energy (GWh) 5346

Total thermal cost (k$) 26,601,718.00

There still exists some amount of dump and emergency energy, but they are much smaller compared to the scenario 1A.

Scenario 2: Consolidate BA(1 pool, 2 areas), no transmission constraintMaximum area load in PROMOD is 100 GW, so we have to divide the consolidated WECC into two areas

Simulation runs gave errors message and final results are not realisticFurther investigation is in progress with PRMOD support

Scenario 3: Consolidate BA (1 pool, 2 areas) with transmission constraint

Full transmissionHydro is scheduled to benefit area where the unit belongsResults summary

Steam (GWh) 562889Nuclear (GWh) 80420Turbine (GWh) 66536Hydro (GWh) 181480Dump Energy (GWh) 49Emergency Energy (GWh) 0

Total thermal cost (k$) 22,439,830.00

Generation and Cost Comparison

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About 4 billion dollars in savings comparing scenario 1B and scenario 3

Regulation in PROMOD

TEPPC cases do not have regulation dataInput data needed (underlined):

Pmax

Pmin

2) Regulation Maximum range

1) Regulation Minimum range

Desired operating point

P [MW]

t [min]

4) Response time [min]

3) Ramp rate [MW/min]

5) Regulation up bid [$/MW], and 6) Regulation down [bid $/MW]

Reg. Capacity (= Ramp rate * Response time)

Regulation in PROMOD

Regulation requirement by Area and by subperiodSubperiods: weekday (1), weekday night (2), weekend (3)

These values are changed monthly

Year Month Area Area ID SubperiodArea RegUp

RequirementArea RegDown Requirement

2018 1 CFE 3 1 40 402018 1 IID 4 1 30 302018 1 LDWP 5 1 100 1002018 1 PG&E_BAY 8 1 150 1502018 1 PG&E_VLY 9 1 220 2202018 1 SCE 6 1 400 4002018 1 SDGE 7 1 80 802018 1 SMUD 1 1 75 752018 1 TIDC 2 1 12 12

Regulation in PROMOD (cont…)

PROMOD optimizes energy and regulation either sequentially (commits ancillary services only after committing energy) or simultaneously (co-optimizes ancillary service and energy during unit commitment and dispatch).Clearing price for regulation:

Determined by most expensive accepted bid if regulation bids are providedDetermined as incremental cost of generation whose dispatch has to be changed to provide regulation if regulation bids are NOT provided

Assumptions for regulation database

For the ramp rate, we used the “ramp rate up” existing in the PROMOD data base (corresponds to power changes from one hour to the next)Generators that do not provide regulation:

Units without “ramp rate up” data

Units that have an hourly profile (such as run-of-river hydro)

Units built after or retired before the study year

Assumptions (cont…)

Technologies with regulation capabilities: CC, Coal, CT, Hydro, Steam

TechnologyPROMOD Categories

that provide RegExamples

Regulation Range

Response Time [min]

CC Frame F Big Hanaford ST Centralia (268 MW) , area BPA

CC Frame GENMAX Shepard Energy Centre, Alberta, Canada (800 MW) , area AESO

CC Old March Point L Anacortes WA (140 MW) , area PSECC Recent Grays Harbor CC (650 MW) , area BPACombined Cycle -

5.4 (Average duration capability at highest ramp [1])

Combined Cycle

from 60% to 85%

Hydro -

Conventional Hydro Grand Coulee (23 x 266 MW) , area BPA

from 0% to 100%

1.9 (Average duration capability at highest ramp [1])

Hydro

[1] Makarov, Y.V., et al., Assessing the Value of Regulation Resources Based on Their Time Response Characteristics . 2008, Pacific Northwest National Laboratory.

Assumptions (cont…)

TechnologyPROMOD Categories

that provide RegExamples

Regulation Range

Response Time [min]

Steam -Steam - Coal -Steam - Other -Steam Large -Steam Large Old Saguaro GT2 Red Rock AZ (99 MW) , area APSSteam Large Recent Etiwanda, Etiwanda CA (2 x 320 MW) , area SCESteam Small -Steam Small Old Olive 1 (Burbank) (44 MW) , area LDWPSteam Small Recent Olive 2 (Burbank) (55 MW) , area LDWP

3.9 (Average duration capability at highest ramp [1])

Steamfrom 50% to

90%

Coal Large -

Coal Large Old Cherokee 1 Denver CO (109.8 MW) , area PSCCoal Large Recent Centralia (2 x 728 MW) , area BPACoal Small -Coal Small Old Arapahoe 3 Denver CO (44.7 MW) , area PSCCoal Small Recent Montana One 1 Colstrip MT (42 MW) , area NWMTCoal Steam -Coal SuperC Comanche 3 (750 MW) , area PSC

from 50% to 90%

3.9 (taken same as Steam T.)

Coal

[1] Makarov, Y.V., et al., Assessing the Value of Regulation Resources Based on Their Time Response Characteristics . 2008, Pacific Northwest National Laboratory.

Assumptions (cont…)

TechnologyPROMOD Categories

that provide RegExamples

Regulation Range

Response Time [min]

Combustion Turbine -CT Future OTC Replacement LDWP (4 x 100 MW) , area LDWPCT Large Haynes CT (6 x 100 MW) , area LDWPCT LM 6000 Canyon Anaheim (4 x 49 MW) , area SCECT Old -CT Old Gas Fredonia, Burlington WA (2 x 104 MW) , area PSECT Old Oil Whitehorn 1 Custer WA (74 MW) , area PSECT Small Finley (30 MW) , area BPA

from 30% to 90%

N/ACombustion

Turbine

Summary of regulation units obtained from assumptions

e.g. California:

120 units connected AGC in CAISO (SCE, SDGE, PG&E_VLY, PG&E_BAY) in 2007 [1]. From the table CAISO has 292 units

AreaEstimated

Requirement [MW]# of AGC

UnitsCapacity of AGC units [MW] Regulaption Cap [MW]

CFE 81.48 17 2604.70 147.70IID 30.15 14 630.00 88.69LDWP 203.79 30 5957.00 374.89PGandE_BAY 292.08 51 6143.97 544.25PGandE_VLY 440.16 92 7612.39 673.02SCE 798.03 107 11854.35 1197.20SDGE 159.87 42 4255.58 453.93SMUD 148.11 18 2264.40 140.39TIDC 24.18 5 493.00 62.62

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SUMMARY of AGC Technologies Capacity for each Area

[1] Makarov, Y.V., et al., Assessing the Value of Regulation Resources Based on Their Time Response Characteristics . 2008, Pacific Northwest National Laboratory.

Explore Hydro Operation in PROMOD

In 2019 TEPPC datasets, most of hydro plants are using Proportional Load Following (PLF) model. Two questions need to be answered:

Which load schedule does the hydro plant follow, the native load, load-wind or load-ContractParticipationEnergy?Wind impacts on hydro schedule;How does the value of PLF factor affect the hydro schedule?

What Does Hydro Follow?

-2000

0

2000

4000

6000

8000

10000

12000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

MW

Hour

Hydro Schedule

Native Load

Wind

Contract Participation

Load-Contract

Load-Wind

What Does Hydro Follow? (continue…)

Hydro is dispatched to follow net load, that is NativeLoad-ContractParticipaptionEnergy (including wind, solar, negative load, conventional hydro (which set as must-runs), and geothermal). Several evidences lead us to this conclusion:

The hydro is not dispatched to follow native load;The hydro is not dispatched to follow NativeLoad-Wind.

Hydro Schedules of cases with and w/o wind

15000

17000

19000

21000

23000

25000

27000

29000

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46

MW

Base No Wind

Wind production is part of the contract participation energy, so it affects the net load and ultimately affects the hydro schedule.

Load following Factor

15000

17000

19000

21000

23000

25000

27000

29000

1 3 5 7 9 11 13 15 17 19 21 23

MW

Base DoubleK

Increase the proportional load following constant K makes more hydro energy is generated during peak time and less is generated during off-peak time.

Next Steps

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WECC will finalize TEPPC 2020 caseNREL will provide 1-minute resolution solar profilesPNNL will generate day-ahead, hour-ahead and real time forecast dataPNNL and NREL will perform load following and regulation analysis for each scenarioWECC will send a request for proposal to perform scenario 4 (intra-hour scheduling)Finalize AGC and Pool structure assumptionsPNNL will perform PROMOD simulation for scenarios 1,2 and 3 using TEPPC 2020 case

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QUESTIONS?

Questions?