Date post: | 27-Mar-2015 |
Category: |
Documents |
Upload: | luke-klein |
View: | 214 times |
Download: | 0 times |
VGS StudyVGS StudyBenefits of Leveraging Diversity across the Benefits of Leveraging Diversity across the
Western InterconnectionWestern Interconnection
1
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
2
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
3
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 )
4
Progress in the Study
5
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)
6
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
8
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)
17
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
33
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
376
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
37
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
38
QUESTIONS?
Questions?