Metropolitan’s SWP Supply Forecasting and Optimal Scheduling
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Metropolitan’s SWP Supply Forecasting and Optimal
Scheduling
CWEMF Annual MeetingFebruary 27, 2007
Peter LouieMetropolitan Water District of So. California
Objectives
• Improve short-term water management decision-making and scheduling for MWD
• Allow varying levels of risk to be considered in decision-making
• Utilize optimization to mimic water supply, water quality, and cost preferences
MWD Water OperationsRegional water supply to 6 counties
26 Member Agencies Supply 18 million people Supply 1.5 billion gallons of water/day 1,072 miles of pipelines, tunnels, & canals 5 treatment plants 17 reservoirs 16 hydroelectric power plants 45 major control structures 5 pumping plants on the CRA
SWP entitlement: 1.9 MAF (2006) CRA entitlement: 652 TAF
Dry-YearDry-Year PortfolioPortfolioDry-YearDry-Year PortfolioPortfolio
San Joaquin Valleytransfers
Sacramento Valley transfers& DWR Drought Bank
Surface ReservoirsSurface Reservoirs Multi-Year ProgramsMulti-Year Programs (Ground water)(Ground water)
Single-Year OptionsSingle-Year Options (Transfers)(Transfers)
Lake PerrisLake Perris
Skinner ReservoirSkinner Reservoir
Diamond Valley LakeDiamond Valley LakeLake MathewsLake Mathews
Castaic LakeCastaic Lake
San Luis ReservoirSan Luis Reservoir
Kern Delta W.D.Kern Delta W.D.
Semitropic W.S.D.Semitropic W.S.D.
Hayfield BasinHayfield Basin
Coachella Valley W.D.
Coachella Valley W.D.
Imperial I.D.Imperial I.D.
Palo Verde I.D.
Palo Verde I.D.
Arizona BankingArizona Banking
Arvin-Edison W.S.D.Arvin-Edison W.S.D.
San Bernardino Valley M.W.D.San Bernardino Valley M.W.D.
Mojave W.A.Mojave W.A.
2005 2006
Dec Jan MayFeb Mar Apr Nov Dec
EWANegotiations
SWP initialAllocation
SBVMWDTransfersNotification
Kern DeltaNotificationFor Put only
Decision to take SBVMWDTransfers
Final Kern DeltaNotificationPut/Take
Arvin EdisonNotificationPut/Take
TurnbackPool B
SemitropicNotification
Put
DWCVCallback
Notification
SemitropicNotification
Take
SWPFinal
Allocaton
DWCVDeliveries
Set Carryover
Limits
WSDM Action Timeline
SWP ForecastsWQ, WS
Delta Ops
Aqd./Res. Model
TransfersNorth of Delta
Transfers South of Delta
CRA ForecastsWQ, WSMWD
Dist. System Model
Availability of quantity,timing and wq characteristics
Availability of quantity,timing and wq characteristics
Allocation and storage conditionswq characteristics
Allocation and storage conditionswq characteristics
Res. ops/ wq targets for treatment plants/consumptive use/seasonal storage
WQCP/ESA/EWA/b2 and otherDelta regulations and requirements
Tracking wq
System Models IntegrationAnd Optimization Schema
OptimizationProcedure
LP/DP approach to determinethe desirable combination of SWP/CRA/EWA/Transfers/MWD storage ops in meetingboth the ws/wq objectives.
Hydrologic Forecasts (DWR Flood Management, CNRFC)
System State (CDEC, USGS, IEP)
Demand Forecasts (Contractors, Env, Reg)
Allocation Forecasting Tool
(CALSIM-CAM)
Scheduling Optimization Tool
(SISAGUA)
Priorities
MWD-Specific Network
MWD Delivery Point Demands
Non-CALSIM-CAM Supplies
Con
trol
ler/I
nter
face
Too
l (V
BA
) (D
ata
acqu
isit
ion
and
tran
sfer
, con
trol
seq
uenc
e of
sim
ulat
ion,
con
trol
it
erat
ion
and
clos
ure,
use
r in
ferf
ace
)
SWP allocation, forecasts of availability of supplies, storage, system conditions
MWD preferred delivery request schedule
Data acquisition/ transfer
Data acquisition/ transfer
Data acquisition/ transfer
Overall Analytical Approach
SWP Allocation Forecasting Tool
Source Data
CAM Input
Runtime Control/ Data Setup
• Period of greatest uncertainty: October – January• Critical information
– Risk of spill of carryover storage – Initial allocation – Positional Analysis provides broad sampling of
possible hydrologic conditions– Monte-Carlo simulation with uniform sampling of
historic hydrology• Climate indicators may indicate skewness from the
uniform sampling– Reshaping of Position Analysis inputs – As forecast becomes available, CAM stand-alone
may be used in conjunction with PA-CAM
Projections under Poor/No Forecast
• Improving forecasts: February – May• Critical information
– Delivery reliability– Storage conditions
• P25, P50, P75, P90, P99 forecasts provide traces of possible hydrologic conditions
• CAM stand-alone study provides delivery and storage estimates
• Longer term assessed with CAM-PA simulations
Projections with Available Forecast
SWP Allocation Forecasting Tool
Source Data
CAM Input
Runtime Control/ Data Setup
0
500
1000
1500
2000
2500
3000
3500
4000
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
S4_DEC Oroville EOM Storage
0
100
200
300
400
500
600
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
D6_DEC SWP Contractor Deliveries
Precipitation Indices
Precipitation or Climate
Indices
Official B-120 Forecast
Historical Inflow Traces Ranked Inflow Distribution
+
+
=
=
Updated Inflow Distribution
Method for developing revised inflow distributions
Proposed Monte Carlo simulation method
Dynamic Programming Schematics For Optimizing Water Quality/Water Supply/CostsProblem Formulation: Optimization Objectives and System Constraints Specifications
Objectives: Minimizing the water quality indices from prescribed targets (As, Br, Cr, Cr+6, NO3, TDS, DOC,TOC, SO4, U, V); this could be a linear combination of all the indices or minimizing each in turn.
Minimizing operating costs (energy consumption, disruption penalties, etc.)
Maximizing supply reliability (probability in meeting the quantities requested)
Constraints: Resources availabilitySystem fill and withdrawal capacitiesOperational requirements (system ramping up and down )Water supply and quality requirementsBudgetary limitationSystem ops requirements
Time step =1Quantity & Quality required
Dynamic Programming Schematics For Optimizing Water Quality/Water Supply/CostsThrough Water Transfers and Exchanges and System Re-ops
Source1(Semitropic)
100%
90%
80%
70%
0%
10%
Source1(Semitropic)
100%
90%
80%
70%
0%
10%
Source2(Arvin Edison)
100%
90%
80%
70%
0%
10%
Source2(Arvin Edison)
100%
90%
80%
70%
0%
10%
SourceN(SC Reservoir
Re-Ops)
100%
90%
80%
70%
0%
10%
SourceN(SC Reservoir
Re-Ops)
100%
90%
80%
70%
0%
10%
Time step =iQuantity & Quality required
Source1(Semitropic)
100%
90%
80%
70%
0%
10%
Source2(Arvin Edison)
100%
90%
80%
70%
0%
10%
SourceN(SC Reservoir
Re-Ops)
100%
90%
80%
70%
0%
10%
Source1(Semitropic)
100%
90%
80%
70%
0%
10%
Source1(Semitropic)
100%
90%
80%
70%
0%
10%
Source2(Arvin Edison)
100%
90%
80%
70%
0%
10%
Source2(Arvin Edison)
100%
90%
80%
70%
0%
10%
SourceN(SC Reservoir
Re-Ops)
100%
90%
80%
70%
0%
10%
SourceN(SC Reservoir
Re-Ops)
100%
90%
80%
70%
0%
10%
Time step =T
Sourcej Sourcej
Dec
isio
n k
Z1(i,j,x)= minimum deviation of WQI from target attainable from source j, j+1,N at time step i with xdollars available to implement the decision dj.
= min f(WQIj, Z1(i,j+1,x-Costdjdj
Where dj would yield the minimum WQI up to the j source from the backward sense. A subsystem model f()* would be used, given the dj, to determine the best WQI can be attained. Among the best WQIs from djs, the minimum would be selected.
Boundary and starting conditions:Z1(i,j,x)= for x<=0 j=1 to N ; i= 1 to TZ1(i,N+1,x)= 0 for x>=0
*The subsystem model(s) could be simulation models or optimization models themselves dependingon the systems involved.
Srf Wtr_In
-800,000
-600,000
-400,000
-200,000
0
200,000
400,000
600,000
800,000
1975 1976 1977 1978 1979
Time Period
Put/T
ake
(AF)
0
100,000
200,000
300,000
400,000
500,000
600,000
700,000
800,000
900,000
Acc
ount
Bal
ance
(AF)
Put/Take Account MaxAccount Min Account TrackingPut Capacity Take Capacity
2 3 4 5 1
Pu
tT
ake
Grd Wtr_Out
-500,000
-400,000
-300,000
-200,000
-100,000
0
100,000
200,000
300,000
400,000
1975 1976 1977 1978 1979
Time Period
Put/T
ake
(AF)
0
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000
1,600,000
1,800,000
Acco
unt B
alan
ce (A
F)
Put/Take Account MaxAccount Min Account TrackingPut Capacity Take Capacity
2 3 4 5 1
Tak
eP
ut
Summary
• Forecast-Optimization approach shows promise for improving MWD water management
• Consideration of uncertainty allows MWD decision-makers/operators to assess internal risk
• Optimization approaches are actively being used in SWP and MWD systems
• Future work will consider continuously-updated adjustments to forecasts
• Prototype for MWD’s SWP-side supplies may be expanded
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