Masoud Asadzadeh 1, Masoud Asadzadeh 1, Saman Razavi 1, Bryan Tolson 1 David Fay 2, William Werick...
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A New Rule Curve Based Regulation Plan for Lake Superior Masoud Asadzadeh 1 , Saman Razavi 1 , Bryan Tolson 1 David Fay 2 , William Werick 3 , Yin Fan 2 2- Great Lakes - St. Lawrence Regulation Office, Meteorologial Service of Canada, Environment Canada 1- Department of Civil and Environmental Engineering, University of Waterloo 3- Werick Creative Solutions
Masoud Asadzadeh 1, Masoud Asadzadeh 1, Saman Razavi 1, Bryan Tolson 1 David Fay 2, William Werick 3, Yin Fan 2 2- Great Lakes - St. Lawrence Regulation
Masoud Asadzadeh 1, Masoud Asadzadeh 1, Saman Razavi 1, Bryan
Tolson 1 David Fay 2, William Werick 3, Yin Fan 2 2- Great Lakes -
St. Lawrence Regulation Office, Meteorologial Service of Canada,
Environment Canada 1- Department of Civil and Environmental
Engineering, University of Waterloo 3- Werick Creative
Solutions
Slide 2
Outline Introduction Methodology Rule Curve Form System
Simulation/Evaluation Optimization Algorithm Results and
Discussions Conclusions 2
Slide 3
3
Slide 4
4 Objectives Develop a rule curve for Lake Superior Outflow
Preforms better than the current plan (Plan 1977A) Respect the
structural outflow constraints Consider the storage conditions
upstream and downstream Parameterize the Lake Superior outflow
Optimize the system performance by automatically calibrating the
rule curve parameters Utilize the most accurate simulation of the
system Consider multiple future climate conditions in the form of
NBS
Slide 5
5 Beginning of Period Lake Superior Surface Elevation (m) 1 1 1
a 1 b d c ef ExcessShortage a b d c 1 1 g h Beginning of Period
Level MH Surface Elevation (m) Excess Shortage 22 2 (seasons) x 11
(a, b, , j, Baseline Flow) = 22 1 1 i j Beginning of Period Level
ER Surface Elevation (m) Excess Shortage
Slide 6
6 System Simulation/Evaluation CGLRRM, Co-ordinated Great Lakes
Regulation and Routing Model (Fortran executable) SP, Shoreline
Protection (Microsoft Excel) SVM, Shared Vision Model (Microsoft
Excel) Commercial Navigation, Hydropower Generation, and Shoreline
Protection benefits/costs relative to Plan 1977A Criteria
satisfaction/violations checks
Slide 7
7 Criteria (IUGLS) Lake Superior Levels Highest level: 183.86 m
Lowest level: 182.76 m Lake Michigan-Huron Levels Highest level:
77A Lowest level: 77A Average 2% high levels: 77A Average 2% low
levels: 77A
Slide 8
8 Selected NBS Scenarios (from stochastic NBS) The 109-year
period Stationary HI Historical From 1900-2008 Historical recorded
NBS, adjusted to current demands and diversions. This sequence has
as many as 7 consecutive years above, and 7 consecutive years below
average NBS. Uncertain Change HM highest Michigan-Huron levels
Based on current climate, but highest Michigan-Huron levels, with a
great range between wettest and driest years. LM lowest
Michigan-Huron levels Based on current climate, but creates the
lowest Michigan-Huron levels while still producing a maximum level
greater than historical. Includes 14 consecutive years of below
average NBS. Change to Drier Period LS lowest Lake Superior level
Based on current climate, but produces the lowest Lake Superior
level in entire stochastic simulation. Change to Wetter Period HS
highest Lake Superior level Current climate, average NBS close to
historical NBS, but with the highest Lake Superior level. Its
wettest portion comes early in the simulation, as would be expected
if recent dry NBS forecast a reversal to wet conditions.
Slide 9
9 Modified Criteria Lake Superior Levels Highest level:
max(183.86 m, 77A) Lowest level: min(182.76 m, 77A) Lake
Michigan-Huron Levels Highest level: 77A Lowest level: 77A Average
2% high levels: 77A Average 2% low levels: 77A
Slide 10
10 Problem Formulation Optimize Criteria-Based Objective
Expected Solution F G 12 F F: Being Maximized Positive value:
Benefits for Commercial Navigation, Hydropower Generation and
Shoreline Protection across all 5 NBS scenarios G G: Being
Maximized Positive value: No criteria Violation in any of the 6
criteria across all 5 NBS scenarios
Slide 13
Optimization Algorithm: PA-DDS Perturb current ND solution
Update ND solutions Continue? STOP New solution is ND? Pick the New
solution Pick a ND solution Initialize starting solutions Y N
Create ND-solution set Y N 13
Slide 14
Simulation-Optimization Components 14 MATLAB: Solution
Generation, preliminary Lake Superior Outflow Simulation Runtime
< 1 sec/solution CGLRRM: Upper Great Lake Simulation by MATLAB
results Runtime ~= 10 sec/solution MS Excel: Shared Vision Model
Runtime ~= 20 sec/solution MS Excel: Shoreline Protection Runtime
> 200 sec/solution 64-bit Intel Core i7 930 @ 2.80 GHz with 12
GB of Ram
Slide 15
Model Pre-emption 15 F G 0 Scenario1 simulation Scenario2
simulation Scenario3 simulation Scenario4 simulation Scenario5
simulation Objective Function Calculation
Slide 16
Pareto Approximate Front Pareto Approximate Front (20,000
solutions eval.) 16 Benefit Selected Solution for further
evaluations Raw sum of benefits and costs
Slide 17
Selected Solution Selected Solution (Validation) 17 Uncertain
ChangeStationary Change to Drier Period WS AT LRDSAVT1T2TR Max SUP
77A183.92 183.93 183.75183.81 183.75183.69- UW3183.97 183.91
183.81183.84183.88183.78183.70183.80 Min SUP 77A182.91 182.73
182.92182.71182.52181.86181.81