Multi-Objective design optimization of a Superconducting Fault Current Limiter
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Zenergy Power Inc.The superconductor energy technology company
Multi-Objective design optimization of a Superconducting Fault Current Limiter
EnginSoft International Conference 2010
Brescia, IT
22 October 2010
[1]
Franco Moriconi, SVP Engineering
Zenergy Power Inc.
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Overview
• About Zenergy Power
• What is a Superconductive Fault Current Limiter (FCL)
• Design and Product Optimization
• The ModeFrontier Results
• Future Work
• Q&A
[2]
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Zenergy Power – Overview
[3]
• Zenergy Power Plc • Admitted to London AIM (ZEN.L) 2006 • Market Cap ~ £90m• Employees 100
• Entities incorporated• Australia 1987 (fault current limiters)• Germany 1999 (MBH, wires, coils, magnets)• USA 2004 (fault current limiters)• UK 2005 (finance, investor relations)
• Intellectual Property – Over 170 patents and applications
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Superconductors – The Quantum Leap in Electricity
Superconductors conduct electricity with no resistance – enabling 2 key properties:
- 100% energy efficiency: no electrical losses - 100 times current carrying capability: reduction in material use
‘Superconductivity is the enabling key technology to unlock the future of clean energy -the ‘optical fibres’ of electricity’ Dr. Jens Mueller, CEO.
[4]
Copper Wire
Superconducting Wire
200 A200 A
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Zenergy Power’s Products
[5]
Sector Application End Products
Smart Grid Transmission & Distribution Fault Current Limiters
Industrial Machines Energy Efficiency Induction Heater
Renewable Power Power Generation Generators
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[6]
Save more than 800 barrels of oil a year with superconducting heating
Industrial Heater – World's 1st Superconductor Energy Product
"This process is a quantumn leap for the metal processing industry – as up to 5% of the electricity of industrialised countries is consumed in conventional induction heaters" Dr. Fritz Brickwedde, General Secretary of the German Enviromental Fund
German Environmental prize 2009
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Superconductor Induction Heaters: Commercial advantages
- World’s first industrial-scale commercial superconductor product- High-efficiency superconductor coils: 50% reduced energy consumption- High-power superconductor coils: 25% increased productivity - Superconducting coils: improved heating quality- Used globally by metals producers to heat metal
Comparison: 0.5 MW heating requirement
Copper Induction Heater HTS Induction Heater
Investment €1.2m ≥ €1.4m
Annual electricity savings 0 €50k - €300k
Productivity increase per annum 0 €200k - €2m
Efficiency levels 40% 90%
Management calculation based on performance data provided by customer “Weseralu”
[7]
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Landmark Installation: Los Angeles, March 2009
115 kV LINE
115/12kVTransformer
BYPASSSWITCH
12 kV AVANTI “Circuit of the Future” - Los Angeles California
First installation in U.S. electricity gridOperated by Southern California EdisonInstalled in Avanti “Circuit of the Future”First Energized on March 9, 2009Supported by DOE and California Energy Commission
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Landmark Installation: Los Angeles, March 2009
FCL
FC
L
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one second3.5 KA peak
0.2 KA load
Fault Event – 12 kV Installation in Los Angeles
Operational Experience
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American Electric Power - AEP Project
Requirements
• 138 kV
• 300 MVA• Fault Current Limitation - 50%
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SATURABLE IRON CORE FCL
Picture-Frame Iron-Cores
AC CoilAC Coil
Boost Buck
Configuration for single phase FCL
Operating Principle
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Installation - Los Angeles
Proprietary [13]
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Inductive Fault Current LimiterThe equivalent FCL inductance is a non-linear function of the instantaneous line current, and it may look like the graph below during a fault:
CLRConstantInductance
-15.0 -10.0 -5.0 0.0 5.0 10.0 15.0 -0.0010
0.0000
0.0010
0.0020
0.0030
0.0040
0.0050
0.0060 +y
-y
-x +x
X Coordinate Y Coordinate
I_Limited L_cusEquivalent Inductance
Instantaneous AC Current [kA]
FCL Inductanceis small at load current
FCL InductanceIncreases dramaticallyduring a fault
Operating Principle
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Confidential & Proprietary | 15
23kA FAULT LEVEL
0.5 1 1.5 2 2.5 3 3.5 4-50
-40
-30
-20
-10
0
10
20
30
40
50TEST 77 - DOUBLE FAULT SEQUENCE - 20kA X/R=22, FCL IN
Time [sec]
Line
Cur
rent
[kA
]
Phase A
Phase BPhase C
0.5 1 1.5 2-50
-40
-30
-20
-10
0
10
20
30
40
50TEST 77 - 1.25s - 80 cycles FAULT - 20kA X/R=22, FCL IN
Time [sec]
Lin
e C
urr
en
t [kA
]
Phase A
Phase BPhase C
-40000
-30000
-20000
-10000
0
10000
20000
30000
40000
50000
60000
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
Time [s]
Cu
rren
t [A
]
FEA - Iac No FCL
FEA - Iac With FCL
Prospective fault current = 19.2 kArmsLimited fault current = 10.26 kA (46.6% reduction)
Single phase AEP 2x1 D-core with 21mm thick tank. If' = 19.2kA. Sing;le Phase Fault Current results.
VS = 138kV l-l Rs =34.79mΩ Xs = 4.1495Ω RLOAD = 79.5Ω X/R = 119
ACORE = 0.20m2 NAC =122 NIDC =730kAT HAC = 3.5m HCORE = 4.0m HDC = 400mm
Fault Current Waveforms
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Confidential & Proprietary | 16
Trade-off Considerations to Meet Requirements
typermeabili relative
length coil
section cross coil
turns AC n
Inductance
AC
r
rAC
l
A
ol
AnL
;2
changedensity Flux
B An dt V
t
BAnemf
t
Φemf
coreAC
coreAC
B
Low InsertionImpedance:nac, A, permeabilitylength
High Fault CurrentReduction:nac, Acore, DB
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FCL Design
Confidential and Proprietary Information
MAGNET OPTIMIZATION
HTS COIL OD 1700 mm
• Electromagnetic force in a magnet is AMPS x TURNS• Cost of magnet is driven by Amp-turns needed and amount of cooling• Price of conductor can be several hundreds $$ / kA-m
we need high current density to reduce cost• For fixed current density we want to reduce conductor length (volume)• Current Density is inversely proportional to working temperature
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multi-objective optimization
Weighted Function approach: transform the given multi-objective problem into an equivalent single-objective problem. The solution depends on the values of the weights αi .
Multi-objective optimization problem:
i=1,…, n objectives
Sx
xg
xf
j
jk
ji
0)(
)(max
Sx
xg
xfxh
j
jk
ji
n
iij
0)(
)()(max1
True Multi-objective approach: An alternative to combining metrics in a predetermined way, approach design as the solutions defined within the n-dimensional space of the design objectives and variables.
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Pareto Frontier: definition
With conflicting objectives, the aim is to find good compromises rather than a unique solution. So, this approach results in a set of solutions, called the “Pareto Frontier”. In any solution contained in the Pareto Frontier, none of the objectives can be improved without
deterioration of at least one other objective. Hence these solutions are known as “non-dominated” solutions.
Performance
Cost
Maximum Performance Solution(1)
Minimum Cost Solution (2)
Compromise Solution (3)
Non-Optimal Solution (0)
Pareto Frontier
Image courtesy of EnginSoft
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Problem Formulation: x, the variables
D_H
TS
H_c
ore
H_a
c
Gap_tank
Gap_tank
HTS_OD/2
h_HTS
Tank_th
Tank_OD
Independent
1: Cryo_Gap
2: Cu_r1
3: Cu_r2
4: Cu_rad
5: D_HTS
6: Gamma1
7: Gamma2
8: H_core
9: NDC_h
10: NDC_v
11: h_ac
12: nac_h
13: r11
14: r12
15: r13
Dependent
1: HTS_th
2: H_ac
3:NDC
4: h_HTS
5: nac
6: v_ac
Constants
1: h_dc
2: v_dc
3: nac_v
4: Thick_Tank
5: Gap_Air
Design Parameters 26+ Variables: 21
Independent: 15 Dependent: 6+
Constants: 5+
nac= nac_h* nac_v
nac_h
nac_v
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Solution
• Used modeFRONTIER®, a multi-objective optimization software
• It wraps around ANSYS, performing optimization by• modifying the values assigned to the input variables, and • analyzing the corresponding outputs calculated by ANSYS, using genetic algorithms.
• For this particular problem:• evaluated 960 Designs• In each evaluation:
• idc kept constant at 130A• iac 25 values : 1.25k:500:13.25kArms• 24000 inductance calculations• @1inductance calculation/min: 400+ hrs: 16+ days
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Results
TBbuck 5.3
HL statesteady 100_
■Pareto Frontier: Feasible Solutions Unfeasible Solutions
faultL
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Results
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Results
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Results
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Results: max performance
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Results: min cost
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Results: compromise
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Design Solution D_HTS HTS_th H_ac NDC h_HTS nac v__acStarting Design 1.35 0.01376 2.1014 2000 0.2425 38 0.0254
Best Performance 1.38666 0.00999 1.872 1591 0.1849 36 0.0236Least Expensive Solution 1.13114 0.00999 1.944 1517 0.1763 36 0.0278
Best Compromise 1.08794 0.00999 1.872 1517 0.1763 36 0.0278
Design Solution BB_buck_Eff_Point Lbuck_Mean_Maximize Lbuck_Min Volume_HTSMax Performance 36.6% 33.3% 27.5% -58.8%
Min Cost 41.4% -12.1% 17.7% -60.7%Compromise 45.9% -6.3% 16.2% -60.7%
Design Solution CRYO_GAP Cu_r1 Cu_r2 Cu_rad D_HTS_Normalized Gamma1 Gamma2 H_core NDC__h NDC__v h__ac nac__h r11 r12 r13Starting Design 0.1 0.05 0.05 0.0254 0.75 0.0254 0.0254 2.6 50 40 0.0553 38 0.01 0.02 0.02
Best Performance 0.0725 0.025 0.04 0.0236 0.8 0.02 0.035 2.665 43 37 0.052 36 0.044 0.027 0.009Least Expensive
Solution 0.0725 0.045 0.015 0.0278 0.6 0.04 0.04 2.385 41 37 0.054 36 0.044 0.027 0.011Best Compromise 0.07 0.045 0.03 0.0278 0.6 0.04 0.04 2.425 41 37 0.052 36 0.044 0.027 0.014
3 alternative designs provided, each improving the initial design under all 4 objectives:
Comparison of Output Variables
Comparison of Dependent Input Variables
Results: summary
Summary
)min(
)min(
)max(
)max(
_
_
coildc
statesteady
fault
buck
vol
L
L
B
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Thermal Optimization of HTS Coil
Initial Design Model
Copper Mass 348.5
HTC Max Temp 34.58
HTC Min Temp 31.15
HTC Avg Temp 33.19
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Thermal Optimization - Workflow
Input geometric variables of the parametric model
Output Variables
Objectives & Constraint
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Thermal Optimization – Sensitivity Analysis
Ranking- The correlation index
Line Correlation+1=Direct Effect-1=Inverse Effect
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Thermal Optimization
Avg Temp
CopperMass
All Designs
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Thermal Optimization of HTS Coil
Avg Temp
CopperMass Design
1105
Design2130
InitialDesign
Design1906
Design1070
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Thermal Optimization – Summary of Results
Description DesignNumber
% Copper Mass Difference
% Max HTC Difference
Initial Design 2178 0.0% 0.0%
Minimum HTC Temp 1105 -247.78% 29.15%Compromise Design 1 2130 2.67% 18.48%Compromise Design 2 1070 42.70% 4.34%Minimum Copper Mass 1906 44.51% -12.32%
Designs Comparison with Initial Design Configuration
+ % refers to reduction
-% refers to increase
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FUTURE WORK
Combine Geometry- Cooling and Magnetic Field Effects
DecreasingTemperature