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Multi-Objective design optimization of a Superconducting Fault Current Limiter

Multi-Objective design optimization of a Superconducting Fault Current Limiter



Presented at the EnginSoft International Conference 2010, Brescia, Italy

Presented at the EnginSoft International Conference 2010, Brescia, Italy
22 October 2010



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    Multi-Objective design optimization of a Superconducting Fault Current Limiter Multi-Objective design optimization of a Superconducting Fault Current Limiter Presentation Transcript

    • Zenergy Power Inc.The superconductor energy technology companyMulti-Objective design optimization of a Superconducting Fault Current LimiterEnginSoft International Conference 2010Brescia, IT22 October 2010[1]Franco Moriconi, SVP EngineeringZenergy Power Inc.franco.moriconi@zenergypower.com
    • Overview• About Zenergy Power• What is a Superconductive Fault Current Limiter (FCL)• Design and Product Optimization• The ModeFrontier Results• Future Work• Q&A[2]
    • 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
    • Superconductors – The Quantum Leap in ElectricitySuperconductors 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]CopperWireSuperconductingWire200 A200 A
    • Zenergy Power’s Products[5]Sector Application End ProductsSmart Grid Transmission & Distribution Fault Current LimitersIndustrial Machines Energy Efficiency Induction HeaterRenewable Power Power Generation Generators
    • [6]Save more than 800 barrels of oil ayear with superconducting heatingIndustrial Heater – Worlds 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 consumedin conventional induction heaters"Dr. Fritz Brickwedde, General Secretary of the German Enviromental FundGerman Environmental prize 2009
    • 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 metalComparison: 0.5 MW heatingrequirementCopper Induction Heater HTS Induction HeaterInvestment €1.2m ≥ €1.4mAnnual electricity savings 0 €50k - €300kProductivity increase per annum 0 €200k - €2mEfficiency levels 40% 90%Management calculation based on performance data provided by customer “Weseralu”[7]
    • 8Landmark Installation: Los Angeles, March 2009115 kV LINE115/12kVTransformerBYPASSSWITCH12 kV AVANTI “Circuit of the Future” - Los Angeles CaliforniaFirst 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
    • 9Landmark Installation: Los Angeles, March 2009FCL
    • one second3.5 KA peak0.2 KA loadFault Event – 12 kV Installation in Los AngelesOperational Experience
    • 11American Electric Power - AEP ProjectRequirements• 138 kV• 300 MVA• Fault Current Limitation - 50%
    • 12SATURABLE IRON CORE FCLPicture-Frame Iron-CoresAC CoilAC CoilBoost BuckConfiguration forsingle phase FCLOperating Principle
    • Installation - Los AngelesProprietary [13]
    • 14Inductive 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 15.0-0.00100.00000.00100.00200.00300.00400.00500.0060+y-y-x +xX Coordinate Y CoordinateI_Limited L_cusEquivalent InductanceInstantaneous AC Current [kA]FCL Inductanceis small at load currentFCL InductanceIncreases dramaticallyduring a faultOperating Principle
    • Confidential & Proprietary | 1523kA FAULT LEVEL0.5 1 1.5 2 2.5 3 3.5 4-50-40-30-20-1001020304050TEST 77 - DOUBLE FAULT SEQUENCE - 20kA X/R=22, FCL INTime [sec]LineCurrent[kA]Phase APhase BPhase C0.5 1 1.5 2-50-40-30-20-1001020304050TEST 77 - 1.25s - 80 cycles FAULT - 20kA X/R=22, FCL INTime [sec]LineCurrent[kA]Phase APhase BPhase C-40000-30000-20000-1000001000020000300004000050000600000 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2Time [s]Current[A]FEA - Iac No FCLFEA - Iac With FCLProspective 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 Currentresults.VS = 138kV l-l Rs =34.79mΩ Xs = 4.1495Ω RLOAD = 79.5Ω X/R = 119ACORE = 0.20m2NAC =122 NIDC =730kAT HAC = 3.5m HCORE = 4.0m HDC = 400mmFault Current Waveforms
    • Confidential & Proprietary | 16Trade-off Considerations to Meet RequirementstypermeabilirelativelengthcoilsectioncrosscoilturnsACnInductanceACrrAClAolAnL ;2changedensityFluxBAndtVtBAnemftΦemfcoreACcoreACBLow InsertionImpedance:nac, A,permeabilitylengthHigh Fault CurrentReduction:nac, Acore, B
    • 17FCL DesignConfidential and Proprietary InformationMAGNET OPTIMIZATIONHTS 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-mwe 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
    • 18multi-objective optimizationWeighted 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 objectivesSxxgxfjjkji0)()(maxSxxgxfxhjjkjiniij0)()()(max1True Multi-objective approach: An alternative to combining metrics in a predetermined way, approachdesign as the solutions defined within the n-dimensional space of the design objectives and variables.
    • 19Pareto 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 withoutdeterioration of at least one other objective. Hence these solutions are known as “non-dominated” solutions.PerformanceCostMaximum Performance Solution(1)Minimum Cost Solution (2)Compromise Solution (3)Non-Optimal Solution (0)Pareto FrontierImage courtesy of EnginSoft
    • 20Problem Formulation: x, the variablesD_HTSH_coreH_acGap_tankGap_tankHTS_OD/2h_HTSTank_thTank_ODIndependent1: Cryo_Gap2: Cu_r13: Cu_r24: Cu_rad5: D_HTS6: Gamma17: Gamma28: H_core9: NDC_h10: NDC_v11: h_ac12: nac_h13: r1114: r1215: r13Dependent1: HTS_th2: H_ac3:NDC4: h_HTS5: nac6: v_acConstants1: h_dc2: v_dc3: nac_v4: Thick_Tank5: Gap_Air Design Parameters 26+ Variables: 21 Independent: 15 Dependent: 6+ Constants: 5+nac= nac_h* nac_vnac_hnac_v
    • 21Solution• 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 geneticalgorithms.• 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
    • 22ResultsTBbuck 5.3HL statesteady 100_■Pareto Frontier: Feasible Solutions Unfeasible SolutionsfaultL
    • 23Results
    • 24Results
    • 25Results
    • 26Results: max performance
    • 27Results: min cost
    • 28Results: compromise
    • 29Design Solution D_HTS HTS_th H_ac NDC h_HTS nac v__acStarting Design 1.35 0.01376 2.1014 2000 0.2425 38 0.0254Best 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 0.0278Best Compromise 1.08794 0.00999 1.872 1517 0.1763 36 0.0278Design 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 0.02Best 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 ExpensiveSolution 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 0.0143 alternative designs provided, each improving the initial design under all 4 objectives:Comparison of Output VariablesComparison of Dependent Input VariablesResults: summarySummary)min()min()max()max(__coildcstatesteadyfaultbuckvolLLB
    • 30Thermal Optimization of HTS CoilInitial Design ModelCopper Mass 348.5HTC Max Temp 34.58HTC Min Temp 31.15HTC Avg Temp 33.19
    • 31Thermal Optimization - WorkflowInput geometric variables of the parametric modelOutput VariablesObjectives & Constraint
    • 32Thermal Optimization – Sensitivity AnalysisRanking- The correlation indexLine Correlation+1=Direct Effect-1=Inverse Effect
    • 33Thermal OptimizationAvg TempCopperMassAll Designs
    • 34Thermal Optimization of HTS CoilAvg TempCopperMass Design1105Design2130InitialDesignDesign1906Design1070
    • 35Thermal Optimization – Summary of ResultsDescription DesignNumber% Copper MassDifference% Max HTCDifferenceInitial 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
    • 36FUTURE WORKCombine Geometry- Cooling and Magnetic Field EffectsDecreasingTemperature
    • simply better[37]Franco MoriconiSVP EngineeringZenergy Power Inc.franco.moriconi@zenergypower.com