Diao, Ruisheng

Huang, Henry

Jin, Shuangshuang

Makarov, Yuri

English

Engineering Conferences International

Engineering Conferences InternationalECI Digital ArchivesModeling, Simulation, And Optimization for the21st Century Electric Power Grid ProceedingsFall 10-22-2012Improving Transmission Asset Utilization ThroughAdvanced Mathematics and ComputingHenry HuangPacific Northwest National LaboratoryRuisheng DiaoPacific Northwest National LaboratoryShuangshuang JinPacific Northwest National LaboratoryYuri MakarovPacific Northwest National LaboratoryFollow this and additional works at: http://dc.engconfintl.org/power_gridPart of the Electrical and Computer Engineering CommonsThis Conference Proceeding is brought to you for free and open access by the Proceedings at ECI Digital Archives. It has been accepted for inclusion inModeling, Simulation, And Optimization for the 21st Century Electric Power Grid by an authorized administrator of ECI Digital Archives. For moreinformation, please contact franco@bepress.com.Recommended CitationHenry Huang, Ruisheng Diao, Shuangshuang Jin, and Yuri Makarov, "Improving Transmission Asset Utilization Through AdvancedMathematics and Computing" in "Modeling, Simulation, And Optimization for the 21st Century Electric Power Grid", M. Petri,Argonne National Laboratory; P. Myrda, Electric Power Research Institute Eds, ECI Symposium Series, (2013).http://dc.engconfintl.org/power_grid/8Improving Transmission Asset Utilization through Advanced Mathematics and Computing Modeling, Simulation and Optimization for the 21st Century Electric Power GridOctober 21-25, 2012 Lake Geneva, Wisconsin1Henry Huang, Ruisheng Diao, Shuangshuang Jin, Yuri MakarovPacific Northwest National LaboratoryOctober 22, 2012Transmission congestion – an ever increasing challenge Incur significant economic cost2004: $1 billion cost at California ISO due to congestion and reliability must-run requirements [1] 2008: >$1.5 billion congestion cost at New York ISO [2] Prevent wind integration Wind generation curtailment  due to transmission congestionCongestion will become worse and more complicatedUncertainty, stochastic power flow patterns due to changing generation and load patterns, increased renewable generation, distributed generation, demand response and the increasing complexity of energy and ancillary service markets and Balancing Authority (BA) coordination.2[1] California Energy Commission, “Strategic Transmission Investment Plan”, November 2005[2] NYISO, Congestion Analysis Summary for 2008.Building more transmission lines is not the best optionTransmission build-out lags behind load growth1988-98: load grew by 30%, transmission grew by only 15% [3]Resulting in a transmission grid that must operate closer to the maximum limit, and this is expected to compound as demand for electricity is expected to double by 2050. Transmission expansion is constrained by:Financial and cost-recovery issues Right-of-way and Environmental considerations 3[3] U.S. Department of Energy, “The Smart Grid: An Introduction.” Possibility of utilizing more of what we already haveThermal rating10,500 MWMeasurement of Transfer Capacity     Example - California Oregon Intertie (COI) [4] Path RatingsU75 – % of time flow exceeds 75% of OTC (3,600 MW for COI)U75, U90 and U(Limit)4Stability Rating(Transient Stability and Voltage Stability)4,800 MW[4] Western interconnection 2006 congestion management studyU90 - % of time flow exceeds 90% of OTC (4,320 MW for COI)U(Limit) - % of time flow reaches 100%  of OTC  (4,800 MW for COI)% of OTC75% 90% 100%Real-time path ratingCurrent Path Rating Practice and LimitationsOffline studies – months or a year ahead of the operating seasonWorst-case scenarioRatings are static for the operating season The result: conservative (most of the time) path rating, leading to artificial transmission congestionReal-Time Path RatingOn-line studiesCurrent operating scenariosRatings are dynamic based on real-time operating conditions  The result: realistic path rating, leading to maximum use of transmission assets and relieving transmission congestion5Real-time path rating – case studies2500IEEE 39-bus power system26% more capacity without building new transmission linesWECC COI Line Full study with realistic case and parametersPeak rating increases 30%65 10 15 200500100015002000Time, hourTransfer limit of a critical path, MW Real-time Path RatingOffline path rating, current practice25.74% more energy transferusing real-time path rating30% increaseBenefits of real-time path ratingIncrease transfer capability of existing power network and enable additional energy transactions $15M annual revenue for a 1000-MW rating increase for one transmission path in the WECC system, even if only 25% of the increased margin can be used for just 25% of the yearReduce total generation production cost7$28M annual product cost saving for only one pathAvoid unnecessary flow curtailment for emergency support, e.g. wind uncertaintiesEnable dynamic transferEnhance system situational awarenessDefer building new transmission linesComputational feasibility of real-time path rating Computational challenges are the major limiting factor in the current path rating practice ~24 hours for one path ratingTarget: 5-10 minutesPath rating studies involve many runs of transient stability simulation and voltage stability simulation Target: seconds for each run8Real-TimeMeasurementsState EstimationTransient Stability SimulationVoltage Stability SimulationReal-Time Path RatingTransient Stability RatingVoltage Stability RatingThermalRatingminFast transient simulation via computational enhancements Achieved 26x speed-up for a WECC-size system (16,000-bus) using 64 threads compared to the sequential version using 1 thread.Only took 9 seconds to run the 30 seconds WECC-size simulation with 64 threads, which is 20 seconds ahead of the real time, and 13x faster than today’s commercial tools (which needs 120 seconds after considering the difference between CPU configurations).250455090501001502001 2 4 8 16 32 64Time in secondsNumber of threads05101520253035401 2 3 4 5 6 7SpeedupNumber of threadsReduced Admittance Matrix ComputingTime-Stepping simulationTotal−0.500.511.52Static Voltage Stability Boundary in State Space [2−machine 3−bus system]V2−RealNon-iterative voltage stability simulation via mathematical advancements AVV0Vcritical.BCLoad FlowPower Flow. .Traditional Iterative MethodX2 X1XEigenvalue-based Non-Iterative Methodmax : λ J −1(X0) ⋅ J(X1)+ I ( )−2−1.5−1−0.500.511.52−2−1.5−1V1−Imag10PL0 PmaxPL0Iterative MethodEigenvalue-based Non-Iterative MethodEnhanced Eigenvalue-based Non-Iterative MethodComputational time61 – 315 sec 4 – 10 sec 2– 4 secSpeed-up w.r.t. Commercial Tool--- 6  – 78 times 15  – 150 timesX = 1+ λ−1 X0− λ−1X1SummaryFast transient stability and voltage stability simulations through computational and mathematical advancements are proven feasible. Fast simulations enable real-time path rating. Real-time path rating minimizes conservativeness while still maintaining stability. Real-time path rating relieves transmission congestion by increasing usable transmission capacity. Real-time path rating improves asset utilization by ~30% in the tested cases. Improved asset utilization brings financial benefits in production cost saving and transaction revenue increase. Improved asset utilization also facilitates integration of renewables (and other new technologies) by minimizing curtailment.  11Where we go from here …Grid is transitioning in three fusions: Fusion of operation and planning to enable more seamless grid management and controlRemove overhead in communication between operation and planningImprove response when facing emergency situationsIntegration of transmission and distribution in managing two-way power flowsUnderstand the emerging behaviors in the power grid due to smarter loads, mobile consumption, and intermittent generationInterdependency between power grid and data networkBring data to applications efficiently and reliably Enable “all-hazard” analysisGridOPTICS™ – methods and tools to support these three fusionshttp://gridoptics.pnnl.gov/Protected Information | Proprietary Information 12Questions?Zhenyu (Henry) HuangPacific Northwest National Laboratoryzhenyu.huang@pnnl.gov509-372-6781 13

Improving Transmission Asset Utilization Through Advanced Mathematics and Computing

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Improving Transmission Asset Utilization Through Advanced Mathematics and Computing

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