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Non-iterative voltage stability analysis methods and prototype software for multi-path rating Yuri V. Makarov WECC JSIS Meeting Salt Lake City, UT September 10, 2014

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Acknowledgement: DOE ARPA-E and DOE OE Office Project Team Dr. Bharat Vyakaranam Research Engineer, Power Systems, PNNL Dr. Da Meng Research Engineer, Power Systems, PNNL Dr. Pavel Etingov Research Engineer, Power Systems, PNNL Dr. Tony Nguyen Research Engineer, Power Systems, PNNL Dr. Di Wu - Research Engineer, Power Systems, PNNL Dr. Zhangshuan (Jason) Hou Exploratory data analyses and uncertainty quantification, PNNL Dr. Shaobu Wang - Research Engineer, Power Systems, PNNL Dr. Steve Elbert High Performance Computing, PNNL Dr. Laurie Miller Research Engineer, Power Systems, PNNL Dr. Yuri Makarov PM, Chief Scientist, Power Systems, PNNL Advisors: Dr. Zhenyu (Henry) Huang Dr. Ruisheng Diao Dr. Mark Morgan Acknowledgements: DOE ARPA-E (Tim Heidel and Sameh Elsharkawy) and DOE OE Office (Gil Bindewald)

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Overview - 1 Research Objectives New non-iterative methods for multi-parameter voltage stability assessment (VSA) in near-real-time. Multi-path rating application. Answers will be given: How far the system is from instability and blackout? What are the most critical contingencies and system elements? What needs to be done to increase the security margin in real time? What is the time remaining for a possible violation? - Future July 2, 20153 Voltage stability boundary of a simple system and its projections. Source: Hiskens and Davy

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Overview - 2 Background/Problem: Different parts of the VS boundary (VSB) correspond to increasingly variable stress directions caused by changing load-generation patterns, contingencies, market forces, cooperation between system operators, variable generation, etc. July 2, 2015 Computational time becomes critically important for: Real-time analyses Massive contingency screenings Simulations of blackouts and cascading Probabilistic methods Synchrophasor-based applications, and Traditional methods (e.g., continuation power flow - CPF) are: Computationally intensive, Limited by a few stress directions Based on simplifications, Sensitive to initial guesses. Continuation power flow process: predictor; corrector. Path 1 Path 2 Path 3

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Overview - 3 Benefits and Impacts: Enhanced situation awareness Early detection of system instability, Improved reliability Actionable information, Prevention of system blackouts, and Better utilization of transmission assets. Other benefits: VSB visibility for multiple paths and contingencies Developing real-time and HPC applications Accurate and flexible quantification of the VS margins Wide-area view on voltage stability Potential for predictive/preventive control Potential for close-loop automatic emergency control systems. July 2, 20155

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Security Margin and Control Direction Security margin d provides situation awareness Control vector d provides actionable information Constraints applied to control parameters and their priorities can be incorporated. July 2, 20156

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Approach -1 We are using powerful methods to explore voltage stability boundary (VSB) Orbiting method Each iteration produces a new VSB point We do not have to repeat continuation power flow for each VSB point! Is very fast and accurate CPF 1 2-D Slice of n-D Voltage Stability Boundary ORBITING 2 3 Path 1 Path 2

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Providing Connectivity With PowerWorld Input: Three System Models Tested 8 Central America Interconnection of Panama, Costa Rica, Honduras, Nicaragua, El Salvador, and Guatemala systems 1985 buses 2298 branches California ISO 3535 buses 4402 branches Western Electricity Coordinating Council planning model 19331 buses 22946 branches

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Simulation Results- Central America CPF run for one VSB point 7.6963 s BOM run 0.1655 s

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SystemsContinuation power flow Boundary orbiting method Average Time Per Run (s) WECC2014 (19331 buses) 19116.64 CAISO (3535 buses) 9.63061.1010 Central America (1985 buses) 7.69630.1655 Simulation Times

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Accuracy Comparison With PowerWorld 11 Stress direction Non-iterative MethodPowerWorldAccuracy Sink Load (MW) Sum(Sink) (MW) Sink Load(MW) Sum(Sink) (MW) % 1740.08 738.11 0.28 21188.9 1192.8 0.82 3260.58 261.61 0.4 4744.561002.4746.951007.00.46

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Connections with Previous, Existing, and Future Funded Projects and Outreach Activities Cost Sharing University of Sydney, Australia, ARC grant X-ray theorem and Delta-plane method, 1993-1997 PNNL LDRD project Further development of Non-iterative voltage stability analysis method PNNL DOE OE project Wide-area security region PNNL BPA project Wide-area security nomogram PNNL DOE OE project Non-iterative voltage stability PNNL DOE ARPA-E project Non-wire methods FY 2013-2015 Further outreach, technology transfer & commercialization: Utilities and ISOs: BPA, Software Vendors: PowerWorld, Consulting Companies: Quanta Technologies, PNNL CEC/ CERTS /EPG project Voltage stability orbiting procedure

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Multi-path Near-Real-Time Path Rating: General Project Progress and Updates Team: PNNL (Prime): Henry Huang, Ruisheng Diao, Shuangshuang Jin, Yuri Makarov, Yousu Chen Quanta Technology (Sub-Prime): Guorui Zhang PowerWorld: James Weber Bonneville Power Administration: James Wong, Brian Tuck 13 ARPA-E 0670-4106

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Transmission congestion cost Incur significant economic cost 2010: >$1.1 billion congestion cost at New York ISO [1] 2010: $ 1.43 billion congestion cost PJM-wide [2] 14 [1] NYISO, 2011 Congestion Assessment and Resource Integration Study, March 2012 [2] PJM, Congestion and the PJM Regional Transmission Expansion Plan, Dec. 2011

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Means of congestion management Three traditional means of congestion management (all require capital investment) [3]: Build more generation close to load centers. Reduce load through energy efficiency and demand reduction programs. Build more transmission capacity in appropriate locations. Near-real-time approaches: Generation redispatch (additional cost) Dynamic Line Rating (DLR), thermal limited Validated at RTE, France and Oncor, TX Real-time path rating, security/stability limited Validated concept at BPA, CAISO and ERCOT No tools available due to intensive computational requirements using existing techniques 15 [3] 2012 National Electric Transmission Congestion Study. David Meyer, U.S. Department of Energy, August 2012.

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Real-time path rating Current Path Rating Practice and Limitations Offline studies months or a year ahead of the operating season Worst-case scenario Ratings are static for the operating season The result: conservative (most of the time) path rating, leading to artificial transmission congestion Real-Time Path Rating On-line studies Current operating scenarios Ratings are dynamic based on real-time operating conditions The result: realistic path rating, leading to maximum use of transmission assets and relieving transmission congestion 16

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Benefits of real-time path rating 17 Increase transfer capability of existing power network and enable additional energy transactions Reduce total generation/consumer cost Avoid unnecessary flow curtailment for emergency support, e.g. wind uncertainties Enable dynamic transfer Enhance system situational awareness

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Technical Approach and Objective 1.Develop HPC based transient and voltage stability simulation with innovative mathematical methods 2.Develop HPC based real-time path rating capability with predictability and uncertainty quantification 3.Develop advanced congestion management methods with hierarchical coordination and optimized control 4.Demonstrate the non-wire method on a commercial software platform with real- life power system scenarios Technology Summary MetricState of the Art Proposed Simulation speed3-5 times slower than real time 10-20 times faster than real time Path rating study internal Months