Los Alamos National Laboratory Planning for Resilience · Power Systems Computation Conference (PSCC) (PSCC 2016), June 2016, Genoa, Italy. • H. Nagarajan. Optimal Resilient Grid

Los Alamos National Laboratory

Planning for Resilience

Russell Bent

February 26, 2018

A Computational Science Perspective of Resilience Tools

LA-UR-15-20362

Operated by Los Alamos National Security, LLC for the U.S. Department of Energy's NNSA


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Extreme Events and Large Scale Failures• Recent Events

• > 20 major hurricanes, snow/ice storms in U.S., 2005-2017• Each outaged ~500,000 customers for days• Hurricane Sandy - ~50,000 sq. miles out-of-service region (4 utilities)• 2017 Hurricanes: Harvey, Irma, Maria

• Hurricane Sandy

Generalized scaling property20% failures amount to 84% affected customers Ref: Toolkit for Resilient Cities (Case Study: New York City Electrical Grid)


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Extreme Events and Large Scale Failures• Recent Events

• > 20 major hurricanes, snow/ice storms in U.S., 2005-2017• Each outaged ~500,000 customers for days• Hurricane Sandy - ~50,000 sq. miles out-of-service region (4 utilities)• 2017 Hurricanes: Harvey, Irma, Maria

• Hurricane Sandy

Generalized scaling property20% failures amount to 84% affected customers Ref: Toolkit for Resilient Cities (Case Study: New York City Electrical Grid)


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Planning for Resilience: Ingredients of a computational framework


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Planning for Resilience: Ingredients of a computational framework• Metric for Measuring Resilience

• Presidential Policy Directive: The ability to prepare for and adapt to changing conditions and withstand and recover rapidly from disruptions. Resilience includes the ability to withstand and recover from deliberate attacks, accidents, or naturally occurring threats or incidents

• Quantify the definition(s) of resilience• Example: 98% of critical load is served during extreme events

• Varies by region or utility

• Description of Resiliency Threats• Historical failures• Fragility (probabilistic) models

• Characterization of Resilience Options and Costs• Microgrids• Powerline redundancy• Hardening• Vegetation management


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Planning for Resilience: System Design and Hardening Tool


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System Design and Hardening: User Inputs • Power Flow Model

– Milsoft, Cyme, GridLAB-D, etc.

• Pole Data• GIS information


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System Design and Hardening: Extreme Events • Hazard-based modeling

– Predictive models of component damage– Ice and Wind, Earthquake, Fire, etc.

• Historical failures

Source: Y. Sa, Reliability analysis of electric distribution linesPh.D. dissertation, McGill University, Montreal, Canada, 2002


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System Design and Hardening: Response

• System operations and control• Calculate baseline resilience score


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System Design and Hardening: Network Optimization• Hardening/Resilience options

– Asset hardening– New Components

• Capabilities – Assess current resilience posture– Optimize over user-suggested

upgrade to improve resilience considering budget


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System Design and Hardening: Network OptimizationPose Resiliency Planning as an optimization problem

minimize ∑𝑖𝑖𝑖𝑖∈𝐸𝐸 𝑐𝑐𝑖𝑖𝑖𝑖𝑥𝑥𝑖𝑖𝑖𝑖 + ∑𝑖𝑖,𝑖𝑖∈𝐸𝐸 𝜅𝜅𝑖𝑖𝑖𝑖𝜏𝜏𝑖𝑖𝑖𝑖 + ∑𝑖𝑖∈𝑁𝑁,𝑘𝑘∈ 𝑝𝑝𝑖𝑖 𝜁𝜁𝑖𝑖𝑘𝑘𝑧𝑧𝑖𝑖𝑘𝑘 + ∑𝑖𝑖∈𝑁𝑁 𝜇𝜇𝑖𝑖𝑢𝑢𝑖𝑖 + ∑𝑖𝑖𝑖𝑖∈𝐸𝐸 𝛼𝛼𝑖𝑖𝑖𝑖𝑡𝑡𝑖𝑖𝑖𝑖

s.t. 𝑥𝑥𝑖𝑖𝑖𝑖𝑠𝑠 ≤ 𝑥𝑥𝑖𝑖𝑖𝑖 , 𝜏𝜏𝑖𝑖𝑖𝑖𝑠𝑠 ≤ 𝜏𝜏𝑖𝑖𝑖𝑖 , 𝑡𝑡𝑖𝑖𝑖𝑖𝑠𝑠 ≤ 𝑡𝑡𝑖𝑖𝑖𝑖, 𝑧𝑧𝑖𝑖𝑘𝑘𝑠𝑠 ≤ 𝑧𝑧𝑖𝑖𝑘𝑘 ,𝑢𝑢𝑖𝑖𝑠𝑠 ≤ 𝑢𝑢𝑖𝑖

−𝑥𝑥𝑖𝑖𝑖𝑖𝑖𝑠𝑠 𝑄𝑄𝑖𝑖𝑖𝑖𝑘𝑘 ≤ �𝑘𝑘∈𝑝𝑝𝑖𝑖𝑖𝑖

𝑓𝑓𝑖𝑖𝑖𝑖𝑠𝑠𝑘𝑘 ≤ 𝑥𝑥𝑖𝑖𝑖𝑖𝑖𝑠𝑠 𝑄𝑄𝑖𝑖𝑖𝑖𝑘𝑘

𝑥𝑥𝑖𝑖𝑖𝑖𝑖𝑠𝑠 + 𝑥𝑥𝑖𝑖𝑖𝑖𝑖𝑠𝑠 ≤ 𝑥𝑥𝑖𝑖𝑖𝑖𝑠𝑠

− 1 − 𝜏𝜏𝑖𝑖𝑖𝑖𝑠𝑠 𝑄𝑄𝑖𝑖𝑖𝑖𝑘𝑘 ≤ �𝑘𝑘∈𝑝𝑝𝑖𝑖𝑖𝑖

𝑓𝑓𝑖𝑖𝑖𝑖𝑘𝑘𝑠𝑠 ≤ 1 − 𝜏𝜏𝑖𝑖𝑖𝑖𝑠𝑠 𝑄𝑄𝑖𝑖𝑖𝑖𝑘𝑘

−𝛽𝛽𝑖𝑖𝑖𝑖∑𝑘𝑘∈𝑝𝑝𝑖𝑖,𝑖𝑖 𝑓𝑓𝑖𝑖𝑖𝑖

𝑘𝑘𝑠𝑠

𝑝𝑝𝑖𝑖𝑖𝑖≤ 𝑓𝑓𝑖𝑖𝑖𝑖𝑘𝑘

′𝑠𝑠 −∑𝑘𝑘∈𝑝𝑝𝑖𝑖,𝑖𝑖 𝑓𝑓𝑖𝑖𝑖𝑖

𝑘𝑘𝑠𝑠

𝑝𝑝𝑖𝑖𝑖𝑖≤ 𝛽𝛽𝑖𝑖𝑖𝑖

∑𝑘𝑘∈𝑝𝑝𝑖𝑖,𝑖𝑖 𝑓𝑓𝑖𝑖𝑖𝑖𝑘𝑘𝑠𝑠

𝑝𝑝𝑖𝑖𝑖𝑖

𝑧𝑧𝑖𝑖𝑘𝑘 ≤ 𝑀𝑀𝑖𝑖𝑘𝑘𝑢𝑢𝑖𝑖

𝑥𝑥𝑖𝑖𝑖𝑖𝑠𝑠 = 𝑡𝑡𝑖𝑖𝑖𝑖𝑠𝑠 when x is damaged

liks = 𝑦𝑦𝑖𝑖𝑠𝑠𝑑𝑑𝑖𝑖𝑘𝑘

0 ≤ 𝑔𝑔𝑖𝑖𝑠𝑠𝑘𝑘 ≤ 𝑧𝑧𝑖𝑖𝑘𝑘𝑠𝑠 + 𝑔𝑔𝑖𝑖𝑘𝑘+

giks − 𝑙𝑙𝑖𝑖𝑘𝑘𝑠𝑠 − ∑𝑖𝑖∈𝑁𝑁 𝑓𝑓𝑖𝑖𝑖𝑖𝑘𝑘𝑠𝑠 = 0

0 ≤ 𝑧𝑧𝑖𝑖𝑘𝑘𝑠𝑠 ≤ 𝑢𝑢𝑖𝑖𝑠𝑠𝑍𝑍𝑖𝑖𝑘𝑘

∑𝑖𝑖𝑖𝑖∈𝑠𝑠 𝑥𝑥𝑖𝑖𝑖𝑖𝑠𝑠 + 1 − 𝜏𝜏𝑖𝑖𝑖𝑖 ≤ 𝑠𝑠 − 1

𝜏𝜏𝑖𝑖𝑖𝑖𝑠𝑠 ≥ 𝑥𝑥𝑖𝑖𝑖𝑖𝑠𝑠 + 𝜏𝜏𝑖𝑖𝑖𝑖𝑠𝑠 − 1, 𝑥𝑥𝑖𝑖𝑖𝑖𝑠𝑠 ≤ 𝑥𝑥𝑖𝑖𝑖𝑖

𝑠𝑠

∑𝑖𝑖∈𝐶𝐶𝐶𝐶 ,𝑘𝑘∈𝑝𝑝𝑖𝑖 𝑙𝑙𝑖𝑖𝑘𝑘𝑠𝑠 ≥ 𝜆𝜆 ∑𝑖𝑖∈𝐶𝐶𝐶𝐶,𝑘𝑘∈𝑝𝑝𝑖𝑖 𝑑𝑑𝑖𝑖

𝑘𝑘

∑𝑖𝑖∈𝑁𝑁∖𝐶𝐶,𝑘𝑘∈𝑝𝑝𝑖𝑖 𝑙𝑙𝑖𝑖𝑘𝑘𝑠𝑠 ≥ 𝛾𝛾 ∑𝑖𝑖∈𝑁𝑁∖𝐶𝐶,𝑘𝑘∈𝑝𝑝𝑖𝑖 𝑑𝑑𝑖𝑖

𝑘𝑘

𝑥𝑥,𝑦𝑦, 𝜏𝜏,𝑢𝑢, 𝑡𝑡 ∈ {0,1}

Least cost set of resilience options

Power flow

Operational Requirements

Resiliency Requirements on a set of failure scenarios


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Finding a Resilience Solution: Research and Development• First approach

• Populate the optimization model with distribution feeder information

• Provide the model to an off-the-shelf solver• Open Source: Ipopt, Bonmin, Couenne, etc.

• Commercial: Cplex, Gurobi, Baron, etc.

• Scaling is a bottleneck• Second approach

• Develop new algorithmic approaches• Exploit the structure present in resilience problems• Leverage subject area knowledge


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Algorithms Based on DecompositionC

onst

rain

tsDesign Variables First Failure

Scenario Operations

Second Failure Scenario Operations

Third Failure Scenario Operations

…

Decomposition strategies exploit the separable structure of the problem over scenarios when the design variables are fixed


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Resiliency Planning Analysis—Ice Storm


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Deployment and Access • LPNORM: A LANL, PNNL, and NRECA Optimal Resiliency Tool

• One of over 80 projects included in the Grid Modernization Laboratory Consortium• Full consortium funding: $220M over 3 years

• http://energy.gov/doe-grid-modernization-laboratory-consortium-gmlc-awards

• April 2016 – April 2019• Guided by a Co-op advisory board• Open source distribution resilient design tool

• Deployed on NRECA’s Open Modeling Framework (OMF)

• https://www.omf.coop/newModel/_resilientDist/lpnorm

http://energy.gov/doe-grid-modernization-laboratory-consortium-gmlc-awards


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Co-Op Community Support• Data Collection

• GIS Models of distribution feeders• Failure records• Resilience options under consideration

• Outreach• Feedback on tool requirements• Vocalize the importance of resilience• Use case discussions and guidance

• Metrics and Operations• Definition(s) of Resilience• Engineering requirements and constraints on operations• New technologies


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Conclusion• Resilience Planning

• Extreme Events and Large-Scale Failures pose threats to modern distribution systems• Motivates the need for resiliency planning and design software tools

• Thanks• DOE Office of Energy Reliability Smart Grid Program (Dan Ton)• Frank Tuffner (PNNL), Pascal van Hentenryck (University of Michigan), David Pinney (NRECA)


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Technical References• F. Tuffner, Y. Tang, P. Thekkumparambath Mana, Evaluating the Loss of Communications in Distribution Protection Systems

using GridLAB-D, 2018 IEEE T&D Expo and Conference, April 2018, Denver, CO.

• G. Byeon, R. Bent, P. van Hentenryck, H. Nagarajan. Communication-constrained Resilient Distribution Grid Design. INFORMS Annual Meeting 2017

• G. Byeon, H. Nagarajan, R. Bent, P. van Hentenryck. Communication-Constrained Resilient Distribution Grid Design, under review.

• A. Barnes, H. Nagarajan, E. Yamangil, R. Bent, and S. Backhaus. Tools for Improving Reliability of Electric Distribution Systems with Networked Microgrids, under review.

• H. Nagarajan, E. Yamangil, R. Bent, P. van Hentenryck, and S. Backhaus. Optimal Resilient Transmission Grid Design. 19th Power Systems Computation Conference (PSCC) (PSCC 2016), June 2016, Genoa, Italy.

• H. Nagarajan. Optimal Resilient Grid Design of Distribution and Transmission Systems. INFORMS International Conference, June 2016, Hawaii.

• R. Bent. Optimal Resilient Distribution Grid Design using a 3-phase Unbalanced AC Power Flow, INFORMS Annual Meeting, Nov 2015, Philadelphia, PA.

• E. Yamangil, R. Bent, S. Backhaus. Designing Resilient Electrical Distribution Grids. Proceedings of the 29th Conference on Artificial Intelligence (AAAI 2015), January 2015, Austin, Texas.

• R. Bent. Optimal Resilient Distribution Grid Design. INFORMS Annual Meeting, October, 2015, San Francisco, CA.

• K. Schneider, F. Tuffner, M. Elizondo, C.C. Liu, Y. Xu, and D. Ton. “Evaluating the Feasibility to Use Microgrids as a Resiliency Resource”, IEEE Transactions on Smart Grid, vol. PP, no. 99, 2016.

• Y. Xu, C.C. Liu, K. Schneider, F. Tuffner, and D. Ton. “Microgrids for Service Restoration to Critical Load in a Resilient Distribution System”. IEEE Transactions on Smart Grid, vol. PP, no. 99, 2016.

• K. Schneider, F. Tuffner, and M. Elizondo. Microgrids as a Resiliency Resource, Tech Report, PNNL-23674, Richland, WA.

Documents

Los Alamos National Laboratory Planning for Resilience · Power Systems Computation Conference (PSCC) (PSCC 2016), June 2016, Genoa, Italy. • H. Nagarajan. Optimal Resilient Grid