Mitigating Cascading Outages in Severe Weather Using Simulation-Based Optimization

Severe weather events can trigger cascading power outages and lead to significant losses. In this work, we investigate cascading outage mitigation under severe weather conditions. Given day-ahead weather forecasts and component failure models, we aim to identify a set of power lines that can be hardened to minimize the expected impact of potential cascading outages. Since the expected load shedding cannot be expressed as an explicit function of line hardening decisions and system states, we developed a cascading outage simulator to estimate the expected value of load shedding under various initial weather-related disruption scenarios generated using a weather forecast. To avoid massive enumeration of all possible combinations of line hardening decisions and reduce the simulation efforts, we employed an efficient simulation-based optimization approach that quickly identifies the (near) optimal line hardening decisions in the presence of both large simulation noises due to the highly variable initial disturbances and system states, and significant randomness in the subsequent cascades. The algorithm is also able to utilize parallel computing to dramatically reduce computation time to support decision making in preparation for severe weather conditions. We performed a case study on the Northeast Power Coordinating Council (NPCC) 140-bus system model to demonstrate that our approach can significantly improve power grid resilience to adverse weather events.

[1]  Hao Wu,et al.  A State-Failure--Network Method to Identify Critical Components in Power Systems , 2019 .

[2]  Jie Xu,et al.  A new particle swarm optimization algorithm for noisy optimization problems , 2016, Swarm Intelligence.

[3]  Rui Yao,et al.  Toward Simulation and Risk Assessment of Weather-Related Outages , 2019, IEEE Transactions on Smart Grid.

[4]  Zhaoyu Wang,et al.  Service restoration based on AMI and networked MGs under extreme weather events , 2016 .

[5]  Ian Dobson,et al.  A Markovian influence graph formed from utility line outage data to mitigate large cascades , 2019, IEEE Transactions on Power Systems.

[6]  P. Luh,et al.  Risk Analysis for Distribution Systems in the Northeast U.S. Under Wind Storms , 2014, IEEE Transactions on Power Systems.

[7]  Jie Xu,et al.  Industrial strength COMPASS: A comprehensive algorithm and software for optimization via simulation , 2010, TOMC.

[8]  Shengwei Mei,et al.  Blackout Model Considering Slow Process , 2013, IEEE Transactions on Power Systems.

[9]  Zhaoyu Wang,et al.  Can an influence graph driven by outage data determine transmission line upgrades that mitigate cascading blackouts? , 2018, 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS).

[10]  Rui Yao,et al.  Towards Simulation and Risk Assessment of Weather-Related Cascading Outages , 2017, ArXiv.

[11]  Quan Chen,et al.  Composite Power System Vulnerability Evaluation to Cascading Failures Using Importance Sampling and Antithetic Variates , 2013, IEEE Transactions on Power Systems.

[12]  Feng Liu,et al.  Risk Assessment of Multi-Timescale Cascading Outages Based on Markovian Tree Search , 2016, IEEE Transactions on Power Systems.

[13]  Kai Sun,et al.  A Multi-Timescale Quasi-Dynamic Model for Simulation of Cascading Outages , 2016, IEEE Transactions on Power Systems.

[14]  I. Dobson,et al.  Risk Assessment of Cascading Outages: Methodologies and Challenges , 2012, IEEE Transactions on Power Systems.

[15]  Kai Zhou,et al.  Exploring cascading outages and weather via processing historic data , 2018, HICSS.

[16]  Pierre-Etienne Labeau,et al.  A Two-Level Probabilistic Risk Assessment of Cascading Outages , 2016, IEEE Transactions on Power Systems.

[17]  Barry L. Nelson,et al.  Using Ranking and Selection to "Clean Up" after Simulation Optimization , 2003, Oper. Res..

[18]  Jie Xu,et al.  Parallel Empirical Stochastic Branch and Bound for large-scale discrete optimization via Simulation , 2016, 2016 Winter Simulation Conference (WSC).

[19]  Marc Timme,et al.  Dynamically induced cascading failures in power grids , 2017, Nature Communications.

[20]  Fred W. Glover,et al.  Transmission-Capacity Expansion for Minimizing Blackout Probabilities , 2014, IEEE Transactions on Power Systems.

[21]  Jie Xu,et al.  An Adaptive Hyperbox Algorithm for High-Dimensional Discrete Optimization via Simulation Problems , 2013, INFORMS J. Comput..

[22]  Barry L. Nelson,et al.  Empirical stochastic branch-and-bound for optimization via simulation , 2010, Proceedings of the 2010 Winter Simulation Conference.

[23]  Shengwei Mei,et al.  Towards Estimating the Statistics of Simulated Cascades of Outages With Branching Processes , 2013, IEEE Transactions on Power Systems.

[24]  David E. Newman,et al.  Optimized implementation of power dispatch in the OPA model and its implications for dispatch sensitivity for the WECC power network , 2020 .

[25]  Barry L. Nelson,et al.  Discrete Optimization via Simulation , 2015 .

[26]  Alberto Borghetti,et al.  Lightning Performance Assessment of Power Distribution Lines by Means of Stratified Sampling Monte Carlo Method , 2018, IEEE Transactions on Power Delivery.

[27]  Paul D. H. Hines,et al.  Cascading Power Outages Propagate Locally in an Influence Graph That is Not the Actual Grid Topology , 2015, IEEE Transactions on Power Systems.

[28]  Kai Sun,et al.  Interaction Graph-Based Active Islanding to Mitigate Cascading Outages , 2019, 2019 IEEE Power & Energy Society General Meeting (PESGM).

[29]  Ian Dobson,et al.  An initial model fo complex dynamics in electric power system blackouts , 2001, Proceedings of the 34th Annual Hawaii International Conference on System Sciences.

[30]  Kai Sun,et al.  An Interaction Model for Simulation and Mitigation of Cascading Failures , 2014, IEEE Transactions on Power Systems.

[31]  Ming Yang,et al.  Interval Estimation for Conditional Failure Rates of Transmission Lines With Limited Samples , 2016, IEEE Transactions on Smart Grid.

[32]  Shengwei Mei,et al.  Fast Searching Strategy for Critical Cascading Paths Toward Blackouts , 2018, IEEE Access.

[33]  F. Marks,et al.  The Hurricane Forecast Improvement Project , 2013 .

[34]  Barry L. Nelson,et al.  Discrete Optimization via Simulation Using COMPASS , 2006, Oper. Res..

[35]  Peter Bauer,et al.  The quiet revolution of numerical weather prediction , 2015, Nature.