Natalia Romero

Investment Planning for Electric Power Systems Under Terrorist Threat

Access to electric power is critical to societal welfare. In this paper, we analyze the interaction between a defender and a terrorist who threatens the operation of an electric power system. The defender wants to find a strategic defense to minimize the consequences of an attack. Both parties have limited budgets and behave in their own self-interest. The problem is formulated as a multi-level mixed-integer programming problem. A Tabu Search with an embedded greedy algorithm for the attack problem is implemented to find the optimum defense strategy. We apply the algorithm to a 24-bus network for a combination of four different defense budgets, three attack budgets, and three assumptions as to how the terrorists craft their attacks.

Seismic Hazards and Water Supply Performance

This article describes seismic hazards, including fault rupture, liquefaction, landslides, and site amplification, using Los Angeles as a case study. Water supply simulation results are presented for a 7.8 MW earthquake on the San Andreas Fault. Severe water losses are shown after 24 h, with nearly 2,700 locations of pipeline damage and a 66% decrease in normal water service. The water supply system was modeled with and without reservoirs that have been removed from service to meet water quality standards. The results show that opening the disconnected reservoirs immediately after a serious earthquake is an effective strategy for emergency response.

Transmission and Generation Expansion to Mitigate Seismic Risk

This paper develops a two-stage stochastic program and solution procedure to optimize the selection of capacity enhancement strategies to increase the resilience of electric power systems to earthquakes. The model explicitly considers the range of earthquake events that are possible and, for each, an approximation of the distribution of damage to be experienced. This is important because electric power systems are spatially distributed; hence their performance is driven by the distribution of damage to the components. We test this solution procedure against the nonlinear integer solver in LINGO 13 and apply the formulation and solution strategy to the Eastern Interconnect where the seismic hazard primarily stems from the New Madrid Seismic Zone. We show the feasibility of optimized capacity expansion to improve the resilience of large-scale power systems with respect to large earthquakes.

Seismic Retrofit for Electric Power Systems

This paper develops a two-stage stochastic program and solution procedure to optimize the selection of seismic retrofit strategies to increase the resilience of electric power systems against earthquake hazards. The model explicitly considers the range of earthquake events that are possible and, for each, an approximation of the distribution of damage experienced. This is important because electric power systems are spatially distributed and so their performance is driven by the distribution of component damage. We test this solution procedure against the nonlinear integer solver in LINGO 13 and apply the formulation and solution strategy to the Eastern Interconnection, where seismic hazard stems from the New Madrid seismic zone.

Optimization-Based Probabilistic Consequence Scenario Construction for Lifeline Systems

The construction of a suite of consequence scenarios that is consistent with the joint distribution of damage to a lifeline system is critical to properly estimating regional loss after an earthquake. This paper describes an optimization method that identifies a suite of consequence scenarios that can be used in regional loss estimation for lifeline systems when computational demands are of concern, and it is important to capture the spatial correlation associated with individual events. This method is applied to a realistic case study focused on the highway network in Memphis, Tennessee, within the New Madrid Seismic Zone. This case study illustrates that significantly fewer consequence scenarios are needed with this method than would be required using Monte Carlo simulation.

Multi-objective optimization for bridge retrofit to address earthquake hazards

Protecting infrastructures against natural hazards is a pressing national and international problem. Given the current budgetary climate, the ability to determine the best mitigation strategies with highly constrained budgets is essential. This papers describes a set of computationally efficient techniques to determine optimal infrastructure investment strategies, given multiple user objectives, that are consistent with an underlying earthquake hazard. These techniques include: optimization methods for developing representative events to characterize the hazard and the post-event condition of infrastructure components, a simulation model to characterize post-event infrastructure performance relative to multiple user objectives, and a multi-objective optimization algorithm for determining protection strategies. They are demonstrated using a case study of the highway network in Memphis, Tennessee.

Optimization of scenario construction for loss estimation in lifeline networks

Natural disasters have become a pressing national and international problem. Population growth, aging infrastructure, and climate change suggest that mounting losses will continue into the foreseeable future, hence mitigation and response planning is of increasing importance. The conduct of studies to support this type of regional planning often requires an estimation of the impacts of a single earthquake scenario on a region. This paper describes a method to identify a set of consequence scenarios that can be used in regional loss estimation for lifeline systems when computational demands are of concern, and the spatial coherence of individual consequence scenarios is important. This method is compared with Monte Carlo simulation.