Resilience-oriented design and proactive preparedness of electrical distribution system

Extreme weather events, such as hurricanes and ice storms, pose a top threat to power distribution systems as their frequency and severity increase over time. Recent severe power outages caused by extreme weather events, such as Hurricane Harvey and Hurricane Irma, have highlighted the importance and urgency to enhance the resilience of electric power distribution systems. The goal of enhancing the resilience of distribution systems against extreme weather events can be fulfilled through upgrading and operating measures. This work focuses on investigating the impacts of upgrading measures and preventive operational measures on distribution system resilience. The objective of this dissertation is to develop a multi-timescale optimization framework to provide some actionable resilience-enhancing strategies for utility companies to harden/upgrade power distribution systems in the long-term and do proactive preparation management in the short-term. In the long-term resilience-oriented design (ROD) of distribution system, the main challenges are i) modeling the spatio-temporal correlation among ROD decisions and uncertainties, ii) capturing the entire failure-recovery-cost process, and iii) solving the resultant large-scale mixed-integer stochastic problem efficiently. To deal with these challenges, we propose a hybrid stochastic process with a deterministic casual structure to model the spatio-temporal correlations of uncertainties. A new two-stage stochastic mixed-integer linear program (MILP) is formulated to capture the impacts of ROD decisions and uncertainties on system responses to extreme weather events. The objective is to minimize the ROD investment cost in the first stage and the expected costs of loss of load, DG operation, and damage repairs in the second stage. A dual decomposition (DD) algorithm with branch-and-bound is developed to solve the proposed model with binary variables in both stages. Case studies on the IEEE 123-bus test feeder have shown the proposed approach can improve the system resilience at minimum costs. For an upcoming extreme weather event, we develop a pre-event proactive energy management and preparation strategy such that flexible resources can be prepared in advance. In order to explicitly materialize the trade-off between the pre-event resource allocation cost and the damage loss risk associated with an event, the strategy is modeled a two-stage stochastic mixed-integer linear programming (SMILP) and Conditional Value at-Risk (CVaR). The progressive algorithm is used to solve the proposed model and obtain the optimal proactive energy management and preparation strategy. Numerical studies on the modified IEEE 123-bus test feeder show the effectiveness of the proposed approach to improve the system resilience at different risk levels

The macro financing of natural hazards in developing countries

The authors propose a financial model to address the design of efficient risk financing strategies against natural disasters at the country level. It is simple enough to shed analytical light on some of the key issues but flexible and realistic enough to provide some quantitative guidance on the ex ante financing of catastrophic losses. The risk financing problem is decomposed into two steps. First, the resource gap, defined as the difference between losses and available ex-post resources (such as post-disaster aid), is identified. It determines the losses to be financed by ex ante financial instruments (reserves, catastrophe insurance, and contingent debt). Second, the cost-minimizing financial arrangements are derived from the marginal costs of the financial instruments. The model is solved through a series of graphical analyses that make this complex financial problem easier to apprehend. This model captures and explains the main impacts of financial parameters (such as insurance premium, cost of capital) on efficient risk financing structures.Insurance&Risk Mitigation,Banks&Banking Reform,Financial Intermediation,Natural Disasters,Non Bank Financial Institutions

Equitable Optimization of Patient Re-allocation and Temporary Facility Placement to Maximize Critical Care System Resilience in Disasters

End-stage renal disease patients face a complicated sociomedical situation and rely on various forms of infrastructure for life-sustaining treatment. Disruption of these infrastructures during disasters poses a major threat to their lives. To improve patient access to dialysis treatment, there is a need to assess the potential threat to critical care facilities from hazardous events. In this study, we propose optimization models to solve critical care system resilience problems including patient and medical resource allocation. We use human mobility data in the context of Harris County (Texas) to assess patient access to critical care facilities, dialysis centers in this study, under the simulated hazard impacts, and we propose models for patient re-allocation and temporary medical facility placement to improve critical care system resilience in an equitable manner. The results show (1) the capability of the optimization model in efficient patient re-allocation to alleviate disrupted access to dialysis facilities; (2) the importance of large facilities in maintaining the functioning of the system. The critical care system, particularly the network of dialysis centers, is heavily reliant on a few larger facilities, making it susceptible to targeted disruption. (3) The consideration of equity in the optimization model formulation reduces access loss for vulnerable populations in the simulated scenarios. (4) The proposed temporary facilities placement could improve access for the vulnerable population, thereby improving the equity of access to critical care facilities in disaster. The proposed patient re-allocation model and temporary facilities placement can serve as a data-driven and analytic-based decision support tool for public health and emergency management plans to reduce the loss of access and disrupted access to critical care facilities and would reduce the dire social costs.Comment: 21 pages, 9 figure

Selected Paper Abstracts, Annual Meetings

Agribusiness, Consumer/Household Economics, Farm Management, Food Consumption/Nutrition/Food Safety, International Relations/Trade, Land Economics/Use, Production Economics, Risk and Uncertainty,

The Economics of Natural Disasters: A Survey

Catastrophes caused by natural disasters are by no means new, yet the evolving understanding of their relevance to economic development and growth is still in its infancy. In order to facilitate further necessary research on this topic, this paper summarizes the state of the economic literature examining the aggregate impact of disasters. The paper reviews the main disaster data sources available, discusses the determinants of the direct effects of disasters, and distinguishes between short- and long-run indirect effects. The paper then examines some of the relevant policy questions and follows up with projections about the likelihood of future disasters, while paying particular attention to climate change. The paper ends by identifying several significant gaps in the literature.Natural disasters, Climate change, Growth

Two-stage models for flood mitigation of electrical substations

We compare stochastic programming and robust optimization decision models for informing the deployment of temporary flood mitigation measures to protect electrical substations prior to an imminent and uncertain hurricane. In our models, the first stage captures the deployment of a fixed quantity of flood mitigation resources, and the second stage captures the operation of a potentially degraded power grid with the primary goal of minimizing load shed. To model grid operation, we introduce novel adaptations of the DC and LPAC power flow approximation models that feature relatively complete recourse by way of a blackout indicator variable and relaxed model of power generation. We apply our models to a pair of geographically realistic flooding case studies, one based on Hurricane Harvey and the other on Tropical Storm Imelda. We investigate the effect of the mitigation budget, the choice of power flow model, and the uncertainty perspective on the optimal mitigation strategy. Our results indicate the mitigation budget and uncertainty perspective are impactful whereas the choice of power flow model is of little to no consequence

The Economics of Natural Disasters - A Survey

Catastrophes caused by natural disasters are by no means new, yet our evolving understanding regarding their relevance to economic development and growth is still at its infancy. In order to facilitate further necessary research on this topic, we summarize the state of the economic literature that examines the aggregate impact of disasters. We review the main disaster data sources available, discuss the determinants of the direct effects of disasters, and distinguish between the short- and long-run indirect effects. After reviewing these literatures, we examine some of the relevant policy questions, and follow up with projections about the future likelihood of disasters, while paying particular attention to the projected climate change. We end by identifying several significant gaps in this literature.natural disasters, climate change, growth

Facility location optimization model for emergency humanitarian logistics

Since the 1950s, the number of natural and man-made disasters has increased exponentially and the facility location problem has become the preferred approach for dealing with emergency humanitarian logistical problems. To deal with this challenge, an exact algorithm and a heuristic algorithm have been combined as the main approach to solving this problem. Owing to the importance that an exact algorithm holds with regard to enhancing emergency humanitarian logistical facility location problems, this paper aims to conduct a survey on the facility location problems that are related to emergency humanitarian logistics based on both data modeling types and problem types and to examine the pre- and post-disaster situations with respect to facility location, such as the location of distribution centers, warehouses, shelters, debris removal sites and medical centers. The survey will examine the four main problems highlighted in the literature review: deterministic facility location problems, dynamic facility location problems, stochastic facility location problems, and robust facility location problems. For each problem, facility location type, data modeling type, disaster type, decisions, objectives, constraints, and solution methods will be evaluated and real-world applications and case studies will then be presented. Finally, research gaps will be identified and be addressed in further research studies to develop more effective disaster relief operations

Functional Attributes of Post-Disturbance Regeneration in Puerto Rican Tropical Dry Forest

The global extent of tropical dry forests has rapidly diminished in recent decades due to a variety of threats, largely from human activity. Efforts to restore these forests require understanding of the various modes of regeneration and how they are impacted across a range of disturbance-types. Studies of tropical forest recovery have traditionally neglected the concept of ‘persistence’ in favor of ‘recruitment’ and seedling dynamics. Increasingly, the role of resprouting as a form of persistence in stressful environments is recognized as an important factor that has implications for population turnover, minimizing disturbance impacts and reducing reliance on seeds. Using a functional-trait approach, this research investigated the functional basis of resprouting and persistence within tropical dry forest from the individual to community scale. The study area was a threatened Puerto Rican tropical dry forest where resprouting is a dominant form of recovery and thought to be an adaptation to drought and occasional windthrow. Firstly, I sought to determine the range of functional types within the community by asking what water-use strategies characterize dominant tree species? A broad range of water-use behaviors were observed but most species converged on a high degree of drought tolerance maintaining dry season resource uptake. Secondly, I considered the life-history consequences associated with resprouting. Conservative, drought tolerant strategies were associated with low adult growth, which unexpectedly also translated to weaker resprouting. The occurrence of Hurricane Maria presented the opportunity to study the short-term physiological responses of trees following defoliation. Interestingly, dry forest species were found to exhibit highly plastic responses suggesting a common ability to exploit high resource windows possibly to fuel recovery. Finally, I asked whether functional recovery and assembly mechanisms were predictable across clearcut and fire chronosequences where resprouting was the dominant form of regeneration. Both types of chronosequences were characterized by functional shifts from conservative to more acquisitive resource-use, but recovery trajectories in clearcut sites were more stable as the effects of lower disturbance severity promoted successful regeneration of resprouts similar to ‘natural’ patterns of recovery. Fire legacy effects by contrast inhibit functional diversity and create species poor communities. Overall, my results suggest that successful persistence through resprouting in tropical dry forest is strongly dependent on species identity, life-history strategy and the type of disturbance. These forests have a diversity of mechanisms available to drive recovery but severe disturbances such as fire will reduce that diversity and ultimately reduce forest resilience