Vulnerability and robustness indices against blackouts in power grids

In this dissertation some novel indices for vulnerability and robustness assessment of power grids are presented. Such indices are mainly defined from the structure of transmission power grids, and with the aim of Blackout (BO) prevention and mitigation. Numerical experiments showing how they could be used alone or in coordination with pre-existing ones to reduce the effects of BOs are discussed. These indices are introduced inside 3 different sujects: The first subject is for taking a look into economical aspects of grids’ operation and their effects in BO propagation. Basically, simulations support that: the determination to operate the grid in the most profitable way could produce an increase in the size or frequency of BOs. Conversely, some uneconomical ways of supplying energy are shown to be less affected by BO phenomena. In the second subject new topological indices are devised to address the question of "which are the best buses to place distributed generation?". The combined use of two indices, is shown as a promising alternative for extracting grid’s significant features regarding robustness against BOs and distributed generation. For this purpose, a new index based on outage shift factors is used along with a previously defined electric centrality index. The third subject is on Static Robustness Analysis of electric networks, from a purely structural point of view. A pair of existing topological indices, (namely degree index and clustering coefficient), are combined to show how degradation of the network structure can be accelerated. Blackout simulations were carried out using the DC Power Flow Method and models of transmission networks from the USA and Europe.

Power and Robustness of Linkage Tests for Quantitative Traits in General Pedigrees

There are numerous statistical methods for quantitative trait linkage analysis in human studies. An ideal such method would have high power to detect genetic loci contributing to the trait, would be robust to non-normality in the phenotype distribution, would be appropriate for general pedigrees, would allow the incorporation of environmental covariates, and would be appropriate in the presence of selective sampling. We recently described a general framework for quantitative trait linkage analysis, based on generalized estimating equations, for which many current methods are special cases. This procedure is appropriate for general pedigrees and easily accommodates environmental covariates. In this paper, we use computer simulations to investigate the power robustness of a variety of linkage test statistics built upon our general framework. We also propose two novel test statistics that take account of higher moments of the phenotype distribution, in order to accommodate non-normality. These new linkage tests are shown to have high power and to be robust to non-normality. While we have not yet examined the performance of our procedures in the context of selective sampling via computer simulations, the proposed tests satisfy all of the other qualities of an ideal quantitative trait linkage analysis method.

Semiparametric Theory for Causal Mediation Analysis: efficiency bounds, multiple robustness, and sensitivity analysis

Whilst estimation of the marginal (total) causal effect of a point exposure on an outcome is arguably the most common objective of experimental and observational studies in the health and social sciences, in recent years, investigators have also become increasingly interested in mediation analysis. Specifically, upon establishing a non-null total effect of the exposure, investigators routinely wish to make inferences about the direct (indirect) pathway of the effect of the exposure not through (through) a mediator variable that occurs subsequently to the exposure and prior to the outcome. Although powerful semiparametric methodologies have been developed to analyze observational studies, that produce double robust and highly efficient estimates of the marginal total causal effect, similar methods for mediation analysis are currently lacking. Thus, this paper develops a general semiparametric framework for obtaining inferences about so-called marginal natural direct and indirect causal effects, while appropriately accounting for a large number of pre-exposure confounding factors for the exposure and the mediator variables. Our analytic framework is particularly appealing, because it gives new insights on issues of efficiency and robustness in the context of mediation analysis. In particular, we propose new multiply robust locally efficient estimators of the marginal natural indirect and direct causal effects, and develop a novel double robust sensitivity analysis framework for the assumption of ignorability of the mediator variable.

Robustness of speckle imaging techniques applied to horizontal imaging scenarios

Atmospheric turbulence near the ground severely limits the quality of imagery acquired over long horizontal paths. In defense, surveillance, and border security applications, there is interest in deploying man-portable, embedded systems incorporating image reconstruction methods to compensate turbulence effects. While many image reconstruction methods have been proposed, their suitability for use in man-portable embedded systems is uncertain. To be effective, these systems must operate over significant variations in turbulence conditions while subject to other variations due to operation by novice users. Systems that meet these requirements and are otherwise designed to be immune to the factors that cause variation in performance are considered robust. In addition robustness in design, the portable nature of these systems implies a preference for systems with a minimum level of computational complexity. Speckle imaging methods have recently been proposed as being well suited for use in man-portable horizontal imagers. In this work, the robustness of speckle imaging methods is established by identifying a subset of design parameters that provide immunity to the expected variations in operating conditions while minimizing the computation time necessary for image recovery. Design parameters are selected by parametric evaluation of system performance as factors external to the system are varied. The precise control necessary for such an evaluation is made possible using image sets of turbulence degraded imagery developed using a novel technique for simulating anisoplanatic image formation over long horizontal paths. System performance is statistically evaluated over multiple reconstruction using the Mean Squared Error (MSE) to evaluate reconstruction quality. In addition to more general design parameters, the relative performance the bispectrum and the Knox-Thompson phase recovery methods is also compared. As an outcome of this work it can be concluded that speckle-imaging techniques are robust to the variation in turbulence conditions and user controlled parameters expected when operating during the day over long horizontal paths. Speckle imaging systems that incorporate 15 or more image frames and 4 estimates of the object phase per reconstruction provide up to 45% reduction in MSE and 68% reduction in the deviation. In addition, Knox-Thompson phase recover method is shown to produce images in half the time required by the bispectrum. The quality of images reconstructed using Knox-Thompson and bispectrum methods are also found to be nearly identical. Finally, it is shown that certain blind image quality metrics can be used in place of the MSE to evaluate quality in field scenarios. Using blind metrics rather depending on user estimates allows for reconstruction quality that differs from the minimum MSE by as little as 1%, significantly reducing the deviation in performance due to user action.

Interlinked dual-time feedback loops can enhance robustness to stochasticity and persistence of memory.

Multiple interlinked positive feedback loops shape the stimulus responses of various biochemical systems, such as the cell cycle or intracellular Ca2+ release. Recent studies with simplified models have identified two advantages of coupling fast and slow feedback loops. This dual-time structure enables a fast response while enhancing resistances of responses and bistability to stimulus noise. We now find that (1) the dual-time structure similarly confers resistance to internal noise due to molecule number fluctuations, and (2) model variants with altered coupling, which better represent some specific biochemical systems, share all the above advantages. We also develop a similar bistable model with coupling of a fast autoactivation loop to a slow loop. This model's topology was suggested by positive feedback proposed to play a role in long-term synaptic potentiation (LTP). The advantages of fast response and noise resistance are also present in this autoactivation model. Empirically, LTP develops resistance to reversal over approximately 1h . The model suggests this resistance may result from increased amounts of synaptic kinases involved in positive feedback.

Institutions for sustainable governance of forests: Equity, robustness and cross-level interactions in Mawlyngbna, Meghalaya, India

This study adopts Ostrom’s Social-Ecological Systems (SES) framework in empirical fieldwork to explain how local forestry institutions affect forest ecosystems and social equity in the community of Mawlyngbna in North-East India. Data was collected through 26 semi-structured interviews, participatory timeline development, policy documents, direct observation, periodicals, transect walks, and a concurrent forest-ecological study in the village. Results show that Mawlyngbna's forests provide important sources of livelihood benefits for the villagers. However, ecological disturbance and diversity varies among the different forest ownership types and forest-based livelihood benefits are inequitably distributed. Based on a bounded rationality approach, our analysis proposes a set of causal mechanisms that trace these observed social-ecological outcomes to the attributes of the resource system, resource units, actors and governance system. We analyse opportunities and constraints of interactions between the village, regional, and state levels. We discuss how Ostrom’s design principles for community-based resource governance inform the explanation of robustness but have a blind spot in explaining social equity. We report experiences made using the SES framework in empirical fieldwork. We conclude that mapping cross-level interactions in the SES framework needs conceptual refinement and that explaining social equity of forest governance needs theoretical advances.