Power system static and dynamic security studies for the 1st phase of Crete Island Interconnection

The island of Crete is currently served by an autonomous electrical system being fed by oil-fired (Heavy fuel or light Diesel oil) thermal power plants and renewables (wind and PVs). The peak load and annual electric energy consumption are approximately 600 MW and 3 TWh respectively; wind and photovoltaic parks contribute approximately 20% of the electricity needs of the island. Due to the expensive fuel used, the Cretan power system has very high electric energy generation cost compared to the Greek mainland. On the other side the limited size of the system poses severe limitations to the penetration of renewable energy sources, not allowing to further exploit the high wind and solar potential of the island. According to the Ten Year Network Development Plan (TYNDP) of the Greek TSO (Independent Power Transmission Operator S.A. IPTO S.A.), the interconnection of Crete to the mainland Transmission System of Greece will be realized through two links: A 150 kV HVAC link between the Peloponnese and the Crete (Phase I) and a HVDC link connecting the metropolitan area of Athens with Crete (Phase II). The total length of submarine and underground cable of the HVAC link will be approximately 174km; it is at the limits of the AC technology and the longest and deepest worldwide at 150 kV level. A number of studies have been conducted by a joint group of IPTO and Hellenic Electricity Distribution Network Operator (HEDNO) for the design of this interconnection. This paper presents briefly the power system static and dynamic studies conducted for the design of the AC link and its operation. Firstly, the paper presents the main results of the static security study regarding the calculation of the maximum power transfer capability of the link and the selection of the reactive power compensation scheme of the cable. Results from dynamic security analysis studies are also presented. The small-signal stability analysis concludes that a new (intra-area) electromechanical oscillation is introduced to the National System after the interconnection. The damping of the electromechanical oscillations is sufficient; however the operation of power system stabilizers at power plants located both at the mainland and at Crete power system can increase significantly the damping of important oscillation modes. Finally with respect to the risk of loss of synchronism after a significant disturbance in the system of Crete, such as a three-phase fault (“transient stability”)- enough safety margin is estimated by means of Critical Clearing Time calculations

Power system static and dynamic security studies for the 1st phase of Crete Island Interconnection

The island of Crete is currently served by an autonomous electrical system being fed by oil-fired (Heavy fuel or light Diesel oil) thermal power plants and renewables (wind and PVs). The peak load and annual electric energy consumption are approximately 600 MW and 3 TWh respectively; wind and photovoltaic parks contribute approximately 20% of the electricity needs of the island. Due to the expensive fuel used, the Cretan power system has very high electric energy generation cost compared to the Greek mainland. On the other side the limited size of the system poses severe limitations to the penetration of renewable energy sources, not allowing to further exploit the high wind and solar potential of the island. According to the Ten Year Network Development Plan (TYNDP) of the Greek TSO (Independent Power Transmission Operator S.A. IPTO S.A.), the interconnection of Crete to the mainland Transmission System of Greece will be realized through two links: A 150 kV HVAC link between the Peloponnese and the Crete (Phase I) and a HVDC link connecting the metropolitan area of Athens with Crete (Phase II). The total length of submarine and underground cable of the HVAC link will be approximately 174km; it is at the limits of the AC technology and the longest and deepest worldwide at 150 kV level. A number of studies have been conducted by a joint group of IPTO and Hellenic Electricity Distribution Network Operator (HEDNO) for the design of this interconnection. This paper presents briefly the power system static and dynamic studies conducted for the design of the AC link and its operation. Firstly, the paper presents the main results of the static security study regarding the calculation of the maximum power transfer capability of the link and the selection of the reactive power compensation scheme of the cable. Results from dynamic security analysis studies are also presented. The small-signal stability analysis concludes that a new (intra-area) electromechanical oscillation is introduced to the National System after the interconnection. The damping of the electromechanical oscillations is sufficient; however the operation of power system stabilizers at power plants located both at the mainland and at Crete power system can increase significantly the damping of important oscillation modes. Finally with respect to the risk of loss of synchronism after a significant disturbance in the system of Crete, such as a three-phase fault (“transient stability”)- enough safety margin is estimated by means of Critical Clearing Time calculations

Multiscale modelling of vascular tumour growth in 3D: the roles of domain size & boundary condition

We investigate a three-dimensional multiscale model of vascular tumour growth, which couples blood flow, angiogenesis, vascular remodelling, nutrient/growth factor transport, movement of, and interactions between, normal and tumour cells, and nutrient-dependent cell cycle dynamics within each cell. In particular, we determine how the domain size, aspect ratio and initial vascular network influence the tumour's growth dynamics and its long-time composition. We establish whether it is possible to extrapolate simulation results obtained for small domains to larger ones, by constructing a large simulation domain from a number of identical subdomains, each subsystem initially comprising two parallel parent vessels, with associated cells and diffusible substances. We find that the subsystem is not representative of the full domain and conclude that, for this initial vessel geometry, interactions between adjacent subsystems contribute to the overall growth dynamics. We then show that extrapolation of results from a small subdomain to a larger domain can only be made if the subdomain is sufficiently large and is initialised with a sufficiently complex vascular network. Motivated by these results, we perform simulations to investigate the tumour's response to therapy and show that the probability of tumour elimination in a larger domain can be extrapolated from simulation results on a smaller domain. Finally, we demonstrate how our model may be combined with experimental data, to predict the spatio-temporal evolution of a vascular tumour

Fournier's gangrene in a patient after third-degree burns: a case report

<p>Abstract</p> <p>Introduction</p> <p>Fournier's gangrene is characterized by tissue ischemia leading to rapidly progressing necrotizing fasciitis.</p> <p>Case presentation</p> <p>We present the case of a patient with Fournier's gangrene after third-degree burns. Clinical manifestations, laboratory results and treatment options are discussed.</p> <p>Conclusion</p> <p>Fournier's gangrene is a surgical emergency. Although it can be lethal, it is still a challenging situation in the field of surgical infections.</p

Spatio-temporal Models of Lymphangiogenesis in Wound Healing

Several studies suggest that one possible cause of impaired wound healing is failed or insufficient lymphangiogenesis, that is the formation of new lymphatic capillaries. Although many mathematical models have been developed to describe the formation of blood capillaries (angiogenesis), very few have been proposed for the regeneration of the lymphatic network. Lymphangiogenesis is a markedly different process from angiogenesis, occurring at different times and in response to different chemical stimuli. Two main hypotheses have been proposed: 1) lymphatic capillaries sprout from existing interrupted ones at the edge of the wound in analogy to the blood angiogenesis case; 2) lymphatic endothelial cells first pool in the wound region following the lymph flow and then, once sufficiently populated, start to form a network. Here we present two PDE models describing lymphangiogenesis according to these two different hypotheses. Further, we include the effect of advection due to interstitial flow and lymph flow coming from open capillaries. The variables represent different cell densities and growth factor concentrations, and where possible the parameters are estimated from biological data. The models are then solved numerically and the results are compared with the available biological literature.Comment: 29 pages, 9 Figures, 6 Tables (39 figure files in total

Predicting disease risks from highly imbalanced data using random forest

<p>Abstract</p> <p>Background</p> <p>We present a method utilizing Healthcare Cost and Utilization Project (HCUP) dataset for predicting disease risk of individuals based on their medical diagnosis history. The presented methodology may be incorporated in a variety of applications such as risk management, tailored health communication and decision support systems in healthcare.</p> <p>Methods</p> <p>We employed the National Inpatient Sample (NIS) data, which is publicly available through Healthcare Cost and Utilization Project (HCUP), to train random forest classifiers for disease prediction. Since the HCUP data is highly imbalanced, we employed an ensemble learning approach based on repeated random sub-sampling. This technique divides the training data into multiple sub-samples, while ensuring that each sub-sample is fully balanced. We compared the performance of support vector machine (SVM), bagging, boosting and RF to predict the risk of eight chronic diseases.</p> <p>Results</p> <p>We predicted eight disease categories. Overall, the RF ensemble learning method outperformed SVM, bagging and boosting in terms of the area under the receiver operating characteristic (ROC) curve (AUC). In addition, RF has the advantage of computing the importance of each variable in the classification process.</p> <p>Conclusions</p> <p>In combining repeated random sub-sampling with RF, we were able to overcome the class imbalance problem and achieve promising results. Using the national HCUP data set, we predicted eight disease categories with an average AUC of 88.79%.</p

Tumor Angiogenesis and Vascular Patterning: A Mathematical Model

Understanding tumor induced angiogenesis is a challenging problem with important consequences for diagnosis and treatment of cancer. Recently, strong evidences suggest the dual role of endothelial cells on the migrating tips and on the proliferating body of blood vessels, in consonance with further events behind lumen formation and vascular patterning. In this paper we present a multi-scale phase-field model that combines the benefits of continuum physics description and the capability of tracking individual cells. The model allows us to discuss the role of the endothelial cells' chemotactic response and proliferation rate as key factors that tailor the neovascular network. Importantly, we also test the predictions of our theoretical model against relevant experimental approaches in mice that displayed distinctive vascular patterns. The model reproduces the in vivo patterns of newly formed vascular networks, providing quantitative and qualitative results for branch density and vessel diameter on the order of the ones measured experimentally in mouse retinas. Our results highlight the ability of mathematical models to suggest relevant hypotheses with respect to the role of different parameters in this process, hence underlining the necessary collaboration between mathematical modeling, in vivo imaging and molecular biology techniques to improve current diagnostic and therapeutic tools

Sparse matrix computations for dynamic network centrality

Time sliced networks describing human-human digital interactions are typically large and sparse. This is the case, for example, with pairwise connectivity describing social media, voice call or physical proximity, when measured over seconds, minutes or hours. However, if we wish to quantify and compare the overall time-dependent centrality of the network nodes, then we should account for the global flow of information through time. Because the time-dependent edge structure typically allows information to diffuse widely around the network, a natural summary of sparse but dynamic pairwise interactions will generally take the form of a large dense matrix. For this reason, computing nodal centralities for a timedependent network can be extremely expensive in terms of both computation and storage; much more so than for a single, static network. In this work, we focus on the case of dynamic communicability, which leads to broadcast and receive centrality measures. We derive a new algorithm for computing time-dependent centrality that works with a sparsified version of the dynamic communicability matrix. In this way, the computation and storage requirements are reduced to those of a sparse, static network at each time point. The new algorithm is justified from first principles and then tested on a large scale data set. We find that even with very stringent sparsity requirements (retaining no more than ten times the number of nonzeros in the individual time slices), the algorithm accurately reproduces the list of highly central nodes given by the underlying full system. This allows us to capture centrality over time with a minimal level of storage and with a cost that scales only linearly with the number of time points. We also describe and test three variants of the proposed algorithm that require fewer parameters and achieve a further reduction in the computational cost

A flexible mathematical model platform for studying branching networks : experimentally validated using the model actinomycete, Streptomyces coelicolor

Branching networks are ubiquitous in nature and their growth often responds to environmental cues dynamically. Using the antibiotic-producing soil bacterium Streptomyces as a model we have developed a flexible mathematical model platform for the study of branched biological networks. Streptomyces form large aggregates in liquid culture that can impair industrial antibiotic fermentations. Understanding the features of these could aid improvement of such processes. The model requires relatively few experimental values for parameterisation, yet delivers realistic simulations of Streptomyces pellet and is able to predict features, such as the density of hyphae, the number of growing tips and the location of antibiotic production within a pellet in response to pellet size and external nutrient supply. The model is scalable and will find utility in a range of branched biological networks such as angiogenesis, plant root growth and fungal hyphal networks

Bistability versus Bimodal Distributions in Gene Regulatory Processes from Population Balance

In recent times, stochastic treatments of gene regulatory processes have appeared in the literature in which a cell exposed to a signaling molecule in its environment triggers the synthesis of a specific protein through a network of intracellular reactions. The stochastic nature of this process leads to a distribution of protein levels in a population of cells as determined by a Fokker-Planck equation. Often instability occurs as a consequence of two (stable) steady state protein levels, one at the low end representing the “off” state, and the other at the high end representing the “on” state for a given concentration of the signaling molecule within a suitable range. A consequence of such bistability has been the appearance of bimodal distributions indicating two different populations, one in the “off” state and the other in the “on” state. The bimodal distribution can come about from stochastic analysis of a single cell. However, the concerted action of the population altering the extracellular concentration in the environment of individual cells and hence their behavior can only be accomplished by an appropriate population balance model which accounts for the reciprocal effects of interaction between the population and its environment. In this study, we show how to formulate a population balance model in which stochastic gene expression in individual cells is incorporated. Interestingly, the simulation of the model shows that bistability is neither sufficient nor necessary for bimodal distributions in a population. The original notion of linking bistability with bimodal distribution from single cell stochastic model is therefore only a special consequence of a population balance model