Large-scale unit commitment under uncertainty: an updated literature survey

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject

The efficacy and safety of chitosan dextran gel in a burr hole neurosurgical sheep model

BACKGROUND Achieving and maintaining haemostasis is of paramount importance in neurosurgery. Chitosan has been shown in both animal and human models to be significantly effective in haemostasis as well as in reducing adhesion formation. OBJECTIVES To evaluate the haemostatic potential and to study histopathological changes caused by novel chitosan dextran gel in a neurosurgical sheep model. METHOD Ten sheep underwent neurosurgical burr hole procedure. Bleeding control was tested at the level of bone, dura and brain separately with both chitosan gel and Gelfoam paste on separate burr holes. Baseline bleeding was measured at the time of injury using the Boezaart scale, and then every 2 min after the application of each agent until complete haemostasis or 10 min, whichever was earlier. Safety was assessed through MRI scans and histopathological analysis. RESULTS Mixed modeling showed no statistical difference in time to haemostasis between chitosan gel and Gelfoam paste (means of log-normalized areas under the curve were 1.3688 and 1.3196 respectively) for each burr hole (p  = 0.7768). Logistic regression modeling showed that Chitosan significantly decreased the incidence of bleeding beyond the first time point measured after application of the treatment when compared to Gelfoam (OR = 2.7, p = 0.04). Average edema volume (cm3) on post-operative MRI was 0.97 for Gelfoam and 1.11 for (p = 0.49) while average histology scores were 2.5 for Gelfoam versus 3.3 for chitosan (p = 0.32). CONCLUSION Chitosan dextran gel is an effective haemostatic agent to control bleeding in brain tissue. It is safe and nontoxic to neural tissue.Sukanya Rajiv, Marguerite Harding, Ahmed Bassiouni, Camille Jardeleza, Amanda Drilling, Craig James, Thanh Ha, Steve Moratti, Simon Robinson, Peter-John Wormal