Transmission network expansion planning for the Colombian electrical system: Connecting the Ituango hydroelectric power plant

The hydroelectric power plant Hidroltuango represents a major expansion for the Colombian electrical system (with a total capacity of 2400 MW). This paper analyzes the possible interconnections and investments involved in connecting Hidroltuango, in order to strengthen the Colombian national transmission system. A Mixed Binary Linear Programming (MBLP) model was used to solve the Multistage Transmission Network Expansion Planning (MTEP) problem of the Colombian electrical system, taking the N-1 safety criterion into account. The N-1 safety criterion indicates that the transmission system must be expanded so that the system will continue to operate properly if an outage in a system element (within a pre-defined set of contingencies) occurs. The use of a MBLP model guaranteed the convergence with existing classical optimization methods and the optimal solution for the MTEP using commercial solvers. Multiple scenarios for generation and demand were used to consider uncertainties within these parameters. The model was implemented using the algebraic modeling language AMPL and solved using the commercial solver CPLEX. The proposed model was then applied to the Colombian electrical system using the planning horizon of 2018-2025. (C) 2014 Elsevier B.V. All rights reserved.

Optimal Reactive Power Planning Using Risk Analysis

In this paper, the optimal reactive power planning problem under risk is presented. The classical mixed-integer nonlinear model for reactive power planning is expanded into two stage stochastic model considering risk. This new model considers uncertainty on the demand load. The risk is quantified by a factor introduced into the objective function and is identified as the variance of the random variables. Finally numerical results illustrate the performance of the proposed model, that is applied to IEEE 30-bus test system to determine optimal amount and location for reactive power expansion.

A mixed-integer quadratically-constrained programming model for the distribution system expansion planning

This paper presents a mixed-integer quadratically-constrained programming (MIQCP) model to solve the distribution system expansion planning (DSEP) problem. The DSEP model considers the construction/reinforcement of substations, the construction/reconductoring of circuits, the allocation of fixed capacitors banks and the radial topology modification. As the DSEP problem is a very complex mixed-integer non-linear programming problem, it is convenient to reformulate it like a MIQCP problem; it is demonstrated that the proposed formulation represents the steady-state operation of a radial distribution system. The proposed MIQCP model is a convex formulation, which allows to find the optimal solution using optimization solvers. Test systems of 23 and 54 nodes and one real distribution system of 136 nodes were used to show the efficiency of the proposed model in comparison with other DSEP models available in the specialized literature. (C) 2014 Elsevier Ltd. All rights reserved.

Transmission network expansion planning considering repowering and reconfiguration

Transmission expansion planning (TEP) is a classic problem in electric power systems. In current optimization models used to approach the TEP problem, new transmission lines and two-winding transformers are commonly used as the only candidate solutions. However, in practice, planners have resorted to non-conventional solutions such as network reconfiguration and/or repowering of existing network assets (lines or transformers). These types of non-conventional solutions are currently not included in the classic mathematical models of the TEP problem. This paper presents the modeling of necessary equations, using linear expressions, in order to include non-conventional candidate solutions in the disjunctive linear model of the TEP problem. The resulting model is a mixed integer linear programming problem, which guarantees convergence to the optimal solution by means of available classical optimization tools. The proposed model is implemented in the AMPL modeling language and is solved using CPLEX optimizer. The Garver test system, IEEE 24-busbar system, and a Colombian system are used to demonstrate that the utilization of non-conventional candidate solutions can reduce investment costs of the TEP problem. (C) 2015 Elsevier Ltd. All rights reserved.

Endovascular treatment for acute ischemic stroke patients: implications and interpretation of IMS III, MR RESCUE, and SYNTHESIS EXPANSION trials: A report from the Working Group of International Congress of Interventional Neurology

OBJECTIVE The results of Interventional Management of Stroke (IMS) III, Magnetic Resonance and REcanalization of Stroke Clots Using Embolectomy (MR RESCUE), and SYNTHESIS EXPANSION trials are expected to affect the practice of endovascular treatment for acute ischemic stroke. The purpose of this report is to review the components of the designs and methods of these trials and to describe the influence of those components on the interpretation of trial results. METHODS A critical review of trial design and conduct of IMS III, MR RESCUE, and SYNTHESIS EXPANSION is performed with emphasis on patient selection, shortcomings in procedural aspects, and methodology of data ascertainment and analysis. The influence of each component is estimated based on published literature including multicenter clinical trials reporting on endovascular treatment for acute ischemic stroke and myocardial infarction. RESULTS We critically examined the time interval between symptom onset and treatment and rates of angiographic recanalization to differentiate between "endovascular treatment" and "parameter optimized endovascular treatment" as it relates to the IMS III, MR RESCUE, and SYNTHESIS EXPANSION trials. All the three trials failed to effectively test "parameter optimized endovascular treatment" due to the delay between symptom onset and treatment and less than optimal rates of recanalization. In all the three trials, the magnitude of benefit with endovascular treatment required to reject the null hypothesis was larger than could be expected based on previous studies. The IMS III and SYNTHESIS EXPANSION trials demonstrated that rates of symptomatic intracerebral hemorrhages subsequent to treatment are similar between IV thrombolytics and endovascular treatment in matched acute ischemic stroke patients. The trials also indirectly validated the superiority/equivalence of IV thrombolytics (compared with endovascular treatment) in patients with minor neurological deficits and those without large vessel occlusion on computed tomographic/magnetic resonance angiography. CONCLUSIONS The results do not support a large magnitude benefit of endovascular treatment in subjects randomized in all the three trials. The possibility that benefits of a smaller magnitude exist in certain patient populations cannot be excluded. Large magnitude benefits can be expected with implementation of "parameter optimized endovascular treatment" in patients with ischemic stroke who are candidates for IV thrombolytics.

Differentiating the Multipoint Expected Improvement for Optimal Batch Design

This work deals with parallel optimization of expensive objective functions which are modelled as sample realizations of Gaussian processes. The study is formalized as a Bayesian optimization problem, or continuous multi-armed bandit problem, where a batch of q > 0 arms is pulled in parallel at each iteration. Several algorithms have been developed for choosing batches by trading off exploitation and exploration. As of today, the maximum Expected Improvement (EI) and Upper Confidence Bound (UCB) selection rules appear as the most prominent approaches for batch selection. Here, we build upon recent work on the multipoint Expected Improvement criterion, for which an analytic expansion relying on Tallis’ formula was recently established. The computational burden of this selection rule being still an issue in application, we derive a closed-form expression for the gradient of the multipoint Expected Improvement, which aims at facilitating its maximization using gradient-based ascent algorithms. Substantial computational savings are shown in application. In addition, our algorithms are tested numerically and compared to state-of-the-art UCB-based batchsequential algorithms. Combining starting designs relying on UCB with gradient-based EI local optimization finally appears as a sound option for batch design in distributed Gaussian Process optimization.

The colony-stimulating factor 1 receptor is expressed on dendritic cells during differentiation and regulates their expansion

The lineage of dendritic cells (DC), and in particular their relationship to monocytes and macrophages, remains obscure. Furthermore, the requirement for the macrophage growth factor CSF-1 during DC homeostasis is unclear. Using a transgenic mouse in which the promoter for the CSF-1R (c-fms) directs the expression of enhanced GFP in cells of the myeloid lineage, we determined that although the c-fms promoter is inactive in DC precursors, it is up-regulated in all DC subsets during differentiation. Furthermore, plasmacytoid DC and all CD11c(high) DC subsets are reduced by 50-70% in CSF-1-deficient osteopetrotic mice, confirming that CSF-1 signaling is required for the optimal differentiation of DC in vivo. These data provide additional evidence that the majority of tissue DC is of myeloid origin during steady state and supports a close relationship between DC and macrophage biology in vivo.