Predictive control for multi-market trade of aggregated demand response using a black box approach

Aggregated demand response for smart grid services is a growing field of interest especially for market participation. To minimize economic and network instability risks, flexibility characteristics such as shiftable capacity must be known. This is traditionally done using lower level, end user, device specifications. However, with these large numbers, having lower level information, has both privacy and computational limitations. Previous studies have shown that black box forecasting of shiftable capacity, using machine learning techniques, can be done accurately for a homogeneous cluster of heating devices. This paper validates the machine learning model for a heterogeneous virtual power plant. Further it applies this model to a control strategy to offer flexibility on an imbalance market while maintaining day ahead market obligations profitably. It is shown that using a black box approach 89% optimal economic performance is met. Further, by combining profits made on imbalance market and the day ahead costs, the overall monthly electricity costs are reduced 20%

Static and Dynamic Magnetism in Underdoped Superconductor BaFe1.92_{1.92}Co0.08_{0.08}As2_2

We report neutron scattering measurements on single crystals of BaFe$_{1.92}$Co$_{0.08}$As$_2$. The magnetic Bragg peak intensity is reduced by 6 % upon cooling through T$_C$. The spin dynamics exhibit a gap of 8 meV with anisotropic three-dimensional (3d) interactions. Below T$_C$ additional intensity appears at an energy of $\sim$4.5(0.5) meV similar to previous observations of a spin resonance in other Fe-based superconductors. No further gapping of the spin excitations is observed below T$_C$ for energies down to 2 meV. These observations suggest the redistribution of spectral weight from the magnetic Bragg position to a spin resonance demonstrating the direct competition between static magnetic order and superconductivity.Comment: 4 pages, 4 figure

Computational modelling of emboli travel trajectories in cerebral arteries: Influence of microembolic particle size and density

This article has been made available through the Brunel Open Access Publishing Fund.Ischaemic stroke is responsible for up to 80 % of stroke cases. Prevention of the reoccurrence of ischaemic attack or stroke for patients who survived the first symptoms is the major treatment target. Accurate diagnosis of the emboli source for a specific infarction lesion is very important for a better treatment for the patient. However, due to the complex blood flow patterns in the cerebral arterial network, little is known so far of the embolic particle flow trajectory and its behaviour in such a complex flow field. The present study aims to study the trajectories of embolic particles released from carotid arteries and basilar artery in a cerebral arterial network and the influence of particle size, mass and release location to the particle distributions, by computational modelling. The cerebral arterial network model, which includes major arteries in the circle of Willis and several generations of branches from them, was generated from MRI images. Particles with diameters of 200, 500 and 800 μ m and densities of 800, 1,030 and 1,300 kg/m 3 were released in the vessel's central and near-wall regions. A fully coupled scheme of particle and blood flow in a computational fluid dynamics software ANASYS CFX 13 was used in the simulations. The results show that heavy particles (density large than blood or a diameter larger than 500 μ m) normally have small travel speeds in arteries; larger or lighter embolic particles are more likely to travel to large branches in cerebral arteries. In certain cases, all large particles go to the middle cerebral arteries; large particles with higher travel speeds in large arteries are likely to travel at more complex and tortuous trajectories; emboli raised from the basilar artery will only exit the model from branches of basilar artery and posterior cerebral arteries. A modified Circle of Willis configuration can have significant influence on particle distributions. The local branch patterns of internal carotid artery to middle cerebral artery and anterior communicating artery can have large impact on such distributions. © 2014 The Author(s)

Triacylglycerol profiling of microalgae strains for biofuel feedstock by liquid chromatography–high-resolution mass spectrometry

Biofuels from photosynthetic microalgae are quickly gaining interest as a viable carbon-neutral energy source. Typically, characterization of algal feedstock involves breaking down triacylglycerols (TAG) and other intact lipids, followed by derivatization of the fatty acids to fatty acid methyl esters prior to analysis by gas chromatography (GC). However, knowledge of the intact lipid profile could offer significant advantages for discovery stage biofuel research such as the selection of an algal strain or the optimization of growth and extraction conditions. Herein, lipid extracts from microalgae were directly analyzed by ultra-high pressure liquid chromatography–mass spectrometry (UHPLC-MS) using a benchtop Orbitrap mass spectrometer. Phospholipids, glycolipids, and TAGs were analyzed in the same chromatographic run, using a combination of accurate mass and diagnostic fragment ions for identification. Using this approach, greater than 100 unique TAGs were identified over the six algal strains studied and TAG profiles were obtained to assess their potential for biofuel applications. Under the growth conditions employed, Botryococcus braunii and Scenedesmus obliquus yielded the most comprehensive TAG profile with a high abundance of TAGs containing oleic acid

Responders vs clinical response: a critical analysis of data from linaclotide phase 3 clinical trials in IBS-C

Background: US Food and Drug Administration (FDA) set a rigorous standard for defining patient responders in irritable bowel syndrome-C (IBS-C; i.e., FDA's Responder Endpoint) for regulatory approval. However, this endpoint's utility for health-care practitioners to assess clinical response has not been determined. We analyzed pooled IBS-C linaclotide trial data to evaluate clinically significant responses in linaclotide-treated patients who did not meet the FDA responder definition. Methods: Percentages of FDA non-responders reporting improvement in abdominal pain, bowel function and/or global relief measures were determined using pooled data from two linaclotide Phase 3 IBS-C trials. Key Results 1602 IBS-C patients enrolled; 34% of linaclotide-treated and 17% of placebo-treated patients met the FDA Responder Endpoint (p < 0.0001). Among FDA non-responders at week 12, 63% of linaclotide-treated patients reported their abdominal pain was at least somewhat relieved, compared with 48% of placebo-treated patients. For stool frequency, 62% of linaclotide-treated patients reported that they were at least somewhat improved at week 12, compared with 46% of placebo-treated patients. For global IBS symptoms, 65% of linaclotide-treated patients reported at least some IBS-symptom relief, 43% reported adequate relief of IBS symptoms, and 57% reported being satisfied with linaclotide treatment, vs placebo rates of 48%, 34%, and 41% respectively. Conclusions & Inferences Most linaclotide-treated IBS-C patients who were FDA non-responders reported some improvement in abdominal pain and stool frequency, and global relief/satisfaction. In addition to the FDA Responder Endpoint, differing response thresholds and symptom-specific change from baseline should be considered by clinicians for a complete understanding of clinical response to linaclotide and other IBS-C therapies