State-of-the-art Methods and software tools for short-term prediction of wind energy production

International audienceThe installed wind energy capacity in Europe today is 20 GW, while the projections for 2010 according to the Kyoto protocol and the EC directives is up to 40-60 GW. The large-scale integration of wind energy emerges the use of advanced operational tools for short-term forecasting of the wind production in the next hours up to the next 2-7 days. End-users (independent power producers, electric companies, transmission system operators, etc) recognize the contribution of wind prediction for a secure and economic operation of the power system. Especially, in a liberalized electricity market, prediction tools enhance the position of wind energy compared to other forms of dispatchable generation. The paper presents in detail the state-of the-art on the methods, the software tools and the relevant R&D projects for wind power forecasting. The paper finally presents experience by end-users that run operationally such prediction systems today as stand-alone applications or interfaced to EMS/DMS systems. The paper reviews the related literature on wind power prediction. Emphasis is given on operational tools such as WPPT, Prediktor, Zephyr, Previento, SIPREÓLICO, LocalPred, More-Care etc. The various models or tools are classified using criteria like: · The type of implemented approach i.e. timeseries (neural networks, ARMA etc) or physical. · The specific spatial scale focused by the models (regional, wind park scale, micro-scale). · The on-line performance of the prediction tools and their coupling to Energy Management Systems

QuantiMus: A Machine Learning-Based Approach for High Precision Analysis of Skeletal Muscle Morphology.

Skeletal muscle injury provokes a regenerative response, characterized by the de novo generation of myofibers that are distinguished by central nucleation and re-expression of developmentally restricted genes. In addition to these characteristics, myofiber cross-sectional area (CSA) is widely used to evaluate muscle hypertrophic and regenerative responses. Here, we introduce QuantiMus, a free software program that uses machine learning algorithms to quantify muscle morphology and molecular features with high precision and quick processing-time. The ability of QuantiMus to define and measure myofibers was compared to manual measurement or other automated software programs. QuantiMus rapidly and accurately defined total myofibers and measured CSA with comparable performance but quantified the CSA of centrally-nucleated fibers (CNFs) with greater precision compared to other software. It additionally quantified the fluorescence intensity of individual myofibers of human and mouse muscle, which was used to assess the distribution of myofiber type, based on the myosin heavy chain isoform that was expressed. Furthermore, analysis of entire quadriceps cross-sections of healthy and mdx mice showed that dystrophic muscle had an increased frequency of Evans blue dye+ injured myofibers. QuantiMus also revealed that the proportion of centrally nucleated, regenerating myofibers that express embryonic myosin heavy chain (eMyHC) or neural cell adhesion molecule (NCAM) were increased in dystrophic mice. Our findings reveal that QuantiMus has several advantages over existing software. The unique self-learning capacity of the machine learning algorithms provides superior accuracy and the ability to rapidly interrogate the complete muscle section. These qualities increase rigor and reproducibility by avoiding methods that rely on the sampling of representative areas of a section. This is of particular importance for the analysis of dystrophic muscle given the "patchy" distribution of muscle pathology. QuantiMus is an open source tool, allowing customization to meet investigator-specific needs and provides novel analytical approaches for quantifying muscle morphology

Impact of UV radiation on DOM transformation on molecular level using FT-ICR-MS and PARAFAC

Dissolved organic matter (DOM) is an omnipresent constituent of natural water bodies. Reuse and transformation of DOM compounds in the water column is driven by physicochemical and biological processes leading to the production of refractory DOM. Typically, breakdown of DOM chemical compounds into smaller or more condensed fragments is triggered by ultraviolet (UV) radiation. Here, we present a study on the photodegradation of DOM produced during an incubation experiment with a natural microbial community. At the end of the first incubation without UV irradiation, the samples from 3 mesocosms were filtered to remove microbes and particles and continuously exposed to UV radiation (280–365 nm). We investigated DOM in depth via monitoring of dissolved organic carbon (DOC) concentrations, DOM molecular characterization by Fourier-Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR-MS) and excitation emission matrix spectroscopy (EEMS). Analysis of variance indicated no significant differences in the DOC concentration between treatments. Main peaks in the fluorescent DOM (FDOM) were photo-bleached by UV radiation, and an increase in the fluorescent intensity of selected peaks was observed on irradiated samples toward the end of the experiment. Parallel factor analysis (PARAFAC) indicated the presence of three main components in all treatments: C1 (Marine humic M), C2 (Bacterial produced humic C), C3 (Tyrosine), and an additional component in the dark incubation of mesocosm 3, C4 (Tryptophan). Despite an intensive filtration protocol through 0.7, 0.2 and 0.1 μm filters, low bacterial abundances were determined (<2.5 × 10−3 cells mL−1). We observed a direct correlation between structural indices and the intensity of PARAFAC components. Average double bond equivalent and aromaticity were strongly positively correlated with PARAFAC components C1 and C2 for one or more mesocosm. Moreover, FT-ICR-MS showed that under the tested conditions, the refractory character of the DOM assessed as the similarity to a deep ocean DOM reference did not increase on molecular level. Thus, mechanisms other than photochemical transformations of relatively recent DOM are likely necessary to facilitate long-term stability of DOM in the oceans

Effective public involvement in the HoST-D Programme for dementia home care support: From proposal and design to methods of data collection (innovative practice)

Public involvement is an important element in health and social care research. However, it is little evaluated in research. This paper discusses the utility and impact of public involvement of carers and people with dementia in a five-year programme on effective home support in dementia, from proposal and design to methods of data collection, and provides a useful guide for future research on how to effectively involve the public. The Home SupporT in Dementia (HoST-D) Programme comprises two elements of public involvement, a small reference group and a virtual lay advisory group. Involving carers and people with dementia is based on the six key values of involvement – respect, support, transparency, responsiveness, fairness of opportunity, and accountability. Carers and people with dementia gave opinions on study information, methods of data collection, an economic model, case vignettes, and a memory aid booklet, which were all taken into account. Public involvement has provided benefits to the programme whilst being considerate of the time constraints and geographical locations of members

Aircraft and ground-based measurements of hydroperoxides during the 2006 MILAGRO field campaign

International audienceMixing ratios of hydrogen peroxide and hydroxymethyl hydroperoxide were determined aboard the US Department of Energy G-1 Research Aircraft during the March 2006 MILAGRO field campaign in Mexico. Ground measurements of total hydroperoxide were made at the T1 site at Universidad Technologica de Tecámac, about 35 km NW of Mexico City. In the air and on the ground, peroxide mixing ratios near the source region were generally near 1 ppbv, much lower than had been predicted from photochemical models based on the 2003 Mexico City study. Strong southerly flow resulted in transport of pollutants from the T0 to T1 and T2 surface sites on several flight days. On these days, it was observed that peroxide concentrations slightly decreased as the G-1 flew progressively downwind. This observation is consistent with low or negative net peroxide production rates calculated for the source region and is due to the very high NOx concentrations above the Mexico City plateau. However, relatively high values of peroxide were observed at takeoff and landing near Veracruz, a site with much higher humidity and lower NOx concentrations