A Protocol for Standardazing the performance evaluation of short term wind power prediction models

International audienceShort-term wind power prediction is a primary requirement for efficient large-scale integration of wind generation in power systems and electricity markets. The choice of an appropriate prediction model among the numerous available models is not trivial, and has to be based on an objective evaluation of model performance.This paper proposes a standardized protocol for the evaluation of short-term wind-power prediction systems. A number of reference prediction models are also described, and their use for performance comparison is analysed. The use of the protocol is demonstrated, using results from both on-shore and offshore wind farms. The work was developed in the frame of the Anemos project (EU R&D project) where the protocol has been used to evaluate more than 10 prediction systems

On-line presentation of mineral occurrences in Greenland

The Geological Survey of Denmark and Greenland (GEUS) and the Bureau of Minerals and Petroleum (BMP, under the Government of Greenland) have co-operated on the international promotion of the mineral resources of Greenland for more than ten years. The Government of Greenland follows a strategy aimed at the development of a mining and petroleum sector in Greenland capable of yielding a significant proportion of the national income. To reach this goal it is necessary to attract international investment. In respect of mineral exploration, many parts of Greenland can still be considered virgin territory and it is therefore vital that all data relevant for the identification of possible exploration targets are available to the international mining industry. GEUS has produced many compilations of geoscience data for that purpose in traditional reports, on CD-ROMs and in scientific journals. In 2004, a new source of geoscience information was developed based on an interactive GIS facility on the Internet, and mineral exploration data and information from a region in central West Greenland are now accessible at the Greenland Mineral Occurrence Map (GMOM) website at GEUS (Fig. 1; www.geus.dk/gmom). Technically, this new facility will be maintained and developed in accordance with general principles for Internet services adopted by GEUS (e.g. Tulstrup 2004). New information from other regions of Greenland will gradually be added

Local linear regression with adaptive orthogonal fitting for the wind power application

Short-term forecasting of wind generation requires a model of the function for the conversion of me-teorological variables (mainly wind speed) to power production. Such a power curve is nonlinear and bounded, in addition to being nonstationary. Local linear regression is an appealing nonparametric ap-proach for power curve estimation, for which the model coefficients can be tracked with recursive Least Squares (LS) methods. This may lead to an inaccurate estimate of the true power curve, owing to the assumption that a noise component is present on the response variable axis only. Therefore, this assump-tion is relaxed here, by describing a local linear regression with orthogonal fit. Local linear coefficients are defined as those which minimize a weighted Total Least Squares (TLS) criterion. An adaptive es-timation method is introduced in order to accommodate nonstationarity. This has the additional benefit of lowering the computational costs of updating local coefficients every time new observations become available. The estimation method is based on tracking the left-most eigenvector of the augmented covari-ance matrix. A robustification of the estimation method is also proposed. Simulations on semi-artificial datasets (for which the true power curve is available) underline the properties of the proposed regression and related estimation methods. An important result is the significantly higher ability of local polynomia

Next Generation Short-Term Forecasting of Wind Power – Overview of the ANEMOS Project.

International audienceThe aim of the European Project ANEMOS is to develop accurate and robust models that substantially outperform current state-of-the-art methods, for onshore and offshore wind power forecasting. Advanced statistical, physical and combined modelling approaches were developed for this purpose. Priority was given to methods for on-line uncertainty and prediction risk assessment. An integrated software platform, 'ANEMOS', was developed to host the various models. This system is installed by several end-users for on-line operation and evaluation at a local, regional and national scale. Finally, the project demonstrates the value of wind forecasts for the power system management and market integration of wind power. Keywords: Wind power, short-term forecasting, numerical weather predictions, on-line software, tools for wind integration

Optimizing Staining Protocols for Laser Microdissection of Specific Cell Types from the Testis Including Carcinoma In Situ

Microarray and RT-PCR based methods are important tools for analysis of gene expression; however, in tissues containing many different cells types, such as the testis, characterization of gene expression in specific cell types can be severely hampered by noise from other cells. The laser microdissection technology allows for enrichment of specific cell types. However, when the cells are not morphologically distinguishable, it is necessary to use a specific staining method for the target cells. In this study we have tested different fixatives, storage conditions for frozen sections and staining protocols, and present two staining protocols for frozen sections, one for fast and specific staining of fetal germ cells, testicular carcinoma in situ cells, and other cells with embryonic stem cell-like properties that express the alkaline phosphatase, and one for specific staining of lipid droplet-containing cells, which is useful for isolation of the androgen-producing Leydig cells. Both protocols retain a morphology that is compatible with laser microdissection and yield RNA of a quality suitable for PCR and microarray analysis

Cervical lymph node metastasis in adenoid cystic carcinoma of the larynx: a collective international review

Adenoid cystic carcinoma (AdCC) of the head and neck is a well-recognized pathologic entity that rarely occurs in the larynx. Although the 5-year locoregional control rates are high, distant metastasis has a tendency to appear more than 5 years post treatment. Because AdCC of the larynx is uncommon, it is difficult to standardize a treatment protocol. One of the controversial points is the decision whether or not to perform an elective neck dissection on these patients. Because there is contradictory information about this issue, we have critically reviewed the literature from 1912 to 2015 on all reported cases of AdCC of the larynx in order to clarify this issue. During the most recent period of our review (1991-2015) with a more exact diagnosis of the tumor histology, 142 cases were observed of AdCC of the larynx, of which 91 patients had data pertaining to lymph node status. Eleven of the 91 patients (12.1%) had nodal metastasis and, based on this low proportion of patients, routine elective neck dissection is therefore not recommended

Tracking Time-Varying Coefficient-Functions

A conditional parametric ARX-model is an ARX-model in which the parameters are replaced by smooth functions of an, possibly multivariate, external input signal. These functions are called coefficientfunctions. A method, which estimates these functions adaptively and recursively, and hence allows for on-line tracking of the coefficientfunctions is suggested. Essentially, in its most simple form, this method is a combination of recursive least squares with exponential forgetting and local polynomial regression. However, it is argued, that it is appropriate to let the forgetting factor vary with the value of the external signal which is argument of the coefficient-functions. The properties of the modified method are studied by simulation. A particular feature is the this effective forgetting factor will adapt to the bandwidth used so that the effective number of observations behind the estimates will be almost independent of the actual bandwidth or of the type of bandwidth selection used ..