Abstract
This paper studies the classification of high-dimensional Gaussian signals from low-dimensional noisy, linear measurements. In particular, it provides upper bounds (sufficient conditions) on the number of measurements required to drive the probability of misclassification to zero in the low-noise regime, both for random measurements and designed ones. Such bounds reveal two important operational regimes that are a function of the characteristics of the source: 1) when the number of classes is less than or equal to the dimension of the space spanned by signals in each class, reliable classification is possible in the low-noise regime by using a one-vs-all measurement design; 2) when the dimension of the spaces spanned by signals in each class is lower than the number of classes, reliable classification is guaranteed in the low-noise regime by using a simple random measurement design. Simulation results both with synthetic and real data show that our analysis is sharp, in the sense that it is able to gauge the number of measurements required to drive the misclassification probability to zero in the low-noise regime.

Abstract
Wind power generation is to play an important role in supplying electric power demand, and will certainly impact the design of future energy and reserve markets. Operators of wind power plants will consequently develop adequate offering strategies, accounting for the market rules and the operational capabilities of the turbines, e.g., to participate in primary reserve markets. We consider two different offering strategies for joint participation of wind power in energy and primary reserve markets, based on the idea of proportional and constant splitting of potentially available power generation from the turbines. These offering strategies aim at maximizing expected revenues from both market floors using probabilistic forecasts for wind power generation, complemented with estimated regulation costs and penalties for failing to provide primary reserve. A set of numerical examples, as well as a case-study based on real-world data, allows illustrating and discussing the properties of these offering strategies. An important conclusion is that, even though technically possible, it may not always make sense for wind power to aim at providing system services in a market environment. © 2010-2012 IEEE.

Abstract

Abstract
Introduction of renewable energy sources (RES) in insular areas is growing on different islands of various regions in the world and the large-scale deployment of renewables in island power systems is appealing to local attention of grid operators as a method to decrease fossil fuel consumption. Planning a grid based on renewable power plants (RPP) presents serious challenges to the normal operation of a power system, precisely on voltage and frequency stability. Despite of its inherent problems, there is a consensus that in near future the RES could supply most of local needs without depending exclusively on fossil fuels. In previous grid code compliance, wind turbines did not required services to support grid operation. Thus, in order to shift to large-scale integration of renewables, the insular grid code ought to incorporate a new set of requirements with the intention of regulating the inclusion of these services. Hence, this paper discusses grid code requirements for large-scale integration of renewables in an island context, as a new contribution to earlier studies. The current trends on grid code formulation, towards an improved integration of distributed renewable resources in island power systems, are addressed. The paper also discusses advanced grid code requirement concepts such as virtual wind inertia and synthetic inertia for improving regulation capability of wind farms and the application of energy storage systems (EES) for enhancing renewable generation integration. Finally, a comparative analysis of insular grid code compliance to these requirements is presented in the European context.

Abstract
The variability of wind generation introduces uncertainty in the optimal scheduling of the system. Consequently, it is difficult for the system operator to determine the optimal amount of conventional generation that should be committed and its corresponding power production in order to reduce generation costs. Incorporation of forecasting error on the optimal unit scheduling has been extensively suggested in the literature. However, it strongly depends on the probability distribution adopted to represent wind power forecasting error. Cauchy distribution has demonstrated to be an adequate tool to represent forecasting error. In this paper, an analytical model to solve dynamic economic dispatch is presented. The proposed model is based on discretization of Cauchy distribution, so that its incorporation in the optimization problem is successfully done. This is illustrated by analyzing a representative case study and the results are compared to a Monte Carlo Simulation approach in order to show the accuracy of the proposed method.

Abstract
A 'hybridization' of a logic, referred to as the base logic, consists of developing the characteristic features of hybrid logic on top of the respective base logic, both at the level of syntax (i.e. modalities, nominals, etc.) and of the semantics (i.e. possible worlds). By 'hybridized institutions' we mean the result of this process when logics are treated abstractly as institutions (in the sense of the institution theory of Goguen and Burstall). This work develops encodings of hybridized institutions into (many-sorted) first-order logic (abbreviated FOL) as a 'hybridization' process of abstract encodings of institutions into FOL, which may be seen as an abstraction of the well-known standard translation of modal logic into FOL. The concept of encoding employed by our work is that of comorphism from institution theory, which is a rather comprehensive concept of encoding as it features encodings both of the syntax and of the semantics of logics/institutions. Moreover, we consider the so-called theoroidal version of comorphisms that encode signatures to theories, a feature that accommodates a wide range of concrete applications. Our theory is also general enough to accommodate various constraints on the possible worlds semantics as well a wide variety of quantifications. We also provide pragmatic sufficient conditions for the conservativity of the encodings to be preserved through the hybridization process, which provides the possibility to shift a formal verification process from the hybridized institution to FOL.