A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches.

An artificial neural network approach for short-term wind power forecasting in Portugal

This paper presents an artificial neural network approach for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. The accuracy of the wind power forecasting attained with the proposed approach is evaluated against persistence and ARIMA approaches, reporting the numerical results from a real-world case study.

Nonlinear optimization method for short-term hydro scheduling considering head-dependency

This paper is on the problem of short-term hydro scheduling, particularly concerning head-dependent reservoirs under competitive environment. We propose a new nonlinear optimization method to consider hydroelectric power generation as a function of water discharge and also of the head. Head-dependency is considered on short-term hydro scheduling in order to obtain more realistic and feasible results. The proposed method has been applied successfully to solve a case study based on one of the main Portuguese cascaded hydro systems, providing a higher profit at a negligible additional computation time in comparison with a linear optimization method that ignores head-dependency.

Enhanced short wavelength response in laser-scanned-photodiode image sensor using an a-SiC : H/a-Si : H tandem structure

We report in this paper the recent advances we obtained in optimizing a color image sensor based on the laser-scanned-photodiode (LSP) technique. A novel device structure based on a a-SiC:H/a-Si:H pin/pin tandem structure has been tested for a proper color separation process that takes advantage on the different filtering properties due to the different light penetration depth at different wavelengths a-SM and a-SiC:H. While the green and the red images give, in comparison with previous tested structures, a weak response, this structure shows a very good recognition of blue color under reverse bias, leaving a good margin for future device optimization in order to achieve a complete and satisfactory RGB image mapping. Experimental results about the spectral collection efficiency are presented and discussed from the point of view of the color sensor applications. The physics behind the device functioning is explained by recurring to a numerical simulation of the internal electrical configuration of the device.

Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach

In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of 1 week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn. (C) 2012 Elsevier Ltd. All rights reserved.

Application of adaptive neuro-fuzzy inference for wind power short-term forecasting

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. In this paper, an adaptive neuro-fuzzy inference approach is proposed for short-term wind power forecasting. Results from a real-world case study are presented. A thorough comparison is carried out, taking into account the results obtained with other approaches. Numerical results are presented and conclusions are duly drawn. (C) 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Hybrid Wavelet-PSO-ANFIS Approach for Short-Term Electricity Prices Forecasting

A novel hybrid approach, combining wavelet transform, particle swarm optimization, and adaptive-network-based fuzzy inference system, is proposed in this paper for short-term electricity prices forecasting in a competitive market. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Finally, conclusions are duly drawn.

Microstrip antenna array for multiband dedicated short range communications systems

Dedicated Short Range Communications (DSRC) is the key enabling technology for the present and future vehicular communication for various applications, such as safety improvement and traffic jam mitigation. This paper describes the development of a microstrip antenna array for the roadside equipment of a DSRC system, whose characteristics are according with the vehicular communications standards. The proposed antenna, with circular polarization, has a wide bandwidth, enough to cover the current European DSRC 5.8 GHz band and the future 5.9 GHz band for next generation DSRC communications. (C) 2011 Wiley Periodicals, Inc. Microwave Opt Technol Lett 53: 2794-2796, 2011; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.26394

Semiconductor Device as Optical Demultiplexer for Short Range Optical Communications

In this paper we present results on the use of a multilayered a-SiC:H heterostructure as a wavelength-division demultiplexing device for the visible light spectrum. The proposed device is composed of two stacked p-i-n photodiodes with intrinsic absorber regions adjusted to short and long wavelength absorption and carrier collection. An optoelectronic characterisation of the device was performed in the visible spectrum. Demonstration of the device functionality for WDM applications was done with three different input channels covering the long, the medium and the short wavelengths in the visible range. The recovery of the input channels is explained using the photocurrent spectral dependence on the applied voltage. An electrical model of the WDM device is proposed and supported by the solution of the respective circuit equations. Short range optical communications constitute the major application field, however other applications are also foreseen.

Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

Short-term Feature Space and Music Genre Classification

In music genre classification, most approaches rely on statistical characteristics of low-level features computed on short audio frames. In these methods, it is implicitly considered that frames carry equally relevant information loads and that either individual frames, or distributions thereof, somehow capture the specificities of each genre. In this paper we study the representation space defined by short-term audio features with respect to class boundaries, and compare different processing techniques to partition this space. These partitions are evaluated in terms of accuracy on two genre classification tasks, with several types of classifiers. Experiments show that a randomized and unsupervised partition of the space, used in conjunction with a Markov Model classifier lead to accuracies comparable to the state of the art. We also show that unsupervised partitions of the space tend to create less hubs.

Short-term wind power forecasting in Portugal by neural networks and wavelet transform

This paper proposes artificial neural networks in combination with wavelet transform for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. Results from a real-world case study are presented. A comparison is carried out, taking into account the results obtained with other approaches. Finally, conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

O metacinema norte-americano e o storytelling : de Orson Welles a David Lynch

ABSTRACT: The American metacinema which, by tradition, is narrative but extremely formulaic favours the story above the telling. No man contributed more to alter this state of affairs than Orson Welles, whose cinematic practice exalted the filmic enunciation and linked it more explicitly to the narrative intentions of the creator, making it obvious that metanarrative is synonymous with metacinema. With Citizen Kane (1941), in particular, the cinema was made more disnarrative, as meant by French writer/director Alain Robbe–Grillet, well ahead of Modernism. The fragmented narration, the temporal convolutions, a tendency for paradox and the interpretative obstacles all come together to anticipate the serial practice of David Lynch in his last four features. Structuring the films in segments which constitute different but complementary versions of the same events, Lynch manages to express the director’s enunciation along with the narration of the characters, reinforcing the role of the telling in the midst of the story. In INLAND EMPIRE (2006) the use of mise-en-abyme as a way of duplicating stories and tellers further increases the objective and complicates what is clearly the reign of the puzzle or mind-game film. In the footsteps of Welles, Lynch contributed for an outbreak of metanarrative / metacinematic crossover indie films closer to the European aesthetic practice but still very much within the American narrative tradition.

Le lexique fourni et interiorisé: un moyen efficace pour construire un genre ?

Cet article présente les premiers résultats d’une recherche s’intéressant à l’articulation entre imitation et invention dans l’écriture chez les jeunes scripteurs. L’étude s’attache à observer les modes de récupération de ressources textuelles fournies par les conditions de production. L’expérimentation a été conçue pour observer l’appropriation d’un genre. Des dispositifs didactiques ont été proposés à plusieurs classes de fin d’école primaire française, à partir de textes littéraires issus de la robinsonnade mis à disposition soit simultanément à l’acte d’écriture soit lors d’une seconde écriture. L’étude montre comment les élèves ont recours à deux procédés contrastés : le réinvestissement du lexique et la reformulation. Les données recueillies mettent en évidence la reprise attendue de mots caractéristiques du genre, et révèlent l’ingéniosité des scripteurs pour restructurer des matériaux langagiers. Certaines stratégies témoignent des difficultés rencontrées par les élèves qui ont eu à interpréter le lexique littéraire puis à le transférer dans leur propre récit. Des modes de reformulation différents coexistent dont on peut offrir une première catégorisation en fonction d’une appropriation plus ou moins réussie du genre considéré.

Wind-CSP short-term coordination by MILP approach

This paper is on the maximization of total profit in a day-ahead market for a price-taker producer needing a short-term scheduling for wind power plants coordination with concentrated solar power plants, having thermal energy storage systems. The optimization approach proposed for the maximization of profit is a mixed-integer linear programming problem. The approach considers not only transmission grid constraints, but also technical operating constraints on both wind and concentrated solar power plants. Then, an improved short-term scheduling coordination is provided due to the more accurate modelling presented in this paper. Computer simulation results based on data for the Iberian wind and concentrated solar power plants illustrate the coordination benefits and show the effectiveness of the approach.