29 resultados para Short-end injection
em Repositório Científico do Instituto Politécnico de Lisboa - Portugal
Resumo:
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.
Resumo:
This article presents the design and test of a receiver front end aimed at LMDS applications at 28.5 GHz. It presents a system-level design after which the receiver was designed. The receiver comprises an LNA, quadrature mixer and quadrature local oscillator. Experimental results at 24 GHz center frequency show a conversion voltage gain of 15 dB and conversion noise figure of 14 5 dB. The receiver operates from a 2 5 V power supply with a total current consumption of 31 mA.
Resumo:
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.
Resumo:
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.
Resumo:
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.
Resumo:
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.
Resumo:
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.
Resumo:
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.
Resumo:
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
Resumo:
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.
Resumo:
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.
Resumo:
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.
Resumo:
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.
Resumo:
Traditionally, a country's electoral system requires the voter to vote at a specific day and place, which conflicts with the mobility usually seen in modern live styles. Thus, the widespread of Internet (mobile) broadband access can be seen as an opportunity to deal with this mobility problem, i.e. the adoption of an Internet voting system can make the live of voter's much more convenient; however, a widespread Internet voting systems adoption relies on the ability to develop trustworthy systems, i.e. systems that are verifiable and preserve the voter's privacy. Building such a system is still an open research problem. Our contribution is a new Internet voting system: EVIV, a highly sound End-to-end Verifiable Internet Voting system, which offers full voter's mobility and preserves the voter's privacy from the vote casting PC even if the voter votes from a public PC, such as a PC at a cybercafe or at a public library. Additionally, EVIV has private vote verification mechanisms, in which the voter just has to perform a simple match of two small strings (4-5 alphanumeric characters), that detect and protect against vote manipulations both at the insecure vote client platform and at the election server side. (c) 2012 Elsevier Ltd. All rights reserved.
Resumo:
We investigate the influence of strong directional, or bonding, interactions on the phase diagram of complex fluids, and in particular on the liquid-vapour critical point. To this end we revisit a simple model and theory for associating fluids which consist of spherical particles having a hard-core repulsion, complemented by three short-ranged attractive sites on the surface (sticky spots). Two of the spots are of type A and one is of type B; the interactions between each pair of spots have strengths [image omitted], [image omitted] and [image omitted]. The theory is applied over the whole range of bonding strengths and results are interpreted in terms of the equilibrium cluster structures of the coexisting phases. In systems where unlike sites do not interact (i.e. where [image omitted]), the critical point exists all the way to [image omitted]. By contrast, when [image omitted], there is no critical point below a certain finite value of [image omitted]. These somewhat surprising results are rationalised in terms of the different network structures of the two systems: two long AA chains are linked by one BB bond (X-junction) in the former case, and by one AB bond (Y-junction) in the latter. The vapour-liquid transition may then be viewed as the condensation of these junctions and we find that X-junctions condense for any attractive [image omitted] (i.e. for any fraction of BB bonds), whereas condensation of the Y-junctions requires that [image omitted] be above a finite threshold (i.e. there must be a finite fraction of AB bonds).