Metaheuristic approach to the Holt-Winters optimal short term load forecast

Electricity short-term load forecast is very important for the operation of power systems. In this work a classical exponential smoothing model, the Holt-Winters with double seasonality was used to test for accurate predictions applied to the Portuguese demand time series. Some metaheuristic algorithms for the optimal selection of the smoothing parameters of the Holt-Winters forecast function were used and the results after testing in the time series showed little differences among methods, so the use of the simple local search algorithms is recommended as they are easier to implement.

Metaheuristhic approach to the Holt-Winters optimal short term load forecast

Electricity short-term load forecast is very important for the operation of power systems. In this work a classical exponential smoothing model, the Holt-Winters with double seasonality was used to test for accurate predictions applied to the Portuguese demand time series. Some metaheuristic algorithms for the optimal selection of the smoothing parameters of the Holt-Winters forecast function were used and the results after testing in the time series showed little differences among methods, so the use of the simple local search algorithms is recommended as they are easier to implement.

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.

Projecto de execução da passagem superior 9A, na concessão Douro Litoral na A32/IC2 - Oliveira de Azeméis/IP1 (S. Lourenço)

O presente trabalho teve como principal objectivo a aplicação dos conceitos adquiridos nas unidades curriculares da licenciatura e do mestrado. Nesse sentido tomou-se a opção da realização de um projecto de execução de uma obra de arte para o trabalho final de mestrado, realizado num conceituado gabinete de projecto de pontes e viadutos, com vista à obtenção do grau de mestre. O projecto refere-se a uma obra de arte que se insere num nó rodoviário de ligação entre duas auto-estradas que, dados os seus condicionamentos de perfil, quer longitudinal quer transversal, e implantação no local, pode ser considerada uma obra de arte especial. O processo de análise foi feito com recurso ao programa de cálculo automático SAP2000®, tendo em conta os regulamentos nacionais aplicáveis a estruturas de pontes e os Eurocódigos em fase de implementação em Portugal. O projecto de execução, objecto deste trabalho, foi realizado em função de uma metodologia de construção simples, que é o recurso à utilização, por fases, de cimbres apoiados no solo. A optimização das fases de construção é um factor condicionante na análise e concepção da obra de arte deste projecto, pelo que se procura obter uma relação optimizada entre o rendimento de construção e o funcionamento estrutural da obra de arte, de forma a garantir a segurança da estrutura e o conforto dos utilizadores a longo prazo.

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.

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.

Two-Higgs-doublet model in light of the standard model H -> tau(+)tau(-) search at the LHC

We study the implications of the searches based on H -> tau(+)tau-by the ATLAS and CMS collaborations on the parameter space of the two-Higgs-doublet model (2HDM). In the 2HDM, the scalars can decay into a tau pair with a branching ratio larger than the SM one, leading to constraints on the 2HDM parameter space. We show that in model II, values of tan beta > 1.8 are definitively excluded if the pseudoscalar is in the mass range 110 GeV < m(A) < 145 GeV. We have also discussed the implications for the 2HDM of the recent dimuon search by the ATLAS collaboration for a CP-odd scalar in the mass range 4-12 GeV.

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.

Análise de desempenho em redes móveis Long Term Evolution (Parceria CELFINET)

A rede móvel Long Term Evolution (LTE) é uma tecnologia que está a ser fortemente implementada, não só em Portugal mas no resto do mundo. A adoção do LTE deve-se em grande parte à maior capacidade e à baixa latência oferecidas, para além de ser expansível ao LTE-Advanced. O trabalho apresentado tem por objetivo a análise do desempenho de uma rede LTE piloto e comparar os resultados com o teoricamente expectável. Foi adotada uma metodologia de planeamento em LTE e comprovada através das medidas empíricas realizadas. Dessas medições são também sugeridos dois novos modelos de propagação para LTE nos 2,6 GHz. Para distâncias inferiores a 1 km sugere-se o modelo LTE-PL. Para distâncias superiores a 1 km foi feita uma adaptação ao modelo Okumura-Hata para que se aproximasse aos resultados obtidos. Das medições efetuadas observou-se que em boas condições rádio, os débitos bináriossão bastante próximos dos máximos teóricos. Além disso foi obtido o desvio padrão em LTE de uma área Urbano Denso de 12 dB. Foi ainda possível definir uma margem para as perdas de penetração in-car de 2,7 dB. Efetuou-se uma análise de vários Key Performance Indicators que permitem avaliar o desempenho do LTE, tendo também sido definidas categorias de qualidade de serviço. Por último foi avaliado o impacto da velocidade e da distância, pelas medidas realizadas.

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.

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.

The adjusted effect of maternal body mass index, energy and macronutrient intakes during pregnancy, and gestational weight gain on body composition of full-term neonates

Objective - To evaluate the effect of prepregnancy body mass index (BMI), energy and macronutrient intakes during pregnancy, and gestational weight gain (GWG) on the body composition of full-term appropriate-for-gestational age neonates. Study Design - This is a cross-sectional study of a systematically recruited convenience sample of mother-infant pairs. Food intake during pregnancy was assessed by food frequency questionnaire and its nutritional value by the Food Processor Plus (ESHA Research Inc, Salem, OR). Neonatal body composition was assessed both by anthropometry and air displacement plethysmography. Explanatory models for neonatal body composition were tested by multiple linear regression analysis. Results - A total of 100 mother-infant pairs were included. Prepregnancy overweight was positively associated with offspring weight, weight/length, BMI, and fat-free mass in the whole sample; in males, it was also positively associated with midarm circumference, ponderal index, and fat mass. Higher energy intake from carbohydrate was positively associated with midarm circumference and weight/length in the whole sample. Higher GWG was positively associated with weight, length, and midarm circumference in females. Conclusion - Positive adjusted associations were found between both prepregnancy BMI and energy intake from carbohydrate and offspring body size in the whole sample. Positive adjusted associations were also found between prepregnancy overweight and adiposity in males, and between GWG and body size in females.