31 resultados para NONLINEAR SIGMA-TERM
em Repositório Científico do Instituto Politécnico de Lisboa - Portugal
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:
This paper is on the problem of short-term hydro scheduling (STHS), particularly concerning a head-dependent hydro chain We propose a novel mixed-integer nonlinear programming (MINLP) approach, considering hydroelectric power generation as a nonlinear function of water discharge and of the head. As a new contribution to eat her studies, we model the on-off behavior of the hydro plants using integer variables, in order to avoid water discharges at forbidden areas Thus, an enhanced STHS is provided due to the more realistic modeling presented in this paper Our approach has been applied successfully to solve a test case based on one of the Portuguese cascaded hydro systems with a negligible computational time requirement.
Resumo:
In this paper, a novel mixed-integer nonlinear approach is proposed to solve the short-term hydro scheduling problem in the day-ahead electricity market, considering not only head-dependency, but also start/stop of units, discontinuous operating regions and discharge ramping constraints. Results from a case study based on one of the main Portuguese cascaded hydro energy systems are presented, showing that the proposedmixed-integer nonlinear approach is proficient. Conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.
Resumo:
We study some properties of the monotone solutions of the boundary value problem (p(u'))' - cu' + f(u) = 0, u(-infinity) = 0, u(+infinity) = 1, where f is a continuous function, positive in (0, 1) and taking the value zero at 0 and 1, and P may be an increasing homeomorphism of (0, 1) or (0, +infinity) onto [0, +infinity). This problem arises when we look for travelling waves for the reaction diffusion equation partial derivative u/partial derivative t = partial derivative/partial derivative x [p(partial derivative u/partial derivative x)] + f(u) with the parameter c representing the wave speed. A possible model for the nonlinear diffusion is the relativistic curvature operator p(nu)= nu/root 1-nu(2). The same ideas apply when P is given by the one- dimensional p- Laplacian P(v) = |v|(p-2)v. In this case, an advection term is also considered. We show that, as for the classical Fisher- Kolmogorov- Petrovski- Piskounov equations, there is an interval of admissible speeds c and we give characterisations of the critical speed c. We also present some examples of exact solutions. (C) 2014 Elsevier Inc. All rights reserved.
Resumo:
Sticky information monetary models have been used in the macroeconomic literature to explain some of the observed features regarding inflation dynamics. In this paper, we explore the consequences of relaxing the rational expectations assumption usually taken in this type of model; in particular, by considering expectations formed through adaptive learning, it is possible to arrive to results other than the trivial convergence to a fixed point long-term equilibrium. The results involve the possibility of endogenous cyclical motion (periodic and a-periodic), which emerges essentially in scenarios of hyperinflation. In low inflation settings, the introduction of learning implies a less severe impact of monetary shocks that, nevertheless, tend to last for additional time periods relative to the pure perfect foresight setup.
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:
Existe uma miríade de ferramentas para a gestão da qualidade. A grande maioria apareceu no meio industrial, e algumas ultrapassaram barreiras, chegando a todas as áreas de negócio. O processo Seis Sigma é uma ferramenta que se destacou pela sua versatilidade e eficácia, e alcançou uma grande notoriedade na indústria fabril. O discente teve a oportunidade de contactar com o processo Seis Sigma, que evidenciou a sua validade, como ferramenta poderosa em qualquer área de negócio. Baseado nesse trabalho, pretende-se demonstrar a mais-valia que esta ferramenta apresenta, e que, com empenho e dedicação, todos podem usar. Os objectivos deste trabalho são: • Identificar o valor superior numa empresa do ramo automóvel na implementação de um processo Seis Sigma numa área de BackOffice; • Verificar se após o fim do projecto Seis Sigma, as medidas implementadas continuam a produzir efeitos. Metodologia usada para a execução deste trabalho • O discente, com a função de Green Belt, foi o responsável pela implementação de um projecto Seis Sigma. No seguimento do que já havia sido efectuado no projecto Seis Sigma, este trabalho usou a ferramenta DMAIC (ver p.5) como metodologia para a sua execução. Conclusões Ficou demonstrado com este projecto, em que o discente teve um profundo envolvimento, que a metodologia Seis Sigma ao ser aplicada num qualquer processo repetitivo de trabalho vai: • Obrigar a repensar todos os procedimentos instalados procurando todas as oportunidades demelhoria; • Criar novas ferramentas para dar solução às oportunidades encontradas; • Verificar a validade e mais-valia nas novas ferramentas e procedimentos; • Em função da constante verificação, melhorar as ferramentas e procedimentos instalados, ou criar novos procedimentos ou ferramentas; • De uma forma permanente, continuar a analisar o processo, monitorizando a qualidade e a procura de novas oportunidades de melhoria. O facto de o processo Seis Sigma obrigar a uma introspecção ao trabalho realizado, e, tornar todo o processo de melhoria sistemático, faz com que seja sempre uma mais-valia a sua aplicação, num ambiente fabril, ou de BackOffice. Ainda que o processo Seis Sigma seja terminado a dada altura, as melhorias que trouxe e as ferramentas que foram desenvolvidas para a sua execução ficam, deixando um legado de melhoria de processos, que, por si só, justificam a sua implementação.
Resumo:
In this paper, a mixed-integer nonlinear approach is proposed to support decision-making for a hydro power producer, considering a head-dependent hydro chain. The aim is to maximize the profit of the hydro power producer from selling energy into the electric market. As a new contribution to earlier studies, a risk aversion criterion is taken into account, as well as head-dependency. The volatility of the expected profit is limited through the conditional value-at-risk (CVaR). The proposed approach has been applied successfully to solve a case study based on one of the main Portuguese cascaded hydro systems.
Resumo:
This paper is on the problem of short-term hydro scheduling (STHS), particularly concerning head-dependent reservoirs under competitive environment. We propose a novel method, based on mixed-integer nonlinear programming (MINLP), for optimising power generation efficiency. This method considers hydroelectric power generation as a nonlinear function of water discharge and of the head. The main contribution of this paper is that discharge ramping constraints and start/stop of units are also considered, in order to obtain more realistic and feasible results. The proposed method has been applied successfully to solve two case studies based on Portuguese cascaded hydro systems, providing a higher profit at an acceptable computation time in comparison with classical optimisation methods based on mixed-integer linear programming (MILP).
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:
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 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.
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:
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.