1000 resultados para hurricane wind


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In this paper, simulation results showing the effect of lower and higher penetration of distributed wind generation on the voltage profile in distribution systems have been presented. The analysis is carried out over two distribution test systems. The detailed mathematical modeling of the system is also presented. It also investigates the small-signal stability of distribution systems using eigenvalue approach. The analyses show that voltage variation problems occur in different nodes of the distribution networks with an increase of penetration level. However, proper selection of dispersion level can improve the voltage profile of the distribution systems

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This paper proposes a decentralised controller design for doubly-fed induction generators (DFIGs) to enhance dynamic performance of distribution networks. The change in the output power due to the variable nature of wind is considered as an uncertain term in the design algorithm. In addition, the interconnection effect of the other subsystems are considered in the design process. The H norm of the uncertain system is found out and simultaneous output-feedback linear controllers are designed based controller is verified on a 16 bus distribution test system for severe disturbances. Simulation results indicate that the designed controller is robust against uncertainties in operating conditions

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The phenomenal growth in economy experienced in developed countries throughout the 20th century has largely been driven by the availability of conventional energy sources for electricity generation. However, increased concern about fossil fuels and adverse effect of carbon dioxide emission in to atmosphere changed the conventional power system to a viable one by integrating renewable energy sources into the existing system. Among the Renewable Energy (RE) sources, wind energy is one of the fastest growing technologies in reducing the Green House Gas (GHG) emissions in to the atmosphere due to its continuous availability throughout a period. Hence, this paper discusses the performance of a wind-grid connected system in a semi-arid region by conducting a case study. Wilson promontory, one of the best locations for wind generation in Victoria is considered as a case study. Hybrid Optimization Model for Electric Renewable (HOMER) is used as a simulating tool for this analysis. This study also presents the influences of storage system in the proposed Hybrid Power System (HPS) allowing energy to be stored during higher generations or lower load demands. In addition this paper also discusses the major integration issues to facilitate the large scale wind energy into the grid for reliable power generation and distribution.

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This paper proposes a hybrid computational framework based on Sequential Quadratic Programming (SQP) and Particle Swarm Optimization (PSO) to address the Combined Unit Commitment and Emission (CUCE) problem. By considering a model which includes both thermal generators and wind farms, the proposed hybrid computational framework can minimize the scheduling cost and greenhouse gases emission cost. The viability of the proposed hybrid technique is demonstrated using a set of numerical case studies. Moreover, comparisons are performed with other optimization algorithms. The simulation results show that our hybrid method is better in terms of the speed and accuracy. The main contribution of this paper is the development of a emission unit commitment model integrating with wind energy and combining the SQP and PSO methods to achieve faster and better performance optimization

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 Urban Heat Island (UHI) has become a growing concern to the quality of densely built urban environments, particularly in tropical cities. Wind speed has widely been reported to have decreased the intensity of heat island effect in urban areas. The cooling effect of the wind helps to mitigate the adverse effects of heat island on the micro climate and human thermal comfort. This paper investigates the existence of heat island in Muar, one of the fast growing cities in southern part of Malaysia and its possible causes, and then examines the effects of different urban geometry on the wind flow. The results of this study indicate that the chaotic development in Muar has caused reduced ventilation in urban canyons. The heat island intensity in the city center was recorded as 4. °C during the day and 3.2. °C during the night. Investigation of various urban geometry modifications showed that step up configuration was the most effective geometry as it can distribute the wind evenly allowing the wind to reach even the leeward side of each building. © 2014 Elsevier Ltd.

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A statistical optimized technique for rapid development of reliable prediction intervals (PIs) is presented in this study. The mean-variance estimation (MVE) technique is employed here for quantification of uncertainties related with wind power predictions. In this method, two separate neural network models are used for estimation of wind power generation and its variance. A novel PI-based training algorithm is also presented to enhance the performance of the MVE method and improve the quality of PIs. For an in-depth analysis, comprehensive experiments are conducted with seasonal datasets taken from three geographically dispersed wind farms in Australia. Five confidence levels of PIs are between 50% and 90%. Obtained results show while both traditional and optimized PIs are hypothetically valid, the optimized PIs are much more informative than the traditional MVE PIs. The informativeness of these PIs paves the way for their application in trouble-free operation and smooth integration of wind farms into energy systems. © 2014 Elsevier Ltd. All rights reserved.

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The forecasting behavior of the high volatile and unpredictable wind power energy has always been a challenging issue in the power engineering area. In this regard, this paper proposes a new multi-objective framework based on fuzzy idea to construct optimal prediction intervals (Pis) to forecast wind power generation more sufficiently. The proposed method makes it possible to satisfy both the PI coverage probability (PICP) and PI normalized average width (PINAW), simultaneously. In order to model the stochastic and nonlinear behavior of the wind power samples, the idea of lower upper bound estimation (LUBE) method is used here. Regarding the optimization tool, an improved version of particle swam optimization (PSO) is proposed. In order to see the feasibility and satisfying performance of the proposed method, the practical data of a wind farm in Australia is used as the case study.

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Water quality monitoring and prediction are critical for ensuring the sustainability of water resources which are essential for social security, especially for countries with limited land like Singapore. For example, the Singapore government identified water as a new growth sector and committed in 2006 to invest S$ 330 million over the following five years for water research and development [1]. To investigate the water quality evolution numerically, some key water quality parameters at several discrete locations in the reservoir (e.g., dissolved oxygen, chlorophyll, and temperature) and some environmental parameters (e.g., the wind distribution above water surface, air temperature and precipitation) are used as inputs to a three-dimensional hydrodynamics-ecological model, Estuary Lake and Coastal Ocean Model - Computational Aquatic Ecosystem Dynamics Model (ELCOM-CAEDYM) [2]. Based on the calculation in the model, we can obtain the distribution of water quality in the whole reservoir. We can also study the effect of different environmental parameters on the water quality evolution, and finally predict the water quality of the reservoir with a time step of 30 seconds. In this demo, we introduce our data collection system which enables water quality studies with real-time sensor data.

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Jared Diamond asked the acclaimed evolutionary biologist Ernst Mayr (1904-2005) why Aristotle didn’t come up with the theory of evolution. Mayr’s answer was ‘Frage stellen’ which Diamond translates as ‘a way of asking questions [sic]’ (Byrne 2013). The idea that a particular way-of-asking might generate a particular way-of-knowing and, indeed, a particular branch-of-knowledge, is utterly intriguing, especially when we frame the practice of creative writing in those terms: as a way of asking questions.Drusilla Modjeska unpacks the concept of ‘temporising’ in her article ‘Writing Poppy’ (Modjeska 2002: 75). This discussion invites us to consider the generative capabilities of the temporising space – as an imaginative space for writers, as an alternate way of asking questions … of seeing, being, knowing. In narrative, the questions that underpin the work do not necessarily appear in the surface-content of the text. In this way, the story is a metaphorical representation of the questions that lie beneath. As Aristotle suggests, metaphor relies on ‘an intuitive perception of the similarity [to homoion theorein] in dissimilars’ (Ricoeur 1977: 23). In narrative we contemplate a question, or an idea, within the context of a metaphorical other. This is a form of temporising: of ‘slip[ping] into other time frames’ as a means of ‘retreat[ing] and consider[ing]’ (Modjeska 2002: 75, 76). In narrative time, we consider one thing through an alternate temporal lens. We prevaricate in otherness.Fiction-making represents a very particular way of asking questions. With reference to the process of writing the short story – ‘Everything that matters is silvery white’ – it is clear that ‘making’ narrative is a way of asking questions that is assisted by the transformative temporising space.