30 resultados para 660304 Energy systems analysis
Resumo:
Studies have shown that large geographical spreading can reduce the wind power variability and smooth production. It is frequently assumed that storage and interconnection can manage wind power variability and are totally flexible. However, constraints do exist. In the future more and more electricity will be provided by renewable energy sources and more electricity interconnectors will be built between European Union (EU) countries, as outlines in many of the Projects of Common Interests. It is essential to understand the correlation of wind generation throughout Europe considering power system constraints. In this study the spatial and temporal correlation of wind power production across several countries is examined in order to understand how “the wind ‘travels’ across Europe”. Three years of historical hourly wind power generation from ten EU countries is analysed to investigate the geographic diversity and time scales influence on correlation of wind power variations. Results are then compared with two other studies and show similar general characteristics of correlation between EU country pairs to identify opportunities for storage optimisation, power system operations, and trading.
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We have operated 25-100 mu m diameter radio frequency microhollow cathode discharges stably, for many hours, in neon and in argon. Electrical and spectroscopic measurements were used to explore three possible electron heating modes and obtain detail regarding the electron energy distribution. Analysis points to the possibility of pendular electron heating at low voltages.
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The phosphonopyruvate hydrolase (PalA) found in Variovorax sp., Pal2, is a novel carbon-phosphorus bond cleavage enzyme, which is expressed even in the presence of high levels of phosphate, thus permitting phosphonopyruvate to be used as the sole carbon and energy source. Analysis of the regions adjacent to the palA gene revealed the presence of the five structural genes that constitute the 2-amino-3-phosphonopropionic acid (phosphonoalanine)-degradative operon. Reverse transcriptase-PCR (RT-PCR) experiments demonstrated that all five genes in the operon are transcribed as a single mRNA and that their transcription is induced by phosphonoalanine or phosphonopyruvate. Transcriptional fusions of the regulatory region of the phosphonoalanine degradative operon with the gfp gene were constructed. Expression analysis indicated that the presence of a LysR-type regulator (encoded by the palR gene) is essential for the transcription of the structural genes of the operon. Similar gene clusters were found in the sequenced genomes of six bacterial species from the Alpha-, Beta- and Gammaproteobacteria, and analysis of metagenomic libraries revealed that sequences related to palA are widely spread in the marine environment.
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This paper presents a new method for calculating the individual generators' shares in line flows, line losses and loads. The method is described and illustrated on active power flows, but it can be applied in the same way to reactive power flows.
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Artificial neural networks (ANNs) can be easily applied to short-term load forecasting (STLF) models for electric power distribution applications. However, they are not typically used in medium and long term load forecasting (MLTLF) electric power models because of the difficulties associated with collecting and processing the necessary data. Virtual instrument (VI) techniques can be applied to electric power load forecasting but this is rarely reported in the literature. In this paper, we investigate the modelling and design of a VI for short, medium and long term load forecasting using ANNs. Three ANN models were built for STLF of electric power. These networks were trained using historical load data and also considering weather data which is known to have a significant affect of the use of electric power (such as wind speed, precipitation, atmospheric pressure, temperature and humidity). In order to do this a V-shape temperature processing model is proposed. With regards MLTLF, a model was developed using radial basis function neural networks (RBFNN). Results indicate that the forecasting model based on the RBFNN has a high accuracy and stability. Finally, a virtual load forecaster which integrates the VI and the RBFNN is presented.
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In this paper we discuss the dualism of gene networks and their role in systems biology. We argue that gene networks ( 1) can serve as a conceptual framework, forming a fundamental level of a phenomenological description, and ( 2) are a means to represent and analyze data. The latter point does not only allow a systems analysis but is even amenable for a direct approach to study biological function. Here we focus on the clarity of our main arguments and conceptual meaning of gene networks, rather than the causal inference of gene networks from data. (C) 2010 John Wiley & Sons, Inc. WIREs Syst Biol Med 2011 3 379-391 DOI: 10.1002/wsbm.134
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This review will summarize the significant body of research within the field of electrical methods of controlling the growth of microorganisms. We examine the progress from early work using current to kill bacteria in static fluids to more realistic treatment scenarios such as flow-through systems designed to imitate the human urinary tract. Additionally, the electrical enhancement of biocide and antibiotic efficacy will be examined alongside recent innovations including the biological applications of acoustic energy systems to prevent bacterial surface adherence. Particular attention will be paid to the electrical engineering aspects of previous work, such as electrode composition, quantitative electrical parameters and the conductive medium used. Scrutiny of published systems from an electrical engineering perspective will help to facilitate improved understanding of the methods, devices and mechanisms that have been effective in controlling bacteria, as well as providing insights and strategies to improve the performance of such systems and develop the next generation of antimicrobial bioelectric materials.
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Reactive power has become a vital resource in modern electricity networks due to increased penetration of distributed generation. This paper examines the extended reactive power capability of DFIGs to improve network stability and capability to manage network voltage profile during transient faults and dynamic operating conditions. A coordinated reactive power controller is designed by considering the reactive power capabilities of the rotor-side converter (RSC) and the grid-side converter (GSC) of the DFIG in order to maximise the reactive power support from DFIGs. The study has illustrated that, a significant reactive power contribution can be obtained from partially loaded DFIG wind farms for stability enhancement by using the proposed capability curve based reactive power controller; hence DFIG wind farms can function as vital dynamic reactive power resources for power utilities without commissioning additional dynamic reactive power devices. Several network adaptive droop control schemes are also proposed for network voltage management and their performance has been investigated during variable wind conditions. Furthermore, the influence of reactive power capability on network adaptive droop control strategies has been investigated and it has also been shown that enhanced reactive power capability of DFIGs can substantially improve the voltage control performance.
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We investigate the basic behavior and performance of simulated quantum annealing (QA) in comparison with classical annealing (CA). Three simple one-dimensional case study systems are considered: namely, a parabolic well, a double well, and a curved washboard. The time-dependent Schrodinger evolution in either real or imaginary time describing QA is contrasted with the Fokker-Planck evolution of CA. The asymptotic decrease of excess energy with annealing time is studied in each case, and the reasons for differences are examined and discussed. The Huse-Fisher classical power law of double-well CA is replaced with a different power law in QA. The multiwell washboard problem studied in CA by Shinomoto and Kabashima and leading classically to a logarithmic annealing even in the absence of disorder turns to a power-law behavior when annealed with QA. The crucial role of disorder and localization is briefly discussed.
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Background: The importance of actively working with other professionals, as part of a single team, is well embedded in discussions relating to effective healthcare. The need for effective teamwork specifically in relation to patient safety is also widely acknowledged; however healthcare has traditionally been poor at building teams and professional groups tend to function semi-autonomously and autocratically.1
Objective: This study aims to gain the views and experiences of students from nursing, pharmacy and medicine involved in an interprofessional workshop in medication safety.
Setting and methods: Interprofessional workshops involving students from nursing, pharmacy and medicine were delivered using case studies involving medication incidents. Focus groups were used to investigate participant’s views and experiences of the workshop.
Results: Focus groups were completed with 22 students. Five main themes were identified from the focus group data relating to medication safety; these were increasing confidence, insight into roles, improving skills, culture of responsibility and application to future practice.
Conclusions: This study represents a model for delivery of training that has demonstrated improvement in the students’ attitudes towards team working and is a first step towards introducing team working into the medication safety program. The programme continues to run using live and virtual workshops.
1. Leape LL. A systems analysis approach to medical error. J Clin Eval Clin Pract. 1997. 3, 3, 213-222.
Resumo:
A new method is presented for transmission loss allocation based on the separation of transmission loss caused by load and the loss due to circulating currents between generators. The theoretical basis for and derivation of the loss formulae are presented using simple systems. The concept is then extended to a general power system using the Ybus model. Details of the application of the proposed method to a typical power system are presented along with results from the IEEE 30 bus test system. The results from both the small system and the standard IEEE test system demonstrate the validity of the proposed method.
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Economic dispatch (ED) problems often exhibit non-linear, non-convex characteristics due to the valve point effects. Further, various constraints and factors, such as prohibited operation zones, ramp rate limits and security constraints imposed by the generating units, and power loss in transmission make it even more challenging to obtain the global optimum using conventional mathematical methods. Meta-heuristic approaches are capable of solving non-linear, non-continuous and non-convex problems effectively as they impose no requirements on the optimization problems. However, most methods reported so far mainly focus on a specific type of ED problems, such as static or dynamic ED problems. This paper proposes a hybrid harmony search with arithmetic crossover operation, namely ACHS, for solving five different types of ED problems, including static ED with valve point effects, ED with prohibited operating zones, ED considering multiple fuel cells, combined heat and power ED, and dynamic ED. In this proposed ACHS, the global best information and arithmetic crossover are used to update the newly generated solution and speed up the convergence, which contributes to the algorithm exploitation capability. To balance the exploitation and exploration capabilities, the opposition based learning (OBL) strategy is employed to enhance the diversity of solutions. Further, four commonly used crossover operators are also investigated, and the arithmetic crossover shows its efficiency than the others when they are incorporated into HS. To make a comprehensive study on its scalability, ACHS is first tested on a group of benchmark functions with a 100 dimensions and compared with several state-of-the-art methods. Then it is used to solve seven different ED cases and compared with the results reported in literatures. All the results confirm the superiority of the ACHS for different optimization problems.