118 resultados para solar system : general


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In the context of increasing demand for potable water and the depletion of water resources, stormwater is a logical alternative. However, stormwater contains pollutants, among which metals are of particular interest due to their toxicity and persistence in the environment. Hence, it is imperative to remove toxic metals in stormwater to the levels prescribed by drinking water guidelines for potable use. Consequently, various techniques have been proposed, among which sorption using low cost sorbents is economically viable and environmentally benign in comparison to other techniques. However, sorbents show affinity towards certain toxic metals, which results in poor removal of other toxic metals. It was hypothesised in this study that a mixture of sorbents that have different metal affinity patterns can be used for the efficient removal of a range of toxic metals commonly found in stormwater. The performance of six sorbents in the sorption of Al, Cr, Cu, Pb, Ni, Zn and Cd, which are the toxic metals commonly found in urban stormwater, was investigated to select suitable sorbents for creating the mixtures. For this purpose, a multi criteria analytical protocol was developed using the decision making methods: PROMETHEE (Preference Ranking Organisation METHod for Enrichment Evaluations) and GAIA (Graphical Analysis for Interactive Assistance). Zeolite and seaweed were selected for the creation of trial mixtures based on their metal affinity pattern and the performance on predetermined selection criteria. The metal sorption mechanisms employed by seaweed and zeolite were defined using kinetics, isotherm and thermodynamics parameters, which were determined using the batch sorption experiments. Additionally, the kinetics rate-limiting steps were identified using an innovative approach using GAIA and Spearman correlation techniques developed as part of the study, to overcome the limitation in conventional graphical methods in predicting the degree of contribution of each kinetics step in limiting the overall metal removal rate. The sorption kinetics of zeolite was found to be primarily limited by intraparticle diffusion followed by the sorption reaction steps, which were governed mainly by the hydrated ionic diameter of metals. The isotherm study indicated that the metal sorption mechanism of zeolite was primarily of a physical nature. The thermodynamics study confirmed that the energetically favourable nature of sorption increased in the order of Zn < Cu < Cd < Ni < Pb < Cr < Al, which is in agreement with metal sorption affinity of zeolite. Hence, sorption thermodynamics has an influence on the metal sorption affinity of zeolite. On the other hand, the primary kinetics rate-limiting step of seaweed was the sorption reaction process followed by intraparticle diffusion. The boundary layer diffusion was also found to limit the metal sorption kinetics at low concentration. According to the sorption isotherm study, Cd, Pb, Cr and Al were sorbed by seaweed via ion exchange, whilst sorption of Ni occurred via physisorption. Furthermore, ionic bonding is responsible for the sorption of Zn. The thermodynamics study confirmed that sorption by seaweed was energetically favourable in the order of Zn < Cu < Cd < Cr . Al < Pb < Ni. However, this did not agree with the affinity series derived for seaweed suggesting a limited influence of sorption thermodynamics on metal affinity for seaweed. The investigation of zeolite-seaweed mixtures indicated that mixing sorbents have an effect on the kinetics rates and the sorption affinity. Additionally, the theoretical relationships were derived to predict the boundary layer diffusion rate, intraparticle diffusion rate, the sorption reaction rate and the enthalpy of mixtures based on that of individual sorbents. In general, low coefficient of determination (R2) for the relationships between theoretical and experimental data indicated that the relationships were not statistically significant. This was attributed to the heterogeneity of the properties of sorbents. Nevertheless, in relative terms, the intraparticle diffusion rate, sorption reaction rate and enthalpy of sorption had higher R2 values than the boundary layer diffusion rate suggesting that there was some relationship between the former set of parameters of mixtures and that of sorbents. The mixture, which contained 80% of zeolite and 20% of seaweed, showed similar affinity for the sorption of Cu, Ni, Cd, Cr and Al, which was attributed to approximately similar sorption enthalpy of the metal ions. Therefore, it was concluded that the seaweed-zeolite mixture can be used to obtain the same affinity for various metals present in a multi metal system provided the metal ions have similar enthalpy during sorption by the mixture.

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This paper focuses on the implementation of a damping controller for the doubly fed induction generator (DFIG) system. Coordinated tuning of the damping controller to enhance the damping of the oscillatory modes is presented using bacterial foraging technique. The effect of the tuned damping controller on converter ratings of the DFIG system is also investigated. The results of both eigenvalue analysis and the time-domain simulation studies are presented to elucidate the effectiveness of the tuned damping controller in the DFIG system. The improvement of the fault ride-through capability of the system is also demonstrated.

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This paper presents a new approach to the design of a rough fuzzy controller for the control loop of the SVC (static VAR system) in a two area power system for stability enhancement with particular emphasis on providing effective damping for oscillatory instabilities. The performances of the rough fuzzy and the conventional fuzzy controller are compared with that of the conventional PI controller for a variety of transient disturbances, highlighting the effectiveness of the rough fuzzy controller in damping the inter-area oscillations. The effect of the rough fuzzy controller in improving the CCT (critical clearing time) of the two area system is elaborated in this paper as well.

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Australia is rich in renewable energy resources such as wind, solar and geothermal. Geographical diversity of these renewable resources combined with developing climate change policies poses a great challenge for the long term interconnection planning. Intermittency of wind and solar potentially driving the development of new transmission lines bring additional complexity to power system operations and planning. This paper provides an overview of generation and transmission planning studies in Australia to meet 20% renewable energy target by 2020. Appraisal of the effectiveness of dispersed energy storage, non schedulable peaking plants, wide area controls and demand management techniques to aid the penetration of renewables is presented in this paper

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The security of power transfer across a given transmission link is typically a steady state assessment. This paper develops tools to assess machine angle stability as affected by a combination of faults and uncertainty of wind power using probability analysis. The paper elaborates on the development of the theoretical assessment tool and demonstrates its efficacy using single machine infinite bus system.

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The available wind power is stochastic and requires appropriate tools in the OPF model for economic and reliable power system operation. This paper exhibit the OPF formulation with factors involved in the intermittency of wind power. Weibull distribution is adopted to find the stochastic wind speed and power distribution. The reserve requirement is evaluated based on the wind distribution and risk of under/over estimation of the wind power. In addition, the Wind Energy Conversion System (WECS) is represented by Doubly Fed Induction Generator (DFIG) based wind farms. The reactive power capability for DFIG based wind farm is also analyzed. The study is performed on IEEE-30 bus system with wind farm located at different buses and with different wind profiles. Also the reactive power capacity to be installed in the wind farm to maintain a satisfactory voltage profile under the various wind flow scenario is demonstrated.

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Over the past few years, the Midwest ISO has experienced a surge in requests to interconnect large amounts of wind generation, driven largely by a favorable political environment and an abundant wind resource in the Midwestern US. This tremendous influx of proposed generators along with a highly constrained transmission system adversely impacted interconnection queue processing, resulting in an unmanageable backlog. Under these circumstances, Midwest ISO successfully reformed the interconnection tariff to improve cycle times and provide increased certainty to interconnection customers. One of the key features of the reformed queue process is the System Planning and Analysis (SPA) phase which allows integration of the interconnection studies with regional transmission planning. This paper presents a brief background of the queue reform effort and then delves deeply in to the work performed at the Midwest ISO during the first SPA cycle - the study approach, the challenges faced in having to study over 50,000 MWs of wind generation and the effective solutions designed to complete these studies within tariff timelines.

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A baculovirus-insect cell expression system potentially provides the means to produce prophylactic HIV-1 virus-like particle (VLP) vaccines inexpensively and in large quantities. However, the system must be optimized to maximize yields and increase process efficiency. In this study, we optimized the production of two novel, chimeric HIV-1 VLP vaccine candidates (GagRT and GagTN) in insect cells. This was done by monitoring the effects of four specific factors on VLP expression: these were insect cell line, cell density, multiplicity of infection (MOI), and infection time. The use of western blots, Gag p24 ELISA, and four-factorial ANOVA allowed the determination of the most favorable conditions for chimeric VLP production, as well as which factors affected VLP expression most significantly. Both VLP vaccine candidates favored similar optimal conditions, demonstrating higher yields of VLPs when produced in the Trichoplusia ni Pro insect cell line, at a cell density of 1 × 106 cells/mL, and an infection time of 96 h post infection. It was found that cell density and infection time were major influencing factors, but that MOI did not affect VLP expression significantly. This work provides a potentially valuable guideline for HIV-1 protein vaccine optimization, as well as for general optimization of a baculovirus-based expression system to produce complex recombinant proteins. © 2009 American Institute of Chemical Engineers.

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The three-component reaction-diffusion system introduced in [C. P. Schenk et al., Phys. Rev. Lett., 78 (1997), pp. 3781–3784] has become a paradigm model in pattern formation. It exhibits a rich variety of dynamics of fronts, pulses, and spots. The front and pulse interactions range in type from weak, in which the localized structures interact only through their exponentially small tails, to strong interactions, in which they annihilate or collide and in which all components are far from equilibrium in the domains between the localized structures. Intermediate to these two extremes sits the semistrong interaction regime, in which the activator component of the front is near equilibrium in the intervals between adjacent fronts but both inhibitor components are far from equilibrium there, and hence their concentration profiles drive the front evolution. In this paper, we focus on dynamically evolving N-front solutions in the semistrong regime. The primary result is use of a renormalization group method to rigorously derive the system of N coupled ODEs that governs the positions of the fronts. The operators associated with the linearization about the N-front solutions have N small eigenvalues, and the N-front solutions may be decomposed into a component in the space spanned by the associated eigenfunctions and a component projected onto the complement of this space. This decomposition is carried out iteratively at a sequence of times. The former projections yield the ODEs for the front positions, while the latter projections are associated with remainders that we show stay small in a suitable norm during each iteration of the renormalization group method. Our results also help extend the application of the renormalization group method from the weak interaction regime for which it was initially developed to the semistrong interaction regime. The second set of results that we present is a detailed analysis of this system of ODEs, providing a classification of the possible front interactions in the cases of $N=1,2,3,4$, as well as how front solutions interact with the stationary pulse solutions studied earlier in [A. Doelman, P. van Heijster, and T. J. Kaper, J. Dynam. Differential Equations, 21 (2009), pp. 73–115; P. van Heijster, A. Doelman, and T. J. Kaper, Phys. D, 237 (2008), pp. 3335–3368]. Moreover, we present some results on the general case of N-front interactions.

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The behaviour of single installations of solar energy systems is well understood; however, what happens at an aggregated location, such as a distribution substation, when output of groups of installations cumulate is not so well understood. This paper considers groups of installations attached to distributions substations on which the load is primarily commercial and industrial. Agent-based modelling has been used to model the physical electrical distribution system and the behaviour of equipment outputs towards the consumer end of the network. The paper reports the approach used to simulate both the electricity consumption of groups of consumers and the output of solar systems subject to weather variability with the inclusion of cloud data from the Bureau of Meteorology (BOM). The data sets currently used are for Townsville, North Queensland. The initial characteristics that indicate whether solar installations are cost effective from an electricity distribution perspective are discussed.

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The IEEE Subcommittee on the Application of Probability Methods (APM) published the IEEE Reliability Test System (RTS) [1] in 1979. This system provides a consistent and generally acceptable set of data that can be used both in generation capacity and in composite system reliability evaluation [2,3]. The test system provides a basis for the comparison of results obtained by different people using different methods. Prior to its publication, there was no general agreement on either the system or the data that should be used to demonstrate or test various techniques developed to conduct reliability studies. Development of reliability assessment techniques and programs are very dependent on the intent behind the development as the experience of one power utility with their system may be quite different from that of another utility. The development and the utilization of a reliability program are, therefore, greatly influenced by the experience of a utlity and the intent of the system manager, planner and designer conducting the reliability studies. The IEEE-RTS has proved to be extremely valuable in highlighting and comparing the capabilities (or incapabilities) of programs used in reliability studies, the differences in the perception of various power utilities and the differences in the solution techniques. The IEEE-RTS contains a reasonably large power network which can be difficult to use for initial studies in an educational environment.

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This paper focuses on the super/sub-synchronous operation of the doubly fed induction generator (DFIG) system. The impact of a damping controller on the different modes of operation for the DFIG based wind generation system is investigated. The co-ordinated tuning of the damping controller to enhance the damping of the oscillatory modes using bacteria foraging (BF) technique is presented. The results from eigenvalue analysis are presented to elucidate the effectiveness of the tuned damping controller in the DFIG system. The robustness issue of the damping controller is also investigated

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This paper focuses on the implementation of the TS (Tagaki-Sugino) fuzzy controller for the active power and the DC capacitor voltage control of the Doubly Fed Induction Generator (DFIG) based wind generator. DFIG system is represented by a third-order model where electromagnetic transients of the stator are neglected. The effectiveness of the TS-fuzzy controller on the rotor speed oscillations and the DC capacitor voltage variations of the DFIG damping controller on converter ratings of the DFIG system is also investigated. The results of the time domain simulation studies are presented to elucidate the effectiveness of the TS-fuzzy controller compared with conventional PI controller in the DFIG system. The proposed TS-fuzzy controller can improve the fault ride through capability of DFIG compared to the conventional PI controller

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The knowledge economy of the 21st century requires skills such as creativity, critical thinking, problem solving, communication and collaboration (Partnership for 21st century skills, 2011) – skills that cannot easily be learnt from books, but rather through learning-by-doing and social interaction. Big ideas and disruptive innovation often result from collaboration between individuals from diverse backgrounds and areas of expertise. Public libraries, as facilitators of education and knowledge, have been actively seeking responses to such changing needs of the general public...

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Many state of the art vision-based Simultaneous Localisation And Mapping (SLAM) and place recognition systems compute the salience of visual features in their environment. As computing salience can be problematic in radically changing environments new low resolution feature-less systems have been introduced, such as SeqSLAM, all of which consider the whole image. In this paper, we implement a supervised classifier system (UCS) to learn the salience of image regions for place recognition by feature-less systems. SeqSLAM only slightly benefits from the results of training, on the challenging real world Eynsham dataset, as it already appears to filter less useful regions of a panoramic image. However, when recognition is limited to specific image regions performance improves by more than an order of magnitude by utilising the learnt image region saliency. We then investigate whether the region salience generated from the Eynsham dataset generalizes to another car-based dataset using a perspective camera. The results suggest the general applicability of an image region salience mask for optimizing route-based navigation applications.