940 resultados para Xanthomonas axonopodis pv. phaseoli


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Large penetration of rooftop PVs has resulted in unacceptable voltage profile in many residential distribution feeders. Limiting real power injection from PVs to alleviate over voltage problem is not feasible due to loss of green power and hence corresponding revenue loss. Reactive capability of the PV inverter can be a solution to address over voltage and voltage dip problems to some extent. This paper proposes an algorithm to utilize reactive capability of PV inverters and investigate their effectiveness for voltage improvement based on R/X ratio of the feeder. The length and loading level of the feeder for a particular R/X ratio to have acceptable voltage profile is also investigated. This can be useful for suburban design and residential distribution planning. Furthermore, coordination among different PVs using residential smart meters via a substation based controller is also proposed.

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Integration of rooftop PVs and increasing peak demand in the residential distribution networks has resulted in unacceptable voltage profile. Curtailing PV generation to alleviate overvoltage problem and making regular network investment to cater peak demand is not always feasible. Reactive capability of the PV inverter can be a solution to address voltage dip and over voltage problems to some extent. This paper proposes an algorithm to utilize reactive capability of PV inverters and investigate their effectiveness on feeder length and R/X ratio of the line. Feeder loading level for a particular R/X ratio to have acceptable voltage profile is also investigated. Furthermore, the need of appropriate feeder distances and R/X ratio for acceptable voltage profile, which can be useful for suburban design and distribution planning, is explored.

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Installation of domestic rooftop photovoltaic cells (PVs) is increasing due to feed–in tariff and motivation driven by environmental concerns. Even though the increase in the PV installation is gradual, their locations and ratings are often random. Therefore, such single–phase bi–directional power flow caused by the residential customers can have adverse effect on the voltage imbalance of a three–phase distribution network. In this chapter, a voltage imbalance sensitivity analysis and stochastic evaluation are carried out based on the ratings and locations of single–phase grid–connected rooftop PVs in a residential low voltage distribution network. The stochastic evaluation, based on Monte Carlo method, predicts a failure index of non–standard voltage imbalance in the network in presence of PVs. Later, the application of series and parallel custom power devices are investigated to improve voltage imbalance problem in these feeders. In this regard, first, the effectiveness of these two custom power devices is demonstrated vis–à–vis the voltage imbalance reduction in feeders containing rooftop PVs. Their effectiveness is investigated from the installation location and rating points of view. Later, a Monte Carlo based stochastic analysis is utilized to investigate their efficacy for different uncertainties of load and PV rating and location in the network. This is followed by demonstrating the dynamic feasibility and stability issues of applying these devices in the network.

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Voltage rise is the main issue which limits the capacity of Low Voltage (LV) network to accommodate more Renewable Energy (RE) sources. In addition, voltage drop at peak load period is a significant power quality concern. This paper proposes a new robust voltage support strategy based on distributed coordination of multiple distribution static synchronous compensators (DSTATCOMs). The study focuses on LV networks with PV as the RE source for customers. The proposed approach applied to a typical LV network and its advantages are shown comparing with other voltage control strategies.

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The rat nucleus accumbens contains medium-sized, spiny projection neurons and intrinsic, local circuit neurons, or interneurons. Sub-classes of interneurons, revealed by calretinin (CR) or parvalbumin (PV) immunoreactivity or reduced nicotinamide adenine dinucleotide phosphate (NADPH)-diaphorase histochemistry, were compared in the nucleus accumbens core, shell and rostral pole. CR, PV and NADPH-diaphorase-containing neurons are shown to form three non-co-localising populations in these three areas. No significant differences in neuronal population densities were found between the subterritories. NADPH-diaphorase-containing neurons could be further separated morphologically into three sub-groups, but CR- and PV-immunoreactive neurons form homogeneous populations. Ultrastructurally, NADPH-diaphorase-, CR- and PV-containing neurons in the nucleus accumbens all possess nuclear indentations. These are deeper and fewer in neurons immunoreactive for PV than in CR- and NADPH-diaphorase-containing neurons. CR-immunoreactive boutons form asymmetrical and symmetrical synaptic specialisations on spines, dendrites and somata, while PV-immunoreactive boutons make only symmetrical synaptic specialisations. Both CR- and PV-immunoreactive boutons form symmetrical synaptic specialisations with medium-sized spiny neurons and contact other CR- and PV-immunoreactive somata, respectively. A novel non-carcinogenic substrate for the peroxidase reaction (Vector Slate Grey, SG) was found to be characteristically electron-dense and may be distinguishable from the diaminobenzidine reaction product. We conclude that the three markers used in this study are localised in distinct populations of nucleus accumbens interneurons. Our studies of their synaptic connections contribute to an increased understanding of the intrinsic circuitry of this area.

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The basic principles and equations are developed for elementary finance, based on the concept of compound interest. The five quantities of interest in such problems are present value, future value, amount of periodic payment, number of periods and the rate of interest per period. We consider three distinct means of computing each of these five quantities in Excel 2007: (i) use of algebraic equations, (ii) by recursive schedule and the Goal Seek facility, and (iii) use of Excel's intrinsic financial functions. The paper is intended to be used as the basis for a lesson plan and contains many examples and solved problems. Comment is made regarding the relative difficulty of each approach, and a prominent theme is the systematic use of more than one method to increase student understanding and build confidence in the answer obtained. Full instructions to build each type of model are given and a complete set of examples and solutions may be downloaded (Examples.xlsx and Solutions.xlsx).

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There has been a recent rapid expansion of the range of applications of low-temperature plasma processing in Si-based photovoltaic (PV) technologies. The desire to produce Si-based PV materials at an acceptable cost with consistent performance and reproducibility has stimulated a large number of major research and research infrastructure programs, and a rapidly increasing number of publications in the field of low-temperature plasma processing for Si photovoltaics. In this article, we introduce the low-temperature plasma sources for Si photovoltaic applications and discuss the effects of low-temperature plasma dissociation and deposition on the synthesis of Si-based thin films. We also examine the relevant growth mechanisms and plasma diagnostics, Si thin-film solar cells, Si heterojunction solar cells and silicon nitride materials for antireflection and surface passivation. Special attention is paid to the low-temperature plasma interactions with Si materials including hydrogen interaction, wafer cleaning, masked or mask-free surface texturization, the direct formation of p-n junction, and removal of phosphorus silicate glass or parasitic emitters. The chemical and physical interactions in such plasmas with Si surfaces are analyzed. Several examples of the plasma processes and techniques are selected to represent a variety of applications aimed at the improvement of Si-based solar cell performance. © 2014 Elsevier B.V.

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A typical low power IPT system employs an H-Bridge converter with a simple control strategy to generate a high frequency current from DC power supply. This paper proposes a cascaded multilevel converter for bidirectional IPT (BIPT) systems, which is suitable for low to medium power applications as well as for situations such as PV cells where several individual DC sources are to be utilized. A novel modulation strategy is proposed for the multilevel converter with the aim of minimizing switching losses. Series - Series (SS) compensation circuit is adopted for the IPT system and a mathematical model is presented to minimize the coil losses of the system under varying output power. Theoretical results presented in comparison to the simulations to demonstrate the applicability of the proposed concept and the validity of the developed model. The experimental results show the feasibility of the proposed phase shift modulation.

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This paper explores a new breed of energy storage system interfacing for grid connected photovoltaic (PV) systems. The proposed system uses the popular dual inverter topology in which one inverter is supplied by a PV cell array and the other by a Battery Energy Storage System (BESS). The resulting conversion structure is controlled in a way that both demand matching and maximum power point tracking of the PV cell array are performed simultaneously. This dual inverter topology can produces 2, 3, 4 and 5 level inverter voltage waveforms at the dc-link voltage ratios of 0:1, 1:1, 2:1 and 3:2 respectively. Since the output voltage of the PV cell array and the battery are uncorrelated and dynamically change, the resulting dc-link voltage ratio can take non-integer values as well. These noninteger dc-link voltage ratios produce unevenly distributed space vectors. Therefore, the main issue with the proposed system is the generation of undistorted current even in the presence of unevenly distributed and dynamically changing space vectors. A modified space vector modulation method is proposed in this paper to address this issue and its efficacy is proved by simulation results. The ability of the proposed system to act as an active power source is also verified.

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Large number of rooftop Photovoltaics (PVs) have turned traditional passive networks into active networks with intermittent and bidirectional power flow. A community based distribution network grid reinforcement process is proposed to address technical challenges associated with large integration of rooftop PVs. Probabilistic estimation of intermittent PV generation is considered. Depending on the network parameters such as the R/X ratio of distribution feeder, either reactive control from PVs or coordinated control of PVs and Battery Energy Storage (BES) has been proposed. Determination of BES capacity is one of the significant outcomes from the proposed method and several factors such as variation in PV installed capacity as well as participation from community members are analyzed. The proposed approach is convenient for the community members providing them flexibility of managing their integrated PV and BES systems

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This paper critically examines research on consumer attitudes and behavior towards solar photovoltaic (PV) and renewable energy technology in Australia. The uptake of renewable energy technology by residential consumers in Australia in the past decade has transformed the electricity supply and demand paradigm. Thus, this paper reviews Australian research on consumer behavior, understanding and choices in order to identify gaps in knowledge. As the role of the consumer transforms there is a critical need to understand the ways consumers may respond to future energy policies to mitigate unforeseen negative social and economic consequence of programs designed to achieve positive environmental outcomes.

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This project has extended the knowledge in the hydrothermal synthesis of copper zinc tin sulphide (CZTS) semiconductor material which is regarded as one of the most promising light absorbing material for PV technologies. The investigation of various reaction parameters on the controlled synthesis of CZTS compound has provided important insight into the formation mechanism as well as the crystal growth behaviour of the material. CZTS nanocrystals with different crystal structure and particle size were synthesised throughout this project. The growth mechanism of CZTS crystals through a high temperature annealing treatment was also explored.

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Rapid development of plug-in hybrid electric vehicles (PHEVs) brings new challenges and opportunities to the power industry. A large number of idle PHEVs can potentially be employed to form a distributed energy storage system for supporting renewable generation. To reduce the negative effects of unsteady renewable generation outputs, a stochastic optimization-based dispatch model capable of handling uncertain outputs of PHEVs and renewable generation is formulated in this paper. The mathematical expectations, second-order original moments, and variances of wind and photovoltaic (PV) generation outputs are derived analytically. Incorporated all the derived uncertainties, a novel generation shifting objective is proposed. The cross-entropy (CE) method is employed to solve this optimal dispatch model. Multiple patterns of renewable generation depending on seasons and renewable market shares are investigated. The feasibility and efficiency of the developed optimal dispatch model, as well as the CE method, are demonstrated with a 33-node distribution system.

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This paper reviews the use of multi-agent systems to model the impacts of high levels of photovoltaic (PV) system penetration in distribution networks and presents some preliminary data obtained from the Perth Solar City high penetration PV trial. The Perth Solar City trial consists of a low voltage distribution feeder supplying 75 customers where 29 consumers have roof top photovoltaic systems. Data is collected from smart meters at each consumer premises, from data loggers at the transformer low voltage (LV) side and from a nearby distribution network SCADA measurement point on the high voltage side (HV) side of the transformer. The data will be used to progressively develop MAS models.

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This paper presents an efficient algorithm for optimizing the operation of battery storage in a low voltage distribution network with a high penetration of PV generation. A predictive control solution is presented that uses wavelet neural networks to predict the load and PV generation at hourly intervals for twelve hours into the future. The load and generation forecast, and the previous twelve hours of load and generation history, is used to assemble load profile. A diurnal charging profile can be compactly represented by a vector of Fourier coefficients allowing a direct search optimization algorithm to be applied. The optimal profile is updated hourly allowing the state of charge profile to respond to changing forecasts in load.