943 resultados para overlapped peak


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Microcontroller-based peak current mode control of a buck converter is investigated. The new solution uses a discrete time controller with digital slope compensation. This is implemented using only a single-chip microcontroller to achieve desirable cycle-by-cycle peak current limiting. The digital controller is implemented as a two-pole, two-zero linear difference equation designed using a continuous time model of the buck converter and a discrete time transform. Subharmonic oscillations are removed with digital slope compensation using a discrete staircase ramp. A 16 W hardware implementation directly compares analog and digital control. Frequency response measurements are taken and it is shown that the crossover frequency and expected phase margin of the digital control system match that of its analog counterpart.

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Energy storage is a potential alternative to conventional network reinforcementof the low voltage (LV) distribution network to ensure the grid’s infrastructure remainswithin its operating constraints. This paper presents a study on the control of such storagedevices, owned by distribution network operators. A deterministic model predictive control (MPC) controller and a stochastic receding horizon controller (SRHC) are presented, wherethe objective is to achieve the greatest peak reduction in demand, for a given storagedevice specification, taking into account the high level of uncertainty in the prediction of LV demand. The algorithms presented in this paper are compared to a standard set-pointcontroller and bench marked against a control algorithm with a perfect forecast. A specificcase study, using storage on the LV network, is presented, and the results of each algorithmare compared. A comprehensive analysis is then carried out simulating a large number of LV networks of varying numbers of households. The results show that the performance of each algorithm is dependent on the number of aggregated households. However, on a typical aggregation, the novel SRHC algorithm presented in this paper is shown to outperform each of the comparable storage control techniques.

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The Distribution Network Operators (DNOs) role is becoming more difficult as electric vehicles and electric heating penetrate the network, increasing the demand. As a result it becomes harder for the distribution networks infrastructure to remain within its operating constraints. Energy storage is a potential alternative to conventional network reinforcement such as upgrading cables and transformers. The research presented here in this paper shows that due to the volatile nature of the LV network, the control approach used for energy storage has a significant impact on performance. This paper presents and compares control methodologies for energy storage where the objective is to get the greatest possible peak demand reduction across the day from a pre-specified storage device. The results presented show the benefits and detriments of specific types of control on a storage device connected to a single phase of an LV network, using aggregated demand profiles based on real smart meter data from individual homes. The research demonstrates an important relationship between how predictable an aggregation is and the best control methodology required to achieve the objective.

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Reinforcing the Low Voltage (LV) distribution network will become essential to ensure it remains within its operating constraints as demand on the network increases. The deployment of energy storage in the distribution network provides an alternative to conventional reinforcement. This paper presents a control methodology for energy storage to reduce peak demand in a distribution network based on day-ahead demand forecasts and historical demand data. The control methodology pre-processes the forecast data prior to a planning phase to build in resilience to the inevitable errors between the forecasted and actual demand. The algorithm uses no real time adjustment so has an economical advantage over traditional storage control algorithms. Results show that peak demand on a single phase of a feeder can be reduced even when there are differences between the forecasted and the actual demand. In particular, results are presented that demonstrate when the algorithm is applied to a large number of single phase demand aggregations that it is possible to identify which of these aggregations are the most suitable candidates for the control methodology.

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Peak residential electricity demand takes place when people conduct simultaneous activities at specific times of the day. Social practices generate patterns of demand and can help understand why, where, with whom and when energy services are used at peak time. The aim of this work is to make use of recent UK time use and locational data to better understand: (i) how a set of component indices on synchronisation, variation, sharing and mobility indicate flexibility to shift demand; and (ii) the links between people’s activities and peaks in greenhouse gases’ intensities. The analysis is based on a recent UK time use dataset, providing 1 minute interval data from GPS devices and 10 minute data from diaries and questionnaires for 175 data days comprising 153 respondents. Findings show how greenhouse gases’ intensities and flexibility to shift activities vary throughout the day. Morning peaks are characterised by high levels of synchronisation, shared activities and occupancy, with low variation of activities. Evening peaks feature low synchronisation, and high spatial mobility variation of activities. From a network operator perspective, the results indicate that periods with lower flexibility may be prone to more significant local network loads due to the synchronization of electricity-demanding activities.

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Wind generation's contribution to supporting peak electricity demand is one of the key questions in wind integration studies. Differently from conventional units, the available outputs of different wind farms cannot be approximated as being statistically independent, and hence near-zero wind output is possible across an entire power system. This paper will review the risk model structures currently used to assess wind's capacity value, along with discussion of the resulting data requirements. A central theme is the benefits from performing statistical estimation of the joint distribution for demand and available wind capacity, focusing attention on uncertainties due to limited histories of wind and demand data; examination of Great Britain data from the last 25 years shows that the data requirements are greater than generally thought. A discussion is therefore presented into how analysis of the types of weather system which have historically driven extreme electricity demands can help to deliver robust insights into wind's contribution to supporting demand, even in the face of such data limitations. The role of the form of the probability distribution for available conventional capacity in driving wind capacity credit results is also discussed.

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The predictability of high impact weather events on multiple time scales is a crucial issue both in scientific and socio-economic terms. In this study, a statistical-dynamical downscaling (SDD) approach is applied to an ensemble of decadal hindcasts obtained with the Max-Planck-Institute Earth System Model (MPI-ESM) to estimate the decadal predictability of peak wind speeds (as a proxy for gusts) over Europe. Yearly initialized decadal ensemble simulations with ten members are investigated for the period 1979–2005. The SDD approach is trained with COSMO-CLM regional climate model simulations and ERA-Interim reanalysis data and applied to the MPI-ESM hindcasts. The simulations for the period 1990–1993, which was characterized by several windstorm clusters, are analyzed in detail. The anomalies of the 95 % peak wind quantile of the MPI-ESM hindcasts are in line with the positive anomalies in reanalysis data for this period. To evaluate both the skill of the decadal predictability system and the added value of the downscaling approach, quantile verification skill scores are calculated for both the MPI-ESM large-scale wind speeds and the SDD simulated regional peak winds. Skill scores are predominantly positive for the decadal predictability system, with the highest values for short lead times and for (peak) wind speeds equal or above the 75 % quantile. This provides evidence that the analyzed hindcasts and the downscaling technique are suitable for estimating wind and peak wind speeds over Central Europe on decadal time scales. The skill scores for SDD simulated peak winds are slightly lower than those for large-scale wind speeds. This behavior can be largely attributed to the fact that peak winds are a proxy for gusts, and thus have a higher variability than wind speeds. The introduced cost-efficient downscaling technique has the advantage of estimating not only wind speeds but also estimates peak winds (a proxy for gusts) and can be easily applied to large ensemble datasets like operational decadal prediction systems.

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Purpose: Peak expiratory flow (PEF) was measured in healthy children aged five to ten years in order to provide baseline values and to determine correlations between PEF and factors such as gender, age and type of school. Methods: After the Ethical Committee of Research in Human of the School of Medicine of ABC - FMABC approval, PEF and height were measured in 1942 children between five and ten years old from nine public schools and nine private schools throughout Sao Bernardo do Campo City. PEF was measured using the Mini-Wright Peak Flow Meter (Clement Clarke International Ltd.) and. height was measured using a Sanny professional stadiometer. Results: Significant differences were found in values for PEF: higher values were seen in older students in comparison with younger students, in males in comparison with females and in students from private schools in comparison with public schools, with average values ranging from 206 L/min to 248 L/min,. Linear correlations were seen for PEF values with both height and age (Spearman Coefficient). Conclusions: Differences were seen for PEF between genders and between types of school, and a linear correlation was seen for PEF with both age and height in healthy children from five to ten years old.

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This paper reports a direct observation of an interesting split of the (022)(022) four-beam secondary peak into two (022) and (022) three-beam peaks, in a synchrotron radiation Renninger scan (phi-scan), as an evidence of the layer tetragonal distortion in two InGaP/GaAs (001) epitaxial structures with different thicknesses. The thickness, composition, (a perpendicular to) perpendicular lattice parameter, and (01) in-plane lattice parameter of the two epitaxial ternary layers were obtained from rocking curves (omega-scan) as well as from the simulation of the (022)(022) split, and then, it allowed for the determination of the perpendicular and parallel (in-plane) strains. Furthermore, (022)(022) omega:phi mappings were measured in order to exhibit the multiple diffraction condition of this four-beam case with their split measurement.

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The thermoluminescence (TL) peak in natural sodalite near 230 degrees C which appears only after submitted to thermal treatments and to gamma irradiation has been studied in parallel with electron paramagnetic resonance (EPR) spectrum appearing under the same procedure This study revealed a full correlation between the 230 degrees C TL peak and the eleven hyperfine lines from EPR spectrum In both case the centers disappear at the same temperature and are restored after gamma irradiation A complete model for the 230 C TL peak is presented and discussed In addition to the correlation and TL model specific characteristics of the TL peaks are described (C) 2010 Elsevier B V All rights reserved

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Samples of natural andalusite (Al(2)SiO(5)) crystal have been investigated in terms of thermoluminescence (TL) and electron paramagnetic resonance (EPR) measurements. The TL glow curves of samples previously annealed at 600 degrees C for 30 min and subsequently gamma-irradiated gave rise to four glow peaks at 150, 210, 280 and 350 degrees C. The EPR spectra of natural samples heat-treated at 600 degrees C for 30 min show signals at g = 5.94 and 2.014 that do not change after gamma irradiation and thermal treatments. However, it was observed that the appearance of a paramagnetic center at g=1.882 for the samples annealed at 600 degrees C for 30 min followed gamma irradiation. This line was attributed to Ti(3+) centers. The EPR signals observed at g=5.94 and 2.014 are due to Fe(3+). Correlations between EPR and TL results of these crystals show that the EPR line at g=1.882 and the TL peak at 280 degrees C can be attributed to the same defect center. (C) 2011 Elsevier B.V. All rights reserved.

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110 degrees C thermoluminescence (TL) peak in quartz is well known due to its pre-dose effect, which is used in dating technique. The generally accepted mechanism for the production of this peak is based on Ge impurity contained in quartz. Its role is to substitute for Si in SiO(4) tetrahedron and under irradiation gives rise to [GeO(4)/e(-)](-) electron centre. Heating for TL read out liberates electron that recombines with hole in [AlO(4)/h]degrees or [H(3)O(4)/h]degrees centres emitting photon. The investigation, carried out on blue quartz, green quartz, black quartz, pink quartz, red quartz, sulphurous quartz, milky quartz, alpha quartz and synthetic quartz, has shown that the 110 degrees C TL peak in all these varieties of quartz has no correlation with the respective Ge content. Electron paramagnetic resonance (EPR) measurements on any of these varieties of quartz revealed a signal with g(1) = 2.0004, g(2) = 1.9986 and g(3) = 1.974 and this signal does not appear to correspond to any known EPR signals in alpha quartz. Furthermore, isothermal decay measurements are carried out on the above mentioned EPR signal and 110 degrees C TL peak in alpha, blue and green quartz. A close correlation has been observed in the decay behavior. A new mechanism is proposed based on an interstitial O(-) centre. (C) 2009 Elsevier Ltd. All rights reserved.

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This study evaluated the spirometry and respiratory static pressures in 17 young women, twice a week for three successive ovulatory menstrual cycles to determine if such variables changed across the menstrual, follicular, periovulatory, early-tomid luteal and late luteal phases. The factors phases of menstrual cycle and individual cycles had no significant effect on the spirometry variables except for peak expiratory flow (PEF) and respiratory static pressures. Significant weak positive correlations were found between the progesterone:estradiol ratio and PEF and between estrogen and tidal volume (r = 0.37), inspiratory time (r = 0.22), expiratory time (r = 0.19), maximal inspiratory pressure (r = 0.25) and maximal expiratory pressure (r = 0.20) and for progesterone and maximal inspiratory pressure (r = 0.32) during the early-to-mid luteal phase. Although most parameters of the spirometry results did not change during the menstrual cycle, the correlations observed between sexual hormones and respiratory control variables suggest a positive influence of sexual female hormones controlling the thoracic pump muscles in the luteal phase