Long term individual load forecast under different electrical vehicles uptake scenarios

More and more households are purchasing electric vehicles (EVs), and this will continue as we move towards a low carbon future. There are various projections as to the rate of EV uptake, but all predict an increase over the next ten years. Charging these EVs will produce one of the biggest loads on the low voltage network. To manage the network, we must not only take into account the number of EVs taken up, but where on the network they are charging, and at what time. To simulate the impact on the network from high, medium and low EV uptake (as outlined by the UK government), we present an agent-based model. We initialise the model to assign an EV to a household based on either random distribution or social influences - that is, a neighbour of an EV owner is more likely to also purchase an EV. Additionally, we examine the effect of peak behaviour on the network when charging is at day-time, night-time, or a mix of both. The model is implemented on a neighbourhood in south-east England using smart meter data (half hourly electricity readings) and real life charging patterns from an EV trial. Our results indicate that social influence can increase the peak demand on a local level (street or feeder), meaning that medium EV uptake can create higher peak demand than currently expected.

DC traction load flow including AC distribution network

In the first part some information and characterisation about an AC distribution network that feeds traction substations and their possible influences on the DC traction load flow are presented. Those influences are investigated and mathematically modelled. To corroborate the mathematical model, an example is presented and their results are confronted with real measurements.

Variety matters: adaptive genetic diversity and parasite load in two mouse opossums from the Brazilian Atlantic forest

The adaptive potential of a species to a changing environment and in disease defence is primarily based on genetic variation. Immune genes, such as genes of the major histocompatibility complex (MHC), may thereby be of particular importance. In marsupials, however, there is very little knowledge about natural levels and functional importance of MHC polymorphism, despite their key role in the mammalian evolution. In a previous study, we discovered remarkable differences in the MHC class II diversity between two species of mouse opossums (Gracilinanus microtarsus, Marmosops incanus) from the Brazilian Atlantic forest, which is one of the most endangered hotspots for biodiversity conservation. Since the main forces in generating MHC diversity are assumed to be pathogens, we investigated in this study gastrointestinal parasite burden and functional associations between the individual MHC constitution and parasite load. We tested two contrasting scenarios, which might explain differences in MHC diversity between species. We predicted that a species with low MHC diversity would either be under relaxed selection pressure by low parasite diversity (`Evolutionary equilibrium` scenario), or there was a recent loss in MHC diversity leading to a lack of resistance alleles and increased parasite burden (`Unbalanced situation` scenario). In both species it became apparent that the MHC class II is functionally important in defence against gastrointestinal helminths, which was shown here for the first time in marsupials. On the population level, parasite diversity did not markedly differ between the two host species. However, we did observe considerable differences in the individual parasite load (parasite prevalence and infection intensity): while M. incanus revealed low MHC DAB diversity and high parasite load, G. microtarsus showed a tenfold higher population wide MHC DAB diversity and lower parasite burden. These results support the second scenario of an unbalanced situation.

Effects of Crossing Saddle Coil Conductors: Electric Length X Mutual Inductance

In magnetic resonance imaging (MRI), either on human or animal studies, the main requirements for radiofrequency (RF) coils are to produce a homogeneous RF field while used as a transmitter coil and to have the best signal-to-noise ratio (SNR) while used as a receiver. Besides, they need to be easily frequency adjustable and have input impedance matching 50 Omega to several different load conditions. New theoretical and practical concepts are presented here for considerable enhancing of RF coil homogeneity for MRI experiments on small animals. To optimize field homogeneity, we have performed simulations using Blot and Savart law varying the coil`s window angle, achieving the optimum one. However, when the coil`s dimensions are the same order of the wave length and according to transmission line theory, differences in electrical length and effects of mutual inductances between adjacent strip conductors decrease both field homogeneity and SNR. The problematic interactions between strip conductors by means of mutual inductance were eliminated by inserting crossings at half electrical length, avoiding distortion on current density, thus eliminating sources of field inhomogeneity. Experimental results show that measured field maps and simulations are in good agreement. The new coil design, dubbed double-crossed saddle described here have field homogeneity and SNR superior than the linearly driven 8-rung birdcage coil. One of our major findings was that the effects of mutual inductance are more significant than differences in electrical length for this frequency and coil dimensions. In vitro images of a primate Cebus paela brain were acquired, confirming double-crossed saddle superiority. (C) 2010 Wiley Periodicals, Inc. Concepts Magn Reson Part B (Magn Reson Engineering) 37B: 193-201, 2010

Direct method for optimal power management in hybrid electric vehicles

Hybrid electric vehicles are powered by an electric system and an internal combustion engine. The components of a hybrid electric vehicle need to be coordinated in an optimal manner to deliver the desired performance. This paper presents an approach based on direct method for optimal power management in hybrid electric vehicles with inequality constraints. The approach consists of reducing the optimal control problem to a set of algebraic equations by approximating the state variable which is the energy of electric storage, and the control variable which is the power of fuel consumption. This approximation uses orthogonal functions with unknown coefficients. In addition, the inequality constraints are converted to equal constraints. The advantage of the developed method is that its computational complexity is less than that of dynamic and non-linear programming approaches. Also, to use dynamic or non-linear programming, the problem should be discretized resulting in the loss of optimization accuracy. The propsed method, on the other hand, does not require the discretization of the problem producing more accurate results. An example is solved to demonstrate the accuracy of the proposed approach. The results of Haar wavelets, and Chebyshev and Legendre polynomials are presented and discussed. © 2011 The Korean Society of Automotive Engineers and Springer-Verlag Berlin Heidelberg.

Effect of noise factors in energy management of series plug-in hybrid electric vehicles

It has been demonstrated that charge depletion (CD) energy management strategies are more efficient choices for energy management of plug-in hybrid electric vehicles (PHEVs). The knowledge of drive cycle as a priori can improve the performance of CD energy management in PHEVs. However, there are many noise factors which affect both drivetrain power demand and vehicle performance even in identical drive cycles. In this research, the effect of each noise factor is investigated by introducing the concept of power cycle instead of drive cycle for a journey. Based on the nature of the noise factors, a practical solution for developing a power-cycle library is introduced. Investigating the predicted power cycle, an energy management strategy is developed which considers the influence of temperature noise factor on engine performance. The effect of different environmental and geographic conditions, driver behavior, aging of battery and other components are considered. Simulation results for a modelled series PHEV similar to GM Volt show that the suggested energy management strategy based on the driver power cycle library improves both vehicle fuel economy and battery health by reducing battery load and temperature.

Impact of dynamic PHEVs load on renewable sources based distribution system

In this paper, charging effect of dynamic Plug in Hybrid Electric Vehicle (PHEV) is presented in a renewable energy based electricity distribution system. For planning and designing a distribution system, PHEVs are one of the most important factor as it is going to be a spinning reserve of energy, and also a major load for distribution network. A dynamic load model of PHEVs is introduced here based on third order battery model. To determine the system adequacy, it is necessary to do a micro level analysis to know the PHEVs load impact on grid. Scope of such analysis will cover the performance of wind and solar generation with dynamic PHEVs load, as well as the stability analysis of the power grid to demonstrate that it is important to consider the dynamics of PHEVs load in a renewable energy based distribution network.

Evidence for an additional effect of whole-body vibration above resistive exercise alone in preventing bone loss during prolonged bed rest

SUMMARY: The addition of whole-body vibration to high-load resistive exercise may provide a better stimulus for the reduction of bone loss during prolonged bed rest (spaceflight simulation) than high-load resistive exercise alone. INTRODUCTION: Prior work suggests that the addition of whole-body vibration to high-load resistive exercise (RVE) may be more effective in preventing bone loss in spaceflight and its simulation (bed rest) than resistive exercise alone (RE), though this hypothesis has not been tested in humans. METHODS: Twenty-four male subjects as part of the 2nd Berlin Bed Rest Study performed RVE (n = 7), RE (n = 8) or no exercise (control, n = 9) during 60-day head-down tilt bed rest. Whole-body, spine and total hip dual X-ray absorptiometry (DXA) measurements as well as peripheral quantitative computed tomography measurements of the tibia were conducted during bed rest and up to 90 days afterwards. RESULTS: A better retention of bone mass in RVE than RE was seen at the tibial diaphysis and proximal femur (p ≤ 0.024). Compared to control, RVE retained bone mass at the distal tibia and DXA leg sub-region (p ≤ 0.020), but with no significant difference to RE (p ≥ 0.10). RE impacted significantly (p = 0.038) on DXA leg sub-region bone mass only. Calf muscle size was impacted similarly by both RVE and RE. On lumbar spine DXA, whole-body DXA and calcium excretion measures, few differences between the groups were observed. CONCLUSIONS: Whilst further countermeasure optimisation is required, the results provide evidence that (1) combining whole-body vibration and high-load resistance exercise may be more efficient than high-load resistive exercise alone in preventing bone loss at some skeletal sites during and after prolonged bed rest and (2) the effects of exercise during bed rest impact upon bone recovery up to 3 months afterwards.

Gestão de riscos na cadeia de suprimentos e valoração do custo da escassez de energia elétrica: Modelos e uma proposta de implementação para o Brasil

Este trabalho apresenta as principais aplicações de técnicas de gestão de riscos ao estudo de interrupções em cadeias de fornecimento, tendo como motivação o caso do fornecimento de energia elétrica, assunto de extrema relevância para o Brasil. Neste sentido, o cálculo do “custo do déficit” ou perda de produção dada uma falha no fornecimento de energia elétrica (parâmetro utilizado em todo o planejamento do setor elétrico brasileiro), foi escolhido como fator relevante a ser analisado. As principais metodologias existentes para a apuração desse parâmetro são apresentadas fazendo uma comparação com aquela atualmente em uso no Brasil. Adicionalmente, apresentamos uma proposta de implementação para as metodologias alternativas, utilizadas no exterior, e baseadas no conceito de VOLL (“Value of Lost Load”) - medida do valor da escassez de energia para empresas ou consumidores individuais e fundamental para o desenho de programas de gerenciamento de demanda.

Effect of dietary energy and stocking density on the performance and sensible heat loss of broilers reared under tropical winter conditions

The objective of the present study was to evaluate the effects of different dietary energy levels and stocking densities on the thermoregulating parameters, live performance, and carcass traits of broilers reared under tropical winter conditions at different times of the day. In total, 1,312 one-d-old male broilers were used. Birds were allotted to three different stocking densities (10, 14 or 18 birds/m²) and two dietary energy levels (2900 or 3200 kcal ME/kg). The following parameters were evaluated:radiant heat load (RHL), rectal temperature (RT), feed intake (FI), weight gain (WG), feed conversion ratio (FCR), livability (L), production of live weight per area (WA), and carcass yield. Stocking density did not affect sensible heat loss (SRL) or rectal temperature (RT); however, as expected, sensible heat loss (SRL) and RT were influenced by time of the day, with higher values in the morning and in the afternoon, respectively. There was no effect of treatment (p>0.05) on carcass or parts yield. Feed intake was reduced in 3%, whereas weight gain and feed conversion ratio improved in 8 and 10%, respectively, as dietary energy level increased. on the other hand, stocking density did not influence live performance or carcass traits. Based on the present results, it is concluded that sensible heat loss depends on dietary energy levels and particularly on time of the day. Therefore, environmental house management is suggested during tropical winters in order to reduce differences between broiler skin and environmental temperatures in the morning and in the afternoon.

Loss minimization by the predictor-corrector modified barrier approach

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A novel neural model to electrical load forecasting in transformers

The paper describes a novel neural model to electrical load forecasting in transformers. The network acts as identifier of structural features to forecast process. So that output parameters can be estimated and generalized from an input parameter set. The model was trained and assessed through load data extracted from a Brazilian Electric Utility taking into account time, current, tension, active power in the three phases of the system. The results obtained in the simulations show that the developed technique can be used as an alternative tool to become more appropriate for planning of electric power systems.

Neural Network-Based Approach for Identification of the Harmonic Content of a Nonlinear Load in a Single-Phase System

In this paper an alternative method based on artificial neural networks is presented to determine harmonic components in the load current of a single-phase electric power system with nonlinear loads, whose parameters can vary so much in reason of the loads characteristic behaviors as because of the human intervention. The first six components in the load current are determined using the information contained in the time-varying waveforms. The effectiveness of this method is verified by using it in a single-phase active power filter with selective compensation of the current drained by an AC controller. The proposed method is compared with the fast Fourier transform.