Electric Vehicles - a well to wheel analysis

The European Union has set a target for 10% renewable energy in transport by 2020, which will be met using both biofuels and electric vehicles. In the case of biofuels, for the purposes of meeting the target, the biofuel must achieve greenhouse gas savings of 35% relative to the fossil fuel replaced. For biofuels, greenhouse gas savings can be calculated using life cycle analysis, or the European Union default values. In contrast, all electricity used in transport is considered to be the same, regardless of the source or the type of electric vehicle. However, the choice of the electric vehicle and electricity source will have a major impact on the greenhouse gas savings. This paper examines different electric-vehicle scenarios in terms of greenhouse gas savings, using a well-to-wheel life cycle analysis.

Molecular cloning, expression, and regulation in Escherichia coli K-12 of a chromosome-mediated aerobactin iron transport system from a human invasive isolate of E. coli K1

We have cloned chromosomal genes determining the aerobactin iron transport system from the Escherichia coli K1 strain VW187. Mapping and hybridization experiments showed that the VW187 aerobactin region was identical to that of the plasmid ColV-K30. However, in the E. coli K-12 background, the biosynthesis of both siderophore and ferric aerobactin receptor encoded by the VW187-derived recombinant plasmids was not repressed by iron to the same extent found when a recombinant plasmid derived from pColV-K30 was used. RNA-DNA dot-blot hybridization experiments demonstrated that the aerobactin-specific mRNA synthesized by the VW187-derived clones was not iron regulated in E. coli K-12. In contrast, the synthesis of aerobactin and its receptor in strain VW187 was completely repressed by iron regardless of whether the recombinant plasmids originated from VW187 or pColV-K30. Similar results were obtained with gene fusions in which a promoterless lac operon was placed under the control of aerobactin promoter regions of either chromosome- or plasmid-mediated aerobactin systems. DNA sequencing of the chromosomal aerobactin promoter region showed changes in bases located immediately upstream to the -35 region compared with the corresponding region in pColV-K30, which is known to be part of the binding site for the Fur repressor protein.

Can we meet targets for biofuels and renewable energy in transport given the constraints imposed by policy in agriculture and energy?

The deployment of biofuels is significantly affected by policy in energy and agriculture. In the energy arena, concerns regarding the sustainability of biofuel systems and their impact on food prices led to a set of sustainability criteria in EU Directive 2009/28/EC on Renewable Energy. In addition, the 10% biofuels target by 2020 was replaced with a 10% renewable energy in transport target. This allows the share of renewable electricity used by electric vehicles to contribute to the mix in achieving the 2020 target. Furthermore, only biofuel systems that effect a 60% reduction in greenhouse gas emissions by 2020 compared with the fuel they replace are allowed to contribute to meeting the target. In the agricultural arena, cross-compliance (which is part of EU Common Agricultural Policy) dictates the allowable ratio of grassland to total agricultural land, and has a significant impact on which biofuels may be supported. This paper outlines the impact of these policy areas and their implications for the production and use of biofuels in terms of the 2020 target for 10% renewable transport energy, focusing on Ireland. The policies effectively impose constraints on many conventional energy crop biofuels and reinforce the merits of using biomethane, a gaseous biofuel. The analysis shows that Ireland can potentially satisfy 15% of renewable energy in transport by 2020 (allowing for double credit for biofuels from residues and ligno-cellulosic materials, as per Directive 2009/28/EC) through the use of indigenous biofuels: grass biomethane, waste and residue derived biofuels, electric vehicles and rapeseed biodiesel. © 2010 Elsevier Ltd. All rights reserved.

Impacts of compressed air energy storage plant on an electricity market with a large renewable energy portfolio

Renewable energy generation is expected to continue to increase globally due to renewable energy targets and obligations to reduce greenhouse gas emissions. Some renewable energy sources are variable power sources, for example wind, wave and solar. Energy storage technologies can manage the issues associated with variable renewable generation and align non-dispatchable renewable energy generation with load demands. Energy storage technologies can play different roles in each of the step of the electric power supply chain. Moreover, large scale energy storage systems can act as renewable energy integrators by smoothing the variability. Compressed air energy storage is one such technology. This paper examines the impacts of a compressed air energy storage facility in a pool based wholesale electricity market in a power system with a large renewable energy portfolio.

A well-to-wheel analysis of electric vehicles in the all-island Single Electricity Market

The European Union has set a target for 10% renewable energy in transport by 2020 to be met using biofuels and electric vehicles. In the case of biofuels, the biofuel must achieve greenhouse gas savings of 35% relative to the fossil fuel replaced. For biofuels, greenhouse gas savings can be calculated using life cycle analysis or the European Union default values. In contrast, all electricity used in transport is considered to be the same, regardless of the source or the type of electric vehicle. However, the choice of the electric vehicle and electricity source will have a major impact on the greenhouse gas saving. In this paper the initial findings of a well-to-wheel analysis of electric vehicle deployment in Northern Ireland are presented. The key finding indicates that electric vehicles require least amount of energy per mile on a well-to-wheel basis, consume the fewest resources, even accommodating inefficient fuel production, in comparison to standard internal combustion engine and hybrid vehicles.

A new self-learning TLBO algorithm for RBF neural modelling of batteries in electric vehicles

One of the main purposes of building a battery model is for monitoring and control during battery charging/discharging as well as for estimating key factors of batteries such as the state of charge for electric vehicles. However, the model based on the electrochemical reactions within the batteries is highly complex and difficult to compute using conventional approaches. Radial basis function (RBF) neural networks have been widely used to model complex systems for estimation and control purpose, while the optimization of both the linear and non-linear parameters in the RBF model remains a key issue. A recently proposed meta-heuristic algorithm named Teaching-Learning-Based Optimization (TLBO) is free of presetting algorithm parameters and performs well in non-linear optimization. In this paper, a novel self-learning TLBO based RBF model is proposed for modelling electric vehicle batteries using RBF neural networks. The modelling approach has been applied to two battery testing data sets and compared with some other RBF based battery models, the training and validation results confirm the efficacy of the proposed method.

The Bdellovibrio bacteriovorus twin-arginine transport system has roles in predatory and prey-independent growth

Bdellovibrio bacteriovorus grows in one of two ways: either (i) predatorily [in a host-dependent (HD) manner], when it invades the periplasm of another Gram-negative bacterium, exporting into the prey co-ordinated waves of soluble enzymes using the prey cell contents for growth; or (ii) in a host-independent (HI) manner, when it grows (slowly) axenically in rich media. Periplasmic invasion potentially exposes B. bacteriovorus to extremes of pH and exposes the need to scavenge electron donors from prey electron transport components by synthesis of metalloenzymes. The twin-arginine transport system (Tat) in other bacteria transports folded metalloenzymes and the B. bacteriovorus genome encodes 21 potential Tat-transported substrates and Tat transporter proteins TatA1, TatA2 and TatBC. GFP tagging of the Tat signal peptide from Bd1802, a high-potential iron-sulfur protein (HiPIP), revealed it to be exported into the prey bacterium during predatory growth. Mutagenesis showed that the B. bacteriovorus tatA2 and tatC gene products are essential for both HI and HD growth, despite the fact that they partially complement (in SDS resistance assays) the corresponding mutations in Escherichia coli where neither TatA nor TatC are essential for life. The essentiality of B. bacteriovorus TatA2 was surprising given that the B. bacteriovorus genome encodes a second tatA homologue, tatA1. Transcription of tatA1 was found to be induced upon entry to the bdelloplast, and insertional inactivation of tatA1 showed that it significantly slowed the rates of both HI and HD growth. B. bacteriovorus is one of a few bacterial species that are reliant on a functional Tat system and where deletion of a single tatA1 gene causes a significant growth defect(s), despite the presence of its tatA2 homologue.

A Brief Review to Integrated Energy System and Energy Internet 综合能源系统与能源互联网简述

Integrated energy system and Energy Internet are two hot topics in the field of energy. In this paper, these two concepts and their focuses are summarized and analyzed. Typical research in the areas of integrated energy system and Energy Internet is reviewed. The research concerns and technologies of these two concepts are then outlined respectively. The differences and similarities of these two concepts and their future development are discussed.

Electric vehicles in urban areas: test cases using a scenario simulator

Electric vehicles introduction will affect cities environment and urban mobility policies. Network system operators will have to consider the electric vehicles in planning and operation activities due to electric vehicles’ dependency on the electricity grid. The present paper presents test cases using an Electric Vehicle Scenario Simulator (EVeSSi) being developed by the authors. The test cases include two scenarios considering a 33 bus network with up to 2000 electric vehicles in the urban area. The scenarios consider a penetration of 10% of electric vehicles (200 of 2000), 30% (600) and 100% (2000). The first scenario will evaluate network impacts and the second scenario will evaluate CO2 emissions and fuel consumption.

Day-ahead Resource Scheduling Including Demand Response for Electric Vehicles

The energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and V2G. The main focus is the comparison of different EV management approaches in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and Demand Response (DR) programs i n the V2G approach. Three different DR programs are designed and tested (trip reduce, shifting reduce and reduce+shifting). Othe r important contribution of the paper is the comparison between deterministic and computational intelligence techniques to reduce the execution time. The proposed scheduling is solved with a modified particle swarm optimization. Mixed integer non-linear programming is also used for comparison purposes. Full ac power flow calculation is included to allow taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G resources is used to illustrate the performance of the proposed method.

Response rainbow trout (Salmon gairdneri) blood gas transport system to temperature, oxygen availability and photoperiod

Hematological status in rainbow trout, Salmo gairdneri, was examined in relation to eight combinations of three environmental fa ctors; temperature (5°, 20°C), oxygen availability «35%, >70% saturation) and photoperiod (16L:8D, 8L:16D) and evaluated by 3-factor analysis of variance. Hemog l obin and hematocrit , indicators of oxygenc arrying capacity increased significantly at the higher temperature, following exposure to hypoxia and in relation to reduced light period. Significant variations in mean corpuscular hemoglobin concentration were not detected. The effects of temperature and oxygen availability were more pronounced than that of photoperiod which was generally masked. Although oxygen availability and photoperiod did not interact with temperature, the interaction of the former fac tors was significant. Elec trophoresis revealed twelve hemoglobin isomorphs. Relative concentration changes were found in re lation to the factors c onsidered with temperature>hypoxia>photoperiod. Howeve r , in terms of absolute concentration, effects were hypoxia>temperature>photoperiod. Photoperiod effects were again masked by temperature and (or) hypoxia. Red cell +2 l eve ls of [CI ] and [Mg ], critical elements in the hemoglobin-oxygen affinity regulating system, were also significantly altered. Red cell CI +2 was influenced only by temperature ; Mg by temper ature and oxygen. No photoperiod influence on either ions was observed. Under nominal 'summer' conditions, these changes point to the likelihood of increases in oxygen-c arrying c apac ity coupled with low Hb-02 affinity adjustments which would be expected to increase oxygen delivery rates to their more rapidly metabolising tissues.