The Impact of Vehicle-to-Grid on Electric Power Systems: A Review

Environmental concerns and fossil fuel shortage put pressure on both power and transportation systems. Electric vehicles (EVs) are thought to be a good solution to these problems. With EV adoption, energy flow is two way: from grid to vehicle and from vehicle to grid, which is known as vehicle-to-grid (V2G) today. This paper considers electric power systems and provides a review of the impact of V2G on power system stability. The concept and basics of V2G technology are introduced at first, followed by a description of EV application in the world. Several technical issues are detailed in V2G modeling and capacity forecasting, steady-state analysis and stability analysis. Research trends of such topics are declared at last.

Day-Ahead Optimal Charging/Discharging Scheduling for Electric Vehicles in Micro-Grids

A micro-grid is an autonomous system which can be operated and connected to an external system or isolated with the help of energy storage systems (ESSs). While the daily output of distributed generators (DGs) strongly depends on the temporal distribution of natural resources such as wind and solar, unregulated electric vehicle (EV) charging demand will deteriorate the imbalance between the daily load and generation curves. In this paper, a statistical model is presented to describe daily EV charging/discharging behaviour. An optimisation problem is proposed to obtain economic operation for the micro-grid based on this model. In day-ahead scheduling, with estimated information of power generation and load demand, optimal charging/discharging of EVs during 24 hours is obtained. A series of numerical optimization solutions in different scenarios is achieved by serial quadratic programming. The results show that optimal charging/discharging of EVs, a daily load curve can better track the generation curve and the network loss and required ESS capacity are both decreased. The paper also demonstrates cost benefits for EVs and operators.

Partial purification of lymphokine activities by iso-electric focusing

A continuous cell-line has been shown to be adaptable to preparation of supernatants containing lymphokine activities. Separation and partial purification of migration inhibiting, colony stimulating and interferon activities from such preparations has been achieved by the use of density gradient iso-electric focusing.

Myeloid cells expressing VEGF and arginase-1 following uptake of damaged retinal pigment epithelium suggests potential mechanism that drives the onset of choroidal angiogenesis in mice

Whilst data recognise both myeloid cell accumulation during choroidal neovascularisation (CNV) as well as complement activation, none of the data has presented a clear explanation for the angiogenic drive that promotes pathological angiogenesis. One possibility that is a pre-eminent drive is a specific and early conditioning and activation of the myeloid cell infiltrate. Using a laser-induced CNV murine model, we have identified that disruption of retinal pigment epithelium (RPE) and Bruch's membrane resulted in an early recruitment of macrophages derived from monocytes and microglia, prior to angiogenesis and contemporaneous with lesional complement activation. Early recruited CD11b(+) cells expressed a definitive gene signature of selective inflammatory mediators particularly a pronounced Arg-1 expression. Accumulating macrophages from retina and peripheral blood were activated at the site of injury, displaying enhanced VEGF expression, and notably prior to exaggerated VEGF expression from RPE, or earliest stages of angiogenesis. All of these initial events, including distinct VEGF (+) Arg-1(+) myeloid cells, subsided when CNV was established and at the time RPE-VEGF expression was maximal. Depletion of inflammatory CCR2-positive monocytes confirmed origin of infiltrating monocyte Arg-1 expression, as following depletion Arg-1 signal was lost and CNV suppressed. Furthermore, our in vitro data supported a myeloid cell uptake of damaged RPE or its derivatives as a mechanism generating VEGF (+) Arg-1(+) phenotype in vivo. Our results reveal a potential early driver initiating angiogenesis via myeloid-derived VEGF drive following uptake of damaged RPE and deliver an explanation of why CNV develops during any of the stages of macular degeneration and can be explored further for therapeutic gain.

Whole-Vehicle modelling of exhaust energy recovery on a diesel-electric hybrid bus

Hybrid vehicles can use energy storage systems to disconnect the engine from the driving wheels of the vehicle. This enables the engine to be run closer to its optimum operating condition, but fuel energy is still wasted through the exhaust system as heat. The use of a turbogenerator on the exhaust line addresses this problem by capturing some of the otherwise wasted heat and converting it into useful electrical energy.

This paper outlines the work undertaken to model the engine of a diesel-electric hybrid bus, coupled with a hybrid powertrain model which analysed the performance of a hybrid vehicle over a drive-cycle. The distribution of the turbogenerator power was analysed along with the effect on the fuel consumption of the bus. This showed that including the turbogenerator produced a 2.4% reduction in fuel consumption over a typical drive-cycle.

The hybrid bus generator was then optimised to improve the performance of the combined vehicle/engine package and the turbogenerator was then shown to offer a 3.0% reduction in fuel consumption. The financial benefits of using the turbogenerator were also considered in terms of fuel savings for operators. For an average bus, a turbogenerator could reduce fuel costs by around £1200 per year.

Switching ferroelectric domain configurations using both electric and magnetic fields in Pb(Zr,Ti)O3–Pb(Fe,Ta)O3 single-crystal lamellae

Thin single-crystal lamellae cut from Pb(Zr,Ti)O3–Pb(Fe,Ta)O3 ceramic samples have been integrated into simple coplanar capacitor devices. The influence of applied electric and magnetic fields on ferroelectric domain configurations has been mapped, using piezoresponse force microscopy. The extent to which magnetic fields alter the ferroelectric domains was found to be strongly history dependent: after switching had been induced by applying electric fields, the susceptibility of the domains to change under a magnetic field (the effective magnetoelectric coupling parameter) was large. Such large, magnetic field-induced changes resulted in a remanent domain state very similar to the remanent state induced by an electric field. Subsequent magnetic field reversal induced more modest ferroelectric switching.

Climate variability drives anchovies and sardines into the North and Baltic Seas

European anchovy (Engraulis encrasicolus) and sardine (Sardina pilchardus) are southern, warm water species that prefer temperatures warmer than those found in boreal waters. After about 40 years of absence, they were again observed in the 1990s in increasing quantities in the North Sea and the Baltic Sea. Whereas global warming probably played a role in these northward migrations, the North Atlantic Oscillation (NAO), the Atlantic Multidecadal Oscillation (AMO) and the contraction of the subpolar gyre were important influences. Sardine re-invaded the North Sea around 1990, probably mainly as a response to warmer temperatures associated with the strengthening of the NAO in the late 1980s. However, increasing numbers of anchovy eggs, larvae, juveniles and adults have been recorded only since the mid-1990s, when, particularly, summer temperatures started to increase. This is probably a result of the complex dynamics of ocean–atmosphere coupling involving changes in North Atlantic current structures, such as the contraction of the subpolar gyre, and dynamics of AMO. Apparently, climate variability drives anchovies and sardines into the North and Baltic Seas. Here, we elucidate the climatic background of the return of anchovies and sardines to the northern European shelf seas and the changes in the North Sea fish community in the mid-1990s in response to climate variability.

On the scaling behavior of electric conductivity in [C(4)mim][NTf2]

In this work we examine, for the first time, the molar conductivity behavior of the deeply supercooled room temperature ionic liquid [C₄mim][NTf₂] in the temperature, pressure and volume thermodynamic space in terms of density scaling (TV^γ)⁻¹ combined with the equation of state (EOS). The exponent γ_σ determined from the Avramov model analysis is compared with the coefficient obtained from the viscosity studies carried out at moderate temperatures. Therefore, the experimental results presented herein provide the answer to the long-standing question regarding the validity of thermodynamic scaling of ionic liquids over a wide temperature range, i.e. from the normal liquid state to the glass transition point. Finally, we investigate the relationship between the dynamic and thermodynamic properties of [C₄mim][NTf₂] represented by scaling exponent γ and Grüneisen constant γ_G, respectively.

Development of a Bridge Weigh-in-Motion Sensor: Performance comparison using fibre optic and electric resistance strain sensor systems

This paper addresses the problems of effective in situ measurement of the real-time strain for bridge weigh in motion in reinforced concrete bridge structures through the use of optical fiber sensor systems. By undertaking a series of tests, coupled with dynamic loading, the performance of fiber Bragg grating-based sensor systems with various amplification techniques were investigated. In recent years, structural health monitoring (SHM) systems have been developed to monitor bridge deterioration, to assess load levels and hence extend bridge life and safety. Conventional SHM systems, based on measuring strain, can be used to improve knowledge of the bridge's capacity to resist loads but generally give no information on the causes of any increase in stresses. Therefore, it is necessary to find accurate sensors capable of capturing peak strains under dynamic load and suitable methods for attaching these strain sensors to existing and new bridge structures. Additionally, it is important to ensure accurate strain transfer between concrete and steel, adhesives layer, and strain sensor. The results show the benefits in the use of optical fiber networks under these circumstances and their ability to deliver data when conventional sensors cannot capture accurate strains and/or peak strains.

New SR drive with integrated charging capacity for plug-in hybrid electric vehicles (PHEVs)

Plug-in hybrid electric vehicles (PHEVs) provide much promise in reducing greenhouse gas emissions and, thus, are a focal point of research and development. Existing on-board charging capacity is effective but requires the use of several power conversion devices and power converters, which reduce reliability and cost efficiency. This paper presents a novel three-phase switched reluctance (SR) motor drive with integrated charging functions (including internal combustion engine and grid charging). The electrical energy flow within the drivetrain is controlled by a power electronic converter with less power switching devices and magnetic devices. It allows the desired energy conversion between the engine generator, the battery, and the SR motor under different operation modes. Battery-charging techniques are developed to operate under both motor-driving mode and standstill-charging mode. During the magnetization mode, the machine's phase windings are energized by the dc-link voltage. The power converter and the machine phase windings are controlled with a three-phase relay to enable the use of the ac-dc rectifier. The power converter can work as a buck-boost-type or a buck-type dc-dc converter for charging the battery. Simulation results in MATLAB/Simulink and experiments on a 3-kW SR motor validate the effectiveness of the proposed technologies, which may have significant economic implications and improve the PHEVs' market acceptance

"'Nothing but a printer's devil ever drives me into finishing': the Genesis of Thomas Moore's Irish Melodies'

This chapter outlines the working methods of the prolific writer and lyricist Thomas Moore—which were characterized by the unfortunate combination of a perfectionist streak, a tendency to release material to the publishers while still in the creative mode, and a tendency to re-visit previously-published material. The Gibson-Massie Moore collection at Queen's University Belfast teaches us a great deal about Moore’s creative processes, and also records the nineteenth-century publishing industry’s response to one of its most prolific and popular creative artists. This chapter is illustrated by an online Exhibition, the 'Thomas Moore Project', Digital Collections, Special Collections, McClay library (see URL below).

Impact of electric vehicles on a carbon constrained power system—a post 2020 case study

Electric vehicles (EVs) offer great potential to move from fossil fuel dependency in transport once some of the technical barriers related to battery reliability and grid integration are resolved. The European Union has set a target to achieve a 10% reduction in greenhouse gas emissions by 2020 relative to 2005 levels. This target is binding in all the European Union member states. If electric vehicle issues are overcome then the challenge is to use as much renewable energy as possible to achieve this target. In this paper, the impacts of electric vehicle charged in the all-Ireland single wholesale electricity market after the 2020 deadline passes is investigated using a power system dispatch model. For the purpose of this work it is assumed that a 10% electric vehicle target in the Republic of Ireland is not achieved, but instead 8% is reached by 2025 considering the slow market uptake of electric vehicles. Our experimental study shows that the increasing penetration of EVs could contribute to approach the target of the EU and Ireland government on emissions reduction, regardless of different charging scenarios. Furthermore, among various charging scenarios, the off-peak charging is the best approach, contributing 2.07% to the target of 10% reduction of Greenhouse gas emissions by 2025.

Non-convex dynamic economic/environmental dispatch with plug-in electric vehicle loads

Electric vehicles are a key prospect for future transportation. A large penetration of electric vehicles has the potential to reduce the global fossil fuel consumption and hence the greenhouse gas emissions and air pollution. However, the additional stochastic loads imposed by plug-in electric vehicles will possibly introduce significant changes to existing load profiles. In his paper, electric vehicles loads are integrated into an 5-unit system using a non-convex dynamic dispatch model. The actual infrastructure characteristics including valve-point effects, load balance constrains and transmission loss have been included in the model. Multiple load profiles are comparatively studied and compared in terms of economic and environmental impacts in order o identify patterns to charge properly. The study as expected shows ha off-peak charging is the best scenario with respect to using less fuels and producing less emissions.

A self-learning teaching-learning based optimization for dynamic economic/environmental dispatch considering multiple plug-in electric vehicle loads

Economic and environmental load dispatch aims to determine the amount of electricity generated from power plants to meet load demand while minimizing fossil fuel costs and air pollution emissions subject to operational and licensing requirements. These two scheduling problems are commonly formulated with non-smooth cost functions respectively considering various effects and constraints, such as the valve point effect, power balance and ramp rate limits. The expected increase in plug-in electric vehicles is likely to see a significant impact on the power system due to high charging power consumption and significant uncertainty in charging times. In this paper, multiple electric vehicle charging profiles are comparatively integrated into a 24-hour load demand in an economic and environment dispatch model. Self-learning teaching-learning based optimization (TLBO) is employed to solve the non-convex non-linear dispatch problems. Numerical results on well-known benchmark functions, as well as test systems with different scales of generation units show the significance of the new scheduling method.