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.

Impact of Heat Pump Load on Distribution Networks

Heat pumps can provide domestic heating at a cost that is competitive with oil heating in particular. If the electricity supply contains a significant amount of renewable generation, a move from fossil fuel heating to heat pumps can reduce greenhouse gas emissions. The inherent thermal storage of heat pump installations can also provide the electricity supplier with valuable flexibility. The increase in heat pump installations in the UK and Europe in the last few years poses a challenge for low-voltage networks, due to the use of induction motors to drive the pump compressors. The induction motor load tends to depress voltage, especially on starting. The paper includes experimental results, dynamic load modelling, comparison of experimental results and simulation results for various levels of heat pump deployment. The simulations are based on a generic test network designed to capture the main characteristics of UK distribution system practice. The simulations employ DIgSlILENT to facilitate dynamic simulations that focus on starting current, voltage variations, active power, reactive power and switching transients.

The Continuing Debate on Deep Molluscan Phylogeny: Evidence for Serialia (Mollusca, Monoplacophora + Polyplacophora)

Molluscs are a diverse animal phylum with a formidable fossil record. Although there is little doubt about the monophyly of the eight extant classes, relationships between these groups are controversial.We analysed a comprehensive multilocus molecular data set for molluscs, the first to include multiple species from all classes, including five monoplacophorans in both extant families. Our analyses of fivemarkers resolve two major clades: the first includes gastropods and bivalves sister to Serialia (monoplacophorans and chitons), and the second comprises scaphopods sister to aplacophorans and cephalopods. Traditional groupings such as Testaria, Aculifera, and Conchifera are rejected by our data with significant Approximately Unbiased (AU) test values. A new molecular clock indicates that molluscs had a terminal Precambrian origin with rapid divergence of all eight extant classes in the Cambrian. Therecovery of Serialia as a derived, Late Cambrian clade is potentially in line with the stratigraphic chronology of morphologically heterogeneous early mollusc fossils. Serialia is in conflict with traditional molluscan classifications and recent phylogenomic data. Yet our hypothesis, as others from molecular data, implies frequent molluscan shell and body transformations by heterochronic shifts in development and multiple convergent adaptations, leading to the variable shells and body plans in extant lineages.

Power take-off and damping of an oscillating wave surge converter

The European Union has set a target of 20% for the share of renewable energy sources in gross final energy consumption in 2020. These renewable energy targets are priority objectives for the Europe 2020 strategy for inclusive growth. In line with the European Union renewable energy policies, the Northern Ireland Executive has a target to deliver 40% renewable electricity by 2020. Currently, Northern Ireland imports 98% of the energy it uses in the form of fossil fuels. Locally produced energy and electricity is needed to ensure sustainable development. The aim of this research is to develop part of a strategy for the mechanical power take-off system for a flap type wave energy converter. Aquamarine Power Ltd’s Oyster flap was the device used for simulation and testing purposes. In this paper the state-of-the-art of wave energy converters is reviewed and a 40th scale test model was developed and built.

Hydroclimatic changes during the 8.2 ka event revealed by Irish pines

A pivotal cold event, deduced from the Greenland ice cores, took place between 8200 and 8000 cal. BP. Modelling of this climatic episode suggests that higher northern latitudes would have also experienced substantial reduction in rainfall and that Ireland would have observed a notable decline. No well-dated proxy record exists from the British Isles to test the model results. We present significant independent data for a phase of increased Scots pine initiation on Irish bogs at around 8150 cal. BP. Dendrochronological dating of sub-fossil Scots pine trees from three locations reveals synchronicity in germination across the area, indicative of a regional forcing, and allows for high-precision radiocarbon based dates. The starting rings of 40% of all samples from the north of Ireland dating to the period 8500-7500 cal. BP fall within a period of 25 years. The present colonisation model of Scots pine on peatland is interpreted as increasing drier conditions in the region and provides the first meaningful proxy data in support of a significant hydrological change in the north of Ireland accompanying the 8.2 ka event. The dating uncertainties associated with the Irish Scots pine record and the Greenland Ice Core Chronology 2005 (GICC05) do not allow for any overlap between the two. The results indicate that the discrepancy could be a result of dating inaccuracy that could have affected analysis of prior proxy alignments.

Spatial and Temporal Changes in Soil Organic Carbon Assessment using an Integrated Geostatistical and Compositional Data Analysis Approach

The Irish and UK governments, along with other countries, have made a commitment to limit the concentrations of greenhouse gases in the atmosphere by reducing emissions from the burning of fossil fuels. This can be achieved (in part) through increasing the sequestration of CO2 from the atmosphere including monitoring the amount stored in vegetation and soils. A large proportion of soil carbon is held within peat due to the relatively high carbon density of peat and organic-rich soils. This is particularly important for a country such as Ireland, where some 16% of the land surface is covered by peat. For Northern Ireland, it has been estimated that the total amount of carbon stored in vegetation is 4.4Mt compared to 386Mt stored within peat and soils. As a result it has become increasingly important to measure and monitor changes in stores of carbon in soils. The conservation and restoration of peat covered areas, although ongoing for many years, has become increasingly important. This is summed up in current EU policy outlined by the European Commission (2012) which seeks to assess the relative contributions of the different inputs and outputs of organic carbon and organic matter to and from soil. Results are presented from the EU-funded Tellus Border Soil Carbon Project (2011 to 2013) which aimed to improve current estimates of carbon in soil and peat across Northern Ireland and the bordering counties of the Republic of Ireland.
Historical reports and previous surveys provide baseline data. To monitor change in peat depth and soil organic carbon, these historical data are integrated with more recently acquired airborne geophysical (radiometric) data and ground-based geochemical data generated by two surveys, the Tellus Project (2004-2007: covering Northern Ireland) and the EU-funded Tellus Border project (2011-2013) covering the six bordering counties of the Republic of Ireland, Donegal, Sligo, Leitrim, Cavan, Monaghan and Louth. The concept being applied is that saturated organic-rich soil and peat attenuate gamma-radiation from underlying soils and rocks. This research uses the degree of spatial correlation (coregionalization) between peat depth, soil organic carbon (SOC) and the attenuation of the radiometric signal to update a limited sampling regime of ground-based measurements with remotely acquired data. To comply with the compositional nature of the SOC data (perturbations of loss on ignition [LOI] data), a compositional data analysis approach is investigated. Contemporaneous ground-based measurements allow corroboration for the updated mapped outputs. This provides a methodology that can be used to improve estimates of soil carbon with minimal impact to sensitive habitats (like peat bogs), but with maximum output of data and knowledge.

Dissolved uranium, radium and radon evolution in the Continental Intercalaire aquifer, Algeria and Tunisia

Natural, dissolved 238U-series radionuclides (U, 226Ra, 222Rn) and activity ratios (A.R.s: 234U/238U; 228Ra/226Ra) in Continental Intercalaire (CI) groundwaters and limited samples from the overlying Complexe Terminal (CT) aquifers of Algeria and Tunisia are discussed alongside core measurements for U/Th (and K) in the contexts of radiological water quality, geochemical controls in the aquifer, and water residence times. A redox barrier is characterised downgradient in the Algerian CI for which a trend of increasing 234U/238U A.R.s with decreasing U-contents due to recoil-dominated 234U solution under reducing conditions allows residence time modelling ∼500 ka for the highest enhanced A.R. = 3.17. Geochemical modelling therefore identifies waters towards the centre of the Grand Erg Oriental basin as palaeowaters in line with reported 14C and 36Cl ages. A similar 234U/238U trend is evidenced in a few of the Tunisian CI waters. The paleoage status of these waters is affirmed by both noble gas recharge temperatures and simple modelling of dissolved, radiogenic 4He-contents both for sampled Algerian and Tunisian CI and CT waters. For the regions studied these waters therefore should be regarded as “fossil��� waters and treated effectively as a non-renewable resource.

Air pollutant contamination and acidification of surface waters in the North York Moors, UK: Multi-proxy evidence from the sediments of a moorland pool

Despite the extensive geographical range of palaeolimnological studies designed to assess the extent of surface water acidification in the United Kingdom during the 1980s, little attention was paid to the status of surface waters in the North York Moors (NYM). In this paper, we present sediment core data from a moorland pool in the NYM that provide a record of air pollution contamination and surface water acidification. The 41-cm-long core was divided into three lithostratigraphic units. The lower two comprise peaty soils and peats, respectively, that date to between approximately 8080 and 6740 cal. BP. The uppermost unit comprises peaty lake muds dating from between approximately ad 1790 and the present day (ad 2006). The lower two units contain pollen dominated by forest taxa, whereas the uppermost unit contains pollen indicative of open landscape conditions similar to those of the present. Heavy metal, spheroidal carbonaceous particle, mineral magnetics and stable isotope analysis of the upper sediments show clear evidence of contamination by air pollutants derived from fossil-fuel combustion over the last c. 150years, and diatom analysis indicates that the naturally acidic pool became more acidic during the 20th century. We conclude that the exceptionally acidic surface waters of the pool at present (pH=c. 4.1) are the result of a long history of air pollution and not because of naturally acidic local conditions. We argue that the highly acidic surface waters elsewhere in the NYM are similarly acidified and that the lack of evidence of significant recovery from acidification, despite major reductions in the emissions of acidic gases that have taken place over the last c. 30years, indicates the continuing influence of pollutant sulphur stored in catchment peats, a legacy of over 150years of acid deposition.

Biomass-derived Oxymethylene Ethers as Diesel Additives: A Thermodynamic Analysis

Conversion of biomass for production of liquid fuels can help in reducing the greenhouse gas (GHG) emissions which are predominantly generated by combustion of fossil fuels. Adding oxymethylene ethers (OMEs) in conventional diesel fuel has the potential to reduce soot formation during the combustion in a diesel engine. OMEs are downstream products of syngas, which can be generated by the gasification of biomass. In this research, a thermodynamic analysis has been conducted through development of data intensive process models of all the unit operations involved in production of OMEs from biomass. Based on the developed model, the key process parameters affecting the OMEs production including equivalence ratio, H2/CO ratio, and extra water flow rate were identified. This was followed by development of an optimal process design for high OMEs production. It was found that for a fluidized bed gasifier with heat capacity of 28 MW, the conditions for highest OMEs production are at an air amount of 317 tonne/day, at H2/CO ratio of 2.1, and without extra water injection. At this level, the total OMEs production is 55 tonne/day (13 tonne/day OME3 and 9 tonne/day OME4). This model would further be used in a techno-economic assessment study of the whole biomass conversion chain to determine the most attractive pathways.

How the mollusc got its scales: Convergent evolution of the molluscan scleritome

Radiation of dramatically disparate forms among the phylum Mollusca remains a key question in metazoan evolution, and requires careful evaluation of homology of hard parts throughout the deep fossil record. Enigmatic early Cambrian taxa such as Halkieria and Wiwaxia (in the clade Halwaxiida) have been proposed to represent stem-group aculiferan molluscs (Caudofoveata+Solenogastres+Polyplacophora), as complex scleritomes were considered to be unique to aculiferans among extant molluscs. The 'scaly-foot gastropod' (Neomphalina: Peltospiridae) from hydrothermal vents of the Indian Ocean, however, also carries dermal sclerites and thus challenges this inferred homology. Despite superficial similarities to various mollusc sclerites, the scaly-foot gastropod sclerites are secreted in layers covering outpockets of epithelium and are largely proteinaceous, while chiton (Polyplacophora: Chitonida) sclerites are secreted to fill an invaginated cuticular chamber and are largely calcareous. Marked differences in the underlying epithelium of the scaly-foot gastropod sclerites and operculum suggest that the sclerites do not originate from multiplication of the operculum. This convergence in different classes highlights the ability of molluscs to adapt mineralized dermal structures, as supported by the extensive early fossil record of molluscs with scleritomes. Sclerites of halwaxiids are morphologically variable, undermining the assumed affinity of specific taxa with chitons, or the larger putative clade Aculifera. Comparisons with independently derived similar structures in living molluscs are essential for determining homology among fossils and their position with respect to the enigmatic evolution of molluscan shell forms in deep time.

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.

Improving fuel economy application of the organic Rankine Cycle on a hybrid bus

Globally vehicle operators are experiencing rising fuel costs and increased
running expenses as governments around the world attempt to decrease carbon dioxide emissions and fossil fuel consumption, due to global warming and the drive to reduce dependency on fossil fuels. Recent advances in hybrid vehicle design have made great strides towards more efficient operation, with regenerative braking being widely used to capture otherwise lost energy. In this paper a hybrid series bus is developed a step further, by installing another method of energy capture on the vehicle. In this case, it is in the form of the Organic Rankine Cycle (ORC). The waste heat expelled to the exhaust and coolant streams is recovered and converted to electrical energy which is then stored in the hybrid vehicles batteries. The electrical energy can then be used for the auxiliary power circuit or to assist in vehicle propulsion, thus reducing the load on the engine, thereby improving the overall fuel economy of the vehicle and reducing carbon dioxide emissions.

Computational scheduling methods for integrating plug-in electric vehicles with power systems: a review

Traditional internal combustion engine vehicles are a major contributor to global greenhouse gas emissions and other air pollutants, such as particulate matter and nitrogen oxides. If the tail pipe point emissions could be managed centrally without reducing the commercial and personal user functionalities, then one of the most attractive solutions for achieving a significant reduction of emissions in the transport sector would be the mass deployment of electric vehicles. Though electric vehicle sales are still hindered by battery performance, cost and a few other technological bottlenecks, focused commercialisation and support from government policies are encouraging large scale electric vehicle adoptions. The mass proliferation of plug-in electric vehicles is likely to bring a significant additional electric load onto the grid creating a highly complex operational problem for power system operators. Electric vehicle batteries also have the ability to act as energy storage points on the distribution system. This double charge and storage impact of many uncontrollable small kW loads, as consumers will want maximum flexibility, on a distribution system which was originally not designed for such operations has the potential to be detrimental to grid balancing. Intelligent scheduling methods if established correctly could smoothly integrate electric vehicles onto the grid. Intelligent scheduling methods will help to avoid cycling of large combustion plants, using expensive fossil fuel peaking plant, match renewable generation to electric vehicle charging and not overload the distribution system causing a reduction in power quality. In this paper, a state-of-the-art review of scheduling methods to integrate plug-in electric vehicles are reviewed, examined and categorised based on their computational techniques. Thus, in addition to various existing approaches covering analytical scheduling, conventional optimisation methods (e.g. linear, non-linear mixed integer programming and dynamic programming), and game theory, meta-heuristic algorithms including genetic algorithm and particle swarm optimisation, are all comprehensively surveyed, offering a systematic reference for grid scheduling considering intelligent electric vehicle integration.