River Sediment Sampling and Environment Quality Standards: A Case Study of the Ravensbourne River

Sediment is a major sink for heavy metals in river, and poses significant risks not only to river quality but also to aquatic and benthic organisms. At present in the UK, there are no mandatory sediment quality standards. This is partly due to insufficient toxicity data but also due to problems with identification of appropriate sediment monitoring and analytical techniques. The aim of this research was to examine the sampling different river sediment compartments in order to monitor compliance with any future UK sediment environmental quality standards (EQS). The significance of sediment physical and chemical characteristics on sampling and analysis was also determined. The Ravensbourne River, a tributary of the River Thames located in the highly urbanised South Eastern area of London was used for this study. Sediment was collected from the bed using the Van Veer grab, the bank using hand trowel, and from the water column (suspended sediment) using the time integrated suspended tube sampler between the period of July 2010 and December, 2011. The result for the total metal extraction carried out using aqua regia found that there were no significant differences in the metal concentrations retained in the different compartments by the <63μm sediment fraction but there were differences between the 63μm-2mm fractions of the bed and bank. The metal concentration in the bed, bank and suspended sediment exceeded the draft UK sediment quality guidelines. Sequential extraction was also carried out to determine metal speciation in each sediment compartment using the Maiz et al. (1997) and Tessier et al. (1979) methods. The Maiz et al. (1997) found over 80% of the metals in each sediment compartment were not bioavailable, while Tessier et al. (1979) method found most of the metals to be associated with the Fe/Mn and the residual phase. The bed sediment compartment and the <2mm (<63μm + 63μm-2mm) fraction appears to be the most suitable sediment sample for sediment monitoring from this study.

Making way for change at the Bar: The practical implications of the new Bar Standards Board Handbook

The Legal Services Act 2007 caused a need to change professional conduct rules for lawyers in England and Wales. The Bar Standards Board Handbook brings substantial changes to the way barristers are regulated. Changes include litigation rights, reporting of professional misconduct, an increased focus on chambers, and expansion to include employees of chambers and barristers without practicing certificates (unregistered or non-practicing barristers). The approach to enforcement and supervision moves to include elements of outcome focused, principle based and risk based approaches. These changes have the potential to change the practice of different groups of barristers and the dynamics between them.

Red cell PMVs, plasma membrane-derived vesicles calling out for standards

Plasma membrane-derived vesicles (PMVs) or microparticles are vesicles (0.1–1 μm in diameter) released from the plasma membrane of all blood cell types under a variety of biochemical and pathological conditions. PMVs contain cytoskeletal elements and some surface markers from the parent cell but lack a nucleus and are unable to synthesise macromolecules. They are also defined on the basis that in most cases PMVs express varying amounts of the cytosolic leaflet lipid phosphatidylserine, which is externalised during activation on their surface. This marks the PMV as a biologically distinct entity from that of its parent cell, despite containing surface markers from the original cell, and also explains its role in events such as phagocytosis and thrombosis. There is currently a large amount of variation between investigators with regard to the pre-analytical steps employed in isolating red cell PMVs or RPMVs (which are slightly smaller than most PMVs), with key differences being centrifugation and sample storage conditions, which often leads to result variability. Unfortunately, standardization of preparation and detection methods has not yet been achieved. This review highlights and critically discusses the variables contributing to differences in results obtained by investigators, bringing to light numerous studies of which RPMVs have been analysed but have not yet been the subject of a review.

Statistical classification of road pavements using near field vehicle rolling noise measurements

Low noise surfaces have been increasingly considered as a viable and cost-effective alternative to acoustical barriers. However, road planners and administrators frequently lack information on the correlation between the type of road surface and the resulting noise emission profile. To address this problem, a method to identify and classify different types of road pavements was developed, whereby near field road noise is analyzed using statistical learning methods. The vehicle rolling sound signal near the tires and close to the road surface was acquired by two microphones in a special arrangement which implements the Close-Proximity method. A set of features, characterizing the properties of the road pavement, was extracted from the corresponding sound profiles. A feature selection method was used to automatically select those that are most relevant in predicting the type of pavement, while reducing the computational cost. A set of different types of road pavement segments were tested and the performance of the classifier was evaluated. Results of pavement classification performed during a road journey are presented on a map, together with geographical data. This procedure leads to a considerable improvement in the quality of road pavement noise data, thereby increasing the accuracy of road traffic noise prediction models.

Data mining techniques contributions to support electrical vehicle demand response

The introduction of Electric Vehicles (EVs) together with the implementation of smart grids will raise new challenges to power system operators. This paper proposes a demand response program for electric vehicle users which provides the network operator with another useful resource that consists in reducing vehicles charging necessities. This demand response program enables vehicle users to get some profit by agreeing to reduce their travel necessities and minimum battery level requirements on a given period. To support network operator actions, the amount of demand response usage can be estimated using data mining techniques applied to a database containing a large set of operation scenarios. The paper includes a case study based on simulated operation scenarios that consider different operation conditions, e.g. available renewable generation, and considering a diversity of distributed resources and electric vehicles with vehicle-to-grid capacity and demand response capacity in a 33 bus distribution network.

Particle swarm optimization based approaches to vehicle-to-grid scheduling

This paper addresses the problem of energy resources management using modern metaheuristics approaches, namely Particle Swarm Optimization (PSO), New Particle Swarm Optimization (NPSO) and Evolutionary Particle Swarm Optimization (EPSO). The addressed problem in this research paper is intended for aggregators’ use operating in a smart grid context, dealing with Distributed Generation (DG), and gridable vehicles intelligently managed on a multi-period basis according to its users’ profiles and requirements. The aggregator can also purchase additional energy from external suppliers. The paper includes a case study considering a 30 kV distribution network with one substation, 180 buses and 90 load points. The distribution network in the case study considers intense penetration of DG, including 116 units from several technologies, and one external supplier. A scenario of 6000 EVs for the given network is simulated during 24 periods, corresponding to one day. The results of the application of the PSO approaches to this case study are discussed deep in the paper.

Intelligent electric vehicle heuristic for energy resource management using simulated annealing

The smart grid concept appears as a suitable solution to guarantee the power system operation in the new electricity paradigm with electricity markets and integration of large amounts of Distributed Energy Resources (DERs). Virtual Power Player (VPP) will have a significant importance in the management of a smart grid. In the context of this new paradigm, Electric Vehicles (EVs) rise as a good available resource to be used as a DER by a VPP. This paper presents the application of the Simulated Annealing (SA) technique to solve the Energy Resource Management (ERM) of a VPP. It is also presented a new heuristic approach to intelligently handle the charge and discharge of the EVs. This heuristic process is incorporated in the SA technique, in order to improve the results of the ERM. The case study shows the results of the ERM for a 33-bus distribution network with three different EVs penetration levels, i. e., with 1000, 2000 and 3000 EVs. The results of the proposed adaptation of the SA technique are compared with a previous SA version and a deterministic technique.

Intelligent energy resource management considering vehicle-to-grid: A simulated annealing approach

This paper proposes a simulated annealing (SA) approach to address energy resources management from the point of view of a virtual power player (VPP) operating in a smart grid. Distributed generation, demand response, and gridable vehicles are intelligently managed on a multiperiod basis according to V2G user´s profiles and requirements. Apart from using the aggregated resources, the VPP can also purchase additional energy from a set of external suppliers. The paper includes a case study for a 33 bus distribution network with 66 generators, 32 loads, and 1000 gridable vehicles. The results of the SA approach are compared with a methodology based on mixed-integer nonlinear programming. A variation of this method, using ac load flow, is also used and the results are compared with the SA solution using network simulation. The proposed SA approach proved to be able to obtain good solutions in low execution times, providing VPPs with suitable decision support for the management of a large number of distributed resources.

Day-ahead resource scheduling in smart grids considering Vehicle-to-Grid and network constraints

Energy resource scheduling becomes increasingly important, as the use of distributed resources is intensified and massive gridable vehicle use is envisaged. The present paper proposes a methodology for dayahead energy resource scheduling for smart grids considering the intensive use of distributed generation and of gridable vehicles, usually referred as Vehicle- o-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with V2G owners. It takes into account these contracts, the user´s requirements subjected to the VPP, and several discharge price steps. Full AC power flow calculation included in the model allows taking into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33 bus distribution network and V2G is used to illustrate the good performance of the proposed method.

The electric vehicle integration into the power system: an application to the portuguese case

Electric vehicles (EV) offer a great potential to address the integration of renewable energy sources (RES) in the power grid, and thus reduce the dependence on oil as well as the greenhouse gases (GHG) emissions. The high share of wind energy in the Portuguese energy mix expected for 2020 can led to eventual curtailment, especially during the winter when high levels of hydro generation occur. In this paper a methodology based on a unit commitment and economic dispatch is implemented, and a hydro-thermal dispatch is performed in order to evaluate the impact of the EVs integration into the grid. Results show that the considered 10 % penetration of EVs in the Portuguese fleet would increase load in 3 % and would not integrate a significant amount of wind energy because curtailment is already reduced in the absence of EVs. According to the results, the EV is charged mostly with thermal generation and the associated emissions are much higher than if they were calculated based on the generation mix.

Modelling and aerodynamic simulation of a vehicle and failure analysis of a laminated front fender

Master Thesis in Mechanical Engineering field of Maintenance and Production

Application-specific modified particle swarm optimization for energy resource scheduling considering vehicle-to-grid

This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

Geostatistical Prediction of Ocean Outfall Plume Characteristics Based on an Autonomous Underwater Vehicle

Geostatistics has been successfully used to analyze and characterize the spatial variability of environmental properties. Besides giving estimated values at unsampled locations, it provides a measure of the accuracy of the estimate, which is a significant advantage over traditional methods used to assess pollution. In this work universal block kriging is novelty used to model and map the spatial distribution of salinity measurements gathered by an Autonomous Underwater Vehicle in a sea outfall monitoring campaign, with the aim of distinguishing the effluent plume from the receiving waters, characterizing its spatial variability in the vicinity of the discharge and estimating dilution. The results demonstrate that geostatistical methodology can provide good estimates of the dispersion of effluents that are very valuable in assessing the environmental impact and managing sea outfalls. Moreover, since accurate measurements of the plume’s dilution are rare, these studies might be very helpful in the future to validate dispersion models.

Non-uniform microstrip antenna array for RX DSRC communications

The urgent need to mitigate traffic problems such as accidents, road hazards, pollution and traffic jam have strongly driven the development of vehicular communications. DSRC (Dedicated Short Range Communications) is the technology of choice in vehicular communications, enabling real time information exchange among vehicles V2V (Vehicle-to-Vehicle) and between vehicles and infrastructure V2I (Vehicle-Infrastructure). This paper presents a receiving antenna for a single lane DSRC control unit. The antenna is a non-uniform array with five microstrip patches. The obtained beam width, bandwidth and circular polarization quality, among other characteristics, are compatible with the DSRC standards, making this antenna suitable for this application. © 2014 IEEE.