A New Heuristic Providing an Effective Initial Solution for a Simulated Annealing approach to Energy Resource Scheduling in Smart Grids

An intensive use of dispersed energy resources is expected for future power systems, including distributed generation, especially based on renewable sources, and electric vehicles. The system operation methods and tool must be adapted to the increased complexity, especially the optimal resource scheduling problem. Therefore, the use of metaheuristics is required to obtain good solutions in a reasonable amount of time. This paper proposes two new heuristics, called naive electric vehicles charge and discharge allocation and generation tournament based on cost, developed to obtain an initial solution to be used in the energy resource scheduling methodology based on simulated annealing previously developed by the authors. The case study considers two scenarios with 1000 and 2000 electric vehicles connected in a distribution network. The proposed heuristics are compared with a deterministic approach and presenting a very small error concerning the objective function with a low execution time for the scenario with 2000 vehicles.

The consumer acceptance of novel vegetable-enriched bread products as a potential vehicle to increase vegetable consumption

Currently UK fruit and vegetable intakes are below recommendations. Bread is a staple food consumed by ~95% of adults in western countries. In addition, bread provides an ideal matrix by which functionality can be delivered to the consumer in an accepted food. Therefore, enriching bread with vegetables may be an effective strategy to increase vegetable consumption. This study evaluated consumer acceptance, purchase intent and intention of product replacement of bread enriched with red beetroot, carrot with coriander, red pepper with tomato or white beetroot (80g vegetable per serving of 200g) compared to white control bread (0g vegetable). Consumers (n=120) rated their liking of the breads overall, as well as their liking of appearance, flavour and texture using nine-point hedonic scales. Product replacement and purchase intent of the breads was rated using five-point scales. The effect of providing consumers with health information about the breads was also evaluated. There were significant differences in overall liking (P<0.0001), as well as liking of appearance (P<0.0001), flavour (P=0.0002) and texture (P=0.04), between the breads. However, the significant differences resulted from the red beetroot bread which was significantly (P<0.05) less liked compared to control bread. There were no significant differences in overall liking between any of the other vegetable-enriched breads compared with the control bread (no vegetable inclusion), apart from the red beetroot bread which was significantly less liked. The provision of health information about the breads did not increase consumer liking of the vegetable-enriched breads. In conclusion, this study demonstrated that vegetable-enriched bread appeared to be an acceptable strategy to increase vegetable intake, however, liking depended on vegetable type.

Towards a Protocol for the Attachment of Semantic Descriptions to Grid Services

Service discovery in large scale, open distributed systems is difficult because of the need to filter out services suitable to the task at hand from a potentially huge pool of possibilities. Semantic descriptions have been advocated as the key to expressive service discovery, but the most commonly used service descriptions and registry protocols do not support such descriptions in a general manner. In this paper, we present a protocol, its implementation and an API for registering semantic service descriptions and other task/user-specific metadata, and for discovering services according to these. Our approach is based on a mechanism for attaching structured and unstructured metadata, which we show to be applicable to multiple registry technologies. The result is an extremely flexible service registry that can be the basis of a sophisticated semantically-enhanced service discovery engine, an essential component of a Semantic Grid.

Minimizing residential distribution system operating costs through intelligently scheduled plug-in hybrid electric vehicle charging

Rising fuel prices and environmental concerns are threatening the stability of current electrical grid systems. These factors are pushing the automobile industry towards more effcient, hybrid vehicles. Current trends show petroleum is being edged out in favor of electricity as the main vehicular motive force. The proposed methods create an optimized charging control schedule for all participating Plug-in Hybrid Electric Vehicles in a distribution grid. The optimization will minimize daily operating costs, reduce system losses, and improve power quality. This requires participation from Vehicle-to-Grid capable vehicles, load forecasting, and Locational Marginal Pricing market predictions. Vehicles equipped with bidirectional chargers further improve the optimization results by lowering peak demand and improving power quality.

Contribution of the noise radiated by a single vehicle to the road traffic noise

El ruido del tráfico rodado supone aproximadamente la mitad del ruido global ambiental. Las técnicas de control de ruido habitual en emisión (límites de emisión de vehículos) e inmisión (barreras acústicas, doble acristalamiento) no han sido suficientes para disminuir significativamente las molestias por el tráfico rodado en las últimas tres décadas. El efecto positivo de estas técnicas de control ha sido contrarrestado por el aumento de la densidad del tráfico. Por otra parte, la molestia del ruido del tráfico está altamente correlacionada con los niveles máximos de ruido (MNL), producidos por lo general por conductores agresivos. Sin embargo, los sistemas actuales de medición de ruido de tráfico se basan en una valoración global, por lo que no son capaces de discriminar entre los conductores silenciosos y ruidosos. Por lo tanto, en esta tesis se propone un sistema de medida de ruido en el campo cercano, que es capaz de medir la contribución de cada vehículo individual al ruido del tráfico rodado, permitiendo la detección de los conductores ruidosos. Este trabajo describe también una combinación de investigaciones analíticas y experimentales para la identificación de los conductores responsables de la generación de niveles máximos de ruido. El sistema se basa en dos micrófonos embarcados, uno para el ruido del motor y otro para el ruido de rodadura. Con el fin de relacionar estas mediciones de campo cercano con el ruido de los vehículos radiado al campo lejano, se desarrolla un procedimiento completo para la extrapolación del ruido medido por los micrófonos de campo próximo a las posiciones de campo lejano, usando una combinación de predicción analítica y mediciones experimentales. Las correcciones para los niveles extrapolados se deben a factores atmosféricos, al término de divergencia esférica y a las condiciones de absorción de la superficie de propagación. Para el micrófono situado próximo al motor, es necesario también caracterizar las propiedades acústicas del capó del motor. Ambos niveles de ruido se extrapolan de forma independiente a la posición de campo lejano, donde se realiza una comparación entre la predicción y mediciones para confirmar que la metodología es fiable para estimar el impacto a distancia del ruido de tráfico

Minicars Research Safety Vehicle to 1979 Dodge Challenger crash test report - frontal aligned impact at 86.52 mph closing speed.

National Highway Traffic Safety Administration, Office of Vehicle Safety Compliance, Washington, D.C.

Pickup and van side structure baseline assessment test no. 4 - vehicle-to-vehicle 60 degree right side impact. Task 3. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Pickup and van side structure baseline assessment, tests 1, 2, and 3, vehicle-to-vehicle 60 degree left side impact. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Impact of driver behaviour on availability of electric vehicle stored energy for STOR

As take up of low carbon vehicles increase, there is interest in using the energy stored in the vehicles to help maintain system frequency through ancillary services on the electricity grid system. Research into this area is generally classed as vehicle-to-grid research. In theory, the energy available from electric vehicles could be directly correlated to the vehicle's state of charge (SoC) and battery capacity during the time the car is parked and plugged in. However, not all the energy in the vehicle may be used, as some capacity is required by the driver for their next journey. As such, this paper uses data captured as part of a large scale electric vehicle trial to investigate the effect of three different types of driver routine on vehicle-to-grid availability. Each driver's behaviour is analysed to assess the energy that is available for STOR, with follow on journey requirements also considered.

Analysis and correction of voltage profile in low voltage distribution networks containing photovoltaic cells and electric vehicles

Voltage drop and rise at network peak and off–peak periods along with voltage unbalance are the major power quality problems in low voltage distribution networks. Usually, the utilities try to use adjusting the transformer tap changers as a solution for the voltage drop. They also try to distribute the loads equally as a solution for network voltage unbalance problem. On the other hand, the ever increasing energy demand, along with the necessity of cost reduction and higher reliability requirements, are driving the modern power systems towards Distributed Generation (DG) units. This can be in the form of small rooftop photovoltaic cells (PV), Plug–in Electric Vehicles (PEVs) or Micro Grids (MGs). Rooftop PVs, typically with power levels ranging from 1–5 kW installed by the householders are gaining popularity due to their financial benefits for the householders. Also PEVs will be soon emerged in residential distribution networks which behave as a huge residential load when they are being charged while in their later generation, they are also expected to support the network as small DG units which transfer the energy stored in their battery into grid. Furthermore, the MG which is a cluster of loads and several DG units such as diesel generators, PVs, fuel cells and batteries are recently introduced to distribution networks. The voltage unbalance in the network can be increased due to the uncertainties in the random connection point of the PVs and PEVs to the network, their nominal capacity and time of operation. Therefore, it is of high interest to investigate the voltage unbalance in these networks as the result of MGs, PVs and PEVs integration to low voltage networks. In addition, the network might experience non–standard voltage drop due to high penetration of PEVs, being charged at night periods, or non–standard voltage rise due to high penetration of PVs and PEVs generating electricity back into the grid in the network off–peak periods. In this thesis, a voltage unbalance sensitivity analysis and stochastic evaluation is carried out for PVs installed by the householders versus their installation point, their nominal capacity and penetration level as different uncertainties. A similar analysis is carried out for PEVs penetration in the network working in two different modes: Grid to vehicle and Vehicle to grid. Furthermore, the conventional methods are discussed for improving the voltage unbalance within these networks. This is later continued by proposing new and efficient improvement methods for voltage profile improvement at network peak and off–peak periods and voltage unbalance reduction. In addition, voltage unbalance reduction is investigated for MGs and new improvement methods are proposed and applied for the MG test bed, planned to be established at Queensland University of Technology (QUT). MATLAB and PSCAD/EMTDC simulation softwares are used for verification of the analyses and the proposals.

Unit commitment in power systems with plug-in hybrid electric vehicles

With the continued development of renewable energy generation technologies and increasing pressure to combat the global effects of greenhouse warming, plug-in hybrid electric vehicles (PHEVs) have received worldwide attention, finding applications in North America and Europe. When a large number of PHEVs are introduced into a power system, there will be extensive impacts on power system planning and operation, as well as on electricity market development. It is therefore necessary to properly control PHEV charging and discharging behaviors. Given this background, a new unit commitment model and its solution method that takes into account the optimal PHEV charging and discharging controls is presented in this paper. A 10-unit and 24-hour unit commitment (UC) problem is employed to demonstrate the feasibility and efficiency of the developed method, and the impacts of the wide applications of PHEVs on the operating costs and the emission of the power system are studied. Case studies are also carried out to investigate the impacts of different PHEV penetration levels and different PHEV charging modes on the results of the UC problem. A 100-unit system is employed for further analysis on the impacts of PHEVs on the UC problem in a larger system application. Simulation results demonstrate that the employment of optimized PHEV charging and discharging modes is very helpful for smoothing the load curve profile and enhancing the ability of the power system to accommodate more PHEVs. Furthermore, an optimal Vehicle to Grid (V2G) discharging control provides economic and efficient backups and spinning reserves for the secure and economic operation of the power system

A hierarchical decomposition approach for coordinated dispatch of plug-in electric vehicles

Plug-in electric vehicles (PEVs) are increasingly popular in the global trend of energy saving and environmental protection. However, the uncoordinated charging of numerous PEVs can produce significant negative impacts on the secure and economic operation of the power system concerned. In this context, a hierarchical decomposition approach is presented to coordinate the charging/discharging behaviors of PEVs. The major objective of the upper-level model is to minimize the total cost of system operation by jointly dispatching generators and electric vehicle aggregators (EVAs). On the other hand, the lower-level model aims at strictly following the dispatching instructions from the upper-level decision-maker by designing appropriate charging/discharging strategies for each individual PEV in a specified dispatching period. Two highly efficient commercial solvers, namely AMPL/IPOPT and AMPL/CPLEX, respectively, are used to solve the developed hierarchical decomposition model. Finally, a modified IEEE 118-bus testing system including 6 EVAs is employed to demonstrate the performance of the developed model and method.

Controller synthesis of a bidirectional inductive power interface for electric vehicles

Bidirectional Inductive Power Transfer (IPT) systems are preferred for Vehicle-to-Grid (V2G) applications. Typically, bidirectional IPT systems consist of high order resonant networks, and therefore, the control of bidirectional IPT systems has always been a difficulty. To date several different controllers have been reported, but these have been designed using steady-state models, which invariably, are incapable of providing an accurate insight into the dynamic behaviour of the system A dynamic state-space model of a bidirectional IPT system has been reported. However, currently this model has not been used to optimise the design of controllers. Therefore, this paper proposes an optimised controller based on the dynamic model. To verify the operation of the proposed controller simulated results of the optimised controller and simulated results of another controller are compared. Results indicate that the proposed controller is capable of accurately and stably controlling the power flow in a bidirectional IPT system.