170,193 research outputs found
The impact of domestic plug-in hybrid electric vehicles on power distribution system loads
No full textThe market for Plug-in Hybrid Electric Vehicle (PHEVs) is expected to grow significantly over the next few years and a number of new products are soon to come onto the market, such as the Toyota Prius plug-in version, . The charging demand of wide-scale use of PHEVs may have a significant impact on domestic electricity loads and could risk of overloading the power system if appropriate charging strategies not applied to prevent this. A Monte Carlo Simulation (MCS) model of domestic PHEV use and availability has been developed based on probabilistic characterisations obtained from UKTUS and quantifies charging demand of PHEVs as a function of time of day. The MCS model has been developed in order to simulate the impact on the electricity distribution system. This article also discusses the potential for responsive battery charging load from PHEVs
Optimizing plug-in electric vehicle charging in interaction with a small office building
No full textThis paper considers the integration of plug-in electric vehicles (PEVs) in micro-grids. Extending a theoretical framework for mobile storage connection, the economic analysis here turns to the interactions of commuters and their driving behavior with office buildings. An illustrative example for a real office building is reported. The chosen system includes solar thermal, photovoltaic, combined heat and power generation as well as an array of plug-in electric vehicles with a combined aggregated capaci-ty of 864 kWh. With the benefit-sharing mechanism proposed here and idea-lized circumstances, estimated cost savings of 5% are possible. Different pricing schemes were applied which include flat rates, demand charges, as well as hourly variable final customer tariffs and their effects on the operation of intermittent storage were revealed and examined in detail. Because the plug-in electric vehicle connection coincides with peak heat and electricity loads as well as solar radiation, it is possible to shift energy demand as desired in order to realize cost savings. --Battery storage,building management systems,dispersed storage and generation,electric vehicles,load management,microgrid,optimization methods,power system economics,road vehicle electric propulsion
Grid integration of intermittent renewable energy sources using price-responsive plug-in electric vehicles
No full textPlug-in electric vehicles (PEVs) are expected to balance the fluctuation of re-newable energy sources (RES). To investigate the contribution of PEVs, the availability of mobile battery storage and the control mechanism for load man-agement are crucial. This study therefore combined the following: a stochastic model to determine mobility behavior, an optimization model to minimize vehicle charging costs and an agent-based electricity market equilibrium model to esti-mate variable electricity prices. The variable electricity prices are calculated based on marginal generation costs. Hence, because of the merit order effect, the electricity prices provide incentives to consume electricity when the supply of renewable generation is high. Depending on the price signals and mobility behavior, PEVs calculate a cost minimizing charging schedule and therefore balance the fluctuation of RES. The analysis shows that it is possible to limit the peak load using the applied control mechanism. The contribution of PEVs to improving the integration of intermittent renewable power generation into the grid depends on the characteristic of the RES generation profile. For the Ger-man 2030 scenario used here, the negative residual load was reduced by 15 to 22 percent and the additional consumption of negative residual load was be-tween 34 and 52 percent. --Plug-in electric vehicles,demand-side management,variable prices,intermittent generation
Optimisation algorithms for the charge dispatch of plug-in vehicles based on variable tariffs
No full textPlug-in vehicles powered by renewable energies are a viable way to reduce local and total emissions and could also support a highly efficient grid operation. Indirect control by variable tariffs is one option to link charging or even discharging time with the grid load and the renewable energy production. Algorithms are required to develop tariffs and evaluate grid impacts of variable tariffs for electric vehicles (BEV) as well as to schedule the charging process optimisation. Therefore a combinatorial optimisation algorithm is developed and an algorithm based on graph search is used and customised. Both algorithms are explained and compared by performance and adequate applications. The developing approach and the correctness of the quick combinatorial algorithm are proved within this paper. For vehicle to grid (V2G) concepts, battery degradation costs have to be considered. Therefore, common life cycle assumptions based on the battery state of charge (SoC) have been used to include degradation costs for different Li-Ion batteries into the graph search algorithm. An application of these optimisation algorithms, like the onboard dispatcher, which is used in the German fleet test "Flottenversuch Elektromobiliät". Grid impact calculations based on the optimisation algorithm are shown. --BEV,V2G,Plug-In-Vehicles (PHEV),optimisation,mobile dispatcher,demand side management,charging,combinatorial algorithm,graph search algorithm,indirect control by variable tariffs
Demand side management for domestic plug-in electric vehicles in power distribution system operation
No full textThe market for electric vehicles (EVs) has been rapidly expanded in the last few years due to the developments of battery technologies. It is expected that wide deployment of domestic owned electric vehicles offer the opportunities to both reduce carbon emission (CO2) and re-fuelling costs for domestic drivers. The batteries of these plug-in electric vehicles (PEVs) can initially be charged at home, from a standard domestic socket, or a special charger installed by the electricity supplier. A Monte Carlo Simulation (MCS) model based on details of UK domestic car use data has been developed in order to analyse the impact of battery charging demand on the power distribution system. These additional battery charging loads can act as responsive load on the system if appropriate control algorithms are applied to them. Demand Side Management has been regarded as one of the most effective approaches to manage EVs charging demand on power distribution system. This paper illustrates the potential for domestic electric vehicles to act as responsive load in order to prevent overloading the power distribution network
Plug-in estimation of level sets in a non-compact setting with applications in multivariate risk theory
No full textThis paper deals with the problem of estimating the level sets of an unknown distribution function . A plug-in approach is followed. That is, given a consistent estimator of , we estimate the level sets of by the level sets of . In our setting no compactness property is a priori required for the level sets to estimate. We state consistency results with respect to the Hausdorff distance and the volume of the symmetric difference. Our results are motivated by applications in multivariate risk theory. In this sense we also present simulated and real examples which illustrate our theoretical results.Level sets ; Distribution function ; Plug-in estimation ; Hausdorff distance ; Conditional Tail Expectation
3DScape: three dimensional visualization plug-in for Cytoscape
No full text3DScape is the first plug-in which enables three-
dimensional network visualization in Cytoscape. The extra dimension is useful in accommodating, visualizing, and distinguishing larger networks with multiple crossing connections.
Special features in 3DScape include 3D layout algorithms, mapping onto 3D models and animation effects on a series of expression data. 3DScape is available at http://www.rendware.co
The novel application of optimization and charge blended energy management control for component downsizing within a plug-in hybrid electric vehicle
No full textThe adoption of Plug-in Hybrid Electric Vehicles (PHEVs) is widely seen as an interim solution for the decarbonization of the transport sector. Within a PHEV, determining the required energy storage capacity of the battery remains one of the primary concerns for vehicle manufacturers and system integrators. This fact is particularly pertinent since the battery constitutes the largest contributor to vehicle mass. Furthermore, the financial cost associated with the procurement, design and integration of battery systems is often cited as one of the main barriers to vehicle commercialization. The ability to integrate the optimization of the energy management control system with the sizing of key PHEV powertrain components presents a significant area of research. Contained within this paper is an optimization study in which a charge blended strategy is used to facilitate the downsizing of the electrical machine, the internal combustion engine and the high voltage battery. An improved Equivalent Consumption Method has been used to manage the optimal power split within the powertrain as the PHEV traverses a range of different drivecycles. For a target CO2 value and drivecycle, results show that this approach can yield significant downsizing opportunities, with cost reductions on the order of 2%–9% being realizable
[Report to Chief J. E. Curry, by an unknown author #1]
No full textReport to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney
[Report to Chief J. E. Curry, by an unknown author #2]
No full textReport to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney
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