270,679 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
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
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
Osteomorphological differences in the appendicular skeleton of Antidorcas marsupialis (Zimmerman, 1780) and Antidorcas bondi (Cooke & Wells, 1951) (Mammalia, Bovidae) with notes on the osteometry of Antidorcas bondi
No full textThe 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
Potential of plug-in electric vehicles for supporting regional power distribution system operation with high penetration of wind generation
No full textWith wider deployment of the plug-in electric vehicle (PEV), a power distribution network operator (DNO) would expect increasing domestic demand due to large numbers of vehicles charging. This could lead potentially to overloading of power system assets unless appropriate demand side management is in place. The UK coalition government has made a commitment to increase the amount of renewable generation capacity. To ensure 15% of energy demand is met from renewable sources by 2020, a massive amount of wind generation needs to be installed across the country. This paper presents the potential opportunities from using domestic owned electric vehicles to support the operation of regional power distribution networks in the context of a high penetration of wind generation
Plug and play : the impact of plug-in frequency on the potential of vehicle to grid to support transport and electricity system decarbonisation
No full textVehicle-to-grid (V2G) from electric vehicles (EVs) represents an opportunity to provide transitioning electricity systems with battery storage as they face increasing shares of variable renewable generation. However, whilst the availability of V2G as dispatchable storage depends on the travel and charging habits of drivers, there is scarce experience of managing portfolios of EVs in this way. This paper investigates the impact of plug-in frequency – given real-life travel data – on the potential of V2G to reduce i) consumer bills and ii) carbon emissions of charging. In doing so, we investigate the extent to which consumers are incentivised to participate in V2G, how this might change based on different charging behaviours and what the implications are for V2G as a storage asset. Two models of plug-in behaviour are input into a time-coupled optimisation that schedules EV (dis)charging to minimise the net cost of an EV’s required energy gain within network constraints, simulating how V2G could be dispatched by a ‘load controller’ in a liberalised electricity market. The cost minimisation is based on the Octopus Agile V2G tariff in January 2021, which is matched to GB grid carbon intensity data from National Grid ESO for the same period. It was found that, on the basis of the time range studied, V2G can reduce the average price paid for EV-charging electricity by 30-68% versus a flat tariff – with the lower end of that range representing a case where consumers only plug in when they ‘need’ to, and the higher end representing the case where consumers plug in whenever their cars are at home. It was also found that due to the positive correlation between price and carbon, optimising for price also resulted in reductions in carbon intensity of the EV-charging electricity by 8-12% compared to uncontrolled charging, with the range representing the same cases as before. Taking into account a review of battery degradation costs from V2G, using an EV’s battery in this manner only makes financial sense to the owner if they maximise their plug-in frequency; this, alongside the increased savings, should provide an incentive to owners to plug in as much as possible – thereby maximising storage resource for a low carbon electricity system
Plug and play : the impact of plug-in frequency on the potential of vehicle to grid to support transport and electricity system decarbonisation
No full textVehicle-to-grid (V2G) from electric vehicles (EVs) represents an opportunity to provide transitioning electricity systems with battery storage as they face increasing shares of variable renewable generation. However, whilst the availability of V2G as dispatchable storage depends on the travel and charging habits of drivers, there is scarce experience of managing portfolios of EVs in this way. This paper investigates the impact of plug-in frequency – given real-life travel data – on the potential of V2G to reduce i) consumer bills and ii) carbon emissions of charging. In doing so, we investigate the extent to which consumers are incentivised to participate in V2G, how this might change based on different charging behaviours and what the implications are for V2G as a storage asset. Two models of plug-in behaviour are input into a time-coupled optimisation that schedules EV (dis)charging to minimise the net cost of an EV’s required energy gain within network constraints, simulating how V2G could be dispatched by a ‘load controller’ in a liberalised electricity market. The cost minimisation is based on the Octopus Agile V2G tariff in January 2021, which is matched to GB grid carbon intensity data from National Grid ESO for the same period. It was found that, on the basis of the time range studied, V2G can reduce the average price paid for EV-charging electricity by 30-68% versus a flat tariff – with the lower end of that range representing a case where consumers only plug in when they ‘need’ to, and the higher end representing the case where consumers plug in whenever their cars are at home. It was also found that due to the positive correlation between price and carbon, optimising for price also resulted in reductions in carbon intensity of the EV-charging electricity by 8-12% compared to uncontrolled charging, with the range representing the same cases as before. Taking into account a review of battery degradation costs from V2G, using an EV’s battery in this manner only makes financial sense to the owner if they maximise their plug-in frequency; this, alongside the increased savings, should provide an incentive to owners to plug in as much as possible – thereby maximising storage resource for a low carbon electricity system
The Causal Effect of Parent’s Schooling on Children’s Schooling: A Comparison of Estimation Methods
No full textRecent studies that aim to estimate the causal link between the education of parents and their children provide evidence that is far from conclusive. This paper explores why. There are a number of possible explanations. One is that these studies rely on different data sources, gathered in different countries at different times. Another one is that these studies use different identification strategies. Three identification strategies that are currently in use rely on: identical twins; adoptees; and instrumental variables. In this paper we apply each of these three strategies to one particular Swedish data set. The purpose is threefold: (i) explain the disparate evidence in the recent literature; (ii) learn more about the quality of each identification procedure; and (iii) get at better perspective about intergenerational effects of education. We find that the three identification strategies all produce intergenerational schooling estimates that are lower than the corresponding OLS estimates, indicating the importance of accounting for ability bias. But interestingly, when applying the three methods to the same data set, we are able to fully replicate the discrepancies across methods found in the previous literature. Our findings therefore indicate that the estimated impact of parental education on that of their child in Sweden does depend on identification, which suggests that country and cohort differences do not lie behind the observed disparities. Finally, we conclude that income is a mechanism linking parent’s and children’s schooling, that can partly explain the diverging results across methods.intergenerational mobility, education, causation, selection, identification
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