Impact of optimal charging of electric vehicles on future generation portfolios

Abstract

Some rights reserved. For more information, please see the item record link above. Abstract-Battery electric vehicles are considered by many to be part of a series of measures necessary to reduce global carbon dioxide emissions and dependence on fossil fuel resources. The extent to which this is possible depends on how successfully they can be implemented into the broader system. This paper considers the power systems impact of different vehicle charging regimes. A test system with a high proportion of variable renewables was considered. Charging profiles were developed for slow, fast and controlled optimal charging and optimal generation portfolios were developed using a least-cost optimisation algorithm. It was found that over-night charging at the slow rate resulted in a reduction in the average cost of electricity by between 4.2 and 6% compared to the base-case. For the high charging rate cases, the average cost of electricity rises by between 3 and 7%. When the charging is controlled centrally and optimised so as to increase the minimum system load maximally, it is found that the average cost of electricity is reduced by between 4.5 and 8.2%. None of the above cases resulted in significant changes in the average CO2 emissions per unit electricity output. However, it was found that by increasing the minimum system load, optimal charging could facilitate additional inflexible generation such as variable renewables or nuclear fission plant. Where nuclear capacity is added to the generation portfolios based on optimal charging, average CO2 emissions per unit of electricity are seen to fall between 22 and 41% for the cases studied, with the average cost of electricity reducing by between 9.5 and 21.5%.

Methodology for modelling plug-in electric vehicles in the power system and cost estimates for a system with either smart or dumb electric vehicles

“…The PHEVs are dispatched according to a preset schedule, and no vehicle-to-grid (V2G) is considered. Article [7] considers the effect of EVs on future generation portfolios and uses a simplified model to dispatch EVs on top of the demand profile. V2G or the use of EVs as reserves was not considered.…”

Impact assessment of varying penetrations of electric vehicles on low voltage distribution systems

“…However, this may not be the case when this added demand coincides with existing peaks. This type of analysis is particularly relevant in countries that are planning to produce large amounts of their electrical energy from renewable energy sources [7]. Confining the charging of EVs to off-peak periods could see an increase in the utilisation of existing plant, although the extent to which the charging of EVs is controllable remains uncertain.…”

Optimal charging of an electric vehicle using a Markov decision process

“…The time-invariant parameters are to be estimated so that an appropriate probability distribution is fitted to the duration of the trips. The time-invariant parameters are estimated by maximizing the likelihood given in (7). For a given number of driving states, the transition probabilities can be estimated using the approach in [22].…”

“…For this reason, EVs have received increased interest from the scientific community in recent years (detailed literature reviews of the state of the art can be found in [1] and [2]). Special attention has been given to the analysis of the effect of EVs integration on the electricity demand profile [3,4], emissions [5] and social welfare [6,7,8], and to the design of charging schemes that avoid increasing the peak consumption [9,10], help mitigate voltage fluctuations and overload of network components in distribution grids [11], and/or get the maximum economic benefit from the storage capability of EVs within a market environment, either from the perspective of a single vehicle [12,13] or the viewpoint of an aggregator of EVs [14,15]. In all these publications, though, and more generally in the technical literature on the topic, the charging problem of an EV is addressed either by considering deterministic driving patterns, when the focus is placed on the management of a single vehicle, or by aggregating the driving needs of different EV users, when the emphasis is on modeling a whole fleet of EVs.…”