RESUMO
Abstract The urban transport electrification is going upward in many countries. However, this electrification faces many hurdles, among them, the limited range and cost that present-day electric vehicles (EV) have. This paper analyzes which Battery Electric Vehicles (BEV) could meet the current car travel needs in different uses. The results from a survey about distance travelled in daily trips in La Havana, allow the assessment of maximum average daily distance travel (MADT) by the private owners, cars in public service, taxis and leasing. The Lognormal distribution adjusts to MADT´s histogram in each group, and yields estimates characterizing its behavior. The use of a database of BEV with more than 60 electric vehicles allows to select an appropriate model for each use. The BEV´s range is normally expressed using several driving cycles, being EPA (Environmental Protection Agency) the most adequate, but the range by EPA is not always available. A regression analysis was made to obtain the EPA range as a function of range by others driving cycles. Finally, a Total Cost of Operation (TCOp) is calculated considering the purchase cost, energy cost, maintenance, etc. The outcomes are that for the private use, only small BEV with a strong subsidy or battery leasing can compete with an Internal Combustion Engine Vehicle (ICEV). In the public, taxis and leasing sector, the BEV are competitive in several years. The daily mileage and electricity cost are decisive. The use of renewable energy to charge batteries can reduce this period to some extent.
RESUMO
Abstract The electrical sector is under constant evolution. One of the areas refers to the consumers that come to be generators, implementing distributed generation, interconnected to a smart grid. This article discusses the improvement of an algorithm, already presented in the literature, to make the best temporal allocation of loads, electric vehicle, storage and many sources of generation, aiming at the maximum financial performance, that is, the lowest value for the energy invoice The modeling consists of a Mixed Integer Linear Programming (MILP) algorithm, which considers each component of the system and weighs the maintenance and shelf life of storage devices, basically batteries, loads that can be reallocated and the concept of Vehicle-to-grid, performing a daily analysis. The simulation has considered the hypothetical case of a residence, in which are included storage, electric vehicle and redistribution of loads, as well as wind and solar generation. Several scenarios are simulated, with or without the presence of some of the components. The results indicate that the simplest model, only redistributing the loads, can provide a sensible monetary savings of approximately 60%, while with the application of all the components modeled, there can be a reduction in the invoice of 90%.