Overview

Vehicle represents a type of vehicle and is most commonly used to model electric vehicles, but may also model plug-in-hybrid electric vehicles (PHEV) or internal combustion (ICE) powered vehicles. Vehicle objects can represent multiple physical vehicles via the Units property. This allows you to expand the size of the fleet being modeled without having to create additional Vehicle objects i.e. it is the 'key' property. Thus, each Vehicle object represents a specific vehicle type and usage pattern e.g. you might create one object to represent a daily-driven domestic commuting vehicle of given efficiency and battery size, and another to represent a commercial vehicle with a very different range, efficiency and usage pattern.

Electric Vehicles

Electric Vehicle objects connect to one or more Charging Station objects via the Charging Stations membership. Vehicles move between charging stations using the Share property i.e. a share value of 100 means the vehicle is present at the charging station, 0 means it is not present. The Share property represents the probability the vehicle is connected to a given charging station.

You may choose between a 'simple' model in which the charging profile is known upfront and no battery storage is modeled, or a 'detailed' model where the travel demand is the input and the charging demand and battery state-of-charge is modeled explicitly.

Simple Model

The simplest EV representation requires only the input of a Fixed Load, which represents the (known) charging load for a single vehicle 'unit'. The Vehicle must still be connected to at least one Charging Station which draws the appropriate load from the grid. When Fixed Load is defined the battery storage of the vehicle is not modeled so properties like Capacity and Max SoC, and Demand are ignored. Like any property, the values of Fixed Load can be input from a Data File or made stochastic with a Variable.

You may optionally define the Vehicle Efficiency (Wh/km) and Charge Efficiency (%) so that the distance travelled can be computed - see below regarding emission constraints based on distance travelled.

Detailed Model

In this model the battery energy storage is modeled explicitly. You define the battery Capacity in kilowatt-hours, and Efficiency in watt-hours per kilometre (metric) or watt-hours per mile (Imperial US). Together these properties determine the vehicle Range for any given state-of-charge (SoC). The Initial SoC defines the initial charge, while the properties Max SoC and Min SoC place constraints on how full or empty the battery is allowed to get.

Vehicle Demand is a dynamic property representing the distance travelled across time (km or miles). Once the Vehicle is connected to at least one charging stations, as indicated by the Share property being non-zero, the vehicle raises a charging demand on the Charging Station(s). The vehicle will charge at the Charging Station Max Charge Rate (in proportion to the Share property) until the SoC returns to the Initial SoC level or the vehicle disconnects from the charging station(s).

V1G and V2G

Charging is subject to losses according to the Charge Efficiency property and the Losses are reported. According to the properties defined on the Charging Station(s), the Vehicle charging demand might be deferred partially or fully for a number of hours ('V1G') and/or the Vehicle may discharge from its battery to the electric grid ('V2G'). Discharge is subject to losses according to the Discharge Efficiency property.

Emissions and Commodities

Hybrid or ICE vehicles consume fuel via the Vehicle Commodities membership. The Commodities in this collection should be of energy type or convertible to energy with the Commodity Energy Density property.

Vehicles can produce or abate emissions via the Emission Vehicles membership. The amount of emissions (+ve value) or abatement (-ve value) is defined with either or both the Distance Coefficient and Charging Coefficient properties.

Ancillary Services

Vehicles can provide ancillary services (frequency control and spinning reserve) as defined by the Charging Station(s).

How to use Vehicle

The following guide will help you get started using the Vehicle and Charging Station classes:

For an electric vehicle, decide if you want to use the 'simple' or 'detailed' representation of the battery/charging load.
If using the 'simple' model, define the Fixed Load profile e.g. from a Data File or Variable and optional Efficiency.
For the 'detailed' model define the Capacity and Efficiency and then the number of Units i.e. the initial number of vehicles represented by the object - see below regarding expansion. As a guide, typical passenger car battery sizes are in the range 30-120 kWh and efficiencies between 150-250 Wh/km. Then define the Demand as a time series e.g. using a Data File or patterned entries. For example, if the vehicle represents a car used for daily commuting you might define a demand of 30 km at 8am and 6pm each weekday and zero outside those hours. Note that, you can 'smear' the travel over a range of hours rather than having discrete travel lumps i.e. you can input the 'expected' value of travel for each hour of the day. Doing this will allow you to use stochastics in your model by connecting the Demand property to a Variable object, to create multiple samples that will produce a more realistic result than all Vehicle 'units' performing the same discrete travel events simultaneously.
Connect your Vehicle to one or more Charging Station objects and use the Share property to indicate where the Vehicle is (or is likely to be) at any given hour. For example you might charge the EV at home and at work so the Share property would be 100% for the "Home" charging station during the weekend and overnight, 0% during the travel time and 100% at the "Work" charging station during work hours and zero at other times. Again, you can use a Data File or patterned entries and also connect to a Variable so the location of the Vehicle is modeled as probabilistic.
Optionally, set the Charge Efficiency and Discharge Efficiency. As a guide, charge efficiencies for EVs are generally in the range 95-99%, while discharge efficiency is more variable 50-75%.
Follow the Charging Station page to set up your charging stations including connecting to the electric grid and optionally to ancillary services co-optimization.
Select the desired reporting properties. The key outputs are Distance, Charging, Discharging ('V2G') and SoC, along with Charge Cost

Discharge Revenue

Vehicle Expansion

Vehicle supports expansion in LT Plan. The key input properties are Max Units Built and Purchase Cost and optionally FO&M Charge. Purchase costs can be treated as a lump sum or automatically annualized by defining WACC and Economic Life. Other available constraints related to expansion are:

Vehicle retirement occurs automatically after the Technical Life. Disposal of Vehicles can be optimized if you define Max Units Retired and will incur a Disposal Cost.

Vehicle Class