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Smart V2G algorithm

Source: R/v2g.R
smart_v2g.Rd

Prototype vehicle-to-grid simulation built on top of smart_charging() helpers. The current implementation mirrors the classic workflow (responsiveness filtering, setpoint definition and scheduling placeholder) but it isolates the new optimisation pieces so the existing API remains untouched.

Usage

smart_v2g(
  sessions,
  opt_data,
  opt_objective = "grid",
  window_days,
  window_start_hour,
  responsive = NULL,
  power_th = 0,
  charging_power_min = 0,
  energy_min = 1,
  include_log = FALSE,
  show_progress = FALSE,
  lambda = 0
)

Arguments

sessions

tibble, sessions data set containig the following variables: "Session", "Timecycle", "Profile", "ConnectionStartDateTime", "ConnectionHours", "Power" and "Energy".

opt_data

tibble, optimization contextual data. The first column must be named datetime (mandatory) containing the date time sequence where the smart charging algorithm is applied, so only sessions starting within the time sequence of column datetime will be optimized. The other columns can be:

  • static: static power demand (in kW) from other sectors like buildings, offices, etc.

  • import_capacity: maximum imported power from the grid (in kW), for example the contracted power with the energy company.

  • export_capacity: maximum exported power from the grid (in kW), for example the contracted power with the energy company.

  • production: local power generation (in kW). This is used when opt_objective = "grid".

  • price_imported: price for imported energy (Euro/kWh). This is used when opt_objective = "cost".

  • price_exported: price for exported energy (Euro/kWh). This is used when opt_objective = "cost".

  • price_turn_down: price for turn-down energy use (Euro/kWh). This is used when opt_objective = "cost".

  • price_turn_up: price for turn-up energy use (Euro/kWh). This is used when opt_objective = "cost".

If columns of opt_data are user profiles names, these are used as setpoints and no optimization is performed for the corresponding user profiles.

opt_objective

character, optimisation objective being "none", "grid", "cost" or a value between 0 (cost) and 1 (grid). Only the "grid" mode is currently supported by the V2G prototype.

window_days

integer, number of days to consider as optimization window.

window_start_hour

integer, starting hour of the optimization window.

responsive

Named two-level list with the ratio (between 0 and 1) of sessions responsive to smart charging program. The names of the list must exactly match the Time-cycle and User profiles names. For example: list(Monday = list(Worktime = 1, Shortstay = 0.1))

power_th

numeric, power threshold (between 0 and 1) accepted from setpoint. For example, with power_th = 0.1 and setpoint = 100 for a certain time slot, then sessions' demand can reach a value of 110 without needing to schedule sessions.

charging_power_min

numeric. It can be configured in two ways: (1) minimum allowed ratio (between 0 and 1) of nominal power (i.e. Power column in sessions), or (2) specific value of minimum power (in kW) higher than 1 kW.

For example, if charging_power_min = 0.5 and method = 'curtail', sessions' charging power can only be curtailed until the 50% of the nominal charging power. And if charging_power_min = 2, sessions' charging power can be curtailed until 2 kW.

energy_min

numeric, minimum allowed ratio (between 0 and 1) of required energy.

include_log

logical, whether to output the algorithm messages for every user profile and time-slot

show_progress

logical, whether to output the progress bar in the console

lambda

numeric, penalty on change for the flexible load.

Value

list with setpoints, sessions and demand similar to smart_charging(). Scheduling is still charging-only while the V2G-specific session logic is under development.