Create new trade object — newTrade • energyRt

Constructor for trade object.

Usage

newTrade(
  name = "",
  desc = "",
  commodity = character(),
  routes = data.frame(),
  trade = data.frame(),
  fixom = data.frame(),
  varom = data.frame(),
  invcost = data.frame(),
  olife = data.frame(),
  start = data.frame(start = -Inf, stringsAsFactors = FALSE),
  end = data.frame(end = Inf, stringsAsFactors = FALSE),
  vintage = data.frame(),
  capacity = data.frame(),
  aux = data.frame(),
  aeff = data.frame(),
  cap2act = 1,
  optimizeRetirement = FALSE,
  misc = list(),
  ...
)

Arguments

name

character. Name of the trade object, used in sets.

desc

character. Description of the trade object.

commodity

character. The traded commodity short name.

routes

data.frame. Source and destination regions. For bivariate trade define both directions in separate rows.

from: character. Source region.
to: character. Destination region.

trade

data.frame. Technical parameters of trade.

vintage: character. Vintage label selecting the variant this row applies to, NA for every vintage. See the vintage slot.
region: character. Region name to apply the parameter, NA for every region.
year: integer. Year to apply the parameter, NA for every year.
slice: character. Time slice to apply the parameter, NA for every slice.
trade: numeric. Trade volume.

fixom

data.frame. (not implemented!) Fixed operation and maintenance costs.

varom

data.frame. (not implemented!) Variable operation and maintenance costs.

invcost

data.frame. Investment cost of the trade capacity (per unit of capacity).

vintage: character. Vintage label selecting the variant this row applies to, NA for every vintage. See the vintage slot.
region: character. Region name to apply the parameter, NA for every region.
year: integer. Year to apply the parameter, NA for every year.
invcost: numeric. Investment cost.
wacc: numeric. Weighted average cost of capital used to annuitise invcost for this corridor. Overrides the model-wide wacc (see the model discount argument). The social discount rate is never used here.
payback: numeric. Cost-recovery period in years. Where given it replaces olife in the annuity AND in the years over which the annuity is charged, so the investment is repaid over payback years while the capacity keeps operating for its full operational life. Must be positive and not exceed olife. Unset (or 0) means recover over olife. Implemented for the GLPK solver only.
eac: numeric. Equivalent annual cost, supplied directly instead of being computed from invcost, wacc and the lifetime. Where given it wins; where absent the annuity is computed. Mutually exclusive with invcost per row.
retcost: numeric. Costs of early retirement of the trade capacity, default is 0.

olife

deprecated, use the olife column of vintage.

start

deprecated, use the start column of vintage.

end

deprecated, use the end column of vintage.

vintage

data.frame. Investment window and operational life of the trade object, one row per vintage. Replaces the former start, end and olife slots. A vintage is a separately investable variant that keeps the characteristics of its build year for its whole life, so several vintages of one corridor mean several capacities on the same (src, dst) route, with their flows summed in the commodity balance. region and cluster are present for a uniform shape across process classes but are unused for trade: its scope comes from the route endpoints, and routes already provides the multiplicity a cluster dimension would add.

vintage: character. Vintage label, normally the build year as a string. NA for an un-vintaged trade.
region: character. Unused for trade (no region slot); present for consistency with the other classes.
cluster: character. Unused for trade (no cluster dimension); present for consistency with the other classes.
start: integer. The first year the trade object is available for investment. Defaults to the vintage year.
end: integer. The last year the trade object is available for investment. Defaults to the vintage year.
olife: integer. Operational life of the trade object in years.

capacity

data.frame. (not implemented!) Capacity parameters of the trade object.

aux

data.frame. Auxiliary commodity of trade.

acomm: character. Name of the auxiliary commodity (used in sets).
unit: character. Unit of the auxiliary commodity.

aeff

data.frame. Auxiliary commodity efficiency parameters.

vintage: character. Vintage label selecting the variant this row applies to, NA for every vintage. See the vintage slot.
acomm: character. Name of the auxiliary commodity (used in sets).
region: character. Region name to apply the parameter, NA for every region.
year: integer. Year to apply the parameter, NA for every year.
slice: character. Time slice to apply the parameter, NA for every slice.
trade2ainp: numeric. Trade-to-auxiliary-input-commodity coefficient (multiplier).
trade2aout: numeric. Trade-to-auxiliary-output-commodity coefficient (multiplier).

cap2act

numeric. Capacity to activity ratio.

optimizeRetirement

logical. Incidates if the retirement of the trade object should be optimized. Also requires the same parameter in the model or scenario class to be set to TRUE to be effective.

misc

list. Additional information.

Value

trade object with given specifications.

Details

Trade objects are used to represent inter-regional exchange in the model. Without trade, every region is isolated and can only use its own resources. The class defines trade routes, efficiency, costs, and other parameters related to the process. Number of routes per trade object is not limited. One trade object can have a part or entire trade network of the model. However, it has a distinct name and all the routs will be optimized together. Create separate trade objects to optimize different parts of the trade network (aka transmission lines).

Examples

PIPELINE1 <- newTrade(
  name = "PIPELINE1",
  desc = "Some transport pipeline",
  commodity = "OIL",
  routes = data.frame(
    src = c("R1", "R2"),
    dst = c("R2", "R3")
  ),
  trade = data.frame(
    src = c("R1", "R2"),
    dst = c("R2", "R3"),
    teff = c(0.99, 0.98)
  ),
  olife = list(olife = 60)
)
draw(PIPELINE1)


PIPELINE2 <- newTrade(
  name = "PIPELINE2",
  desc = "Some transport pipeline",
  commodity = "OIL",
  routes = data.frame(
    src = c("R1", "R1", "R2", "R3"),
    dst = c("R2", "R3", "R3", "R2")
  ),
  trade = data.frame(
    src = c("R1", "R1", "R2", "R3"),
    dst = c("R2", "R3", "R3", "R2"),
    teff = c(0.912, 0.913, 0.923, 0.932)
  ),
  aux = data.frame(
    acomm = c("ELC", "CH4"),
    unit = c("MWh", "kt")
  ),
  aeff = data.frame(
    acomm = c("ELC", "CH4", "ELC", "CH4"),
    src = c("R1", "R1", "R2", "R3"),
    dst = c("R2", "R2", "R3", "R2"),
    csrc2ainp = c(.5, NA, .3, NA),
    cdst2ainp = c(.4, NA, .6, NA),
    csrc2aout = c(NA, .1, NA, .2)
  ),
  olife = list(olife = 60)
)
draw(PIPELINE2, node = "R1")

draw(PIPELINE2, node = "R2")

draw(PIPELINE2, node = "R3")