Create new storage object — newStorage • energyRt

Storage type of technological processes with accumulating capacity of a commodity.

Usage

newStorage(
  name = "",
  desc = "",
  commodity = character(),
  aux = data.frame(),
  region = character(),
  start = data.frame(),
  end = data.frame(),
  olife = data.frame(),
  charge = data.frame(),
  seff = data.frame(),
  aeff = data.frame(),
  af = data.frame(),
  fixom = data.frame(),
  varom = data.frame(),
  invcost = data.frame(),
  capacity = data.frame(),
  cap2stg = 1,
  fullYear = TRUE,
  weather = data.frame(),
  optimizeRetirement = FALSE,
  misc = list(),
  ...
)

Arguments

name

character. Name of the storage (used in sets).

desc

character. Description of the storage.

commodity

character. Name of the stored commodity.

aux

data.frame. Auxiliary commodities.

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

region

character. Region where the storage technology exists or can be installed.

start

data.frame. Start year when the storage is available for installation.

region: character. Regions where the storage is available for investment.
start: integer. The first year when the storage is available for investment.

end

data.frame. Last year when the storage is available for investment.

region: character. Region name to apply the parameter, NA for every region.
end: integer. The last year when the storage is available for investment.

olife

data.frame. Operational life of the storage technology, applicable to the new investment only, the operational life (retirement) of preexiting capacity is described in the stock slot.

region: character. Region name to apply the parameter, NA for every region.
olife: integer. Operational life of the storage technology in years.

charge

data.frame. Pre-charged level at the beginning of the operational cycle.

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 for which the charged level will be specified.
charge: numeric. Pre-charged or targeted level at the specified slice.

seff

data.frame. Storage efficiency parameters.

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.
stgeff: numeric. Storage decay annual rate.
inpeff: numeric. Input efficiency rate.
outeff: numeric. Output efficiency rate.

aeff

data.frame. Auxiliary commodities efficiency parameters.

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.
stg2ainp: numeric. Storaage-level-to-auxiliary-input-commodity coefficient (multiplier).
cinp2ainp: numeric. Input-commodity-to-auxiliary-input-commodity coefficient (multiplier).
cout2ainp: numeric. Output-commodity-to-auxiliary-input-commodity coefficient (multiplier).
stg2aout: numeric. Storage-level-to-auxiliary-output-commodity coefficient (multiplier).
cinp2aout: numeric. Input-commodity-to-auxiliary-output-commodity coefficient (multiplier).
cout2aout: numeric. Output-commodity-to-auxiliary-output-commodity coefficient (multiplier).
cap2ainp: numeric. Capacity-to-auxiliary-input-commodity coefficient (multiplier).
cap2aout: numeric. Capacity-to-auxiliary-output-commodity coefficient (multiplier).
ncap2ainp: numeric. New-capacity-to-auxiliary-input-commodity coefficient (multiplier).
ncap2aout: numeric. New-capacity-to-auxiliary-output-commodity coefficient (multiplier).
ncap2stg: numeric. New-capacity-to-storage-level coefficient (multiplier).

af

data.frame. Availability factor parameters.

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.
af.lo: numeric. Lower bound of the availability factor.
af.up: numeric. Upper bound of the availability factor.
af.fx: numeric. Fixed value of the availability factor. This parameter overrides af.lo and af.up.
cinp.lo: numeric. Lower bound of the input commodity availability factor.
cinp.up: numeric. Upper bound of the input commodity availability factor.
cinp.fx: numeric. Fixed value of the input commodity availability factor. This parameter overrides cinp.lo and cinp.up.
cout.lo: numeric. Lower bound of the output commodity availability factor.
cout.up: numeric. Upper bound of the output commodity availability factor.
cout.fx: numeric. Fixed value of the output commodity availability factor. This parameter overrides cout.lo and cout.up.

fixom

data.frame. Fixed operation and maintenance cost.

region: character. Region name to apply the parameter, NA for every region.
year: integer. Year to apply the parameter, NA for every year.
fixom: numeric. Fixed operation and maintenance cost for the specified sets.

varom

data.frame. Variable operation and maintenance cost.

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.
inpcost: numeric. Costs associated with the input commodity.
outcost: numeric. Costs associated with the output commodity.
stgcost: numeric. Costs associated with the storage level.

invcost

data.frame. Investment cost.

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. Overnight investment cost for the specified region and year.
wacc: numeric. Weighted average cost of capital. If not supplied, the discount from the model or scenario is used. (currently ignored)

capacity

data.frame. Capacity parameters of the storage technology.

region: character. Region name to apply the parameter, NA for every region.
year: integer. Year to apply the parameter, NA for every year.
cap: numeric. Capacity of the storage technology.
cap.lo: numeric. Lower bound of the storage capacity.
cap.up: numeric. Upper bound of the storage capacity.
cap.fx: numeric. Fixed value of the storage capacity. This parameter overrides cap.lo and cap.up.
ncap.lo: numeric. Lower bound of the new storage capacity.
ncap.up: numeric. Upper bound of the new storage capacity.
ncap.fx: numeric. Fixed value of the new storage capacity. This parameter overrides ncap.lo and ncap.up.
ret.lo: numeric. Lower bound of the storage capacity retirement.
ret.up: numeric. Upper bound of the storage capacity retirement.
ret.fx: numeric. Fixed value of the storage capacity retirement. This parameter overrides ret.lo and ret.up.

cap2stg

numeric. Charging and discharging capacity to the storing capacity inverse ratio. Can be used to define the storage duration.

fullYear

logical. If TRUE (default), the storage technology operates between parent timeframes through the year. The last time-slice in the timeframe is used as a preciding time-slice for the first time-slice in the the same group of time-slices within the parent timeframe. if FALSE, the storage charge and discchare cycle is limited to the parent timeframe. The last time-slice in the timeframe is used as a preciding time-slice for the first time-slice in the the same group of time-slices within the parent timeframe.

weather

data.frame. Weather factors multipliers.

weather: character. Name of the weather factor to apply.
waf.lo: numeric. Coefficient that links the weather factor with the lower bound of the availability factor.
waf.up: numeric. Coefficient that links the weather factor with the upper bound of the availability factor.
waf.fx: numeric. Coefficient that links the weather factor with the fixed value of the availability factor. This parameter overrides waf.lo and waf.up.
wcinp.lo: numeric. Coefficient that links the weather factor with the lower bound of the input commodity availability factor.
wcinp.up: numeric. Coefficient that links the weather factor with the upper bound of the input commodity availability factor.
wcinp.fx: numeric. Coefficient that links the weather factor with the fixed value of the input commodity availability factor. This parameter overrides wcinp.lo and wcinp.up.
wcout.lo: numeric. Coefficient that links the weather factor with the lower bound of the output commodity availability factor.
wcout.up: numeric. Coefficient that links the weather factor with the upper bound of the output commodity availability factor.
wcout.fx: numeric. Coefficient that links the weather factor with the fixed value of the output commodity availability factor. This parameter overrides wcout.lo and wcout.up.

optimizeRetirement

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

misc

list. List of additional parameters that are not used in the model but can be used for reference or user-defined functions. For example, links to the source of the storage data, or other metadata.

Value

storage object

Details

Storage can be used in combination with other processes, such as technologies, supply, or demand to represent complex technological chains, demand or supply technologies with time-shift. Operation of storage includes accumulation, storing, and release of the stored commodity. The storing cycle operates on the ordered time-slices of the commodity timeframe. The cycle is looped either on an annual basis (last time-slice of a year follows the first time slice of the same year) or within the parent time-frame (for example, when commodity time-frame is "HOUR" and the parent time-frame is "DAY" then the storage cycle will be a calendar day).

Examples

STG1 <- newStorage(
  name = "STG1",
  desc = "Storage description",
  commodity = "electricity",
  region = "R1",
  start = data.frame(region = "R1", start = 0),
  end = data.frame(region = "R1", end = 1),
  olife = data.frame(region = "R1", olife = 20),
  charge = data.frame(
    # region = "R1",
    year = 2020,
    # slice = "HOUR",
    charge = 0.1
  ),
  seff = data.frame(
    # region = "R1",
    # year = 2020,
    # slice = "HOUR",
    stgeff = 0.999,
    inpeff = 0.9,
    outeff = 0.9
  ),
  aeff = data.frame(
    acomm = "electricity",
    region = "R1",
    year = 2020,
    # slice = "HOUR",
    stg2ainp = 0.9,
    cinp2ainp = 0.1,
    cout2ainp = 0.2,
    stg2aout = 0.9,
    cinp2aout = 0.9,
    cout2aout = 0.9,
    cap2ainp = 0.9,
    cap2aout = 0.9,
    ncap2ainp = 0.9,
    ncap2aout = 0.9,
    ncap2stg = 0.9
  ),
  af = data.frame(
    region = "R1", year = 2020, slice = "HOUR",
    af.lo = 0.9, af.up = 0.9, af.fx = 0.9, cinp.up = 0.9,
    cinp.fx = 0.9, cinp.lo = 0.9, cout.up = 0.9,
    cout.fx = 0.9, cout.lo = 0.9
  ),
  fixom = data.frame(region = "R1", year = 2020, fixom = 0.9),
  varom = data.frame(
    region = "R1", year = 2020, slice = "HOUR",
    inpcost = 0.9, outcost = 0.9, stgcost = 0.9
  ),
  invcost = data.frame(
    region = "R1", year = 2020, invcost = 0.9,
    wacc = 0.9, retcost = 0.9
  ),
  capacity = data.frame(
    region = "R1", year = 2020, stock = 0.9,
    cap.lo = 0.9, cap.up = 0.9, cap.fx = 0.9, ncap.lo = 0.9,
    ncap.up = 0.9, ncap.fx = 0.9, ret.lo = 0.9, ret.up = 0.9,
    ret.fx = 0.9
  ),
  cap2stg = 1,
  fullYear = TRUE,
  weather = data.frame(
    weather = "sunny",
    waf.lo = 0.9,
    waf.up = 0.9,
    waf.fx = 0.9, wcinp.lo = 0.9,
    wcinp.fx = 0.9, wcinp.up = 0.9, wcout.lo = 0.9, wcout.fx = 0.9,
    wcout.up = 0.9
  ), 
  optimizeRetirement = FALSE,
  misc = list()
  )