storage: Create new storage object

In olugovoy/energyRt: Energy systems modeling toolbox in R, development version

Create new storage object

Description

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.

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).

Value

storage object

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()
  )

olugovoy/energyRt documentation built on Nov. 21, 2024, 2:24 a.m.