Compute optimal candidates for H2 system — MultiStock_H2_Investment_reward_compute

Search optimal solution for bounded candidates for the H2 systems including storage, must-run clusters and flexibles clusters.

Usage

MultiStock_H2_Investment_reward_compute_once(
  areas_invest,
  max_ite,
  list_storage_bounds,
  storage_points_nb,
  candidates_types_gen,
  penalty_low = 5000,
  penalty_high = 5000,
  penalty_final_level = 5000,
  opts,
  mc_years_optim,
  cvar = 1,
  storage_annual_cost,
  nb_sims = 51,
  parallelprocess = F,
  nb_sockets = 0,
  unspil_cost = 3000,
  file_intermediate_results,
  list_ratio_max_hydro,
  remove_cluster = F
)

Arguments

areas_invest: Vector of characters of the names of areas to optimize.
max_ite: Integer. Maximum number of iterations for each area.
list_storage_bounds: List of vectors of integers of length 2, with the form (min, max) for each area.
storage_points_nb: Integer. Number of storage points to test at each iteration. Must be >3 to update bounds at each iterations and approach solution.
candidates_types_gen: Data_frame with column names : c(index, name, type, TOTEX, Marg_price, Part_fixe, Prix_fixe, Borne_min, Borne_max, Points_nb, Zone). Each row describes a cluster candidate. The index should correspond to the index of the candidate in candidates_data. The name is a character, the type is either "cluster_flexible" or "cluster_bande", TOTEX is in eur/MW/year, Marg_price is in eur/MWh. Part_fixe is the fixed part for a variable cluster between 0 and 1, Prix_fixe in eur/MWh is its price. Borne_min and Borne_max are in MW, Points_nb is an integer (number of candidates tested at each iteration, it should be at least 4). Zone is a character containing the name of the area where to propose the candidate.
penalty_low: Integer. Penalty for lower guide curve.
penalty_high: Integer. Penalty for higher guide curve.
penalty_final_level: Integer. Penalty for higher and lower final level.
opts: List of study parameters returned by the function antaresRead::setSimulationPath(simulation="input") in input mode.
mc_years_optim: Vector of integers. Monte Carlo years to perform the optimization.
cvar: Numeric in [0,1]. The probability used in cvar algorithm.
storage_annual_cost: Numeric. Annual cost of storage in eur/MWh.
nb_sims: Integer. Number of simulations to launch to evaluate reward.
parallelprocess: Boolean. True to compute Water values with parallel processing.
nb_sockets: Integer. Number of sockets for parallel processing
unspil_cost: Numeric. Unspilled energy cost in eur/MW for all concerned areas.
file_intermediate_results: Character. Local path to save intermediate results.
list_ratio_max_hydro: List of vectors. For each area, give the maximum generating (turb)/pumping (pump) capacity ratio
remove_cluster: Boolean. Should cluster candidate be removed before running the investment process

Value

a list containing for each area detailed results (best candidate, all total costs, reward function, optimization time)