Dev dynamic model

DESCRIPTION

@@ -18,6 +18,6 @@ Imports:
     data.table,
     magrittr,
     plotly
-RoxygenNote: 5.0.1
+RoxygenNote: 6.0.1
 Suggests: knitr
 VignetteBuilder: knitr

NAMESPACE

@@ -11,8 +11,11 @@ export(filter_output_areas)
 export(filter_output_links)
 export(get_playlist)
 export(get_whole_simulation_name)
+export(investment_path)
 export(read_candidates)
 export(read_options)
+export(read_studies)
+export(read_studies_OLD)
 export(report)
 export(run_simulation)
 export(set_first_day)

R/TEST_read_studies.R

@@ -0,0 +1,56 @@
+read_studies <- function(studies_file_name)
+{
+  # read file
+  param_data <- scan(studies_file_name, what=character(), sep="", quiet = TRUE)
+
+  #initialisation du data frame 
+  #search of the first line of the studies.ini file
+
+  empty_line=TRUE
+  first_line=1
+
+  while(empty_line&&first_line<=length(param_data)){
+  option_name <- strsplit(param_data[first_line], "=")[[1]][1]
+    if(option_name == ""){
+      first_line<-first_line+1
+    } # empty line
+    else{
+      option_value <- strsplit(param_data[first_line], "=")[[1]][2]
+      empty_line=FALSE
+    }
+  }
+  # remove white spaces in the beginning and the end
+  option_name <- sub("^\\s+", "", option_name)
+  option_name <- sub("\\s+$", "", option_name)
+  option_value <- sub("^\\s+", "", option_value)
+  option_value <- sub("\\s+$", "", option_value)
+
+  #initialisation of the data frame
+  studies<-data.frame(option_name,option_value)
+  names(studies)<-c("simulated_years","paths")
+
+
+  # go through every line of the file from the first non-empty line to the end
+  for(line in (first_line+1):length(param_data))
+  {
+    # read option and value
+    option_name <- strsplit(param_data[line], "=")[[1]][1]
+    if(option_name == ""){next} # empty line
+
+    option_value <- strsplit(param_data[line], "=")[[1]][2]
+
+    # remove white spaces in the beginning and the end
+    option_name <- sub("^\\s+", "", option_name)
+    option_name <- sub("\\s+$", "", option_name)
+    option_value <- sub("^\\s+", "", option_value)
+    option_value <- sub("\\s+$", "", option_value)
+
+    df<-data.frame(option_name,option_value)
+    names(df)<-c("simulated_years","paths")
+
+    studies<-rbind(df,studies)
+  }
+  return(studies)
+}
+
+TEST<-read_studies("D:/testdavid.ini")

R/benders.R

@@ -38,12 +38,14 @@ benders <- function(path_solver, display = TRUE, report = TRUE, clean = TRUE, pa
   assertthat::assert_that(file.copy(from = paste0(opts$studyPath, "/settings/generaldata.ini"), 
             to = paste0(opts$studyPath, "/settings/generaldata_tmpsvg.ini"),
             overwrite = TRUE))
-  
+
   # read expansion planning options
-  exp_options <- read_options(opts)
+  option_file_name <- paste0(opts$studyPath,"/user/expansion/settings.ini")
+  exp_options <- read_options(option_file_name)
 
   # read investment candidates file
-  candidates <- read_candidates(opts)
+  candidates_file_name <- paste0(opts$studyPath,"/user/expansion/candidates.ini")
+  candidates <- read_candidates(candidates_file_name,opts)
   n_candidates <- length(candidates)
   assertthat::assert_that(n_candidates > 0)
 
@@ -118,8 +120,8 @@ benders <- function(path_solver, display = TRUE, report = TRUE, clean = TRUE, pa
     }
     else
     { out <- c$max_invest/2}
-    return(out)}))
-
+    #return(out)}))
+  return(0)}))
   row.names(x$invested_capacities) <- sapply(candidates, FUN = function(c){c$name})
 
 
@@ -477,9 +479,10 @@ benders <- function(path_solver, display = TRUE, report = TRUE, clean = TRUE, pa
 
 
   # add information in the output file
-  x$expansion_options <- read_options(opts)
+  option_file_name_2 <- paste0(opts$studyPath,"/user/expansion/settings.ini")
+  x$expansion_options <- read_options(option_file_name_2)
   x$study_options <- opts
-  x$candidates <- read_candidates(opts)
+  x$candidates <- read_candidates(candidates_file_name,opts)
 
   # reset options of the ANTARES study to their initial values
   assertthat::assert_that(file.remove(paste0(opts$studyPath, "/settings/generaldata.ini")))

R/benders_tools.R

@@ -277,25 +277,26 @@ update_weekly_cuts <- function(current_it, candidates, output_area_w, output_lin
 
       if (y != last_y || w != last_w) {script_cost <- paste0(script_cost, "\n")}
 
-      
+
       for(c in 1:n_candidates)
       {
         if(candidates[[c]]$has_link_profile)
         {
-          first_h <- 7*24*(w-1)+1
-          last_h <- 7*24*w
+            first_h <- 7*24*(w-1)+1
+            last_h <- 7*24*w
           tmp_rentability <- sum(as.numeric(subset(output_link_h, link == candidates[[c]]$link & mcYear == y & timeId >= first_h & timeId <= last_h)$"MARG. COST")* candidates[[c]]$link_profile[first_h:last_h,1]) - candidates[[c]]$cost /52
+          #tmp_rentability <- sum(as.numeric(subset(output_link_h, link == candidates[[c]]$link & mcYear == y & timeId >= first_h & timeId <= last_h)$"MARG. COST")* candidates[[c]]$link_profile[first_h:last_h,1])
         }
         else
         {
           tmp_rentability <- sum(as.numeric(subset(output_link_w, link == candidates[[c]]$link & mcYear == y & timeId == w)$"MARG. COST")) - candidates[[c]]$cost /52
+          #tmp_rentability <- sum(as.numeric(subset(output_link_w, link == candidates[[c]]$link & mcYear == y & timeId == w)$"MARG. COST"))
         }
-
         script_rentability <- paste0(script_rentability, current_it$id, " ", y , " ", w , " ", candidates[[c]]$name, " ", tmp_rentability)
 
         if (c != n_candidates || y != last_y || w != last_w)
         {
-          script_rentability <- paste0(script_rentability, "\n")
+           script_rentability <- paste0(script_rentability, "\n")
         }
       }
     }
@@ -392,3 +393,237 @@ convergence <-  function(best_sol, best_under, benders_options)
   # is convergence of the relaxed problem reached ?
   return((best_sol - best_under) <= opt_gap)
 }
+
+#' Update costs and rentability files of the weekly cuts
+#' Create files in_weeklyrentability.txt and in_weeklycuts.txt which
+#' will be later read by AMPL as input of the master problem
+#' 
+#' 
+#' @param current_it
+#' list of current iteration characteristics
+#' @param candidates
+#'   list of investment candidates, as returned by
+#'   \code{\link{read_candidates}}
+#' @param output_area_w
+#'   antaresDataList of all the areas of the study with a weekly time step
+#' @param output_link_w
+#'   antaresDataList of all the links of the study with a weekly time step
+#' @param output_link_h
+#'   antaresDataList of all the links of the study with a weekly time step
+#' @param inv_cost
+#'   investments costs of this iteration
+#' @param tmp_folder
+#'   temporary folder in which to write the files
+#' @param benders_options
+#'   list of benders decomposition options, as returned by
+#'   \code{\link{read_options}}.
+#'   
+#' @return nothing
+#' 
+#' 
+update_weekly_cuts_path <- function(current_it, simulated_year, candidates, output_area_w, output_link_w, output_link_h, inv_cost, tmp_folder, benders_options)
+{
+  #INV COST TO BE REMOVER FROM THE FUNCTION
+  # compute a few intermediate variables
+  n_candidates <- length(candidates)
+  last_w <- current_it$weeks[length(current_it$weeks)]
+  last_y <- current_it$mc_years[length(current_it$mc_years)]
+
+  # initiate scripts
+  script_rentability  <-  ""
+  script_cost <- ""
+
+  # for every mc years and every week
+  for(y in current_it$mc_years)
+  {
+    for(w in current_it$weeks)
+
+    {
+
+      if(benders_options$uc_type == "relaxed_fast")
+      {
+        # in that case, non-linear cost has to be removed because they are computed in a post-processing and are not
+        # part of the ANTARES optimization  
+        w_cost <- sum(as.numeric(subset(output_area_w, mcYear == y & timeId == w)$"OV. COST")) +
+          sum(as.numeric(subset(output_link_w, mcYear == y & timeId == w)$"HURDLE COST")) -
+          sum(as.numeric(subset(output_area_w, mcYear == y & timeId == w)$"NP COST"))
+      }
+      else
+      {
+        w_cost <- sum(as.numeric(subset(output_area_w, mcYear == y & timeId == w)$"OV. COST")) +
+          sum(as.numeric(subset(output_link_w, mcYear == y & timeId == w)$"HURDLE COST"))
+      }
+
+      script_cost <- paste0(script_cost, simulated_year, " ", current_it$id, " ", y , " ", w, " ", w_cost)
+
+
+      if (y != last_y || w != last_w) {script_cost <- paste0(script_cost, "\n")}
+
+
+      for(c in 1:n_candidates)
+      {
+        if(candidates[[c]]$has_link_profile)
+        {
+          first_h <- 7*24*(w-1)+1
+          last_h <- 7*24*w
+          #tmp_rentability <- sum(as.numeric(subset(output_link_h, link == candidates[[c]]$link & mcYear == y & timeId >= first_h & timeId <= last_h)$"MARG. COST")* candidates[[c]]$link_profile[first_h:last_h,1]) - candidates[[c]]$cost /52
+          tmp_rentability <- sum(as.numeric(subset(output_link_h, link == candidates[[c]]$link & mcYear == y & timeId >= first_h & timeId <= last_h)$"MARG. COST")* candidates[[c]]$link_profile[first_h:last_h,1])
+        }
+        else
+        {
+          #tmp_rentability <- sum(as.numeric(subset(output_link_w, link == candidates[[c]]$link & mcYear == y & timeId == w)$"MARG. COST")) - candidates[[c]]$cost /52
+          tmp_rentability <- sum(as.numeric(subset(output_link_w, link == candidates[[c]]$link & mcYear == y & timeId == w)$"MARG. COST"))
+        }
+        script_rentability <- paste0(script_rentability, simulated_year, " ", current_it$id, " ", y , " ", w , " ", candidates[[c]]$name, " ", tmp_rentability)
+
+        if (c != n_candidates || y != last_y || w != last_w)
+        {
+          script_rentability <- paste0(script_rentability, "\n")
+        }
+      }
+    }
+  }
+  write(script_rentability, file = paste0(tmp_folder, "/in_weeklyrentability.txt"), append = TRUE )
+  write(script_cost, file = paste0(tmp_folder, "/in_weeklycuts.txt"), append = TRUE )
+}
+#' Update costs and rentability files of the average cuts
+#' Create files in_avgrentability.txt and in_avgcuts.txt which
+#' will be later read by AMPL as input of the master problem
+#' 
+#' 
+#' @param current_it
+#'   list of current iteration characteristics
+#' @param candidates
+#'   list of investment candidates, as returned by
+#'   \code{\link{read_candidates}}
+#' @param output_link_s
+#'   antaresDataList of all the links of the study with a yearly time step
+#'   and averaged on all MC years
+#' @param output_link_h_s
+#'   antaresDataList of all the links of the study with an hourly time step
+#'   and averaged on all MC years
+#' @param op_cost
+#'   operation costs of this iteration
+#' @param n_w
+#'   number of weeks per year
+#' @param tmp_folder
+#'   temporary folder in which to write the files
+#' @param benders_options
+#'   list of benders decomposition options, as returned by
+#'   \code{\link{read_options}}.
+#'   
+#' @return nothing
+#' 
+
+update_average_cuts_path <- function(current_it, simulated_year, candidates, output_link_s, output_link_h_s, op_cost, n_w, tmp_folder, benders_options)
+{
+  n_candidates <- length(candidates)
+
+  #write in_avgcuts.txt file 
+  script  <-  paste0(simulated_year," ", current_it$id, " ", op_cost)
+  write(script, file = paste0(tmp_folder, "/in_avgcuts.txt"), append = TRUE )      
+
+  # write in_avgrentability.txt file
+  script  <-  ""
+  for (c in 1:n_candidates)
+  {
+    if(candidates[[c]]$has_link_profile)
+    {
+      len = length(subset(output_link_h_s, link == candidates[[c]]$link)$"MARG. COST")
+      #tmp_rentability <- sum(as.numeric(subset(output_link_h_s, link == candidates[[c]]$link)$"MARG. COST")*candidates[[c]]$link_profile[1:len, 1]) - candidates[[c]]$cost * n_w / 52
+      tmp_rentability <- sum(as.numeric(subset(output_link_h_s, link == candidates[[c]]$link)$"MARG. COST")*candidates[[c]]$link_profile[1:len, 1])
+    }
+    else
+    {
+      #tmp_rentability <- sum(as.numeric(subset(output_link_s, link == candidates[[c]]$link)$"MARG. COST")) - candidates[[c]]$cost * n_w / 52
+      tmp_rentability <- sum(as.numeric(subset(output_link_s, link == candidates[[c]]$link)$"MARG. COST")) 
+    }
+    script <- paste0(script, simulated_year," ", current_it$id, " ", candidates[[c]]$name, " ", tmp_rentability)
+    if (c != n_candidates) { script <- paste0(script, "\n")}
+  }
+  write(script, file = paste0(tmp_folder, "/in_avgrentability.txt"), append = TRUE )
+}
+#' Update costs and rentability files of the yearly cuts
+#' Create files in_yearlyrentability.txt and in_yearlycuts.txt which
+#' will be later read by AMPL as input of the master problem
+#' 
+#' 
+#' @param current_it
+#'   list of current iteration characteristics
+#' @param candidates
+#'   list of investment candidates, as returned by
+#'   \code{\link{read_candidates}}
+#' @param output_area_y
+#'   antaresDataList of all the areas of the study with a yearly time step
+#' @param output_link_y
+#'   antaresDataList of all the links of the study with a yearly time step
+#' @param output_link_h
+#'   antaresDataList of all the links of the study with an hourly time step
+#' @param inv_cost
+#'   investments costs of this iteration
+#' @param n_w
+#'   number of weeks per year
+#' @param tmp_folder
+#'   temporary folder in which to write the files
+#' @param benders_options
+#'   list of benders decomposition options, as returned by
+#'   \code{\link{read_options}}.
+#'   
+#' @return nothing
+#' 
+#' 
+update_yearly_cuts_path <- function(current_it, simulated_year, candidates, output_area_y,output_link_y, output_link_h, inv_cost, n_w, tmp_folder, benders_options)
+{
+  # compute a few intermediate variables
+  n_candidates <- length(candidates)
+  last_y <- current_it$mc_years[length(current_it$mc_years)]
+
+  # initiate scripts
+  script_rentability  <-  ""
+  script_cost <- ""
+
+  # for every mc years and every week
+  for(y in current_it$mc_years)
+  {
+    if(benders_options$uc_type == "relaxed_fast")
+    {
+      # in that case, non-linear cost has to be removed because they are computed in a post-processing and are not
+      # part of the ANTARES optimization  
+      y_cost <- sum(as.numeric(subset(output_area_y, mcYear == y)$"OV. COST")) +
+        sum(as.numeric(subset(output_link_y, mcYear == y)$"HURDLE COST")) -
+        sum(as.numeric(subset(output_area_y, mcYear == y)$"NP COST"))
+    }
+    else
+    {
+      y_cost <- sum(as.numeric(subset(output_area_y, mcYear == y)$"OV. COST")) +
+        sum(as.numeric(subset(output_link_y, mcYear == y)$"HURDLE COST"))
+    }
+
+
+    script_cost <- paste0(script_cost," ", simulated_year, " ", current_it$id, " ", y , " ",y_cost)
+
+    if (y != last_y) {script_cost <- paste0(script_cost, "\n")}
+
+    for(c in 1:n_candidates)
+    {
+      if(candidates[[c]]$has_link_profile)
+      {
+        len = length(subset(output_link_h, link == candidates[[c]]$link & mcYear == y)$"MARG. COST")
+        #tmp_rentability <- sum(as.numeric(subset(output_link_h, link == candidates[[c]]$link & mcYear == y)$"MARG. COST")*candidates[[c]]$link_profile[1:len, 1]) - candidates[[c]]$cost * n_w / 52
+        tmp_rentability <- sum(as.numeric(subset(output_link_h, link == candidates[[c]]$link & mcYear == y)$"MARG. COST")*candidates[[c]]$link_profile[1:len, 1])
+      }
+      else
+      {
+        #tmp_rentability <- sum(as.numeric(subset(output_link_y, link == candidates[[c]]$link & mcYear == y)$"MARG. COST")) - candidates[[c]]$cost * n_w / 52
+        tmp_rentability <- sum(as.numeric(subset(output_link_y, link == candidates[[c]]$link & mcYear == y)$"MARG. COST"))
+      }
+      script_rentability <- paste0(script_rentability, simulated_year, " ", current_it$id, " ", y, " ", candidates[[c]]$name, " ", tmp_rentability)
+      if (c != n_candidates || y != last_y)
+      {
+        script_rentability <- paste0(script_rentability, "\n")
+      }
+    }
+  }
+  write(script_rentability, file = paste0(tmp_folder, "/in_yearlyrentability.txt"), append = TRUE )
+  write(script_cost, file = paste0(tmp_folder, "/in_yearlycuts.txt"), append = TRUE )
+}