cor_2017_html.Rmd

---
title: "TD R/ANTARES"
author: "Jalal-Edine ZAWAM"
date: "13 décembre 2017"
output:
  #pdf_document:
  #  toc: yes
  html_document:
    number_sections: yes
    toc: yes
  word_document:
    toc: yes
always_allow_html: yes
---

```{r setup and include, include=FALSE}

library(antaresRead)
library(antaresProcessing)
library(antaresViz)
library(data.table)
library(rpart)
library(rpart.plot)
library(magrittr)
library(manipulateWidget)
library(knitr)
library(lubridate)
library(plotly)
library(webshot)

knitr::opts_chunk$set(echo = TRUE)
knitr::opts_chunk$set(fig.align = 'center')


```

## readAntares

Most data from a simulation can be imported in the R session with function `readAntares()`. 

```{r readData, warning=FALSE}
myPath<-"E:\\ANTARES\\Exemple_antares\\2_exemple_etudes_importantes\\TYNDP\\ST2030\\ST2030"
opts<-setSimulationPath(myPath, "20170830-1049eco-reference")

myData<-readAntares(
  areas = "all", 
  links="all", 
  clusters = "all", 
  linkCapacity = TRUE,
  mustRun = TRUE,
  showProgress = FALSE
)

```

## Remove your virtual areas

You can remove your virtual areas and correct your initial data. 

```{r removeVirtualAreas, echo=TRUE}
myConData<-removeVirtualAreas(
   x=myData,
   storageFlexibility = getAreas(select = c("pum", "tur", "z_dsr", "y_mul")), 
   newCols = FALSE
 )
```

## getAreas ans getLinks 

Compute the number of areas without virtual areas. 

```{r getAreas, echo=TRUE}

virtuarAreas<-getAreas(select = c("z_dsr", "y_mul", "pum", "tur"))
realAreas<-getAreas(exclude = virtuarAreas)

length(getAreas(exclude = virtuarAreas))
```

Compute the number of links without virtual areas

```{r getLinks, echo=TRUE}

length(getLinks(areas = realAreas, exclude = virtuarAreas))
```

## antaresDataList : List of date.tables

Compute the number of areas with unsupplied energy

```{r get areas with unspilled energy, echo=TRUE}

length(unique(myConData$areas[`UNSP. ENRG`>0]$area))


```

Compute the number of areas with spilled energy

```{r get areas with unspilled spilled energy, echo=TRUE}

length(unique(myConData$areas[`SPIL. ENRG`>0]$area))


```

Compute the number of links with congestion

```{r getLinks with congestion, echo=TRUE}

length(unique(myConData$links[`CONG. PROB +`>0]$link)) 

length(unique(myConData$links[`CONG. PROB -`>0]$link)) 

length(unique(myConData$links[`CONG. PROB +`>0  | `CONG. PROB -`>0]$link)) 

length(unique(myConData$links[`CONG. PROB +`>0  & `CONG. PROB -`>0]$link))

```


Compute the sum of the spilled energy by area and order the result by the spilled energy

```{r Compute the sum of the spilled energy, echo=FALSE}

myConData$areas[, sumSpilled:=sum(`SPIL. ENRG`), by=area]
resCompute<-unique(myConData$areas[order(sumSpilled, decreasing = TRUE),.(area, sumSpilled),])
## NO PRINT

```

```{r RES compute the sum of the spilled energy, echo=TRUE}

## PRINT ONLY RESULT 
kable(resCompute[, .SD[1:7], ])

```

Compute the sum of the unsupplied energy by area and order the result by the unsupplied energy

```{r Compute the sum of the unsupplied energy, echo=FALSE}

myConData$areas[, sumUnspilled:=sum(`UNSP. ENRG`), by=area]
resComputeUnsEne<-unique(myConData$areas[order(sumUnspilled, decreasing = TRUE),.(area, sumUnspilled),])
## NO PRINT

```

```{r RES compute the sum of the unsupplied energy, echo=TRUE}

## PRINT ONLY RESULT 
kable(resComputeUnsEne[, .SD[1:7], ])

```

##Explain the result for unsupplied energy in France: with rpart or others statical packages FactoMineR, kmeans


```{r rpart, echo=FALSE}

onlyAreaNoFar<-c("fr", "es", "pt", "ch", "itn", "itcn", "be", "gb", "ni", "ie", "nl", "de", "nos", "pl", "cz")

mySubset<-subset(myConData, areas=onlyAreaNoFar)
myMergeSubset<-mergeAllAntaresData(mySubset)

myRpart<-rpart(`UNSP. ENRG_fr`~. - `UNSP. ENRG_std_fr` - `OV. COST_fr` -`UNSP. ENRG_max_fr`, data=myMergeSubset[`UNSP. ENRG_fr`>0])
rpart.plot(myRpart)

```

## Explain the result for unsupplied energy in France without some variables

```{r rpart 2 , echo=FALSE}

myRpart<-rpart(`UNSP. ENRG_fr`~. - `UNSP. ENRG_std_fr` - `OV. COST_fr` - `UNSP. ENRG_max_fr` - `MAX MRG_fr` - `MAX MRG_min_fr` - `MAX MRG_std_fr`, data=myMergeSubset[`UNSP. ENRG_fr`>0])
rpart.plot(myRpart)

```

##antaresViz : prodStack, exchangesStack and plot

Get the first year and the first date where there is more than 700MW of unsupplied energy in France and use prodStack to visualize the production stack for this week.


```{r date where there is unsupplied energy in France , echo=FALSE, fig.align="center"}

#find the two first mcYear
count<-0
timesIds<-NULL
mcYears<-NULL
timeId2<-NULL
for(i in 1:50){
  myDataFr<-readAntares(areas = "fr", mcYears = i, showProgress = FALSE)
  if(!is.na(myDataFr[`UNSP. ENRG`>700 & area=="fr",]$time[1])){
    print(paste0("mcYear :", i))
    print(paste0("time :", myDataFr[`UNSP. ENRG`>700 & area=="fr", ]$time[1]))
    print(paste0("timeId :", myDataFr[`UNSP. ENRG`>700 & area=="fr", ]$timeId[1]))
    print(paste0("day :", myDataFr[`UNSP. ENRG`>700 & area=="fr", ]$day[1]))
    timesIds<-c(timesIds, as.character(myDataFr[`UNSP. ENRG`>700 & area=="fr", ]$time[1]))
    timeId2<-c(timeId2, as.character(myDataFr[`UNSP. ENRG`>700 & area=="fr", ]$timeId[1]))
    mcYears<-c(mcYears, i)
    count<-count+1
    if(count>=2){
      break()
    }  
  }
}

```
# prodStack, exchangesStack

```{r use prodStack , echo=TRUE, fig.show='hold',fig.align='center', error=TRUE, fig.align="center"}

myDataFr<-suppressWarnings(readAntares(areas = "fr", mcYears = mcYears[1], showProgress = FALSE, links = "all", linkCapacity = TRUE))

prodStack(myDataFr, dateRange=c("2018-01-01 00:00:00", "2018-01-07 23:00:00"), interactive = FALSE, area="fr")

exchangesStack(myDataFr, dateRange=c("2018-01-01 00:00:00", "2018-01-07 23:00:00"), interactive = FALSE, area="fr")

plot(myDataFr$areas, dateRange=c("2018-01-01 00:00:00", "2018-01-07 23:00:00"), interactive = FALSE, elements="fr", variable="MRG. PRICE", mcYear=4, type="ts", stepPlot=TRUE)

```

# use consolidated data 

```{r consolidated data , echo=TRUE, fig.show='hold',fig.align='center'}

myDataFr<-suppressWarnings(readAntares(links = getLinks(areas = c("z_dsr450", "y_mul", "pum", "tur", "fr")), areas = getAreas(select = c("z_dsr450", "y_mul", "pum", "tur", "fr")), mcYears = 4, linkCapacity = TRUE, showProgress = FALSE))

myConDataFr<-removeVirtualAreas(
  x=myDataFr,
  storageFlexibility = getAreas(select = c("pum", "tur", "z_dsr", "y_mul")),
  newCols = FALSE, 
  reassignCosts = TRUE
)

prodStack(myConDataFr, dateRange=c("2018-01-01 00:00:00", "2018-01-07 23:00:00"), interactive = FALSE, area="fr")

exchangesStack(myConDataFr, dateRange=c("2018-01-01 00:00:00", "2018-01-07 23:00:00"), interactive = FALSE, area="fr")

```

# antaresViz : plotMap

configure a layout or import one 


```{r layout , echo=TRUE, fig.show='hold',fig.align='center'}

#mlTyndp<-mapLayout(readLayout())
#plotMapLayout(mlTyndp)
#saveRDS(mlTyndp, file = "E:\\ANTARES\\Exemple_antares\\2_exemple_etudes_importantes\\TYNDP\\ST2030\\ST2030\\user\\mlTyndp2017_V2.rds")

mlTyndp<-readRDS(file = "E:\\ANTARES\\Exemple_antares\\2_exemple_etudes_importantes\\TYNDP\\ST2030\\mapLayoutTyndp.rds")

```

#Data for Europe

```{r import Data for Europe , echo=TRUE}
myDataEurope<-suppressWarnings(readAntares(links = "all", areas = "all", linkCapacity = TRUE, showProgress = FALSE, mcYears = mcYears[1]))

myConDataEurope<-removeVirtualAreas(
  x=myDataEurope,
  storageFlexibility = getAreas(select = c("pum", "tur", "z_dsr", "y_mul")),
  newCols = FALSE
)

addLoadFactorLink(myConDataEurope)

```

<!--- #get the variables -->

```{r get the variables , echo=FALSE, message=FALSE, results='hide', fig.align="center"}

#select your variables 
resGen<-invisible(showAliases(names="generation"))
resRen<-showAliases(names="renewable")
vecGen<-as.vector(resGen$select)
vecRen<-as.vector(resRen$select)
vecGen <- strsplit(vecGen,", ",fixed=TRUE)[[1]]
vecRen <- strsplit(vecRen,", ",fixed=TRUE)[[1]]

varPlotMap<-c(vecGen, vecRen)

popUpVar<-showAliases(names="adequacy")
vecAde<-as.vector(popUpVar$select)
vecAde <- strsplit(vecAde,", ",fixed=TRUE)[[1]]

```

#Use plotMap 

The flow value of Great Britain/France is equal to zero, these two countries have unsupplied energy.

The flow between Belgium/France is 1295 but the link is not congested because Belgium has no marge. 

All others flows to France are congested.  


```{r plotMap , echo=TRUE, message=FALSE, fig.show='hold',fig.align='center', error=TRUE}

plotMap(
  myConDataEurope, 
  mlTyndp, 
  sizeAreaVars=varPlotMap, 
  areaChartType="pie", 
  interactive = FALSE,
  sizeMiniPlot = TRUE, 
  colAreaVar="LOAD", 
  colLinkVar="congestion",
  sizeLinkVar="FLOW LIN.",
  popupAreaVars = c(varPlotMap, vecAde, "PSP", "LOAD", "SPIL. ENRG"), 
  timeId = 115, 
  type = "detail"
)

```

#With interaction

```{r plotMap interactive TRUE, eval=FALSE, echo=TRUE, message=FALSE}

plotMap(
  myConDataEurope, 
  mlTyndp, 
  .updateBtn = TRUE, 
  .updateBtnInit=TRUE
)

```

#You can change color option with plotMapOption

```{r plotMap options, eval=TRUE, echo=TRUE, fig.show='hold',fig.align='center', error=TRUE }

linkColorScaleOpts<-colorScaleOptions(
  breaks = 1, 
  negCol = "#00FF00", 
  zeroCol = "#FFFFFF", 
  posCol = "#FF0000", 
  naCol = "#EEEEEE",
  levels = c(0,1)
)

resOptions<-plotMapOptions(
  linkColorScaleOpts = linkColorScaleOpts
)

plotMap(
  myConDataEurope, 
  mlTyndp, 
  sizeAreaVars=varPlotMap, 
  areaChartType="pie", 
  interactive = FALSE,
  sizeMiniPlot = TRUE, 
  colAreaVar="LOAD", 
  colLinkVar="congestion",
  sizeLinkVar="FLOW LIN.",
  popupAreaVars = c(varPlotMap, vecAde, "PSP", "LOAD", "SPIL. ENRG"), 
  timeId = 115, 
  type = "detail", 
  options = resOptions
)

```

#Upward margin 


```{r Upward margin get the data, eval=TRUE, echo=TRUE, cache=TRUE}

ListMyDataFr<-list()
for(i in mcYears){

  ListMyDataFr[[i]]<-suppressWarnings(
    readAntares(
      links = "all", 
      areas = "all",  
      linkCapacity = TRUE, 
      showProgress = FALSE, 
      mcYears = i,
      hydroStorageMaxPower = TRUE
      )
    )
  
 ListMyDataFr[[i]]<-removeVirtualAreas(
   x=ListMyDataFr[[i]],
   storageFlexibility = getAreas(select = c("pum", "tur", "z_dsr", "y_mul")), 
   newCols = FALSE
 )}


resPlotMap<-list()
timeId<-NULL
for(i in mcYears){
  addLoadFactorLink(ListMyDataFr[[i]])
  addUpwardMargin(ListMyDataFr[[i]])
  
  ListMyDataFr[[i]]$areas[area=="tr", interconnectedUpwardMargin:=0]

}

```

```{r Upward margin plot the data, eval=TRUE, echo=FALSE, results='hold'}

  
timeId4<-115
timeId5<-931  
  
plotMap(
  ListMyDataFr[[4]], 
  mlTyndp, 
  colAreaVar="interconnectedUpwardMargin",
  sizeAreaVars=c("interconnectedUpwardMargin", "isolatedUpwardMargin"), 
  areaChartType="pie", 
  interactive = FALSE,
  sizeMiniPlot = TRUE, 
  colLinkVar="congestion",
  sizeLinkVar="FLOW LIN.",
  popupAreaVars = c(varPlotMap, vecAde, "PSP", "LOAD", "SPIL. ENRG"), 
  timeId = timeId4, 
  type = "detail", 
  showLabels=TRUE, 
  labelAreaVar="interconnectedUpwardMargin"
)

plotMap(
  ListMyDataFr[[5]], 
  mlTyndp, 
  colAreaVar="interconnectedUpwardMargin",
  sizeAreaVars=c("interconnectedUpwardMargin", "isolatedUpwardMargin"), 
  areaChartType="pie", 
  interactive = FALSE,
  sizeMiniPlot = TRUE, 
  colLinkVar="congestion",
  sizeLinkVar="FLOW LIN.",
  popupAreaVars = c(varPlotMap, vecAde, "PSP", "LOAD", "SPIL. ENRG"), 
  timeId = timeId5, 
  type = "detail", 
  showLabels=TRUE, 
  labelAreaVar="interconnectedUpwardMargin"
)

```

#Save memory and time with h5

Write your simulation in h5. 
```{r h5, eval=FALSE, echo=TRUE, message=FALSE}

writeAntaresH5(
  path="E:\\ANTARES\\Exemple_antares\\2_exemple_etudes_importantes\\TYNDP\\ST2030\\ST2030\\writeH5",
  allData = FALSE, #thermalAvailabilites and hydroStorage were not exported
  misc = TRUE, 
  thermalAvailabilities = FALSE,
  hydroStorageMaxPower = TRUE, 
  reserve = TRUE,
  linkCapacity = TRUE,
  mustRun = TRUE, 
  writeAllSimulations = TRUE,
  writeMcAll = TRUE,
  nbCores=3,
  removeVirtualAreas=TRUE,
  storageFlexibility=getAreas(select = c("pum", "tur", "z_dsr", "y_mul")),
  newCols = FALSE,
  overwrite = TRUE, 
  timeSteps = "hourly"
)
```