R Notebook

library(readxl)

Mensagen de aviso:
In file.info(path, extra_cols = FALSE) :
  não é possível abrir o arquivo 'C:/Users/thiago.gardin/AppData/Local/Microsoft/WindowsApps/PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0/python.exe': Não é possível o acesso ao arquivo pelo sistema

library(tidyverse)

Aviso: pacote ‘ggplot2’ foi compilado no R versão 4.4.3
Aviso: pacote ‘purrr’ foi compilado no R versão 4.4.3

── Attaching core tidyverse packages ────────────────────────────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.5.2     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.1
✔ purrr     1.0.4     
── Conflicts ──────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the ]8;;http://conflicted.r-lib.org/conflicted package]8;; to force all conflicts to become errors

library(zoo)

Anexando pacote: ‘zoo’

Os seguintes objetos são mascarados por ‘package:base’:

    as.Date, as.Date.numeric

prc_energia <- read_excel("Historico_do_Preco_Horario_-_17_de_abril_de_2018_a_3_de_junho_de_2025.xlsx")

prc_energia %>% gather("dia","Valor",-Hora,-Submercado) %>% mutate(dia=as.Date(as.integer(dia), origin = "1899-12-30")) ->p_ene
p_ene$Submercado %>% table

.
NORDESTE    NORTE  SUDESTE      SUL 
   64825    64825    64825    64825 

p_ene %>% #spread(Submercado,Valor)->p_ene

Erro: Incomplete expression: p_ene %>% #spread(Submercado,Valor)->p_ene

summary(p_ene)

     Hora            Submercado             dia                 Valor        
 Length:264486      Length:264486      Min.   :2018-04-17   Min.   :  39.68  
 Class :character   Class :character   1st Qu.:2020-02-06   1st Qu.:  61.07  
 Mode  :character   Mode  :character   Median :2021-11-15   Median :  72.56  
                                       Mean   :2021-11-14   Mean   : 169.92  
                                       3rd Qu.:2023-08-25   3rd Qu.: 249.23  
                                       Max.   :2025-06-03   Max.   :1470.57  
                                                            NA's   :15558    

p_ene$Hora %>% unique

 [1] "0"                                                                                                                          
 [2] "1"                                                                                                                          
 [3] "2"                                                                                                                          
 [4] "3"                                                                                                                          
 [5] "4"                                                                                                                          
 [6] "5"                                                                                                                          
 [7] "6"                                                                                                                          
 [8] "7"                                                                                                                          
 [9] "8"                                                                                                                          
[10] "9"                                                                                                                          
[11] "10"                                                                                                                         
[12] "11"                                                                                                                         
[13] "12"                                                                                                                         
[14] "13"                                                                                                                         
[15] "14"                                                                                                                         
[16] "15"                                                                                                                         
[17] "16"                                                                                                                         
[18] "17"                                                                                                                         
[19] "18"                                                                                                                         
[20] "19"                                                                                                                         
[21] "20"                                                                                                                         
[22] "21"                                                                                                                         
[23] "22"                                                                                                                         
[24] "23"                                                                                                                         
[25] NA                                                                                                                           
[26] "Observação: As linhas 98 a 101 são referentes a segunda hora 23h as 23h59 no dia 16/02/2019 considerando o horário de verão"

p_ene %>% group_by(dia,Submercado) %>% summarise(n=n(),na=sum(is.na(Valor)),
                                                 max=max(Valor,na.rm=T),
                                                 min=min(Valor,na.rm=T),
                                                 mean=mean(Valor,na.rm=T))

Aviso: There were 5186 warnings in `summarise()`.
The first warning was:
ℹ In argument: `max = max(Valor, na.rm = T)`.
ℹ In group 5: `dia = 2018-04-17` `Submercado = NA`.
Caused by warning in `max()`:
! nenhum argumento não faltante para max; retornando -Inf
ℹ Run ]8;;ide:run:dplyr::last_dplyr_warnings()dplyr::last_dplyr_warnings()]8;; to see the 5185 remaining warnings.

`summarise()` has grouped output by 'dia'. You can override using the `.groups` argument.

p_ene %>% drop_na() %>% mutate(data_hora=ymd_hms(paste0(dia,"-",as.integer(Hora),"-00-0"))) %>% 
  group_by(dia,Submercado) %>% summarise(Valor=mean(Valor)) %>% 
  group_by(Submercado) %>% 
  mutate(Valor=rollmean(Valor,24,fill = NA)) %>% 
  ggplot(aes(dia,Valor,col=Submercado))+geom_line() +facet_grid(Submercado~"Submercado")

`summarise()` has grouped output by 'dia'. You can override using the `.groups` argument.

Aviso: Removed 92 rows containing missing values or values outside the scale range (`geom_line()`).

library(readxl)library(readxl)
pc_semana <- read_excel("Historico_do_Preco_Medio_Semanal_-_30_de_junho_de_2001_a_30_de_maio_de_2025.xls")
View(pc_semana)
pc_semana <- read_excel("Historico_do_Preco_Medio_Semanal_-_30_de_junho_de_2001_a_30_de_maio_de_2025.xls")

pc_semana %>% ggplot(aes(DATA_INICIO))+
  geom_line(aes(y=rollmean(SUDESTE,3*4*4,fill = NA)
                  ),col="blue")+
    geom_line(aes(y=rollmean(SUL,3*4*4,fill = NA)
                  ),col="red")+
    geom_line(aes(y=rollmean(NORDESTE,3*4*4,fill = NA)
                  ),col="green")+
    geom_line(aes(y=rollmean(NORTE,3*4*4,fill = NA)
                  ),col="grey")+theme_minimal()

Aviso: Removed 47 rows containing missing values or values outside the scale range (`geom_line()`).
Aviso: Removed 47 rows containing missing values or values outside the scale range (`geom_line()`).
Aviso: Removed 47 rows containing missing values or values outside the scale range (`geom_line()`).
Aviso: Removed 47 rows containing missing values or values outside the scale range (`geom_line()`).

p_semana

daas_completas

ena_ear_hidr_ceg_amb %>% left_join(daas_completas,by = c("ena_data"="datas")) %>% 
  mutate(preco=case_when(nom_subsistema.x=="SUDESTE"~SUDESTE,
                         nom_subsistema.x=="SUL"~SUL,
                         nom_subsistema.x=="NORDESTE"~NORDESTE,
                         nom_subsistema.x=="NORTE"~NORTE,TRUE~NA
                         ))->hidr_amb_prec

Erro: objeto 'ena_ear_hidr_ceg_amb' não encontrado

hidr_amb_prec$preco %>%  summary

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
   4.00   25.31  101.24  177.25  247.01  822.83   45390 

hidr_amb_prec %>% filter(ena_data>inicio-1) ->hidr_amb_prec

hidr_amb_prec %>% group_by(ena_data,nom_subsistema.x,ANO,MES) %>% 
  summarise(preco=mean(preco,na.rm = T),
            temperature=mean(temperature,na.rm = T),
            preciptation=sum(preciptation,na.rm = T),
            humidity=mean(humidity,na.rm = T),
            wind_speed=mean(wind_speed,na.rm = T),
            ear_reservatorio_subsistema_proprio_mwmes=sum(ear_reservatorio_subsistema_proprio_mwmes,na.rm = T),
            ena_bruta_res_mwmed=sum(ena_bruta_res_mwmed,na.rm = T),
            val_geracao=sum(val_geracao,na.rm = T),
            val_geracao_day_subsistema=mean(val_geracao_day_subsistema,na.rm = T))->df

`summarise()` has grouped output by 'ena_data', 'nom_subsistema.x', 'ANO'. You can override using the `.groups` argument.

lm(log(preco)~trend+log(val_geracao_day_subsistema)+log(ear_reservatorio_subsistema_proprio_mwmes)+nom_subsistema.x+0,df) %>% summary

Call:
lm(formula = log(preco) ~ trend + log(val_geracao_day_subsistema) + 
    log(ear_reservatorio_subsistema_proprio_mwmes) + nom_subsistema.x + 
    0, data = df)

Residuals:
    Min      1Q  Median      3Q     Max 
-2.9879 -0.7228 -0.0397  0.6442  4.1871 

Coefficients:
                                                Estimate Std. Error t value Pr(>|t|)    
trend                                           0.163419   0.001746  93.622   <2e-16 ***
log(val_geracao_day_subsistema)                -0.052492   0.025951  -2.023   0.0431 *  
log(ear_reservatorio_subsistema_proprio_mwmes) -0.626629   0.012498 -50.139   <2e-16 ***
nom_subsistema.xNORDESTE                        9.097699   0.201835  45.075   <2e-16 ***
nom_subsistema.xNORTE                           8.220124   0.192135  42.783   <2e-16 ***
nom_subsistema.xSUDESTE                        10.454692   0.237149  44.085   <2e-16 ***
nom_subsistema.xSUL                             8.952210   0.206150  43.426   <2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1.031 on 25517 degrees of freedom
Multiple R-squared:  0.9467,    Adjusted R-squared:  0.9467 
F-statistic: 6.477e+04 on 7 and 25517 DF,  p-value: < 2.2e-16

options(scipen = 9)