library(dplyr)
library(lubridate)
library(ggplot2)
library(tidyverse)
library(readxl)

electricitydf <- read_xlsx("C:/Users/hüseyin/Desktop/Dersler/BDA503-Data Analytics Essentials/Electricity Data.xlsx")

Electricity Market Prices

The ‘electricitydf’ dataset is a report about September 2020’s electricity prices. The data shows “Market Concumption Price”, “System Marjinal Price”, “Positive Imbalance Price”, “Negative Imbalance Price”, “System Marjinal Price Direction” by time basis.

electricity_def <- electricitydf %>% filter(MCP > SMP) %>% select("Time", "PIP", "NIP")


sc_plot <- ggplot(electricity_def, aes(x = Time, y = PIP)) + geom_point()

sc_plot2 <- sc_plot + labs(x="September 2020", y="Positive Imbalance Price (TL/MWh)", title = "Positive Imbalance Price in Turkish Electricity Market in September 2020")

sc_plot2

Conclusion

In this dataset, we use the data to see whether the energy surplus are accumulated in some specific days or it is normally distributed all days in Semptember 2020. The gragh shows that energy surplus are accumulated around 7th, 20th and 29th September.