In JimDuggan/aimsir17: Irish Weather Observing Stations Hourly Records for 2017

knitr::opts_chunk$set(echo = FALSE)

R tools such as dplyr and tidyr can be used to summarise data (e.g. add rain observations to obtain monthly and annual cumulative amounts). The three libraries are first loaded.

library(aimsir17)
library(dplyr)
library(tidyr)
library(ggplot2)

We can link the energyu data with the weather observations to explore the link between wind speed and power generated. First, we use dplyr to get the hourly mean of wind power generated for March 2017

march <- eirgrid17 %>% filter(month==3) %>%
                       group_by(year,month,day,hour) %>%
                       summarise(AvrHourWind=mean(IEWindGeneration))
march

Next, get the weather observations for March for two stations (Mace Head and Belmullet)

w <- observations %>% filter(month==3, station=="MACE HEAD" | station == "BELMULLET") %>% 
                 select(station, year, month, day, hour, wdsp)
w

Next, join the two tables.

j <- full_join(w, march)
j

Next, summarise the merged data set

summary(j)

Finally, explore any possible relationship between average hourley wind speed and average wind power generated

ggplot(j,aes(x=wdsp,y=AvrHourWind,colour=station))+geom_point()+geom_jitter()+geom_smooth()

JimDuggan/aimsir17 documentation built on Aug. 22, 2020, 9:46 p.m.