Total solar irradiance according to ISO 52010-1:2017

Lukas Lundström 2019-03-05

Introduction

Total solar irradiance on a surface with arbitrary orientation and tilt, calculated according to ISO 52010-1:2017 [2]. This code was originally developed as part of this article [1].

Currently only available via GitHub, install by:

if (!require('devtools')) install.packages('devtools')
#> Loading required package: devtools
devtools::install_github("lukas-rokka/solarCalcISO52010")
#> Skipping install of 'solarCalcISO52010' from a github remote, the SHA1 (7b4b54fb) has not changed since last install.
#>   Use `force = TRUE` to force installation
library(solarCalcISO52010)

The code is written in C++, so C++ compilation toolchain need to be installed to be able to install this package.

https://github.com/lukas-rokka/ISO14N_example has some further example code on how to use this package for building energy simulation purposes. The camsRad R-package can be used to acquire satellite-based solar irradiance data from CAMS.

Validation

The ‘tests/testthat/test_data.csv.gz’ file holds climate data from the ISO 52010 standard: station DRYCOLD.TMY (Denver, USA), latitude = 39.76, longitude = -104.86, time zone = -7. The file also has validation cases calculated with the ISO_FDIS_52010_SS_ISO-TC163-SC2-WG15_N0075_20160705.xlsm spreadsheet provided with the standard. The result of the cases are stored in the following four variables: * I_tot_s1: azimuth=90, tilt angle=90 * I_tot_s2: azimuth=-90, tilt angle=90 * I_tot_s3: azimuth=-35, tilt angle=0 * I_tot_s4: azimuth=45, tilt angle=30

df <- read.csv("tests/testthat/test_data.csv.gz")

df$timestamp = seq.POSIXt(as.POSIXct("2014-01-01 01:00", tz="Etc/GMT+7"), 
                          as.POSIXct("2015-01-01 00:00", tz="Etc/GMT+7"), by="hour")

df$albedo = 0.2

df2 <- solarCalcISO52010:::tidyISO52010(
  df, 
  lat=39.76, 
  lng=-104.86, 
  tz=-7, 
  t_shift=0.5, 
  surfaceAzimuths = c(90, -90, -35, 45), 
  surfaceTilts = c(90, 90, 0, 30),
  interp_perez = 0 # the validation data is calc with binned Perez data
  ) 

df2$I_tot_s1 = df2$I_tot_dir_s1 + df2$I_tot_dif_s1
df2$I_tot_s2 = df2$I_tot_dir_s2 + df2$I_tot_dif_s2
df2$I_tot_s3 = df2$I_tot_dir_s3 + df2$I_tot_dif_s3
df2$I_tot_s4 = df2$I_tot_dir_s4 + df2$I_tot_dif_s4
df2$alpha_sol = df2$alpha_sol*180/pi


df2 %>% mutate(method="This package") %>% 
  bind_rows(df %>% mutate(method="Spreadsheet")) %>% 
  as_tibble() %>% 
  filter(timestamp < as.POSIXct("2014-01-15 01:00")) %>% 
  select(timestamp, method, 
         'Azimuth = 90°, tilt = 90°' = I_tot_s1, 
         'Azimuth = -90°, tilt = 90°' = I_tot_s2, 
         'Azimuth = -35°, tilt = 0°' = I_tot_s3, 
         'Azimuth = 45°, tilt = 30°' = I_tot_s4) %>%
  gather(case, I, -timestamp, -method) %>%
  ggplot(aes(timestamp, I, color=method, linetype=method)) + 
  facet_wrap(~case,ncol=2) +
  geom_line(size=1) +
  labs(y="Total irradiance, W/m2")

Licensing

All C++ code is licensed under the New BSD License. All R code is licensed under the GPL-2 License. All documentation is licensed CC-BY.

References

1. Lundström, Lukas, Jan Akander, and Jesús Zambrano. 2019. “Development of a Space Heating Model Suitable for the Automated Model Generation of Existing Multifamily Buildings – A Case Study in Nordic Climate”. Energies 12 (3). https://doi.org/10.3390/en12030485

2. ISO 52016-1:2017. “Energy performance of buildings – External climatic conditions – Part 1: Conversion of climatic data for energy calculations (ISO 52010-1:2017)” https://www.iso.org/standard/65703.html