In btaute/powerResource: Tools To Analyze And Extrapolate Solar Resource Data

knitr::opts_chunk$set(echo = FALSE, message = FALSE, warning = FALSE)

r params$site_name Solar Resource Assessment

r Sys.Date()

Measured Data

count_flags(params$sms_flagged) %>%
  plot_flag_count_bar_chart()

MCP Results

params$mcp$daily_results_table %>%
  knitr::kable()

Concurrent Measurements

params$mcp$megaframe %>%
  filter(datetime >= min(filter(params$mcp$megaframe, model == 'sms')$datetime),
         datetime <= max(filter(params$mcp$megaframe, model == 'sms')$datetime),
         ghi > 0) %>%
  plot_monthly_ghi(title = '') +
  facet_wrap(~ year, ncol = 1) +
  theme(legend.position="bottom")

Long Term Annual Trends

params$mcp$megaframe %>%
  select_longterm_models() %>%
  summarise_annual_total_ghi() %>%
  add_normalized_ghi() %>%
  plot_annual_model_values('ghi', 'Annualized Total GHI')

Model Performance

timestep <- 'daily'
value <- 'fitted.values'

grab_model_list(params$mcp$model_fits, timestep, 'ghi', value) %>%
  plot_model_comparison(value, title = paste(timestep, 'ghi', value))

grab_model_list(params$mcp$model_fits, timestep, 'temp', value) %>%
  plot_model_comparison(value, title = paste(timestep, 'temp', value))

SMS Campaign Impact

campaign_df <- compile_monthly_ghi_results_of_campaign(params$mcp$megaframe)
plot_campaign_ghi_longterm_adjustments(campaign_df)
plot_campaign_ghi_uncertainty(campaign_df)

btaute/powerResource documentation built on Sept. 4, 2020, 4:36 p.m.