Tech opportunity testing and analysis

[calmc]

Overview

• Preliminary technical opportunity results have been completed using the following: run_tech_opp_parallel.py, tech_opp_calcs_parallel.py, format_rev_output.py, tech_opp_h5.py, tech_opp_demand.py, and /heat_load_calculations/run_demand_8760.py
• Results have been run for summer and winter peaks.
• All reV output files have been uploaded to the ESIF Data Repo under dataset 9b6afbc1-3307-40f4-a6d3-3eeaddd01f3f.
• Initial tech opp results have been uploaded to the ESIF Data Repo under dataset f5902ee2-48d5-4912-b6eb-7e1d36aa17ae

Testing (with pytest or equivalent package)

What are useful tests to write for checking results of analysis? Need to write testing results to logs.

Analysis

• [ ] Summary table (with heatmap?) by 3-digit NAICS and technology package. Show separate tables (in appendix?) for low and high operating hours

NAICS	Tech Pack 1	Tech Pack 2	...
311	Absolute opp (relative opp)	...	...
...	...	...	...

• [ ] (Net) GHG emissions savings

• [ ] Tech opp by hour, averaged over all counties, by technology package. This might be split up by season, by daytype (weekend, weekday), month, etc. Purpose is to show the hourly variation and indicate where storage may help.

• [ ] Temperature. We're assuming that the solar techs are providing the necessary process temperature at all times, which isn't the case. This gap should be explored in some way-- maybe by calculating the % of hours that max process temp is not met? This would require the construction of an aggregate load curve by temperature by county.

• [ ] Mapping (national maps)

  • [ ] Average tech opp by tech package
  • [ ] Tech opp by fuel
  • [ ] GHG savings

[calmc]

Hi @carriescho , the code that @wxi1995 has written so far to unpack the tech opp results h5 files is here: process_parity_calc/Tech_Opp_Results_Script/hdf5_file_analysis.py

[calmc]

@carriescho has tech opp code up and running. A remaining bug has been documented in #17. Analysis ideas have been transferred to #18.