sssmatch package

Submodules

sssmatch.cli module

sssmatch.cli.cli_parser()[source]
sssmatch.cli.datasets()[source]
sssmatch.cli.cli_main()[source]

sssmatch.request module

class sssmatch.request.AML[source]

Bases: enum.Enum

Supported Algebraic Modeling Languages

GAMS = 1
class sssmatch.request.Request(nodes, generators, dataset, desired_mix, exclusions=[])[source]

Bases: object

RESOURCE_INDEPENDENT = ['Biopower', 'Coal', 'NG-CC', 'NG-CT', 'Nuclear', 'Oil-Gas-Steam', 'Storage']
R2PD_TECHS_MAP = {'Land-based Wind': ['wind'], 'Rooftop PV': ['solar', 'rooftop'], 'Utility PV': ['solar', 'one-axis-tracking']}
DEFAULT_GENTYPE_DISTANCE_FILE = 'C:\\projects\\sssmatch\\sssmatch\\models\\default_gendists.csv'
classmethod nodes_columns(re_types)[source]
classmethod generators_columns()[source]
classmethod generators_swapped_columns()[source]
gentypes
current_mix
drop_default_gendists(filename=None)[source]

Prepopulates a gendists csv and saves it to filename, see fulfill.

preprocess()[source]
classmethod annual_useable_generation(genmix, gentypes)[source]

Returns the useable generation in TWh for genmix.

fulfill(outdir, gendists=None, precision=0, aml=<AML.GAMS: 1>)[source]
Parameters:
  • outdir (-) – results
  • gendists (-) – distance)
  • precision (-) – match desired mix to, in MW
  • aml (-) – algebraic modeling language you would like to use
register_results(capacity, capacity_added, capacity_kept, capacity_swapped, capacity_removed, distance)[source]

All of the arguments except for distance are dataframes in the same format as self.generators. Distance is the scalar objective function value.

compile_result_summary()[source]
save_results(outdir)[source]
print_report()[source]
class sssmatch.request.Model(request, outdir)[source]

Bases: object

Base class for optimization models that determine the new, by node and generation type, generation mix for a given power system.

MODEL_FILE = None
setup(gendists=None, precision=0)[source]
run()[source]
collect_results()[source]
class sssmatch.request.GamsModel(request, outdir)[source]

Bases: sssmatch.request.Model

Realization of Model using the GAMS AML. Depends on gdx-pandas, which is a Python package available on github.com.

MODEL_FILE = 'match_generators.gms'
setup(gendists=None, precision=0)[source]
run()[source]
collect_results()[source]

Module contents

exception sssmatch.SSSMatchError[source]

Bases: Exception