Modeling

class gtep.gtep_model.ExpansionPlanningModel(stages=1, formulation=None, data=None, num_reps=3, len_reps=24, num_commit=24, num_dispatch=4)

A generalized generation and transmission expansion planning model.

create_model()

Create concrete Pyomo model object associated with the ExpansionPlanningModel

report_large_coefficients(outfile, magnitude_cutoff=100000.0)

Dump very large magnitude (>= 1e5) coefficients to a json file.

Outfile:

should accept filename or open file and write there; see how we do this in pyomo elsewhere

Magnitude_cutoff:

magnitude above which to report coefficients

report_model(outfile='pretty_model_output.txt')

Pretty prints Pyomo model to outfile.

Outfile:

(str, optional) _description_. Defaults to “pretty_model_output.txt”.

gtep.gtep_model.add_commitment_constraints(b, comm_per)

Add commitment-associated disjunctions and constraints to representative period block.

gtep.gtep_model.add_commitment_variables(b, commitment_period)

Add variables and disjuncts to commitment period block.

gtep.gtep_model.add_dispatch_constraints(b, disp_per)

Add dispatch-associated inequalities to representative period block.

gtep.gtep_model.add_dispatch_variables(b, dispatch_period)

Add dispatch-associated variables to representative period block.

gtep.gtep_model.add_investment_constraints(b, investment_stage)

Add standard inequalities (i.e., those not involving disjunctions) to investment stage block.

gtep.gtep_model.add_investment_variables(b, investment_stage)

Add variables to investment stage block.

Parameters:

• b – Investment block

• investment_stage – Investment stage index or name

Returns:

None

gtep.gtep_model.commitment_period_rule(b, commitment_period)

Create commitment period block.

Parameters:

• b – commitment period block

• commitment_period – corresponding commitment period label

gtep.gtep_model.create_objective_function(m)

Creates objective function. Total cost is operating cost plus expansion cost plus penalty cost (penalties include generation deficits, renewable quota deficits, and curtailment) :param m: Pyomo GTEP model.

gtep.gtep_model.investment_stage_rule(b, investment_stage)

Creates investment stage block.

B:

Investment block

Investment_stage:

ID for current investment stage

gtep.gtep_model.model_create_investment_stages(m, stages)

Creates investment blocks and linking constraints for GTEP model. Largely manages retirements and links operational units in a given investment stage to operational + installed - retired in the previous investment stage.

M:

Pyomo model object

Stages:

Number of investment stages in planning horizon

gtep.gtep_model.model_data_references(m)

Creates and labels data for GTEP model; ties input data to model directly. :param m: Pyomo model object

gtep.gtep_model.model_set_declaration(m, stages, rep_per=['a', 'b'], com_per=2, dis_per=2)

Creates Pyomo Sets necessary (convenient) for solving the GTEP model.

M:

Pyomo model object

Stages:

Number of stages in investment horizon

gtep.gtep_model.representative_period_rule(b, representative_period)

Create representative period block.

B:

Representative period block

Representative_period:

corresponding representative period label