dispaset.postprocessing package

Submodules

dispaset.postprocessing.postprocessing module

Set of functions useful to analyse to DispaSET output data.

@author: Sylvain Quoilin, JRC

dispaset.postprocessing.postprocessing.CostExPost(inputs, results)[source]

Ex post computation of the operational costs with plotting. This allows breaking down the cost into its different components and check that it matches with the objective function from the optimization.

The cost objective function is the following:
SystemCost(i) =E= sum(u,CostFixed(u)*Committed(u,i)) +sum(u,CostStartUpH(u,i) + CostShutDownH(u,i)) +sum(u,CostRampUpH(u,i) + CostRampDownH(u,i)) +sum(u,CostVariable(u,i) * Power(u,i)) +sum(l,PriceTransmission(l,i)*Flow(l,i)) +sum(n,CostLoadShedding(n,i)*ShedLoad(n,i)) +sum(chp, CostHeatSlack(chp,i) * HeatSlack(chp,i)) +sum(chp, CostVariable(chp,i) * CHPPowerLossFactor(chp) * Heat(chp,i)) +Config(“ValueOfLostLoad”,”val”)*(sum(n,LL_MaxPower(n,i)+LL_MinPower(n,i))) +0.8*Config(“ValueOfLostLoad”,”val”)*(sum(n,LL_2U(n,i)+LL_2D(n,i)+LL_3U(n,i))) +0.7*Config(“ValueOfLostLoad”,”val”)*sum(u,LL_RampUp(u,i)+LL_RampDown(u,i)) +Config(“CostOfSpillage”,”val”)*sum(s,spillage(s,i));
Returns:tuple with the cost components and their cumulative sums in two dataframes.
dispaset.postprocessing.postprocessing.aggregate_by_fuel(PowerOutput, Inputs, SpecifyFuels=None)[source]

This function sorts the power generation curves of the different units by technology

Parameters:
  • PowerOutput – Dataframe of power generationwith units as columns and time as index
  • Inputs – Dispaset inputs version 2.1.1
  • SpecifyFuels – If not all fuels should be considered, list containing the relevant ones
Returns PowerByFuel:
 

Dataframe with power generation by fuel

dispaset.postprocessing.postprocessing.filter_by_zone(PowerOutput, inputs, z)[source]

This function filters the dispaset Output Power dataframe by zone

Parameters:
  • PowerOutput – Dataframe of power generationwith units as columns and time as index
  • Inputs – Dispaset inputs version 2.1.1
  • z – Selected zone (e.g. ‘BE’)
Returns Power:

Dataframe with power generation by zone

dispaset.postprocessing.postprocessing.get_imports(flows, z)[source]

Function that computes the balance of the imports/exports of a given zone

Parameters:
  • flows – Pandas dataframe with the timeseries of the exchanges
  • z – Zone to consider
Returns NetImports:
 

Scalar with the net balance over the whole time period

dispaset.postprocessing.postprocessing.get_indicators_powerplant(inputs, results)[source]

Function that analyses the dispa-set results at the power plant level Computes the number of startups, the capacity factor, etc

Parameters:
  • inputs – DispaSET inputs
  • results – DispaSET results
Returns out:

Dataframe with the main power plants characteristics and the computed indicators

dispaset.postprocessing.postprocessing.get_load_data(inputs, z)[source]

Get the load curve, the residual load curve, and the net residual load curve of a specific zone

Parameters:
  • inputs – DispaSET inputs (output of the get_sim_results function)
  • z – Zone to consider (e.g. ‘BE’)
Return out:

Dataframe with the following columns: Load: Load curve of the specified zone ResidualLoad: Load minus the production of variable renewable sources NetResidualLoad: Residual netted from the interconnections with neightbouring zones

dispaset.postprocessing.postprocessing.get_plot_data(inputs, results, z)[source]

Function that reads the results dataframe of a DispaSET simulation and extract the dispatch data spedific to one zone

Parameters:
  • results – Pandas dataframe with the results (output of the GdxToDataframe function)
  • z – Zone to be considered (e.g. ‘BE’)
Returns plotdata:
 

Dataframe with the dispatch data storage and outflows are negative

dispaset.postprocessing.postprocessing.get_result_analysis(inputs, results)[source]

Reads the DispaSET results and provides useful general information to stdout

Parameters:
  • inputs – DispaSET inputs
  • results – DispaSET results
dispaset.postprocessing.postprocessing.get_units_operation_cost(inputs, results)[source]

Function that computes the operation cost for each power unit at each instant of time from the DispaSET results Operation cost includes: CostFixed + CostStartUp + CostShutDown + CostRampUp + CostRampDown + CostVariable

Parameters:
  • inputs – DispaSET inputs
  • results – DispaSET results
Returns out:

Dataframe with the the power units in columns and the operatopn cost at each instant in rows

Main Author: @AbdullahAlawad

Module contents