Model Data

DataFiles

A container for loading and storing output data related to a model run. Each field corresponds to a specific dataset represented as a DataFrame. The constructor can be called by providing the directory that contains the results. The path to the specific results of each model run consists of the 'resultdir' and the 'scenarioname' (see section ModelRun).

Fields

• params::Parameters: Configuration and model parameters loaded from params.jld2.
• CHARGE::DataFrame: Charging data for storage units.
• EXCHANGE::DataFrame: Cross-border or inter-zonal energy exchange data.
• FEEDIN::DataFrame: Feed-in data from renewable or other sources.
• GEN::DataFrame: Power generation data.
• REDISP::DataFrame: Redispatch actions and adjustments.
• PRS::DataFrame: Price or reserve-related data.
• LINEFLOW::DataFrame: AC line power flow data.
• DCLINEFLOW::DataFrame: DC line power flow data.
• NETINPUT::DataFrame: Net input to zones or nodes.
• NTC::DataFrame: Net Transfer Capacities between zones.
• STO_LVL::DataFrame: Storage level data.
• STO_LVL_REDISP::DataFrame: Redispatch-related storage level changes.
• ZonalMarketBalance::DataFrame: Market balance data aggregated per zone.
• NodalMarketBalance::DataFrame: Market balance data at the nodal level.
• NodalMarketRedispBalance::DataFrame: Redispatch-adjusted nodal market balance.

Constructor

DataFiles(dir::String)

Example

results_path = joinpath("results", scen_name)

### reading in the result files
results = DataFiles(results_path)

transform_results_by_type(results, kind, zone)

Aggregates generation results by plant type and time for a specified market kind and zone.

Arguments

• results: DataFiles object containing generation data and parameters.
• kind: Symbol or string specifying the market result to extract (:REDISP, :GEN, or :DA).
• zone: The name or key of the market zone to filter on.

Returns

A DataFrame with time as rows and columns for each plant type, containing the sum of generation for each time step and plant type in the specified zone.

Notes

• For kind = :REDISP, uses the GEN_REDISP field.
• For kind = :GEN or :DA, uses the GEN field (:GEN and :DA are treated identically).
• If an unsupported kind is given, a warning is issued and nothing is returned.

Example

julia> transform_results_by_type(results, :DA, "DE")
4×3 DataFrame
 Row │ Time   wind      coal     
     │ Int64  Float64?  Float64?
─────┼───────────────────────────
   1 │     1      60.0       0.0
   2 │     2     100.0       0.0
   3 │     3     120.0       0.0
   4 │     4     140.0      40.0

summarize_result(result_table)

Summarizes a generation results table by summing each column (plant type) over all time steps.

Arguments

• result_table: DataFrame produced by transform_results_by_type.

Returns

A DataFrame with a single row, where each column contains the total sum of generation (over all time steps) for the corresponding plant type.

Example

julia> summarize_result(transform_results_by_type(results, :DA, "DE"))
1×2 DataFrame
 Row │ wind     coal    
     │ Float64  Float64
─────┼──────────────────
   1 │   420.0     40.0

get_redispatch_by_type_node(results::DataFiles)

Calculates the difference between day-ahead generation (GEN) and redispatch generation (GEN_REDISP) for each technology type at each node across all time steps.

Arguments

• results::DataFiles: DataFiles object containing generation data, redispatch data, and parameters.

Returns

A DataFrame with the following columns:

• Time: Time step
• node: Node identifier
• type: Technology/plant type
• GEN: Day-ahead generation value
• GEN_REDISP: Redispatch generation value
• difference: The difference (GEN_REDISP - GEN), representing redispatch adjustments

Positive differences indicate upward redispatch, negative values indicate downward redispatch.

Notes

• Only includes plants that appear in both GEN and REDISP data.
• Results are grouped by Time, node, and technology type.
• Empty DataFrames for GEN or REDISP will result in an empty output DataFrame.

Example

julia> redispatch_diff = get_redispatch_by_type_node(results)
100×6 DataFrame
 Row │ Time   node    type     GEN      GEN_REDISP  difference
     │ Int64  String  String   Float64  Float64     Float64
─────┼──────────────────────────────────────────────────────────
   1 │     1  N1      wind      60.0        65.0         5.0
   2 │     1  N1      coal       0.0         0.0         0.0
   3 │     2  N2      gas       50.0        45.0        -5.0
  ⋮  │   ⋮      ⋮       ⋮        ⋮          ⋮           ⋮

get_market_statistics(results::DataFiles, zone::String="DE")

Calculate statistical overview of key market parameters for a specified zone.

Computes descriptive statistics (mean, median, standard deviation, min, max, sum) for exchange flows, lost load events, and market prices in the given zone. Returns both a summary statistics table and a time series dataframe for detailed analysis.

Arguments

• results::DataFiles: DataFiles object containing model results with EXCHANGE and ZonalMarketBalance data.
• zone::String="DE": Zone identifier for which to calculate statistics. Defaults to "DE".

Returns

A tuple containing two DataFrames:

1. Statistics DataFrame: Contains rows for each statistic (mean, median, std, min, max, sum) for three parameters (Exchange, Lost_Load, Price). Additional rows with NaN values mark the presence of time series data. Columns are:
   • metric::String: The statistical measure or "timeseries"
   • parameter::String: The parameter name (Exchange, Lost_Load, or Price)
   • value::Float64: The computed statistical value (or value vector for timeseries markers)

If EXCHANGE or ZonalMarketBalance data is empty, returns empty DataFrames with appropriate structure.

Notes

• Lost Load statistics include a count_positive metric indicating the number of time steps with positive lost load events.
• Exchange values represent net flows for the specified zone.
• Prices are extracted from the MarketBalance column of ZonalMarketBalance.

Example

```julia julia> statsdf = getmarket_statistics(results, "DE")

julia> stats_df 18×3 DataFrame Row │ metric parameter value │ String String Float64 ─────┼───────────────────────────────────── 1 │ mean Exchange 150.5 2 │ median Exchange 145.0 3 │ std Exchange 45.2 ⋮ │ ⋮ ⋮ ⋮