PowerModels Dictionary to DataFrame Conversion

VegaLite uses tabular data when creating a plot, and this requires converting the PowerModels dictionary data into a DataFrame. A struct is used for all of the supported components of the base power plot, where each component type is a DataFrame. This struct is created when powerplot() is called. Multi-network dictionaries are supported.

mutable struct PowerModelsDataFrame
    metadata::DataFrames.DataFrame
    bus::DataFrames.DataFrame
    gen::DataFrames.DataFrame
    branch::DataFrames.DataFrame
    dcline::DataFrames.DataFrame
    load::DataFrames.DataFrame
    connector::DataFrames.DataFrame

Using tabular data can be convenient for a statistical analysis of the components. To create this data struct, call the constructor on a powermodels dictionary.

using PowerModels
using PowerPlots
case = parse_file("case14.m")

case_PMDF = PowerModelsDataFrame(case)

PowerModelsDataFrame(1×5 DataFrame
 Row │ source_version  per_unit  source_type  name                   baseMVA
     │ SubString…      Bool      String       SubString…             Float64
─────┼───────────────────────────────────────────────────────────────────────
   1 │ 2                   true  matpower     pglib_opf_case14_ieee    100.0, 14×12 DataFrame
 Row │ zone   bus_i  bus_type  vmax     ComponentType  source_id       area    ⋯
     │ Int64  Int64  Int64     Float64  String         String          Int64   ⋯
─────┼──────────────────────────────────────────────────────────────────────────
   1 │     1      4         1     1.06  bus            Any["bus", 4]       1   ⋯
   2 │     1      1         3     1.06  bus            Any["bus", 1]       1
   3 │     1     12         1     1.06  bus            Any["bus", 12]      1
   4 │     1      2         2     1.06  bus            Any["bus", 2]       1
   5 │     1      6         2     1.06  bus            Any["bus", 6]       1   ⋯
   6 │     1     11         1     1.06  bus            Any["bus", 11]      1
   7 │     1     13         1     1.06  bus            Any["bus", 13]      1
   8 │     1      5         1     1.06  bus            Any["bus", 5]       1
   9 │     1     14         1     1.06  bus            Any["bus", 14]      1   ⋯
  10 │     1      7         1     1.06  bus            Any["bus", 7]       1
  11 │     1      8         2     1.06  bus            Any["bus", 8]       1
  12 │     1     10         1     1.06  bus            Any["bus", 10]      1
  13 │     1      9         1     1.06  bus            Any["bus", 9]       1   ⋯
  14 │     1      3         2     1.06  bus            Any["bus", 3]       1
                                                               5 columns omitted, 5×18 DataFrame
 Row │ pg       model  shutdown  startup  qg       gen_bus  pmax     Component ⋯
     │ Float64  Int64  Float64   Float64  Float64  Int64    Float64  String    ⋯
─────┼──────────────────────────────────────────────────────────────────────────
   1 │   0.0        2       0.0      0.0     0.09        6     0.0   gen       ⋯
   2 │   1.7        2       0.0      0.0     0.05        1     3.4   gen
   3 │   0.0        2       0.0      0.0     0.09        8     0.0   gen
   4 │   0.295      2       0.0      0.0     0.0         2     0.59  gen
   5 │   0.0        2       0.0      0.0     0.2         3     0.0   gen       ⋯
                                                              11 columns omitted, 20×20 DataFrame
 Row │ br_r     rate_a   shift    rate_b   br_x     rate_c   g_to     Componen ⋯
     │ Float64  Float64  Float64  Float64  Float64  Float64  Float64  String   ⋯
─────┼──────────────────────────────────────────────────────────────────────────
   1 │ 0.05811     1.58      0.0     1.58  0.17632     1.58      0.0  branch   ⋯
   2 │ 0.01938     4.72      0.0     4.72  0.05917     4.72      0.0  branch
   3 │ 0.12291     1.04      0.0     1.04  0.25581     1.04      0.0  branch
   4 │ 0.17093     0.76      0.0     0.76  0.34802     0.76      0.0  branch
   5 │ 0.05403     1.28      0.0     1.28  0.22304     1.28      0.0  branch   ⋯
   6 │ 0.06701     1.6       0.0     1.6   0.17103     1.6       0.0  branch
   7 │ 0.09498     1.34      0.0     1.34  0.1989      1.34      0.0  branch
   8 │ 0.06615     2.01      0.0     2.01  0.13027     2.01      0.0  branch
  ⋮  │    ⋮        ⋮        ⋮        ⋮        ⋮        ⋮        ⋮           ⋮  ⋱
  14 │ 0.0         1.41      0.0     1.41  0.20912     1.41      0.0  branch   ⋯
  15 │ 0.12711     0.99      0.0     0.99  0.27038     0.99      0.0  branch
  16 │ 0.0         1.17      0.0     1.17  0.25202     1.17      0.0  branch
  17 │ 0.22092     0.99      0.0     0.99  0.19988     0.99      0.0  branch
  18 │ 0.0         0.53      0.0     0.53  0.55618     0.53      0.0  branch   ⋯
  19 │ 0.08205     1.41      0.0     1.41  0.19207     1.41      0.0  branch
  20 │ 0.04699     1.45      0.0     1.45  0.19797     1.45      0.0  branch
                                                   13 columns and 5 rows omitted, 0×0 DataFrame, 11×7 DataFrame
 Row │ source_id       ComponentType  load_bus  status  qd       pd       inde ⋯
     │ String          String         Int64     Int8    Float64  Float64  Int6 ⋯
─────┼──────────────────────────────────────────────────────────────────────────
   1 │ Any["bus", 5]   load                  5       1    0.016    0.076       ⋯
   2 │ Any["bus", 2]   load                  2       1    0.127    0.217
   3 │ Any["bus", 3]   load                  3       1    0.19     0.942
   4 │ Any["bus", 9]   load                  9       1    0.166    0.295
   5 │ Any["bus", 14]  load                 14       1    0.05     0.149     1 ⋯
   6 │ Any["bus", 6]   load                  6       1    0.075    0.112
   7 │ Any["bus", 10]  load                 10       1    0.058    0.09
   8 │ Any["bus", 11]  load                 11       1    0.018    0.035
   9 │ Any["bus", 13]  load                 13       1    0.058    0.135     1 ⋯
  10 │ Any["bus", 12]  load                 12       1    0.016    0.061
  11 │ Any["bus", 4]   load                  4       1   -0.039    0.478
                                                                1 column omitted, 0×0 DataFrame, 0×0 DataFrame, 0×0 DataFrame)

To create an individual component dictionary, use the comp_dict_to_dataframe function.

using PowerModels
using PowerPlots
case = parse_file("case14.m")

case_PMDF = comp_dict_to_dataframe(case["bus"])

14×11 DataFrame

Row	zone	bus_i	bus_type	vmax	source_id	area	vmin	index	va	vm	base_kv
	Int64	Int64	Int64	Float64	String	Int64	Float64	Int64	Float64	Float64	Float64
1	1	4	1	1.06	Any["bus", 4]	1	0.94	4	0.0	1.0	1.0
2	1	1	3	1.06	Any["bus", 1]	1	0.94	1	0.0	1.0	1.0
3	1	12	1	1.06	Any["bus", 12]	1	0.94	12	0.0	1.0	1.0
4	1	2	2	1.06	Any["bus", 2]	1	0.94	2	0.0	1.0	1.0
5	1	6	2	1.06	Any["bus", 6]	1	0.94	6	0.0	1.0	1.0
6	1	11	1	1.06	Any["bus", 11]	1	0.94	11	0.0	1.0	1.0
7	1	13	1	1.06	Any["bus", 13]	1	0.94	13	0.0	1.0	1.0
8	1	5	1	1.06	Any["bus", 5]	1	0.94	5	0.0	1.0	1.0
9	1	14	1	1.06	Any["bus", 14]	1	0.94	14	0.0	1.0	1.0
10	1	7	1	1.06	Any["bus", 7]	1	0.94	7	0.0	1.0	1.0
11	1	8	2	1.06	Any["bus", 8]	1	0.94	8	0.0	1.0	1.0
12	1	10	1	1.06	Any["bus", 10]	1	0.94	10	0.0	1.0	1.0
13	1	9	1	1.06	Any["bus", 9]	1	0.94	9	0.0	1.0	1.0
14	1	3	2	1.06	Any["bus", 3]	1	0.94	3	0.0	1.0	1.0