2-buses UCBlock, NetworkBlock and two ThermalUnitBlocks¶

In the following, we provide a quick example on how to add a simple optimization model with SMS++. The problem below optimizes the dispatch of two thermal generators connected by a transmission line between two buses over 24 hours.

In [1]:

from pysmspp import SMSNetwork, SMSFileType, Variable, Block, SMSConfig
import numpy as np

sn = SMSNetwork(file_type=SMSFileType.eBlockFile)  # Empty Block

sn

from pysmspp import SMSNetwork, SMSFileType, Variable, Block, SMSConfig import numpy as np sn = SMSNetwork(file_type=SMSFileType.eBlockFile) # Empty Block sn

Out[1]:

SMSNetwork Object
Block object
Attributes (1): SMS++_file_type
Dimensions (0): None
Variables (0): None
Blocks (0): None

Creating an SMS++ Network¶

First, we create an empty SMS++ network with the block file format and import necessary components:

Defining the UCBlock Parameters¶

The network does not contain any block inside, so it has to be populated. The first step is to specify the main parameters of the UCBlock.

1- Parameters for time, number of units, generators, and nodes:

In [2]:

kwargs = {
    "TimeHorizon": 24,  # number of time steps
    "NumberUnits": 2,  # number of units
    "NumberElectricalGenerators": 2,  # number of electrical generators
    "NumberNodes": 2,  # number of nodes
    "NumberLines": 1,  # number of lines
}

kwargs = { "TimeHorizon": 24, # number of time steps "NumberUnits": 2, # number of units "NumberElectricalGenerators": 2, # number of electrical generators "NumberNodes": 2, # number of nodes "NumberLines": 1, # number of lines }

2- Demand for each node: This has to be defined as a Variable object:

In [3]:

demand_array = np.full((2, 24), 50.0)
demand = {
    "ActivePowerDemand": Variable(  # active power demand
        "ActivePowerDemand",
        "float",
        ("NumberNodes", "TimeHorizon"),
        demand_array,
    )
}  # constant demand of 50kW

kwargs = {**kwargs, **demand}

demand_array = np.full((2, 24), 50.0) demand = { "ActivePowerDemand": Variable( # active power demand "ActivePowerDemand", "float", ("NumberNodes", "TimeHorizon"), demand_array, ) } # constant demand of 50kW kwargs = {**kwargs, **demand}

3- Parameters for the line: A line can be described with a DCNetworkBlock (DC power flow) or a TransportBlock. Here we use a TransportBlock with the following parameters:

In [4]:

line_variables = {
    "StartLine": Variable("StartLine", "int", ("NumberLines",), [0]),
    "EndLine": Variable("EndLine", "int", ("NumberLines",), [1]),
    "MinPowerFlow": Variable("MinPowerFlow", "float", ("NumberLines",), [-50.0]),
    "MaxPowerFlow": Variable("MaxPowerFlow", "float", ("NumberLines",), [50.0]),
    "LineSusceptance": Variable("LineSusceptance", "float", ("NumberLines",), [0.0]),
}

kwargs = {**kwargs, **line_variables}

line_variables = { "StartLine": Variable("StartLine", "int", ("NumberLines",), [0]), "EndLine": Variable("EndLine", "int", ("NumberLines",), [1]), "MinPowerFlow": Variable("MinPowerFlow", "float", ("NumberLines",), [-50.0]), "MaxPowerFlow": Variable("MaxPowerFlow", "float", ("NumberLines",), [50.0]), "LineSusceptance": Variable("LineSusceptance", "float", ("NumberLines",), [0.0]), } kwargs = {**kwargs, **line_variables}

4- Generator location: Variable to specify in which bus (node) the generator is attached:

In [5]:

generator_node = {
    "GeneratorNode": Variable(
        "GeneratorNode", int, ("NumberElectricalGenerators",), [0, 1]
    ),
}

kwargs = {**kwargs, **generator_node}

generator_node = { "GeneratorNode": Variable( "GeneratorNode", int, ("NumberElectricalGenerators",), [0, 1] ), } kwargs = {**kwargs, **generator_node}

Adding the UCBlock to the Network¶

Add everything with the SMSNetwork.add function:

In [6]:

sn.add(
    "UCBlock",  # block type
    "Block_0",  # block name
    id="0",  # block id
    **kwargs,
)

sn

sn.add( "UCBlock", # block type "Block_0", # block name id="0", # block id **kwargs, ) sn

Out[6]:

SMSNetwork Object
Block object
Attributes (1): SMS++_file_type
Dimensions (0): None
Variables (0): None
Blocks (1): Block_0

Inspecting the Network Structure¶

Now the SMSNetwork object has a UCBlock called Block_0. Let's see how it is organized:

In [7]:

sn.blocks["Block_0"]

sn.blocks["Block_0"]

Out[7]:

Block object
Attributes (2): type, id
Dimensions (5): TimeHorizon, NumberUnits, NumberElectricalGenerators, NumberNodes, NumberLines
Variables (7): ActivePowerDemand, StartLine, EndLine, MinPowerFlow, MaxPowerFlow, LineSusceptance, GeneratorNode
Blocks (0): None

Adding Thermal Unit Blocks¶

Now, the two thermal units have to be added to the UCBlock as ThermalUnitBlocks. First, we create a thermal unit block with the following parameters:

In [8]:

thermal_unit_block = Block().from_kwargs(
    block_type="ThermalUnitBlock",
    MinPower=Variable("MinPower", "float", (), 0.0),
    MaxPower=Variable("MaxPower", "float", (), 70.0),
    LinearTerm=Variable("LinearTerm", "float", (), 0.3),
    InitUpDownTime=Variable("InitUpDownTime", "int", (), 1),
)

thermal_unit_block

thermal_unit_block = Block().from_kwargs( block_type="ThermalUnitBlock", MinPower=Variable("MinPower", "float", (), 0.0), MaxPower=Variable("MaxPower", "float", (), 70.0), LinearTerm=Variable("LinearTerm", "float", (), 0.3), InitUpDownTime=Variable("InitUpDownTime", "int", (), 1), ) thermal_unit_block

Out[8]:

Block object
Attributes (1): type
Dimensions (0): None
Variables (4): MinPower, MaxPower, LinearTerm, InitUpDownTime
Blocks (0): None

Then, the unit block is added to the UCBlock:

In [9]:

# Add it to the existing UCBlock (Block_0)
sn.blocks["Block_0"].add_block("UnitBlock_0", block=thermal_unit_block)

sn.blocks["Block_0"]

# Add it to the existing UCBlock (Block_0) sn.blocks["Block_0"].add_block("UnitBlock_0", block=thermal_unit_block) sn.blocks["Block_0"]

Out[9]:

Block object
Attributes (2): type, id
Dimensions (5): TimeHorizon, NumberUnits, NumberElectricalGenerators, NumberNodes, NumberLines
Variables (7): ActivePowerDemand, StartLine, EndLine, MinPowerFlow, MaxPowerFlow, LineSusceptance, GeneratorNode
Blocks (1): UnitBlock_0

Similarly for the second ThermalUnitBlock. The max power is chosen to force the unit to be turned on to supply the demand:

In [10]:

thermal_unit_block = Block().from_kwargs(
    block_type="ThermalUnitBlock",
    MinPower=Variable("MinPower", "float", (), 0.0),
    MaxPower=Variable("MaxPower", "float", (), 90.0),
    LinearTerm=Variable("LinearTerm", "float", (), 0.8),
    InitUpDownTime=Variable("InitUpDownTime", "int", (), 1),
)

# Add it to the existing UCBlock (Block_0)
sn.blocks["Block_0"].add_block("UnitBlock_1", block=thermal_unit_block)

sn.blocks["Block_0"]

thermal_unit_block = Block().from_kwargs( block_type="ThermalUnitBlock", MinPower=Variable("MinPower", "float", (), 0.0), MaxPower=Variable("MaxPower", "float", (), 90.0), LinearTerm=Variable("LinearTerm", "float", (), 0.8), InitUpDownTime=Variable("InitUpDownTime", "int", (), 1), ) # Add it to the existing UCBlock (Block_0) sn.blocks["Block_0"].add_block("UnitBlock_1", block=thermal_unit_block) sn.blocks["Block_0"]

Out[10]:

Block object
Attributes (2): type, id
Dimensions (5): TimeHorizon, NumberUnits, NumberElectricalGenerators, NumberNodes, NumberLines
Variables (7): ActivePowerDemand, StartLine, EndLine, MinPowerFlow, MaxPowerFlow, LineSusceptance, GeneratorNode
Blocks (2): UnitBlock_0, UnitBlock_1

Optimizing the Network¶

The problem can now be optimized using a solver configuration:

In [11]:

configfile = SMSConfig(
    template="UCBlock/uc_solverconfig"
)  # path to the template solver config file "uc_solverconfig"
temporary_smspp_file = "./2buses_2thermal.nc"  # path to temporary SMS++ file
output_file = "./2buses_2thermal.txt"  # path to the output file (optional)
fp_solution = "./fp_solution_2buses_2thermal.nc4"  # path to the file where the full problem solution will be saved (optional). When provided, the result.solution object will be populated with the SMS++ solution object

result = sn.optimize(
    configfile,
    temporary_smspp_file,
    output_file,
    fp_solution=fp_solution,
)

configfile = SMSConfig( template="UCBlock/uc_solverconfig" ) # path to the template solver config file "uc_solverconfig" temporary_smspp_file = "./2buses_2thermal.nc" # path to temporary SMS++ file output_file = "./2buses_2thermal.txt" # path to the output file (optional) fp_solution = "./fp_solution_2buses_2thermal.nc4" # path to the file where the full problem solution will be saved (optional). When provided, the result.solution object will be populated with the SMS++ solution object result = sn.optimize( configfile, temporary_smspp_file, output_file, fp_solution=fp_solution, )

Executing command:
ucblock_solver 2buses_2thermal.nc -S uc_solverconfig.txt -c /home/docs/checkouts/readthedocs.org/user_builds/pysmspp/checkouts/latest/pysmspp/data/configs/UCBlock/ -p /home/docs/checkouts/readthedocs.org/user_builds/pysmspp/checkouts/latest/docs/examples/ -O /home/docs/checkouts/readthedocs.org/user_builds/pysmspp/checkouts/latest/docs/examples/fp_solution_2buses_2thermal.nc4

Using a default Block configuration
Running HiGHS 1.14.0 (git hash: n/a): Copyright (c) 2026 under MIT licence terms
Solver: HiGHSMILPSolver
MIP has 432 rows; 264 cols; 1004 nonzeros; 144 integer variables (142 binary)
Coefficient ranges:
  Matrix  [1e+00, 9e+01]
  Cost    [3e-01, 8e-01]
  Bound   [1e+00, 5e+01]
  RHS     [1e+00, 5e+01]
Presolving model
282 rows, 164 cols, 748 nonzeros 0s
0 rows, 0 cols, 0 nonzeros 0s
Presolve reductions: rows 0(-432); columns 0(-264); nonzeros 0(-1004) - Reduced to empty
Presolve: Optimal

Src: B => Branching; C => Central rounding; F => Feasibility pump; H => Heuristic;
     I => Shifting; J => Feasibility jump; L => Sub-MIP; P => Empty MIP; R => Randomized rounding;
     S => Solve LP; T => Evaluate node; U => Unbounded; X => User solution; Y => HiGHS solution;
     Z => ZI Round; l => Trivial lower; p => Trivial point; u => Trivial upper; z => Trivial zero

        Nodes      |    B&B Tree     |            Objective Bounds              |  Dynamic Constraints |       Work      
Src  Proc. InQueue |  Leaves   Expl. | BestBound       BestSol              Gap |   Cuts   InLp Confl. | LpIters     Time

         0       0         0   0.00%   1080            1080               0.00%        0      0      0         0     0.0s

Solving report
  Status            Optimal
  Primal bound      1080
  Dual bound        1080
  Gap               0% (tolerance: 0.01%)
  P-D integral      0
  Solution status   feasible
                    1080 (objective)
                    0 (bound viol.)
                    0 (int. viol.)
                    0 (row viol.)
  Timing            0.00
  Max sub-MIP depth 0
  Nodes             0
  Repair LPs        0
  LP iterations     0
Elapsed time: 2.66157000e-03 s
Status = 10 (Success)
Upper bound = 1.08000000e+03
Lower bound = 1.08000000e+03

----- ThermalUnitBlock 0 -----
Function value = 5.04000000e+02
Commitment     = [ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 ]
Start up       = [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
Shut down      = [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
Active power   = [      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01 ]

----- ThermalUnitBlock 1 -----
Function value = 5.76000000e+02
Commitment     = [ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 ]
Start up       = [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
Shut down      = [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
Active power   = [      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01 ]

----- DCNetworkBlock 0 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 1 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 2 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 3 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 4 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 5 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 6 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 7 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 8 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 9 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 10 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 11 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 12 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 13 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 14 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 15 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 16 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 17 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 18 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 19 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 20 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 21 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 22 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

----- DCNetworkBlock 23 -----
Function value   = 0.00000000e+00
Power flow       = [      2.00000000e+01 ]

Peak CPU Usage: 0.00 %
Peak Memory Usage: 2.48 MB
Total Time: 0.21 seconds

Viewing Results¶

The value of the objective function and the complete log can be obtained with:

In [12]:

result.objective_value

result.objective_value

Out[12]:

1080.0

In [13]:

result.log

result.log

Out[13]:

'Using a default Block configuration\nRunning HiGHS 1.14.0 (git hash: n/a): Copyright (c) 2026 under MIT licence terms\nSolver: HiGHSMILPSolver\nMIP has 432 rows; 264 cols; 1004 nonzeros; 144 integer variables (142 binary)\nCoefficient ranges:\n  Matrix  [1e+00, 9e+01]\n  Cost    [3e-01, 8e-01]\n  Bound   [1e+00, 5e+01]\n  RHS     [1e+00, 5e+01]\nPresolving model\n282 rows, 164 cols, 748 nonzeros 0s\n0 rows, 0 cols, 0 nonzeros 0s\nPresolve reductions: rows 0(-432); columns 0(-264); nonzeros 0(-1004) - Reduced to empty\nPresolve: Optimal\n\nSrc: B => Branching; C => Central rounding; F => Feasibility pump; H => Heuristic;\n     I => Shifting; J => Feasibility jump; L => Sub-MIP; P => Empty MIP; R => Randomized rounding;\n     S => Solve LP; T => Evaluate node; U => Unbounded; X => User solution; Y => HiGHS solution;\n     Z => ZI Round; l => Trivial lower; p => Trivial point; u => Trivial upper; z => Trivial zero\n\n        Nodes      |    B&B Tree     |            Objective Bounds              |  Dynamic Constraints |       Work      \nSrc  Proc. InQueue |  Leaves   Expl. | BestBound       BestSol              Gap |   Cuts   InLp Confl. | LpIters     Time\n\n         0       0         0   0.00%   1080            1080               0.00%        0      0      0         0     0.0s\n\nSolving report\n  Status            Optimal\n  Primal bound      1080\n  Dual bound        1080\n  Gap               0% (tolerance: 0.01%)\n  P-D integral      0\n  Solution status   feasible\n                    1080 (objective)\n                    0 (bound viol.)\n                    0 (int. viol.)\n                    0 (row viol.)\n  Timing            0.00\n  Max sub-MIP depth 0\n  Nodes             0\n  Repair LPs        0\n  LP iterations     0\nElapsed time: 2.66157000e-03 s\nStatus = 10 (Success)\nUpper bound = 1.08000000e+03\nLower bound = 1.08000000e+03\n\n----- ThermalUnitBlock 0 -----\nFunction value = 5.04000000e+02\nCommitment     = [ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 ]\nStart up       = [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]\nShut down      = [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]\nActive power   = [      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01      7.00000000e+01 ]\n\n----- ThermalUnitBlock 1 -----\nFunction value = 5.76000000e+02\nCommitment     = [ 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 ]\nStart up       = [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]\nShut down      = [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]\nActive power   = [      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01      3.00000000e+01 ]\n\n----- DCNetworkBlock 0 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 1 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 2 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 3 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 4 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 5 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 6 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 7 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 8 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 9 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 10 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 11 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 12 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 13 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 14 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 15 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 16 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 17 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 18 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 19 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 20 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 21 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 22 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\n----- DCNetworkBlock 23 -----\nFunction value   = 0.00000000e+00\nPower flow       = [      2.00000000e+01 ]\n\nPeak CPU Usage: 0.00 %\nPeak Memory Usage: 2.48 MB\nTotal Time: 0.21 seconds\n'

In [14]:

result.solution

result.solution

Out[14]:

SMSNetwork Object
Block object
Attributes (1): SMS++_file_type
Dimensions (0): None
Variables (0): None
Blocks (1): Solution_0