add_constraints

Complexity

Total Complexity

6

Size/Duplication

Total Lines	162
Duplicated Lines	0 %

Importance

Changes

0

1 Function

Rating	Name	Duplication	Size	Complexity
B	main()	0	105	6

# -*- coding: utf-8 -*-

"""
General description
-------------------
This script shows how to add an individual constraint to the oemof solph
OperationalModel.
The constraint we add forces a flow to be greater or equal a certain share
of all inflows of its target bus. Moreover we will set an emission constraint.

Code
----
Download source code: :download:`add_constraints.py </../examples/flexible_modelling/add_constraints.py>`

.. dropdown:: Click to display code

    .. literalinclude:: /../examples/flexible_modelling/add_constraints.py
        :language: python
        :lines: 41-158

Installation requirements
-------------------------
This example requires oemof.solph (v0.5.x), install by:

.. code:: bash

    pip install oemof.solph[examples]

To draw the graph pygraphviz is required, installed by:

.. code:: bash

    pip install pygraphviz

License
-------
Simon Hilpert - 31.10.2016 - simon.hilpert@uni-flensburg.de

`MIT license <https://github.com/oemof/oemof-solph/blob/dev/LICENSE>`_
"""
import logging

import pandas as pd
import pyomo.environ as po

from oemof.solph import Bus
from oemof.solph import EnergySystem
from oemof.solph import Flow
from oemof.solph import Model
from oemof.solph import components as cmp


def main(solver="cbc", nologg=False, optimize=True):
    if not nologg:
        logging.basicConfig(level=logging.INFO)
    # ##### creating an oemof solph optimization model, nothing special here ##
    # create an energy system object for the oemof solph nodes
    es = EnergySystem(
        timeindex=pd.date_range("1/1/2017", periods=5, freq="h"),
        infer_last_interval=False,
    )
    # add some nodes

    boil = Bus(label="oil", balanced=False)
    blig = Bus(label="lignite", balanced=False)
    b_el = Bus(label="b_el")

    es.add(boil, blig, b_el)

    sink = cmp.Sink(
        label="Sink",
        inputs={b_el: Flow(nominal_capacity=40, fix=[0.5, 0.4, 0.3, 1])},
    )
    pp_oil = cmp.Converter(
        label="pp_oil",
        inputs={boil: Flow()},
        outputs={b_el: Flow(nominal_capacity=50, variable_costs=25)},
        conversion_factors={b_el: 0.39},
    )
    pp_lig = cmp.Converter(
        label="pp_lig",
        inputs={blig: Flow()},
        outputs={b_el: Flow(nominal_capacity=50, variable_costs=10)},
        conversion_factors={b_el: 0.41},
    )

    es.add(sink, pp_oil, pp_lig)

    if optimize is False:
        return es

    # create the model
    om = Model(energysystem=es)

    # add specific emission values to flow objects if source is a commodity bus
    for s, t in om.flows.keys():
        if s is boil:
            om.flows[s, t].emission_factor = 0.27  # t/MWh
        if s is blig:
            om.flows[s, t].emission_factor = 0.39  # t/MWh
    emission_limit = 60e3

    # add the outflow share
    om.flows[(boil, pp_oil)].outflow_share = [1, 0.5, 0, 0.3]

    # Now we are going to add a 'sub-model' and add a user specific constraint
    # first we add a pyomo Block() instance that we can use to add our
    # constraints. Then, we add this Block to our previous defined
    # Model instance and add the constraints.
    myblock = po.Block()

    # create a pyomo set with the flows (i.e. list of tuples),
    # there will of course be only one flow inside this set, the one we used to
    # add outflow_share
    myblock.MYFLOWS = po.Set(
        initialize=[
            k for (k, v) in om.flows.items() if hasattr(v, "outflow_share")
        ]
    )

    # pyomo does not need a po.Set, we can use a simple list as well
    myblock.COMMODITYFLOWS = [
        k for (k, v) in om.flows.items() if hasattr(v, "emission_factor")
    ]

    # add the sub-model to the oemof Model instance
    om.add_component("MyBlock", myblock)

    def _inflow_share_rule(m, s, e, t):
        """pyomo rule definition: Here we can use all objects from the block or
        the om object, in this case we don't need anything from the block
        except the newly defined set MYFLOWS.
        """
        expr = om.flow[s, e, t] >= om.flows[s, e].outflow_share[t] * sum(

The variable om does not seem to be defined for all execution paths.

            om.flow[i, o, t] for (i, o) in om.FLOWS if o == e
        )
        return expr

    myblock.inflow_share = po.Constraint(
        myblock.MYFLOWS, om.TIMESTEPS, rule=_inflow_share_rule
    )
    # add emission constraint
    myblock.emission_constr = po.Constraint(
        expr=(
            sum(
                om.flow[i, o, t]
                for (i, o) in myblock.COMMODITYFLOWS
                for t in om.TIMESTEPS
            )
            <= emission_limit
        )
    )

    # solve and write results to dictionary
    # you may print the model with om.pprint()
    om.solve(solver=solver)
    logging.info("Successfully finished.")


if __name__ == "__main__":
    main()