| Conditions | 5 |
| Total Lines | 105 |
| Code Lines | 56 |
| Lines | 0 |
| Ratio | 0 % |
| Changes | 0 | ||
Small methods make your code easier to understand, in particular if combined with a good name. Besides, if your method is small, finding a good name is usually much easier.
For example, if you find yourself adding comments to a method's body, this is usually a good sign to extract the commented part to a new method, and use the comment as a starting point when coming up with a good name for this new method.
Commonly applied refactorings include:
If many parameters/temporary variables are present:
| 1 | # -*- coding: utf-8 -*- |
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| 29 | def test_add_constraints_example(solver="cbc", nologg=False): |
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| 30 | if not nologg: |
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| 31 | logging.basicConfig(level=logging.INFO) |
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| 32 | # ##### creating an oemof solph optimization model, nothing special here ## |
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| 33 | # create an energy system object for the oemof solph nodes |
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| 34 | es = EnergySystem( |
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| 35 | timeindex=pd.date_range("1/1/2012", periods=4, freq="h"), |
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| 36 | infer_last_interval=True, |
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| 37 | ) |
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| 38 | |||
| 39 | # add some nodes |
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| 40 | boil = Bus(label="oil", balanced=False) |
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| 41 | blig = Bus(label="lignite", balanced=False) |
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| 42 | b_el = Bus(label="b_el") |
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| 43 | es.add(boil, blig, b_el) |
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| 44 | |||
| 45 | es.add( |
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| 46 | components.Sink( |
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| 47 | label="Sink", |
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| 48 | inputs={b_el: Flow(nominal_capacity=40, fix=[0.5, 0.4, 0.3, 1])}, |
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| 49 | ) |
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| 50 | ) |
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| 51 | pp_oil = components.Converter( |
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| 52 | label="pp_oil", |
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| 53 | inputs={boil: Flow()}, |
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| 54 | outputs={b_el: Flow(nominal_capacity=50, variable_costs=25)}, |
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| 55 | conversion_factors={b_el: 0.39}, |
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| 56 | ) |
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| 57 | |||
| 58 | es.add(pp_oil) |
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| 59 | es.add( |
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| 60 | components.Converter( |
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| 61 | label="pp_lig", |
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| 62 | inputs={blig: Flow()}, |
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| 63 | outputs={b_el: Flow(nominal_capacity=50, variable_costs=10)}, |
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| 64 | conversion_factors={b_el: 0.41}, |
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| 65 | ) |
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| 66 | ) |
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| 67 | |||
| 68 | # create the model |
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| 69 | om = Model(energysystem=es) |
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| 70 | |||
| 71 | # add specific emission values to flow objects if source is a commodity bus |
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| 72 | for s, t in om.flows.keys(): |
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| 73 | if s is boil: |
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| 74 | om.flows[s, t].emission_factor = 0.27 # t/MWh |
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| 75 | if s is blig: |
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| 76 | om.flows[s, t].emission_factor = 0.39 # t/MWh |
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| 77 | emission_limit = 60e3 |
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| 78 | |||
| 79 | # add the outflow share |
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| 80 | om.flows[(boil, pp_oil)].outflow_share = [1, 0.5, 0, 0.3] |
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| 81 | |||
| 82 | # Now we are going to add a 'sub-model' and add a user specific constraint |
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| 83 | # first we add ad pyomo Block() instance that we can use to add our |
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| 84 | # constraints. Then, we add this Block to our previous defined |
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| 85 | # Model instance and add the constraints. |
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| 86 | myblock = po.Block() |
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| 87 | |||
| 88 | # create a pyomo set with the flows (i.e. list of tuples), |
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| 89 | # there will of course be only one flow inside this set, the one we used to |
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| 90 | # add outflow_share |
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| 91 | myblock.MYFLOWS = po.Set( |
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| 92 | initialize=[ |
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| 93 | k for (k, v) in om.flows.items() if hasattr(v, "outflow_share") |
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| 94 | ] |
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| 95 | ) |
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| 96 | |||
| 97 | # pyomo does not need a po.Set, we can use a simple list as well |
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| 98 | myblock.COMMODITYFLOWS = [ |
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| 99 | k for (k, v) in om.flows.items() if hasattr(v, "emission_factor") |
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| 100 | ] |
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| 101 | |||
| 102 | # add the sub-model to the oemof Model instance |
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| 103 | om.add_component("MyBlock", myblock) |
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| 104 | |||
| 105 | def _inflow_share_rule(m, si, e, ti): |
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| 106 | """pyomo rule definition: Here we can use all objects from the block or |
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| 107 | the om object, in this case we don't need anything from the block |
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| 108 | except the newly defined set MYFLOWS. |
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| 109 | """ |
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| 110 | expr = om.flow[si, e, ti] >= om.flows[si, e].outflow_share[ti] * sum( |
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| 111 | om.flow[i, o, ti] for (i, o) in om.FLOWS if o == e |
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| 112 | ) |
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| 113 | return expr |
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| 114 | |||
| 115 | myblock.inflow_share = po.Constraint( |
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| 116 | myblock.MYFLOWS, om.TIMESTEPS, rule=_inflow_share_rule |
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| 117 | ) |
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| 118 | # add emission constraint |
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| 119 | myblock.emission_constr = po.Constraint( |
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| 120 | expr=( |
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| 121 | sum( |
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| 122 | om.flow[i, o, t] |
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| 123 | for (i, o) in myblock.COMMODITYFLOWS |
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| 124 | for t in om.TIMESTEPS |
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| 125 | ) |
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| 126 | <= emission_limit |
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| 127 | ) |
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| 128 | ) |
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| 129 | |||
| 130 | # solve and write results to dictionary |
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| 131 | # you may print the model with om.pprint() |
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| 132 | assert om.solve(solver=solver) |
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| 133 | logging.info("Successfully finished.") |
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| 134 |