Source code for oemof.solph.constraints

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

"""Additional constraints to be used in an oemof energy model.
This file is part of project oemof ( It's copyrighted
by the contributors recorded in the version control history of the file,
available from its original location oemof/oemof/solph/

SPDX-License-Identifier: MIT

import pyomo.environ as po
from import sequence

[docs]def investment_limit(model, limit=None): """ Set an absolute limit for the total investment costs of an investment optimization problem: .. math:: \sum_{investment\_costs} \leq limit Parameters ---------- model : oemof.solph.Model Model to which the constraint is added limit : float Absolute limit of the investment (i.e. RHS of constraint) """ def investment_rule(m): expr = 0 if hasattr(m, "InvestmentFlow"): expr += m.InvestmentFlow.investment_costs if hasattr(m, "GenericInvestmentStorageBlock"): expr += m.GenericInvestmentStorageBlock.investment_costs return expr <= limit model.investment_limit = po.Constraint(rule=investment_rule) return model
[docs]def emission_limit(om, flows=None, limit=None): """ Short handle for generic_integral_limit() with keyword="emission_factor". Note ---- Flow objects required an attribute "emission_factor"! """ generic_integral_limit(om, keyword='emission_factor', flows=flows, limit=limit)
[docs]def generic_integral_limit(om, keyword, flows=None, limit=None): """Set a global limit for flows weighted by attribute called keyword. The attribute named by keyword has to be added to every flow you want to take into account. Total value of keyword attributes after optimization can be retrieved calling the :attr:`om.oemof.solph.Model.integral_limit_${keyword}()`. Parameters ---------- om : oemof.solph.Model Model to which constraints are added. flows : dict Dictionary holding the flows that should be considered in constraint. Keys are (source, target) objects of the Flow. If no dictionary is given all flows containing the keyword attribute will be used. keyword : attribute to consider limit : numeric Absolute limit of keyword attribute for the energy system. Note ---- Flow objects required an attribute named like keyword! **Constraint:** .. math:: \sum_{i \in F_E} \sum_{t \in T} P_i(t) \cdot w_i(t) \cdot \tau(t) \leq M With `F_I` being the set of flows considered for the integral limit and `T` being the set of time steps. The symbols used are defined as follows (with Variables (V) and Parameters (P)): ================ ==== ===================================================== math. symbol type explanation ================ ==== ===================================================== :math:`P_n(t)` V power flow :math:`n` at time step :math:`t` :math:`w_N(t)` P weight given to Flow named according to `keyword` :math:`\tau(t)` P width of time step :math:`t` :math:`L` P global limit given by keyword `limit` """ if flows is None: flows = {} for (i, o) in om.flows: if hasattr(om.flows[i, o], keyword): flows[(i, o)] = om.flows[i, o] else: for (i, o) in flows: if not hasattr(flows[i, o], keyword): raise AttributeError( ('Flow with source: {0} and target: {1} ' 'has no attribute {2}.').format( i.label, o.label, keyword)) limit_name = "integral_limit_"+keyword setattr(om, limit_name, po.Expression( expr=sum(om.flow[inflow, outflow, t] * om.timeincrement[t] * sequence(getattr(flows[inflow, outflow], keyword))[t] for (inflow, outflow) in flows for t in om.TIMESTEPS))) setattr(om, limit_name+"_constraint", po.Constraint( expr=(getattr(om, limit_name) <= limit))) return om
[docs]def equate_variables(model, var1, var2, factor1=1, name=None): r""" Adds a constraint to the given model that set two variables to equal adaptable by a factor. **The following constraints are build:** .. math:: var\textit{1} \cdot factor\textit{1} = var\textit{2} Parameters ---------- var1 : pyomo.environ.Var First variable, to be set to equal with Var2 and multiplied with factor1. var2 : pyomo.environ.Var Second variable, to be set equal to (Var1 * factor1). factor1 : float Factor to define the proportion between the variables. name : str Optional name for the equation e.g. in the LP file. By default the name is: equate + string representation of var1 and var2. model : oemof.solph.Model Model to which the constraint is added. Examples -------- The following example shows how to define a transmission line in the investment mode by connecting both investment variables. Note that the equivalent periodical costs (epc) of the line are 40. You could also add them to one line and set them to 0 for the other line. >>> import pandas as pd >>> from oemof import solph >>> date_time_index = pd.date_range('1/1/2012', periods=5, freq='H') >>> energysystem = solph.EnergySystem(timeindex=date_time_index) >>> bel1 = solph.Bus(label='electricity1') >>> bel2 = solph.Bus(label='electricity2') >>> energysystem.add(bel1, bel2) >>> energysystem.add(solph.Transformer( ... label='powerline_1_2', ... inputs={bel1: solph.Flow()}, ... outputs={bel2: solph.Flow( ... investment=solph.Investment(ep_costs=20))})) >>> energysystem.add(solph.Transformer( ... label='powerline_2_1', ... inputs={bel2: solph.Flow()}, ... outputs={bel1: solph.Flow( ... investment=solph.Investment(ep_costs=20))})) >>> om = solph.Model(energysystem) >>> line12 = energysystem.groups['powerline_1_2'] >>> line21 = energysystem.groups['powerline_2_1'] >>> solph.constraints.equate_variables( ... om, ... om.InvestmentFlow.invest[line12, bel2], ... om.InvestmentFlow.invest[line21, bel1]) """ if name is None: name = '_'.join(["equate", str(var1), str(var2)]) def equate_variables_rule(m): return var1 * factor1 == var2 setattr(model, name, po.Constraint(rule=equate_variables_rule))