Beispiel #1
0
def create_explicit_subproblem(model,
                               subproblem,
                               model_data,
                               include_angle_diff_limits=False,
                               include_bigm=False):
    ### power system data
    md = model_data

    ### create dictionaries of object sets
    gens = dict(md.elements(element_type='generator'))
    buses = dict(md.elements(element_type='bus'))
    branches = dict(md.elements(element_type='branch'))
    loads = dict(md.elements(element_type='load'))
    shunts = dict(md.elements(element_type='shunt'))

    ### create dictionaries across object attributes for an object of the same set type
    gen_attrs = md.attributes(element_type='generator')
    bus_attrs = md.attributes(element_type='bus')
    branch_attrs = md.attributes(element_type='branch')

    inlet_branches_by_bus, outlet_branches_by_bus = \
        tx_utils.inlet_outlet_branches_by_bus(branches, buses)
    gens_by_bus = tx_utils.gens_by_bus(buses, gens)

    ### declare (and fix) the loads at the buses
    bus_p_loads, _ = tx_utils.dict_of_bus_loads(buses, loads)
    buses_with_loads = list(k for k in bus_p_loads.keys()
                            if bus_p_loads[k] != 0.)

    ### declare load shed variables
    decl.declare_var('load_shed',
                     subproblem,
                     buses_with_loads,
                     initialize=0.0,
                     domain=pe.NonNegativeReals)

    #libbus.declare_var_pl(model.subproblem, bus_attrs['names'], initialize=bus_p_loads)
    #model.subproblem.pl.fix()
    subproblem.pl = bus_p_loads

    ### declare the fixed shunts at the buses
    _, bus_gs_fixed_shunts = tx_utils.dict_of_bus_fixed_shunts(buses, shunts)

    ### declare the polar voltages
    va_bounds = {k: (-pi, pi) for k in bus_attrs['va']}
    va_init = {k: bus_attrs['va'][k] * (pi / 180) for k in bus_attrs['va']}
    libbus.declare_var_va(subproblem,
                          bus_attrs['names'],
                          initialize=bus_attrs['va'],
                          bounds=va_bounds)

    ### fix the reference bus
    ref_bus = md.data['system']['reference_bus']
    ref_angle = md.data['system']['reference_bus_angle']
    subproblem.va[ref_bus].fix(radians(ref_angle))

    ### declare the generator real power
    pg_init = {
        k: (gen_attrs['p_min'][k] + gen_attrs['p_max'][k]) / 2.0
        for k in gen_attrs['pg']
    }
    libgen.declare_var_pg(subproblem, gen_attrs['names'], initialize=pg_init)

    ### declare the current flows in the branches
    vr_init = {
        k: bus_attrs['vm'][k] * pe.cos(bus_attrs['va'][k])
        for k in bus_attrs['vm']
    }
    vj_init = {
        k: bus_attrs['vm'][k] * pe.sin(bus_attrs['va'][k])
        for k in bus_attrs['vm']
    }
    pf_init = dict()
    for branch_name, branch in branches.items():
        from_bus = branch['from_bus']
        to_bus = branch['to_bus']
        y_matrix = tx_calc.calculate_y_matrix_from_branch(branch)
        ifr_init = tx_calc.calculate_ifr(vr_init[from_bus], vj_init[from_bus],
                                         vr_init[to_bus], vj_init[to_bus],
                                         y_matrix)
        ifj_init = tx_calc.calculate_ifj(vr_init[from_bus], vj_init[from_bus],
                                         vr_init[to_bus], vj_init[to_bus],
                                         y_matrix)
        pf_init[branch_name] = tx_calc.calculate_p(ifr_init, ifj_init,
                                                   vr_init[from_bus],
                                                   vj_init[from_bus])

    libbranch.declare_var_pf(model=subproblem,
                             index_set=branch_attrs['names'],
                             initialize=pf_init)

    # need to include variable references on subproblem to variables, which exist on the master block
    #bi.components.varref(subproblem, origin = model)
    subproblem.add_component("u", Reference(model.u))
    subproblem.add_component("v", Reference(model.v))
    subproblem.add_component("w", Reference(model.w))
    if include_bigm:
        # create big-M
        _create_bigm(subproblem, md)
        ### declare the branch power flow disjuncts
        subcons.declare_eq_branch_power_btheta_approx_bigM(
            model=subproblem,
            index_set=branch_attrs['names'],
            branches=branches)

        ### declare the real power flow limits
        p_max = {k: branches[k]['rating_long_term'] for k in branches.keys()}
        subcons.declare_ineq_p_branch_thermal_lbub_switch(
            model=subproblem,
            index_set=branch_attrs['names'],
            p_thermal_limits=p_max)

    else:
        ### declare the branch power flow with indicator variable in the bilinear term
        subcons.declare_eq_branch_power_btheta_approx_nonlin(
            model=subproblem,
            index_set=branch_attrs['names'],
            branches=branches)

        ### declare the real power flow limits
        p_max = {k: branches[k]['rating_long_term'] for k in branches.keys()}
        libbranch.declare_ineq_p_branch_thermal_lbub(
            model=subproblem,
            index_set=branch_attrs['names'],
            branches=branches,
            p_thermal_limits=p_max,
            approximation_type=ApproximationType.BTHETA)

    ### declare the load shed
    subcons.declare_ineq_load_shed(model=subproblem,
                                   index_set=buses_with_loads)

    ### declare the generator compromised
    subcons.declare_ineq_gen(model=subproblem,
                             index_set=gen_attrs['names'],
                             gens=gens)

    ### declare the p balance
    rhs_kwargs = {'include_feasibility_slack_neg': 'load_shed'}
    libbus.declare_eq_p_balance_dc_approx(
        model=subproblem,
        index_set=bus_attrs['names'],
        bus_p_loads=bus_p_loads,
        gens_by_bus=gens_by_bus,
        bus_gs_fixed_shunts=bus_gs_fixed_shunts,
        inlet_branches_by_bus=inlet_branches_by_bus,
        outlet_branches_by_bus=outlet_branches_by_bus,
        approximation_type=ApproximationType.BTHETA,
        **rhs_kwargs)

    ### declare angle difference limits on interconnected buses
    if include_angle_diff_limits:
        libbranch.declare_ineq_angle_diff_branch_lbub(
            model=subproblem,
            index_set=branch_attrs['names'],
            branches=branches,
            coordinate_type=CoordinateType.POLAR)

    ### lower-level objective for interdiction problem (opposite to upper-level objective)
    subproblem.obj = pe.Objective(expr=sum(subproblem.load_shed[l]
                                           for l in buses_with_loads),
                                  sense=pe.minimize)

    return model, md
Beispiel #2
0
def _btheta_dcopf_network_model(md,block):
    buses = dict(md.elements(element_type='bus'))
    branches = dict(md.elements(element_type='branch'))
    loads = dict(md.elements(element_type='load'))
    shunts = dict(md.elements(element_type='shunt'))

    bus_attrs = md.attributes(element_type='bus')
    branch_attrs = md.attributes(element_type='branch')

    inlet_branches_by_bus, outlet_branches_by_bus = \
        tx_utils.inlet_outlet_branches_by_bus(branches, buses)

    ## this is not the "real" gens by bus, but the
    ## index of net injections from the UC model
    gens_by_bus = block.gens_by_bus

    ### declare (and fix) the loads at the buses
    bus_p_loads, _ = tx_utils.dict_of_bus_loads(buses, loads)

    libbus.declare_var_pl(block, bus_attrs['names'], initialize=bus_p_loads)
    block.pl.fix()

    ### declare the fixed shunts at the buses
    _, bus_gs_fixed_shunts = tx_utils.dict_of_bus_fixed_shunts(buses, shunts)

    ### declare the polar voltages
    va_bounds = {k: (-pi, pi) for k in bus_attrs['names']}
    libbus.declare_var_va(block, bus_attrs['names'], initialize=None,
                          bounds=va_bounds
                          )

    ### fix the reference bus
    ref_bus = md.data['system']['reference_bus']
    block.va[ref_bus].fix(0.0)

    ref_angle = md.data['system']['reference_bus_angle']
    if ref_angle != 0.0:
        raise ValueError('The BTHETA DCOPF formulation currently only supports'
                         ' a reference bus angle of 0 degrees, but an angle'
                         ' of {} degrees was found.'.format(ref_angle))

    p_max = {k: branches[k]['rating_long_term'] for k in branches.keys()}
    p_lbub = {k: (-p_max[k],p_max[k]) for k in branches.keys()}
    pf_bounds = p_lbub

    libbranch.declare_var_pf(model=block,
                             index_set=branch_attrs['names'],
                             initialize=None,
                             bounds=pf_bounds
                             )

    ### declare the branch power flow approximation constraints
    libbranch.declare_eq_branch_power_btheta_approx(model=block,
                                                    index_set=branch_attrs['names'],
                                                    branches=branches
                                                    )

    ### declare the p balance
    libbus.declare_eq_p_balance_dc_approx(model=block,
                                          index_set=bus_attrs['names'],
                                          bus_p_loads=bus_p_loads,
                                          gens_by_bus=gens_by_bus,
                                          bus_gs_fixed_shunts=bus_gs_fixed_shunts,
                                          inlet_branches_by_bus=inlet_branches_by_bus,
                                          outlet_branches_by_bus=outlet_branches_by_bus,
                                          approximation_type=ApproximationType.BTHETA
                                          )

    ### declare the real power flow limits
    libbranch.declare_ineq_p_branch_thermal_lbub(model=block,
                                                 index_set=branch_attrs['names'],
                                                 branches=branches,
                                                 p_thermal_limits=p_max,
                                                 approximation_type=ApproximationType.BTHETA
                                                 )

    ### declare angle difference limits on interconnected buses
    libbranch.declare_ineq_angle_diff_branch_lbub(model=block,
                                                  index_set=branch_attrs['names'],
                                                  branches=branches,
                                                  coordinate_type=CoordinateType.POLAR
                                                  )

    return block
Beispiel #3
0
def create_ptdf_dcopf_model(model_data,
                            include_feasibility_slack=False,
                            base_point=BasePointType.FLATSTART,
                            ptdf_options=None):

    ptdf_options = lpu.populate_default_ptdf_options(ptdf_options)

    baseMVA = model_data.data['system']['baseMVA']
    lpu.check_and_scale_ptdf_options(ptdf_options, baseMVA)

    md = model_data.clone_in_service()
    tx_utils.scale_ModelData_to_pu(md, inplace=True)

    gens = dict(md.elements(element_type='generator'))
    buses = dict(md.elements(element_type='bus'))
    branches = dict(md.elements(element_type='branch'))
    loads = dict(md.elements(element_type='load'))
    shunts = dict(md.elements(element_type='shunt'))

    gen_attrs = md.attributes(element_type='generator')
    ## to keep things in order
    buses_idx = tuple(buses.keys())
    branches_idx = tuple(branches.keys())

    inlet_branches_by_bus, outlet_branches_by_bus = \
        tx_utils.inlet_outlet_branches_by_bus(branches, buses)
    gens_by_bus = tx_utils.gens_by_bus(buses, gens)

    model = pe.ConcreteModel()

    ### declare (and fix) the loads at the buses
    bus_p_loads, _ = tx_utils.dict_of_bus_loads(buses, loads)

    libbus.declare_var_pl(model, buses_idx, initialize=bus_p_loads)
    model.pl.fix()

    ### declare the fixed shunts at the buses
    _, bus_gs_fixed_shunts = tx_utils.dict_of_bus_fixed_shunts(buses, shunts)

    ### declare the generator real power
    pg_init = {
        k: (gen_attrs['p_min'][k] + gen_attrs['p_max'][k]) / 2.0
        for k in gen_attrs['pg']
    }
    libgen.declare_var_pg(model,
                          gen_attrs['names'],
                          initialize=pg_init,
                          bounds=zip_items(gen_attrs['p_min'],
                                           gen_attrs['p_max']))

    ### include the feasibility slack for the system balance
    p_rhs_kwargs = {}
    if include_feasibility_slack:
        p_rhs_kwargs, penalty_expr = _include_system_feasibility_slack(
            model, gen_attrs, bus_p_loads)

    ### declare the p balance
    libbus.declare_eq_p_balance_ed(model=model,
                                   index_set=buses_idx,
                                   bus_p_loads=bus_p_loads,
                                   gens_by_bus=gens_by_bus,
                                   bus_gs_fixed_shunts=bus_gs_fixed_shunts,
                                   **p_rhs_kwargs)

    ### declare net withdraw expression for use in PTDF power flows
    libbus.declare_expr_p_net_withdraw_at_bus(
        model=model,
        index_set=buses_idx,
        bus_p_loads=bus_p_loads,
        gens_by_bus=gens_by_bus,
        bus_gs_fixed_shunts=bus_gs_fixed_shunts,
    )

    ### add "blank" power flow expressions
    libbranch.declare_expr_pf(
        model=model,
        index_set=branches_idx,
    )

    ## Do and store PTDF calculation
    reference_bus = md.data['system']['reference_bus']

    PTDF = ptdf_utils.get_ptdf_potentially_from_file(ptdf_options,
                                                     branches_idx, buses_idx)
    if PTDF is None:
        PTDF = ptdf_utils.PTDFMatrix(branches,
                                     buses,
                                     reference_bus,
                                     base_point,
                                     ptdf_options,
                                     branches_keys=branches_idx,
                                     buses_keys=buses_idx)

    model._PTDF = PTDF
    model._ptdf_options = ptdf_options

    ptdf_utils.write_ptdf_potentially_to_file(ptdf_options, PTDF)

    if ptdf_options['lazy']:

        ### add "blank" real power flow limits
        libbranch.declare_ineq_p_branch_thermal_bounds(
            model=model,
            index_set=branches_idx,
            branches=branches,
            p_thermal_limits=None,
            approximation_type=None,
        )

        ### add helpers for tracking monitored branches
        lpu.add_monitored_flow_tracker(model)

        ### add initial branches to monitored set
        lpu.add_initial_monitored_branches(model, branches, branches_idx,
                                           ptdf_options, PTDF)

    else:
        p_max = {k: branches[k]['rating_long_term'] for k in branches.keys()}
        ## add all the constraints
        ### declare the branch power flow approximation constraints
        libbranch.declare_eq_branch_power_ptdf_approx(
            model=model,
            index_set=branches_idx,
            PTDF=PTDF,
            abs_ptdf_tol=ptdf_options['abs_ptdf_tol'],
            rel_ptdf_tol=ptdf_options['rel_ptdf_tol'],
        )

        ### add all the limits
        libbranch.declare_ineq_p_branch_thermal_lbub(
            model=model,
            index_set=branches_idx,
            branches=branches,
            p_thermal_limits=p_max,
            approximation_type=ApproximationType.PTDF,
        )

    ### declare the generator cost objective
    libgen.declare_expression_pgqg_operating_cost(model=model,
                                                  index_set=gen_attrs['names'],
                                                  p_costs=gen_attrs['p_cost'])

    obj_expr = sum(model.pg_operating_cost[gen_name]
                   for gen_name in model.pg_operating_cost)
    if include_feasibility_slack:
        obj_expr += penalty_expr

    model.obj = pe.Objective(expr=obj_expr)

    return model, md
Beispiel #4
0
def create_btheta_dcopf_model(model_data):
    md = tx_utils.scale_ModelData_to_pu(model_data)

    gens = dict(md.elements(element_type='generator'))
    buses = dict(md.elements(element_type='bus'))
    branches = dict(md.elements(element_type='branch'))
    loads = dict(md.elements(element_type='load'))
    shunts = dict(md.elements(element_type='shunt'))

    gen_attrs = md.attributes(element_type='generator')
    bus_attrs = md.attributes(element_type='bus')
    branch_attrs = md.attributes(element_type='branch')
    load_attrs = md.attributes(element_type='load')
    shunt_attrs = md.attributes(element_type='shunt')

    inlet_branches_by_bus, outlet_branches_by_bus = \
        tx_utils.inlet_outlet_branches_by_bus(branches, buses)
    gens_by_bus = tx_utils.gens_in_service_by_bus(buses, gens)

    model = pe.ConcreteModel()

    ### declare (and fix) the loads at the buses
    bus_p_loads, _ = tx_utils.dict_of_bus_loads(buses, loads)

    libbus.declare_var_pl(model, bus_attrs['names'], initialize=bus_p_loads)
    model.pl.fix()

    ### declare the fixed shunts at the buses
    _, bus_gs_fixed_shunts = tx_utils.dict_of_bus_fixed_shunts(buses, shunts)

    ### declare the polar voltages
    va_bounds = {k: (-pi, pi) for k in bus_attrs['va']}
    libbus.declare_var_va(model,
                          bus_attrs['names'],
                          initialize=bus_attrs['va'],
                          bounds=va_bounds)

    ### fix the reference bus
    ref_bus = md.data['system']['reference_bus']
    model.va[ref_bus].fix(0.0)

    ref_angle = md.data['system']['reference_bus_angle']
    if ref_angle != 0.0:
        raise ValueError('The BTHETA DCOPF formulation currently only supports'
                         ' a reference bus angle of 0 degrees, but an angle'
                         ' of {} degrees was found.'.format(ref_angle))

    ### declare the generator real power
    pg_init = {
        k: (gen_attrs['p_min'][k] + gen_attrs['p_max'][k]) / 2.0
        for k in gen_attrs['pg']
    }
    libgen.declare_var_pg(model,
                          gen_attrs['names'],
                          initialize=pg_init,
                          bounds=zip_items(gen_attrs['p_min'],
                                           gen_attrs['p_max']))

    ### declare the current flows in the branches
    vr_init = {
        k: bus_attrs['vm'][k] * pe.cos(bus_attrs['va'][k])
        for k in bus_attrs['vm']
    }
    vj_init = {
        k: bus_attrs['vm'][k] * pe.sin(bus_attrs['va'][k])
        for k in bus_attrs['vm']
    }
    p_max = {k: branches[k]['rating_long_term'] for k in branches.keys()}
    p_lbub = {k: (-p_max[k], p_max[k]) for k in branches.keys()}
    pf_bounds = p_lbub
    pf_init = dict()
    for branch_name, branch in branches.items():
        from_bus = branch['from_bus']
        to_bus = branch['to_bus']
        y_matrix = tx_calc.calculate_y_matrix_from_branch(branch)
        ifr_init = tx_calc.calculate_ifr(vr_init[from_bus], vj_init[from_bus],
                                         vr_init[to_bus], vj_init[to_bus],
                                         y_matrix)
        ifj_init = tx_calc.calculate_ifj(vr_init[from_bus], vj_init[from_bus],
                                         vr_init[to_bus], vj_init[to_bus],
                                         y_matrix)
        pf_init[branch_name] = tx_calc.calculate_p(ifr_init, ifj_init,
                                                   vr_init[from_bus],
                                                   vj_init[from_bus])

    libbranch.declare_var_pf(model=model,
                             index_set=branch_attrs['names'],
                             initialize=pf_init,
                             bounds=pf_bounds)

    ### declare the branch power flow approximation constraints
    libbranch.declare_eq_branch_power_dc_approx(
        model=model,
        index_set=branch_attrs['names'],
        branches=branches,
        approximation_type=ApproximationType.BTHETA)

    ### declare the p balance
    libbus.declare_eq_p_balance_dc_approx(
        model=model,
        index_set=bus_attrs['names'],
        bus_p_loads=bus_p_loads,
        gens_by_bus=gens_by_bus,
        bus_gs_fixed_shunts=bus_gs_fixed_shunts,
        inlet_branches_by_bus=inlet_branches_by_bus,
        outlet_branches_by_bus=outlet_branches_by_bus,
        approximation_type=ApproximationType.BTHETA)

    ### declare the real power flow limits
    libbranch.declare_ineq_p_branch_thermal_lbub(
        model=model,
        index_set=branch_attrs['names'],
        branches=branches,
        p_thermal_limits=p_max,
        approximation_type=ApproximationType.BTHETA)

    ### declare angle difference limits on interconnected buses
    libbranch.declare_ineq_angle_diff_branch_lbub(
        model=model,
        index_set=branch_attrs['names'],
        branches=branches,
        coordinate_type=CoordinateType.POLAR)

    ### declare the generator cost objective
    libgen.declare_expression_pgqg_operating_cost(model=model,
                                                  index_set=gen_attrs['names'],
                                                  p_costs=gen_attrs['p_cost'])

    obj_expr = sum(model.pg_operating_cost[gen_name]
                   for gen_name in model.pg_operating_cost)

    model.obj = pe.Objective(expr=obj_expr)

    return model
Beispiel #5
0
def _ptdf_dcopf_network_model(block, tm):
    m, gens_by_bus, bus_p_loads, bus_gs_fixed_shunts = \
            _setup_egret_network_model(block, tm)

    buses, branches, branches_in_service, branches_out_service, interfaces = \
            _setup_egret_network_topology(m, tm)

    ptdf_options = m._ptdf_options

    libbus.declare_var_p_nw(block, m.Buses)

    ### declare net withdraw expression for use in PTDF power flows
    libbus.declare_eq_p_net_withdraw_at_bus(
        model=block,
        index_set=m.Buses,
        bus_p_loads=bus_p_loads,
        gens_by_bus=gens_by_bus,
        bus_gs_fixed_shunts=bus_gs_fixed_shunts,
    )

    ### declare the p balance
    libbus.declare_eq_p_balance_ed(
        model=block,
        index_set=m.Buses,
        bus_p_loads=bus_p_loads,
        gens_by_bus=gens_by_bus,
        bus_gs_fixed_shunts=bus_gs_fixed_shunts,
    )

    ### add "blank" power flow expressions
    libbranch.declare_expr_pf(
        model=block,
        index_set=branches_in_service,
    )

    ### interface setup
    libbranch.declare_expr_pfi(model=block, index_set=interfaces.keys())

    _setup_interface_slacks(m, block, tm)

    ### Get the PTDF matrix from cache, from file, or create a new one
    if branches_out_service not in m._PTDFs:
        buses_idx = tuple(buses.keys())

        reference_bus = value(m.ReferenceBus)

        PTDF = data_utils.get_ptdf_potentially_from_file(ptdf_options,
                                                         branches_in_service,
                                                         buses_idx,
                                                         interfaces=interfaces)

        ## NOTE: For now, just use a flat-start for unit commitment
        if PTDF is None:
            PTDF = data_utils.PTDFMatrix(branches,
                                         buses,
                                         reference_bus,
                                         BasePointType.FLATSTART,
                                         ptdf_options,
                                         branches_keys=branches_in_service,
                                         buses_keys=buses_idx,
                                         interfaces=interfaces)

        m._PTDFs[branches_out_service] = PTDF

    else:
        PTDF = m._PTDFs[branches_out_service]

    ### attach the current PTDF object to this block
    block._PTDF = PTDF
    rel_ptdf_tol = m._ptdf_options['rel_ptdf_tol']
    abs_ptdf_tol = m._ptdf_options['abs_ptdf_tol']

    if ptdf_options['lazy']:
        ### add "blank" real power flow limits
        libbranch.declare_ineq_p_branch_thermal_lbub(
            model=block,
            index_set=branches_in_service,
            branches=branches,
            p_thermal_limits=None,
            approximation_type=None,
        )
        ### add helpers for tracking monitored branches
        lpu.add_monitored_branch_tracker(block)

    else:  ### add all the dense constraints
        p_max = {
            k: branches[k]['rating_long_term']
            for k in branches_in_service
        }

        ### declare the branch power flow approximation constraints
        libbranch.declare_eq_branch_power_ptdf_approx(
            model=block,
            index_set=branches_in_service,
            PTDF=PTDF,
            abs_ptdf_tol=abs_ptdf_tol,
            rel_ptdf_tol=rel_ptdf_tol)
        ### declare the real power flow limits
        libbranch.declare_ineq_p_branch_thermal_lbub(
            model=block,
            index_set=branches_in_service,
            branches=branches,
            p_thermal_limits=p_max,
            approximation_type=ApproximationType.PTDF)

    ## for now, just add all the interface constraints
    ## TODO: incorporate into lazy logic
    ### declare the branch power flow approximation constraints
    libbranch.declare_eq_interface_power_ptdf_approx(
        model=block,
        index_set=interfaces.keys(),
        PTDF=PTDF,
        abs_ptdf_tol=abs_ptdf_tol,
        rel_ptdf_tol=rel_ptdf_tol)

    ### declare the interface flow limits
    libbranch.declare_ineq_p_interface_lbub(
        model=block,
        index_set=interfaces.keys(),
        interfaces=interfaces,
    )
Beispiel #6
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def create_btheta_dcopf_model(model_data, include_angle_diff_limits=False, include_feasibility_slack=False, pw_cost_model='delta'):
    md = model_data.clone_in_service()
    tx_utils.scale_ModelData_to_pu(md, inplace = True)

    gens = dict(md.elements(element_type='generator'))
    buses = dict(md.elements(element_type='bus'))
    branches = dict(md.elements(element_type='branch'))
    loads = dict(md.elements(element_type='load'))
    shunts = dict(md.elements(element_type='shunt'))

    dc_branches = dict(md.elements(element_type='dc_branch'))

    gen_attrs = md.attributes(element_type='generator')
    bus_attrs = md.attributes(element_type='bus')
    branch_attrs = md.attributes(element_type='branch')

    inlet_branches_by_bus, outlet_branches_by_bus = \
        tx_utils.inlet_outlet_branches_by_bus(branches, buses)
    gens_by_bus = tx_utils.gens_by_bus(buses, gens)

    model = pe.ConcreteModel()

    ### declare (and fix) the loads at the buses
    bus_p_loads, _ = tx_utils.dict_of_bus_loads(buses, loads)

    libbus.declare_var_pl(model, bus_attrs['names'], initialize=bus_p_loads)
    model.pl.fix()

    ### declare the fixed shunts at the buses
    _, bus_gs_fixed_shunts = tx_utils.dict_of_bus_fixed_shunts(buses, shunts)

    ### declare the polar voltages
    va_bounds = {k: (-pi, pi) for k in bus_attrs['va']}
    libbus.declare_var_va(model, bus_attrs['names'],
                          initialize=tx_utils.radians_from_degrees_dict(bus_attrs['va']),
                          bounds=va_bounds
                          )

    ### include the feasibility slack for the bus balances
    p_rhs_kwargs = {}
    penalty_expr = None
    if include_feasibility_slack:
        p_marginal_slack_penalty = _validate_and_extract_slack_penalty(md)        
        p_rhs_kwargs, penalty_expr = _include_feasibility_slack(model, bus_attrs['names'], bus_p_loads,
                                                                gens_by_bus, gen_attrs, p_marginal_slack_penalty)

    ### fix the reference bus
    ref_bus = md.data['system']['reference_bus']
    ref_angle = md.data['system']['reference_bus_angle']
    model.va[ref_bus].fix(radians(ref_angle))

    ### declare the generator real power
    pg_init = {k: (gen_attrs['p_min'][k] + gen_attrs['p_max'][k]) / 2.0 for k in gen_attrs['pg']}
    libgen.declare_var_pg(model, gen_attrs['names'], initialize=pg_init,
                          bounds=zip_items(gen_attrs['p_min'], gen_attrs['p_max'])
                          )

    ### declare the current flows in the branches
    vr_init = {k: bus_attrs['vm'][k] * pe.cos(radians(bus_attrs['va'][k])) for k in bus_attrs['vm']}
    vj_init = {k: bus_attrs['vm'][k] * pe.sin(radians(bus_attrs['va'][k])) for k in bus_attrs['vm']}
    p_max = {k: branches[k]['rating_long_term'] for k in branches.keys()}
    p_lbub = dict()
    for k in branches.keys():
        k_pmax = p_max[k]
        if k_pmax is None:
            p_lbub[k] = (None, None)
        else:
            p_lbub[k] = (-k_pmax,k_pmax)
    pf_bounds = p_lbub
    pf_init = dict()
    for branch_name, branch in branches.items():
        from_bus = branch['from_bus']
        to_bus = branch['to_bus']
        y_matrix = tx_calc.calculate_y_matrix_from_branch(branch)
        ifr_init = tx_calc.calculate_ifr(vr_init[from_bus], vj_init[from_bus], vr_init[to_bus],
                                         vj_init[to_bus], y_matrix)
        ifj_init = tx_calc.calculate_ifj(vr_init[from_bus], vj_init[from_bus], vr_init[to_bus],
                                         vj_init[to_bus], y_matrix)
        pf_init[branch_name] = tx_calc.calculate_p(ifr_init, ifj_init, vr_init[from_bus], vj_init[from_bus])

    libbranch.declare_var_pf(model=model,
                             index_set=branch_attrs['names'],
                             initialize=pf_init,
                             bounds=pf_bounds
                             )

    if dc_branches:
        dcpf_bounds = dict()
        for k, k_dict in dc_branches.items():
            kp_max = k_dict['rating_long_term']
            if kp_max is None:
                dcpf_bounds[k] = (None, None)
            else:
                dcpf_bounds[k] = (-kp_max, kp_max)
        libbranch.declare_var_dcpf(model=model,
                                   index_set=dc_branches.keys(),
                                   initialize=0.,
                                   bounds=dcpf_bounds,
                                  )
        dc_inlet_branches_by_bus, dc_outlet_branches_by_bus = \
                tx_utils.inlet_outlet_branches_by_bus(dc_branches, buses)
    else:
        dc_inlet_branches_by_bus = None
        dc_outlet_branches_by_bus = None


    ### declare the branch power flow approximation constraints
    libbranch.declare_eq_branch_power_btheta_approx(model=model,
                                                    index_set=branch_attrs['names'],
                                                    branches=branches
                                                    )

    ### declare the p balance
    libbus.declare_eq_p_balance_dc_approx(model=model,
                                          index_set=bus_attrs['names'],
                                          bus_p_loads=bus_p_loads,
                                          gens_by_bus=gens_by_bus,
                                          bus_gs_fixed_shunts=bus_gs_fixed_shunts,
                                          inlet_branches_by_bus=inlet_branches_by_bus,
                                          outlet_branches_by_bus=outlet_branches_by_bus,
                                          approximation_type=ApproximationType.BTHETA,
                                          dc_inlet_branches_by_bus=dc_inlet_branches_by_bus,
                                          dc_outlet_branches_by_bus=dc_outlet_branches_by_bus,
                                          **p_rhs_kwargs
                                          )

    ### declare the real power flow limits
    libbranch.declare_ineq_p_branch_thermal_lbub(model=model,
                                                 index_set=branch_attrs['names'],
                                                 branches=branches,
                                                 p_thermal_limits=p_max,
                                                 approximation_type=ApproximationType.BTHETA
                                                 )

    ### declare angle difference limits on interconnected buses
    if include_angle_diff_limits:
        libbranch.declare_ineq_angle_diff_branch_lbub(model=model,
                                                      index_set=branch_attrs['names'],
                                                      branches=branches,
                                                      coordinate_type=CoordinateType.POLAR
                                                      )

    # declare the generator cost objective
    p_costs = gen_attrs['p_cost']
    pw_pg_cost_gens = list(libgen.pw_gen_generator(gen_attrs['names'], costs=p_costs))
    if len(pw_pg_cost_gens) > 0:
        if pw_cost_model == 'delta':
            libgen.declare_var_delta_pg(model=model, index_set=pw_pg_cost_gens, p_costs=p_costs)
            libgen.declare_pg_delta_pg_con(model=model, index_set=pw_pg_cost_gens, p_costs=p_costs)
        else:
            libgen.declare_var_pg_cost(model=model, index_set=pw_pg_cost_gens, p_costs=p_costs)
            libgen.declare_piecewise_pg_cost_cons(model=model, index_set=pw_pg_cost_gens, p_costs=p_costs)
    libgen.declare_expression_pg_operating_cost(model=model, index_set=gen_attrs['names'], p_costs=p_costs, pw_formulation=pw_cost_model)
    obj_expr = sum(model.pg_operating_cost[gen_name] for gen_name in model.pg_operating_cost)

    if include_feasibility_slack:
        obj_expr += penalty_expr

    model.obj = pe.Objective(expr=obj_expr)

    return model, md