test_esipp_prices.py

            )
            for qpk in tf.qpk()
            }
        mynet.add_import_node(
            node_key=imp_node_key,
            prices=imp_prices
        )
    
        # export node
        exp_node_key = 'thatexpnode'
        exp_prices = {
            qpk: ResourcePrice(
                prices=1.5,
                volumes=None,
            )
            for qpk in tf.qpk()
            }
        mynet.add_export_node(
            node_key=exp_node_key,
            prices=exp_prices,
        )
        
        # add arc without fixed losses from import node to export
        arc_tech_IE = Arcs(
            name="IE",
            # efficiency=[1, 1, 1, 1],
            efficiency={(0, 0): 1, (0, 1): 1, (0, 2): 1, (0, 3): 1},
            efficiency_reverse=None,
            static_loss=None,
            validate=False,
            capacity=[0.5, 1.0, 2.0],
            minimum_cost=[5, 5.1, 5.2],
            specific_capacity_cost=1,
            capacity_is_instantaneous=False,
        )
        mynet.add_directed_arc(
            node_key_a=imp_node_key, node_key_b=exp_node_key, arcs=arc_tech_IE
        )
    
        # no sos, regular time intervals
        ipp = self.build_solve_ipp(
            solver_options={},
            perform_analysis=False,
            plot_results=False,  # True,
            print_solver_output=False,
            networks={"mynet": mynet},
            time_frame=tf,
            static_losses_mode=InfrastructurePlanningProblem.STATIC_LOSS_MODE_DEP,
            mandatory_arcs=[],
            max_number_parallel_arcs={},
            use_prices_block=use_prices_block
        )
    
        # export prices are higher: it makes sense to install the arc since the
        # revenue (@ max. cap.) exceeds the cost of installing the arc

        assert (
            True
            in ipp.networks["mynet"]
            .edges[(imp_node_key, exp_node_key, 0)][Network.KEY_ARC_TECH]
            .options_selected
        )
        
        # overview
        (imports_qpk, 
         exports_qpk, 
         balance_qpk, 
         import_costs_qpk, 
         export_revenue_qpk, 
         ncf_qpk, 
         aggregate_static_demand_qpk,
         aggregate_static_supply_qpk,
         aggregate_static_balance_qpk) = statistics(ipp)

        # there should be no imports

        abs_tol = 1e-6
        
        abs_tol = 1e-3
        imports_qp = sum(imports_qpk[qpk] for qpk in tf.qpk() if qpk[1] == 0)
        assert imports_qp > 0.0 - abs_tol

        abs_tol = 1e-3
        import_costs_qp = sum(import_costs_qpk[qpk] for qpk in tf.qpk() if qpk[1] == 0)
        assert import_costs_qp > 0.0 - abs_tol

        # there should be no exports

        abs_tol = 1e-2

        exports_qp = sum(exports_qpk[(q, 0, k)] for k in tf.time_intervals[q])
        export_revenue_qp = sum(export_revenue_qpk[(q, 0, k)] for k in tf.time_intervals[q])
        assert exports_qp > 0.0 - abs_tol
        assert export_revenue_qp > 0.0 - abs_tol

        # the revenue should exceed the costs

        abs_tol = 1e-2

        assert (
            export_revenue_qp > import_costs_qp - abs_tol
        )

        # the capex should be positive

        abs_tol = 1e-6

        assert pyo.value(ipp.instance.var_capex) > 0 - abs_tol
        
    # *************************************************************************
    # *************************************************************************

# *****************************************************************************
# *****************************************************************************