Conditions | 24 |
Total Lines | 554 |
Code Lines | 358 |
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:
Complex classes like data.datasets.sanity_checks.sanitycheck_emobility_mit() often do a lot of different things. To break such a class down, we need to identify a cohesive component within that class. A common approach to find such a component is to look for fields/methods that share the same prefixes, or suffixes.
Once you have determined the fields that belong together, you can apply the Extract Class refactoring. If the component makes sense as a sub-class, Extract Subclass is also a candidate, and is often faster.
1 | """ |
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589 | def sanitycheck_emobility_mit(): |
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590 | """Execute sanity checks for eMobility: motorized individual travel |
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591 | |||
592 | Checks data integrity for eGon2035, eGon2035_lowflex and eGon100RE scenario |
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593 | using assertions: |
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594 | 1. Allocated EV numbers and EVs allocated to grid districts |
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595 | 2. Trip data (original inout data from simBEV) |
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596 | 3. Model data in eTraGo PF tables (grid.egon_etrago_*) |
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597 | |||
598 | Parameters |
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599 | ---------- |
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600 | None |
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601 | |||
602 | Returns |
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603 | ------- |
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604 | None |
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605 | """ |
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606 | |||
607 | def check_ev_allocation(): |
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608 | # Get target number for scenario |
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609 | ev_count_target = scenario_variation_parameters["ev_count"] |
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610 | print(f" Target count: {str(ev_count_target)}") |
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611 | |||
612 | # Get allocated numbers |
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613 | ev_counts_dict = {} |
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614 | with db.session_scope() as session: |
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615 | for table, level in zip( |
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616 | [ |
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617 | EgonEvCountMvGridDistrict, |
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618 | EgonEvCountMunicipality, |
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619 | EgonEvCountRegistrationDistrict, |
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620 | ], |
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621 | ["Grid District", "Municipality", "Registration District"], |
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622 | ): |
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623 | query = session.query( |
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624 | func.sum( |
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625 | table.bev_mini |
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626 | + table.bev_medium |
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627 | + table.bev_luxury |
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628 | + table.phev_mini |
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629 | + table.phev_medium |
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630 | + table.phev_luxury |
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631 | ).label("ev_count") |
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632 | ).filter( |
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633 | table.scenario == scenario_name, |
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634 | table.scenario_variation == scenario_var_name, |
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635 | ) |
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636 | |||
637 | ev_counts = pd.read_sql( |
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638 | query.statement, query.session.bind, index_col=None |
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639 | ) |
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640 | ev_counts_dict[level] = ev_counts.iloc[0].ev_count |
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641 | print( |
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642 | f" Count table: Total count for level {level} " |
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643 | f"(table: {table.__table__}): " |
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644 | f"{str(ev_counts_dict[level])}" |
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645 | ) |
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646 | |||
647 | # Compare with scenario target (only if not in testmode) |
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648 | if TESTMODE_OFF: |
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649 | for level, count in ev_counts_dict.items(): |
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650 | np.testing.assert_allclose( |
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651 | count, |
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652 | ev_count_target, |
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653 | rtol=0.0001, |
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654 | err_msg=f"EV numbers in {level} seems to be flawed.", |
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655 | ) |
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656 | else: |
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657 | print(" Testmode is on, skipping sanity check...") |
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658 | |||
659 | # Get allocated EVs in grid districts |
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660 | with db.session_scope() as session: |
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661 | query = session.query( |
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662 | func.count(EgonEvMvGridDistrict.egon_ev_pool_ev_id).label( |
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663 | "ev_count" |
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664 | ), |
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665 | ).filter( |
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666 | EgonEvMvGridDistrict.scenario == scenario_name, |
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667 | EgonEvMvGridDistrict.scenario_variation == scenario_var_name, |
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668 | ) |
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669 | ev_count_alloc = ( |
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670 | pd.read_sql(query.statement, query.session.bind, index_col=None) |
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671 | .iloc[0] |
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672 | .ev_count |
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673 | ) |
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674 | print( |
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675 | f" EVs allocated to Grid Districts " |
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676 | f"(table: {EgonEvMvGridDistrict.__table__}) total count: " |
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677 | f"{str(ev_count_alloc)}" |
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678 | ) |
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679 | |||
680 | # Compare with scenario target (only if not in testmode) |
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681 | if TESTMODE_OFF: |
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682 | np.testing.assert_allclose( |
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683 | ev_count_alloc, |
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684 | ev_count_target, |
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685 | rtol=0.0001, |
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686 | err_msg=( |
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687 | "EV numbers allocated to Grid Districts seems to be flawed." |
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688 | ), |
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689 | ) |
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690 | else: |
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691 | print(" Testmode is on, skipping sanity check...") |
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692 | |||
693 | return ev_count_alloc |
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694 | |||
695 | def check_trip_data(): |
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696 | # Check if trips start at timestep 0 and have a max. of 35040 steps |
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697 | # (8760h in 15min steps) |
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698 | print(" Checking timeranges...") |
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699 | with db.session_scope() as session: |
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700 | query = session.query( |
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701 | func.count(EgonEvTrip.event_id).label("cnt") |
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702 | ).filter( |
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703 | or_( |
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704 | and_( |
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705 | EgonEvTrip.park_start > 0, |
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706 | EgonEvTrip.simbev_event_id == 0, |
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707 | ), |
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708 | EgonEvTrip.park_end |
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709 | > (60 / int(meta_run_config.stepsize)) * 8760, |
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710 | ), |
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711 | EgonEvTrip.scenario == scenario_name, |
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712 | ) |
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713 | invalid_trips = pd.read_sql( |
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714 | query.statement, query.session.bind, index_col=None |
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715 | ) |
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716 | np.testing.assert_equal( |
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717 | invalid_trips.iloc[0].cnt, |
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718 | 0, |
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719 | err_msg=( |
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720 | f"{str(invalid_trips.iloc[0].cnt)} trips in table " |
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721 | f"{EgonEvTrip.__table__} have invalid timesteps." |
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722 | ), |
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723 | ) |
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724 | |||
725 | # Check if charging demand can be covered by available charging energy |
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726 | # while parking |
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727 | print(" Compare charging demand with available power...") |
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728 | with db.session_scope() as session: |
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729 | query = session.query( |
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730 | func.count(EgonEvTrip.event_id).label("cnt") |
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731 | ).filter( |
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732 | func.round( |
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733 | cast( |
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734 | (EgonEvTrip.park_end - EgonEvTrip.park_start + 1) |
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735 | * EgonEvTrip.charging_capacity_nominal |
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736 | * (int(meta_run_config.stepsize) / 60), |
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737 | Numeric, |
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738 | ), |
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739 | 3, |
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740 | ) |
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741 | < cast(EgonEvTrip.charging_demand, Numeric), |
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742 | EgonEvTrip.scenario == scenario_name, |
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743 | ) |
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744 | invalid_trips = pd.read_sql( |
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745 | query.statement, query.session.bind, index_col=None |
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746 | ) |
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747 | np.testing.assert_equal( |
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748 | invalid_trips.iloc[0].cnt, |
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749 | 0, |
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750 | err_msg=( |
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751 | f"In {str(invalid_trips.iloc[0].cnt)} trips (table: " |
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752 | f"{EgonEvTrip.__table__}) the charging demand cannot be " |
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753 | f"covered by available charging power." |
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754 | ), |
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755 | ) |
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756 | |||
757 | def check_model_data(): |
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758 | # Check if model components were fully created |
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759 | print(" Check if all model components were created...") |
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760 | # Get MVGDs which got EV allocated |
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761 | with db.session_scope() as session: |
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762 | query = ( |
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763 | session.query( |
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764 | EgonEvMvGridDistrict.bus_id, |
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765 | ) |
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766 | .filter( |
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767 | EgonEvMvGridDistrict.scenario == scenario_name, |
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768 | EgonEvMvGridDistrict.scenario_variation |
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769 | == scenario_var_name, |
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770 | ) |
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771 | .group_by(EgonEvMvGridDistrict.bus_id) |
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772 | ) |
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773 | mvgds_with_ev = ( |
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774 | pd.read_sql(query.statement, query.session.bind, index_col=None) |
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775 | .bus_id.sort_values() |
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776 | .to_list() |
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777 | ) |
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778 | |||
779 | # Load model components |
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780 | with db.session_scope() as session: |
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781 | query = ( |
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782 | session.query( |
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783 | EgonPfHvLink.bus0.label("mvgd_bus_id"), |
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784 | EgonPfHvLoad.bus.label("emob_bus_id"), |
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785 | EgonPfHvLoad.load_id.label("load_id"), |
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786 | EgonPfHvStore.store_id.label("store_id"), |
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787 | ) |
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788 | .select_from(EgonPfHvLoad, EgonPfHvStore) |
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789 | .join( |
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790 | EgonPfHvLoadTimeseries, |
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791 | EgonPfHvLoadTimeseries.load_id == EgonPfHvLoad.load_id, |
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792 | ) |
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793 | .join( |
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794 | EgonPfHvStoreTimeseries, |
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795 | EgonPfHvStoreTimeseries.store_id == EgonPfHvStore.store_id, |
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796 | ) |
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797 | .filter( |
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798 | EgonPfHvLoad.carrier == "land transport EV", |
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799 | EgonPfHvLoad.scn_name == scenario_name, |
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800 | EgonPfHvLoadTimeseries.scn_name == scenario_name, |
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801 | EgonPfHvStore.carrier == "battery storage", |
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802 | EgonPfHvStore.scn_name == scenario_name, |
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803 | EgonPfHvStoreTimeseries.scn_name == scenario_name, |
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804 | EgonPfHvLink.scn_name == scenario_name, |
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805 | EgonPfHvLink.bus1 == EgonPfHvLoad.bus, |
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806 | EgonPfHvLink.bus1 == EgonPfHvStore.bus, |
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807 | ) |
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808 | ) |
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809 | model_components = pd.read_sql( |
||
810 | query.statement, query.session.bind, index_col=None |
||
811 | ) |
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812 | |||
813 | # Check number of buses with model components connected |
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814 | mvgd_buses_with_ev = model_components.loc[ |
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815 | model_components.mvgd_bus_id.isin(mvgds_with_ev) |
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816 | ] |
||
817 | np.testing.assert_equal( |
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818 | len(mvgds_with_ev), |
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819 | len(mvgd_buses_with_ev), |
||
820 | err_msg=( |
||
821 | f"Number of Grid Districts with connected model components " |
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822 | f"({str(len(mvgd_buses_with_ev))} in tables egon_etrago_*) " |
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823 | f"differ from number of Grid Districts that got EVs " |
||
824 | f"allocated ({len(mvgds_with_ev)} in table " |
||
825 | f"{EgonEvMvGridDistrict.__table__})." |
||
826 | ), |
||
827 | ) |
||
828 | |||
829 | # Check if all required components exist (if no id is NaN) |
||
830 | np.testing.assert_equal( |
||
831 | model_components.drop_duplicates().isna().any().any(), |
||
832 | False, |
||
833 | err_msg=( |
||
834 | f"Some components are missing (see True values): " |
||
835 | f"{model_components.drop_duplicates().isna().any()}" |
||
836 | ), |
||
837 | ) |
||
838 | |||
839 | # Get all model timeseries |
||
840 | print(" Loading model timeseries...") |
||
841 | # Get all model timeseries |
||
842 | model_ts_dict = { |
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843 | "Load": { |
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844 | "carrier": "land transport EV", |
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845 | "table": EgonPfHvLoad, |
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846 | "table_ts": EgonPfHvLoadTimeseries, |
||
847 | "column_id": "load_id", |
||
848 | "columns_ts": ["p_set"], |
||
849 | "ts": None, |
||
850 | }, |
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851 | "Link": { |
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852 | "carrier": "BEV charger", |
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853 | "table": EgonPfHvLink, |
||
854 | "table_ts": EgonPfHvLinkTimeseries, |
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855 | "column_id": "link_id", |
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856 | "columns_ts": ["p_max_pu"], |
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857 | "ts": None, |
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858 | }, |
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859 | "Store": { |
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860 | "carrier": "battery storage", |
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861 | "table": EgonPfHvStore, |
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862 | "table_ts": EgonPfHvStoreTimeseries, |
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863 | "column_id": "store_id", |
||
864 | "columns_ts": ["e_min_pu", "e_max_pu"], |
||
865 | "ts": None, |
||
866 | }, |
||
867 | } |
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868 | |||
869 | with db.session_scope() as session: |
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870 | for node, attrs in model_ts_dict.items(): |
||
871 | print(f" Loading {node} timeseries...") |
||
872 | subquery = ( |
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873 | session.query(getattr(attrs["table"], attrs["column_id"])) |
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874 | .filter(attrs["table"].carrier == attrs["carrier"]) |
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875 | .filter(attrs["table"].scn_name == scenario_name) |
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876 | .subquery() |
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877 | ) |
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878 | |||
879 | cols = [ |
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880 | getattr(attrs["table_ts"], c) for c in attrs["columns_ts"] |
||
881 | ] |
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882 | query = session.query( |
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883 | getattr(attrs["table_ts"], attrs["column_id"]), *cols |
||
884 | ).filter( |
||
885 | getattr(attrs["table_ts"], attrs["column_id"]).in_( |
||
886 | subquery |
||
887 | ), |
||
888 | attrs["table_ts"].scn_name == scenario_name, |
||
889 | ) |
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890 | attrs["ts"] = pd.read_sql( |
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891 | query.statement, |
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892 | query.session.bind, |
||
893 | index_col=attrs["column_id"], |
||
894 | ) |
||
895 | |||
896 | # Check if all timeseries have 8760 steps |
||
897 | print(" Checking timeranges...") |
||
898 | for node, attrs in model_ts_dict.items(): |
||
899 | for col in attrs["columns_ts"]: |
||
900 | ts = attrs["ts"] |
||
901 | invalid_ts = ts.loc[ts[col].apply(lambda _: len(_)) != 8760][ |
||
902 | col |
||
903 | ].apply(len) |
||
904 | np.testing.assert_equal( |
||
905 | len(invalid_ts), |
||
906 | 0, |
||
907 | err_msg=( |
||
908 | f"{str(len(invalid_ts))} rows in timeseries do not " |
||
909 | f"have 8760 timesteps. Table: " |
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910 | f"{attrs['table_ts'].__table__}, Column: {col}, IDs: " |
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911 | f"{str(list(invalid_ts.index))}" |
||
912 | ), |
||
913 | ) |
||
914 | |||
915 | # Compare total energy demand in model with some approximate values |
||
916 | # (per EV: 14,000 km/a, 0.17 kWh/km) |
||
917 | print(" Checking energy demand in model...") |
||
918 | total_energy_model = ( |
||
919 | model_ts_dict["Load"]["ts"].p_set.apply(lambda _: sum(_)).sum() |
||
920 | / 1e6 |
||
921 | ) |
||
922 | print(f" Total energy amount in model: {total_energy_model} TWh") |
||
923 | total_energy_scenario_approx = ev_count_alloc * 14000 * 0.17 / 1e9 |
||
924 | print( |
||
925 | f" Total approximated energy amount in scenario: " |
||
926 | f"{total_energy_scenario_approx} TWh" |
||
927 | ) |
||
928 | np.testing.assert_allclose( |
||
929 | total_energy_model, |
||
930 | total_energy_scenario_approx, |
||
931 | rtol=0.1, |
||
932 | err_msg=( |
||
933 | "The total energy amount in the model deviates heavily " |
||
934 | "from the approximated value for current scenario." |
||
935 | ), |
||
936 | ) |
||
937 | |||
938 | # Compare total storage capacity |
||
939 | print(" Checking storage capacity...") |
||
940 | # Load storage capacities from model |
||
941 | with db.session_scope() as session: |
||
942 | query = session.query( |
||
943 | func.sum(EgonPfHvStore.e_nom).label("e_nom") |
||
944 | ).filter( |
||
945 | EgonPfHvStore.scn_name == scenario_name, |
||
946 | EgonPfHvStore.carrier == "battery storage", |
||
947 | ) |
||
948 | storage_capacity_model = ( |
||
949 | pd.read_sql( |
||
950 | query.statement, query.session.bind, index_col=None |
||
951 | ).e_nom.sum() |
||
952 | / 1e3 |
||
953 | ) |
||
954 | print( |
||
955 | f" Total storage capacity ({EgonPfHvStore.__table__}): " |
||
956 | f"{round(storage_capacity_model, 1)} GWh" |
||
957 | ) |
||
958 | |||
959 | # Load occurences of each EV |
||
960 | with db.session_scope() as session: |
||
961 | query = ( |
||
962 | session.query( |
||
963 | EgonEvMvGridDistrict.bus_id, |
||
964 | EgonEvPool.type, |
||
965 | func.count(EgonEvMvGridDistrict.egon_ev_pool_ev_id).label( |
||
966 | "count" |
||
967 | ), |
||
968 | ) |
||
969 | .join( |
||
970 | EgonEvPool, |
||
971 | EgonEvPool.ev_id |
||
972 | == EgonEvMvGridDistrict.egon_ev_pool_ev_id, |
||
973 | ) |
||
974 | .filter( |
||
975 | EgonEvMvGridDistrict.scenario == scenario_name, |
||
976 | EgonEvMvGridDistrict.scenario_variation |
||
977 | == scenario_var_name, |
||
978 | EgonEvPool.scenario == scenario_name, |
||
979 | ) |
||
980 | .group_by(EgonEvMvGridDistrict.bus_id, EgonEvPool.type) |
||
981 | ) |
||
982 | count_per_ev_all = pd.read_sql( |
||
983 | query.statement, query.session.bind, index_col="bus_id" |
||
984 | ) |
||
985 | count_per_ev_all["bat_cap"] = count_per_ev_all.type.map( |
||
986 | meta_tech_data.battery_capacity |
||
987 | ) |
||
988 | count_per_ev_all["bat_cap_total_MWh"] = ( |
||
989 | count_per_ev_all["count"] * count_per_ev_all.bat_cap / 1e3 |
||
990 | ) |
||
991 | storage_capacity_simbev = count_per_ev_all.bat_cap_total_MWh.div( |
||
992 | 1e3 |
||
993 | ).sum() |
||
994 | print( |
||
995 | f" Total storage capacity (simBEV): " |
||
996 | f"{round(storage_capacity_simbev, 1)} GWh" |
||
997 | ) |
||
998 | |||
999 | np.testing.assert_allclose( |
||
1000 | storage_capacity_model, |
||
1001 | storage_capacity_simbev, |
||
1002 | rtol=0.01, |
||
1003 | err_msg=( |
||
1004 | "The total storage capacity in the model deviates heavily " |
||
1005 | "from the input data provided by simBEV for current scenario." |
||
1006 | ), |
||
1007 | ) |
||
1008 | |||
1009 | # Check SoC storage constraint: e_min_pu < e_max_pu for all timesteps |
||
1010 | print(" Validating SoC constraints...") |
||
1011 | stores_with_invalid_soc = [] |
||
1012 | for idx, row in model_ts_dict["Store"]["ts"].iterrows(): |
||
1013 | ts = row[["e_min_pu", "e_max_pu"]] |
||
1014 | x = np.array(ts.e_min_pu) > np.array(ts.e_max_pu) |
||
1015 | if x.any(): |
||
1016 | stores_with_invalid_soc.append(idx) |
||
1017 | |||
1018 | np.testing.assert_equal( |
||
1019 | len(stores_with_invalid_soc), |
||
1020 | 0, |
||
1021 | err_msg=( |
||
1022 | f"The store constraint e_min_pu < e_max_pu does not apply " |
||
1023 | f"for some storages in {EgonPfHvStoreTimeseries.__table__}. " |
||
1024 | f"Invalid store_ids: {stores_with_invalid_soc}" |
||
1025 | ), |
||
1026 | ) |
||
1027 | |||
1028 | def check_model_data_lowflex_eGon2035(): |
||
1029 | # TODO: Add eGon100RE_lowflex |
||
1030 | print("") |
||
1031 | print("SCENARIO: eGon2035_lowflex") |
||
1032 | |||
1033 | # Compare driving load and charging load |
||
1034 | print(" Loading eGon2035 model timeseries: driving load...") |
||
1035 | with db.session_scope() as session: |
||
1036 | query = ( |
||
1037 | session.query( |
||
1038 | EgonPfHvLoad.load_id, |
||
1039 | EgonPfHvLoadTimeseries.p_set, |
||
1040 | ) |
||
1041 | .join( |
||
1042 | EgonPfHvLoadTimeseries, |
||
1043 | EgonPfHvLoadTimeseries.load_id == EgonPfHvLoad.load_id, |
||
1044 | ) |
||
1045 | .filter( |
||
1046 | EgonPfHvLoad.carrier == "land transport EV", |
||
1047 | EgonPfHvLoad.scn_name == "eGon2035", |
||
1048 | EgonPfHvLoadTimeseries.scn_name == "eGon2035", |
||
1049 | ) |
||
1050 | ) |
||
1051 | model_driving_load = pd.read_sql( |
||
1052 | query.statement, query.session.bind, index_col=None |
||
1053 | ) |
||
1054 | driving_load = np.array(model_driving_load.p_set.to_list()).sum(axis=0) |
||
1055 | |||
1056 | print( |
||
1057 | " Loading eGon2035_lowflex model timeseries: dumb charging " |
||
1058 | "load..." |
||
1059 | ) |
||
1060 | with db.session_scope() as session: |
||
1061 | query = ( |
||
1062 | session.query( |
||
1063 | EgonPfHvLoad.load_id, |
||
1064 | EgonPfHvLoadTimeseries.p_set, |
||
1065 | ) |
||
1066 | .join( |
||
1067 | EgonPfHvLoadTimeseries, |
||
1068 | EgonPfHvLoadTimeseries.load_id == EgonPfHvLoad.load_id, |
||
1069 | ) |
||
1070 | .filter( |
||
1071 | EgonPfHvLoad.carrier == "land transport EV", |
||
1072 | EgonPfHvLoad.scn_name == "eGon2035_lowflex", |
||
1073 | EgonPfHvLoadTimeseries.scn_name == "eGon2035_lowflex", |
||
1074 | ) |
||
1075 | ) |
||
1076 | model_charging_load_lowflex = pd.read_sql( |
||
1077 | query.statement, query.session.bind, index_col=None |
||
1078 | ) |
||
1079 | charging_load = np.array( |
||
1080 | model_charging_load_lowflex.p_set.to_list() |
||
1081 | ).sum(axis=0) |
||
1082 | |||
1083 | # Ratio of driving and charging load should be 0.9 due to charging |
||
1084 | # efficiency |
||
1085 | print(" Compare cumulative loads...") |
||
1086 | print(f" Driving load (eGon2035): {driving_load.sum() / 1e6} TWh") |
||
1087 | print( |
||
1088 | f" Dumb charging load (eGon2035_lowflex): " |
||
1089 | f"{charging_load.sum() / 1e6} TWh" |
||
1090 | ) |
||
1091 | driving_load_theoretical = ( |
||
1092 | float(meta_run_config.eta_cp) * charging_load.sum() |
||
1093 | ) |
||
1094 | np.testing.assert_allclose( |
||
1095 | driving_load.sum(), |
||
1096 | driving_load_theoretical, |
||
1097 | rtol=0.01, |
||
1098 | err_msg=( |
||
1099 | f"The driving load (eGon2035) deviates by more than 1% " |
||
1100 | f"from the theoretical driving load calculated from charging " |
||
1101 | f"load (eGon2035_lowflex) with an efficiency of " |
||
1102 | f"{float(meta_run_config.eta_cp)}." |
||
1103 | ), |
||
1104 | ) |
||
1105 | |||
1106 | print("=====================================================") |
||
1107 | print("=== SANITY CHECKS FOR MOTORIZED INDIVIDUAL TRAVEL ===") |
||
1108 | print("=====================================================") |
||
1109 | |||
1110 | for scenario_name in ["eGon2035", "eGon100RE"]: |
||
1111 | scenario_var_name = DATASET_CFG["scenario"]["variation"][scenario_name] |
||
1112 | |||
1113 | print("") |
||
1114 | print(f"SCENARIO: {scenario_name}, VARIATION: {scenario_var_name}") |
||
1115 | |||
1116 | # Load scenario params for scenario and scenario variation |
||
1117 | scenario_variation_parameters = get_sector_parameters( |
||
1118 | "mobility", scenario=scenario_name |
||
1119 | )["motorized_individual_travel"][scenario_var_name] |
||
1120 | |||
1121 | # Load simBEV run config and tech data |
||
1122 | meta_run_config = read_simbev_metadata_file( |
||
1123 | scenario_name, "config" |
||
1124 | ).loc["basic"] |
||
1125 | meta_tech_data = read_simbev_metadata_file(scenario_name, "tech_data") |
||
1126 | |||
1127 | print("") |
||
1128 | print("Checking EV counts...") |
||
1129 | ev_count_alloc = check_ev_allocation() |
||
1130 | |||
1131 | print("") |
||
1132 | print("Checking trip data...") |
||
1133 | check_trip_data() |
||
1134 | |||
1135 | print("") |
||
1136 | print("Checking model data...") |
||
1137 | check_model_data() |
||
1138 | |||
1139 | print("") |
||
1140 | check_model_data_lowflex_eGon2035() |
||
1141 | |||
1142 | print("=====================================================") |
||
1143 |