### Apache Airflow version

2.2.0 (latest released)

### Operating System

Mac

### Versions of Apache Airflow Providers

_No response_

### Deployment

Other Docker-based deployment

### Deployment details

_No response_

### What happened

Getting an exception when returning None from next_dagrun_info in a custom timetable. The timetable protocol says that when None is returned a DagRun will not happen but right now it throws an exception.

Exception:
```
Traceback (most recent call last):
  File "/home/airflow/.local/lib/python3.9/site-packages/airflow/jobs/scheduler_job.py", line 623, in _execute
    self._run_scheduler_loop()
  File "/home/airflow/.local/lib/python3.9/site-packages/airflow/jobs/scheduler_job.py", line 704, in _run_scheduler_loop
    num_queued_tis = self._do_scheduling(session)
  File "/home/airflow/.local/lib/python3.9/site-packages/airflow/jobs/scheduler_job.py", line 787, in _do_scheduling
    callback_to_run = self._schedule_dag_run(dag_run, session)
  File "/home/airflow/.local/lib/python3.9/site-packages/airflow/jobs/scheduler_job.py", line 1039, in _schedule_dag_run
    self._update_dag_next_dagruns(dag, dag_model, active_runs)
  File "/home/airflow/.local/lib/python3.9/site-packages/airflow/jobs/scheduler_job.py", line 930, in _update_dag_next_dagruns
    data_interval = dag.get_next_data_interval(dag_model)
  File "/home/airflow/.local/lib/python3.9/site-packages/airflow/models/dag.py", line 629, in get_next_data_interval
    return self.infer_automated_data_interval(dag_model.next_dagrun)
  File "/home/airflow/.local/lib/python3.9/site-packages/airflow/models/dag.py", line 671, in infer_automated_data_interval
    raise ValueError(f"Not a valid timetable: {self.timetable!r}")
ValueError: Not a valid timetable: <my_timetables.workday_timetable.WorkdayTimetable object at 0x7f42b1f02430>
```

### What you expected to happen

DagRun to not happen.

### How to reproduce

Create a custom timetable and return None in next_dagrun_info after a few DagRuns are created by that timetable

### Anything else

_No response_

### Are you willing to submit PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

airflow/models/dag.py
DagContext.push_context_managed_dag(self)
        return self
    def __exit__(self, _type, _value, _tb):
        DagContext.pop_context_managed_dag()
    
    @staticmethod
    def _upgrade_outdated_dag_access_control(access_control=None):
        """
        Looks for outdated dag level actions (can_dag_read and can_dag_edit) in DAG
        access_controls (for example, {'role1': {'can_dag_read'}, 'role2': {'can_dag_read', 'can_dag_edit'}})
        and replaces them with updated actions (can_read and can_edit).
        """
        if not access_control:
            return None
        new_perm_mapping = {
            permissions.DEPRECATED_ACTION_CAN_DAG_READ: permissions.ACTION_CAN_READ,
            permissions.DEPRECATED_ACTION_CAN_DAG_EDIT: permissions.ACTION_CAN_EDIT,
        }
        updated_access_control = {}
        for role, perms in access_control.items():
            updated_access_control[role] = {new_perm_mapping.get(perm, perm) for perm in perms}
        if access_control != updated_access_control:
            warnings.warn(
                "The 'can_dag_read' and 'can_dag_edit' permissions are deprecated. "
                "Please use 'can_read' and 'can_edit', respectively.",
                DeprecationWarning,
                stacklevel=3,
            )
        return updated_access_control
    def date_range(