### 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)

tests/models/test_dag.py
"""Verify tasks with Duplicate task_id raises error"""
        with pytest.raises(DuplicateTaskIdFound, match="Task id 't1' has already been added to the DAG"):
            with DAG("test_dag", start_date=DEFAULT_DATE) as dag:
                op1 = DummyOperator(task_id="t1")
                op2 = BashOperator(task_id="t1", bash_command="sleep 1")
                op1 >> op2
        assert dag.task_dict == {op1.task_id: op1}
    def test_duplicate_task_ids_not_allowed_without_dag_context_manager(self):
        """Verify tasks with Duplicate task_id raises error"""
        with pytest.raises(DuplicateTaskIdFound, match="Task id 't1' has already been added to the DAG"):
            dag = DAG("test_dag", start_date=DEFAULT_DATE)
            op1 = DummyOperator(task_id="t1", dag=dag)
            op2 = DummyOperator(task_id="t1", dag=dag)
            op1 >> op2
        assert dag.task_dict == {op1.task_id: op1}
    def test_duplicate_task_ids_for_same_task_is_allowed(self):
        """Verify that same tasks with Duplicate task_id do not raise error"""
        with DAG("test_dag", start_date=DEFAULT_DATE) as dag:
            op1 = op2 = DummyOperator(task_id="t1")
            op3 = DummyOperator(task_id="t3")
            op1 >> op3
            op2 >> op3
        assert op1 == op2
        assert dag.task_dict == {op1.task_id: op1, op3.task_id: op3}
        assert dag.task_dict == {op2.task_id: op2, op3.task_id: op3}
    def test_sub_dag_updates_all_references_while_deepcopy(self):