### 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
@task_decorator
            def return_num(num):
                return num
            assert isinstance(value, DagParam)
            xcom_arg = return_num(value)
            self.operator = xcom_arg.operator
        dag = xcom_pass_to_op()
        new_value = 52
        dr = dag.create_dagrun(
            run_id=DagRunType.MANUAL.value,
            start_date=timezone.utcnow(),
            execution_date=self.DEFAULT_DATE,
            state=State.RUNNING,
            conf={'value': new_value},
        )
        self.operator.run(start_date=self.DEFAULT_DATE, end_date=self.DEFAULT_DATE)
        ti = dr.get_task_instances()[0]
        assert ti.xcom_pull(), new_value
    def test_set_params_for_dag(self):
        """Test that dag param is correctly set when using dag decorator"""
        @dag_decorator(default_args=self.DEFAULT_ARGS)
        def xcom_pass_to_op(value=self.VALUE):
            @task_decorator
            def return_num(num):
                return num
            xcom_arg = return_num(value)
            self.operator = xcom_arg.operator
        dag = xcom_pass_to_op()
        assert dag.params['value'] == self.VALUE
def test_set_task_instance_state(session, dag_maker):