### Apache Airflow version

2.7.0

### What happened

Relates to investigation of #30327

When you define a DAG with a `schedule=datetime.timedelta(days=1)` and `catchup=False` and you manually trigger a run in the past (logical date in the past, e.g. a few days ago) then upon completion of the run another scheduled run is triggered - irrespective of a previous scheduled run was made just before (not a day ago)

### What you think should happen instead

A manual run should not trigger another run as the scheduling in general should follow the delta time definition of the DAG.

### How to reproduce

Use the following example DAG code and enable scheduling:
```
with DAG(
    dag_id="after_workday_delta_regression",
    start_date=pendulum.datetime(2023, 8, 1, tz="UTC"),
    catchup=False,
    schedule=datetime.timedelta(days=1),
    params={"test": 123}
):
    @task
    def test(ti: TaskInstance=None):
        print(ti.execution_date)
    test()
```

Wait a moment and see that one schedule is run automatically.
Then trigger a manual DAG run and set the execution date/logical date a few days into the past.
After execution you see a third run of the DAG just at the time of completion of the manual trigger as execution date. But the first execution was just a few moments before, not respecting the desired delta of 1 day.

### Operating System

Ubuntu 20.04 / Breeze Dev setup in Py 3.8 Container

### Versions of Apache Airflow Providers

not relevant

### Deployment

Other

### Deployment details

Started and tested with latest main branch and breeze.

### Anything else

I tried to find the root cause but was not able to locate it. Suspect it is rooted in scheduler_job_runner.py.
I'd supply a fix but was not able to fund the root cause. Expert knowledge is needed probably.

### 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)

dag_id = "test_task_start_date_scheduling"
            dag = self.dagbag.get_dag(dag_id)
            dag.is_paused_upon_creation = False
            dagbag.bag_dag(dag=dag, root_dag=dag)
            
            other_dag = self.dagbag.get_dag("test_start_date_scheduling")
            other_dag.is_paused_upon_creation = True
            dagbag.bag_dag(dag=other_dag, root_dag=other_dag)
            dagbag.sync_to_db()
            scheduler_job = Job(
                executor=self.null_exec,
            )
            self.job_runner = SchedulerJobRunner(job=scheduler_job, subdir=dag.fileloc, num_runs=3)
            run_job(scheduler_job, execute_callable=self.job_runner._execute)
            session = settings.Session()
            tiq = session.query(TaskInstance).filter(TaskInstance.dag_id == dag_id)
            ti1s = tiq.filter(TaskInstance.task_id == "dummy1").all()
            ti2s = tiq.filter(TaskInstance.task_id == "dummy2").all()
            assert len(ti1s) == 0
            assert len(ti2s) >= 2
            for task in ti2s:
                assert task.state == State.SUCCESS
    @pytest.mark.parametrize(
        "configs",
        [
            {("scheduler", "standalone_dag_processor"): "False"},
            {("scheduler", "standalone_dag_processor"): "True"},
        ],
    )
    def test_scheduler_multiprocessing(self, configs):