### 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)

if not task_instances_to_examine:
                self.log.debug("No tasks to consider for execution.")
                break
            
            task_instance_str = "\n".join(f"\t{x!r}" for x in task_instances_to_examine)
            self.log.info("%s tasks up for execution:\n%s", len(task_instances_to_examine), task_instance_str)
            for task_instance in task_instances_to_examine:
                pool_name = task_instance.pool
                pool_stats = pools.get(pool_name)
                if not pool_stats:
                    self.log.warning("Tasks using non-existent pool '%s' will not be scheduled", pool_name)
                    starved_pools.add(pool_name)
                    continue
                
                pool_num_starving_tasks.setdefault(pool_name, 0)
                pool_total = pool_stats["total"]
                open_slots = pool_stats["open"]
                if open_slots <= 0:
                    self.log.info(
                        "Not scheduling since there are %s open slots in pool %s", open_slots, pool_name
                    )
                    
                    pool_num_starving_tasks[pool_name] += 1
                    num_starving_tasks_total += 1
                    starved_pools.add(pool_name)
                    continue
                if task_instance.pool_slots > pool_total:
                    self.log.warning(
                        "Not executing %s. Requested pool slots (%s) are greater than "
                        "total pool slots: '%s' for pool: %s.",