Fix accuracy in calibration of solar

[springfall2008]

No description provided.

[Copilot]

Pull request overview

This PR updates Predbat’s solar PV forecast calibration to improve numerical accuracy by refining how historical PV/forecast data is sampled and how scaling factors are applied across future forecast days, and adds a synthetic regression test to validate key calibration outputs.

Changes:

• Update SolarAPI.pv_calibration() to use a 7-day history window (fetching 8 days for data availability) and compute worst/best scaling relative to an average-day scaling factor.
• Add per-forecast-day scaling compensation so future-day totals remain consistent after applying per-slot adjustments.
• Add a new synthetic-value calibration test case and bump Predbat version to v8.34.7.

Reviewed changes

Copilot reviewed 3 out of 3 changed files in this pull request and generated 1 comment.

File	Description
apps/predbat/solcast.py	Adjusts PV calibration algorithm (history window, average/worst/best scaling logic, and per-day scaling correction).
apps/predbat/tests/test_solcast.py	Updates existing calibration tests for the new signature and adds a synthetic regression test covering key numeric expectations.
apps/predbat/predbat.py	Bumps version from v8.34.6 to v8.34.7.