feat(optimization): split the control horizon from the forecast tail

The optimizer treated the end of `optimization.horizon_hours` as the end of the
world: energy left in the battery there was worth a single configured price per
kWh, so it either dumped the battery into the last hours or hoarded it,
depending on that one number.

The horizon is now two spans. `horizon_hours` still receives every control
command. The new `optimization.tail_horizon_hours` (default 48 h) is a pure
lookahead that never produces a command. In AUTO terminal-value mode a
deterministic dynamic program solves that tail backwards on a 101-point SoC
grid using the production battery and inverter models - SoC bounds, power caps,
conversion losses, configured charge and export rates, direct-marketing
permission and LCOS on delivered DC energy - and the existing AUTO proxy
supplies the continuation value at the tail end. Genetic fitness reads the
resulting curve. `tail_horizon_hours: 0` restores the plain proxy at the control
end, FIXED is unchanged.

The forecast budget is reported, never enforced by refusal: a tail that does not
fit is shortened to what the forecast covers and reported as
`effective_tail_hours`, and a control horizon that does not fit is warned about
at configuration time and rejected by the optimizer at run time, which knows
which series ran out. `prediction.hours` defaults to 72 so the new defaults fit
out of the box; existing shorter configurations keep starting.

Control arrays and warm-start genomes now begin at the run timestamp rather than
midnight, flagged by `controls_start_at_now` so the adapters still read older
solutions. `forecast_interval_seconds` declares the resolution of shortened
native quarter-hour inputs.

Required forecasts are no longer silently replaced by demo providers. A missing
PV, price, load, feed-in or weather forecast used to rewrite the configured
provider and retry, so a run could quietly optimize against invented data.
Missing values now stay missing, and provider values are held only within their
own source interval instead of being extended indefinitely.

Also fixes a config update that could leave EOS half-updated: the merged
candidate is validated before the singleton is reinitialized.

Four provider tests that hard-coded the old 48 h prediction default are rewritten
to derive their expectations from the configured horizon.

docs/_generated/openapi.md

@@ -1,6 +1,6 @@
 # Akkudoktor-EOS
 
-**Version**: `v0.3.0.dev2609040861878062`
+**Version**: `v0.3.0.dev2609090521492067`
 
 <!-- pyml disable line-length -->
 **Description**: This project provides a comprehensive solution for simulating and optimizing an energy system based on renewable energy sources. With a focus on photovoltaic (PV) systems, battery storage (batteries), load management (consumer requirements), heat pumps, electric vehicles, and consideration of electricity price data, this system enables forecasting and optimization of energy flow and costs over a specified period.