5 Commits

Include renames

Author	SHA1	Message	Date
Andreas	a2f4ef6f54	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.	2026-09-09 07:56:38 +02:00
AndreasandClaude Opus 4.8	67cf6f7d8a	feat(optimization): schedule any number of flexible consumers ... Replace the single hourly "dishwasher" home appliance with a list of flexible consumers (home_appliances). Each consumer defines its load either as an explicit power profile (energy-preservingly resampled onto the optimization slot grid, incl. 15-min and non-integer interval ratios) or the flat consumption_wh/duration_h fallback, and runs ONCE or DAILY within its time windows and the optimization horizon. - ConsumerScheduleMode + shared load-definition validation (XOR of profile/fallback, reject negative/NaN/inf, unique device_id) - ApplianceGeneLayout: variable appliance gene block (index into allowed_start_slots), ONCE/DAILY calendar-day based, no snapping - per-device output: result.home_appliance_energy_wh, appliance_starts (absolute local times), per-device solution columns and DDBC RUN/OFF instructions on state transitions only - deprecate dishwasher/washingstart/Home_appliance_wh_per_hour with backward-compatible mapping and explicit conflict rejection - max_home_appliances is now an upper bound only; no demo appliance and no on/off behaviour - docs, openapi.json, CHANGELOG and optimize_result_2* fixtures updated; new tests/test_homeappliance.py covers the mandatory test matrix Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>	2026-07-15 14:19:46 +02:00
Andreas	bed1f0f275	feat(optimization): model battery LCOS and probabilistic bypass	2026-07-15 09:23:29 +02:00
Andreas	cd5cdf8b47	fix(genetic): limit EV charging to unmet min SoC	2026-07-05 12:56:08 +02:00
Christopher NadlerandGitHub	3ccc25d731	Adds inverter AC/DC efficiency and break-even penalty (#888) ... * feat: add inverter AC/DC efficiency and break-even penalty * test: update tests/test_geneticoptimize.py with new ac_charge_break_even parameter * docs: update documentation * chore: update version numbers in configuration files to v0.2.0.dev2602272006923535	2026-02-27 23:12:08 +01:00