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Andreas
a2f4ef6f54
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.
134 lines
5.8 KiB
Markdown
134 lines
5.8 KiB
Markdown
# Control horizon and battery lookahead
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The genetic optimizer issues controls only for `optimization.horizon_hours`,
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measured from the run start. The default is 24 hours. Battery and EV genomes,
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appliance schedules, simulation costs and returned control arrays all stop at
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that boundary. A larger prediction horizon does not add control genes.
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```json
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{
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"optimization": {
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"horizon_hours": 24,
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"tail_horizon_hours": 48,
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"terminal_value_mode": "AUTO"
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},
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"prediction": {"hours": 72}
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}
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```
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The forecast budget is never enforced by rejecting the configuration.
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`prediction.hours` also serves callers that do not optimize at all, so a budget
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that cannot serve the optimization horizons is reported rather than refused.
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A `prediction.hours` below `horizon_hours + tail_horizon_hours` shortens the
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tail to `prediction.hours - horizon_hours`, logged once at INFO and reported per
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run as `effective_tail_hours`. A `prediction.hours` below `horizon_hours` is
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logged as a warning at configuration time and rejected by the optimizer itself
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when a run starts, naming the forecast series that ends too early. EOS never
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rewrites the settings; raise `prediction.hours` to use the requested horizons in
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full.
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## Tail value and continuation
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In AUTO mode, a deterministic dynamic program evaluates the battery state at
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the end of the control horizon against the following forecast intervals. It
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uses a 101-point SOC grid and interpolates between states. Each transition uses
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the production battery and inverter models, including SOC bounds, power caps,
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conversion losses, configured charging/export rates, PV, load, direct-marketing
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permission and LCOS on delivered DC energy.
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The value curve is computed once per run. Genetic fitness subtracts its
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interpolated value from the simulated control cost. The older AC break-even
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penalty is disabled in TAIL mode because it does not account for future tail
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opportunities. Other feasibility penalties, including EV targets, still apply.
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The curve may decrease with SOC: free capacity can earn money at negative
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prices. Even an empty battery can have nonzero value. Values include net tail
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cash flows and the continuation credit; this constant baseline does not affect
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which control plan wins within a run. Tail actions are never returned.
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The existing AUTO proxy supplies the continuation value at the **effective tail
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end**. Its trailing window is controlled by `terminal_value_window_hours`. A
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window with no valuable load or export opportunities conservatively has zero
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continuation credit. With `tail_horizon_hours: 0`, AUTO uses the existing proxy
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directly at the control end. FIXED preserves the scalar terminal credit directly
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at the control end and does not solve a tail.
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This is a deterministic approximation on a discretized SOC grid, using the
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configured action levels. It does not model forecast uncertainty or schedule
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additional EV/appliance activity beyond the control horizon.
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## Forecast availability and API indexing
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The four required series are load, PV, import price and feed-in tariff. Every
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control interval must contain a finite value. Missing control data rejects the
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run. The tail stops at the first missing value in any required series, logs a
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warning and moves continuation to that point. No missing price becomes zero.
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Provider interval values are held within their source interval, never extended
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indefinitely beyond the last observed forecast timestamp.
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Legacy API forecast arrays still begin at midnight of the run's start day.
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They must therefore include the elapsed prefix plus the desired forecast
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coverage from now. The prefix is removed before optimization. Declare
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`forecast_interval_seconds: 900` for shortened native quarter-hour inputs;
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hourly inputs use `3600`. Fully sized native arrays remain auto-detected for
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compatibility. Scalar feed-in tariffs represent an explicitly constant tariff.
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New solutions set `controls_start_at_now: true`: index zero of every returned
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control array and warm-start genome corresponds to the run timestamp. The
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generic solution and plan adapters still understand older, midnight-indexed
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solutions where this flag is absent. Incompatible old genome lengths are
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discarded by warm-start validation.
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`terminal_value` reports the mode (`TAIL`, `AUTO`, or `FIXED`), usable remaining
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AC energy, control hours, requested/effective tail hours, continuation mode and
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any degradation reason. `tail_end_hour` is elapsed hours from the run start.
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FIXED mode reports zero effective tail hours.
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The credited amount is explicitly decomposed:
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```json
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{
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"mode": "TAIL",
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"battery_energy_wh": 5230,
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"credited_euro": 1.84,
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"tail_operating_euro": 1.21,
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"continuation_value_euro": 0.63,
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"control_horizon_hours": 24,
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"requested_tail_hours": 48,
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"effective_tail_hours": 48,
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"tail_end_hour": 72,
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"continuation_mode": "AUTO",
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"curve": {
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"energy_wh": [],
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"value_euro": [],
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"operating_value_euro": [],
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"continuation_value_euro": [],
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"marginal_euro_per_kwh": []
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},
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"continuation_curve": {
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"energy_wh": [],
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"value_euro": [],
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"marginal_euro_per_kwh": []
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},
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"tail_diagnostics": {
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"slots": 192,
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"slot_hours": 0.25,
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"soc_grid_points": 101,
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"min_import_price_euro_per_kwh": -0.08,
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"max_import_price_euro_per_kwh": 0.34,
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"min_feed_in_tariff_euro_per_kwh": 0.0,
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"max_feed_in_tariff_euro_per_kwh": 0.29,
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"negative_import_price_slots": 4,
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"positive_battery_export_slots": 160
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}
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}
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```
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`credited_euro` always equals `tail_operating_euro +
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continuation_value_euro`. The combined `curve` is the function read by genetic
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fitness. It contains the same decomposition at every SOC breakpoint.
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`continuation_curve` is the proxy at the effective tail end before the dynamic
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program folds the tail backwards onto it. Tail diagnostics summarize the actual
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forecast segment; they do not contain executable actions.
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