vpp-ai-platform/skills-py/vpp_contracts/bid_optimization_request.py
Thomas Bayes 8796faca63 M2: skill contracts, Python skill service, L2 eval harness with baseline
- packages/domain: ForecastRequest, BidOptimizationRequest/Result,
  ReportRequest, SkillReport (+ golden and invalid fixtures, exported to
  contracts/ and regenerated as pydantic models).
- skills-py/vpp_skills: FastAPI service with versioned registry; load/PV/
  price forecasts (same-day-type EWM point forecast, conformal residual
  quantiles — coverage test as acceptance gate); bid-optimization MILP on
  HiGHS (binary block participation, hard ledger energy bounds, exact
  Decimal fit of the rounded curve inside the bounds, revenue distribution
  over quantile paths); report generator whose every figure is a
  {tool_call_id, path} reference, with a verifier. 48 tests incl. hypothesis
  property test that bids respect ledger constraints.
- packages/services: LedgerService.dayAheadBounds (the P7 cascade band
  handed to the optimizer); Decimal resolved once for CJS/ESM interop.
- packages/evals: L2 metrics (MAPE, nRMSE, coverage, direction accuracy,
  naive/hindsight revenue baselines), HTTP skill client, rolling-origin
  harness that pushes each bid through the real ledger, CLI with
  --check/--write-baseline; committed baseline on the SYNTHETIC dataset
  (no historical Hubei data yet — baselines measure the harness, not KPI).
- CI: evals job boots the skill service and fails on baseline digest drift.
- docs/open-questions: A6 (flexibility marginal cost = offer floor); A4/B6
  wired as placeholders. README/CLAUDE.md status → M2 done, M3 next.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01UoYoGYzHkFyv3ALenkRPhA
2026-09-02 06:29:08 -04:00

130 lines
2.9 KiB
Python

# generated by datamodel-codegen:
# filename: bid_optimization_request.json
from __future__ import annotations
from enum import StrEnum
from typing import Literal
from pydantic import (
AwareDatetime,
BaseModel,
ConfigDict,
Field,
RootModel,
conint,
constr,
)
class Kind(StrEnum):
LOAD = 'LOAD'
PV = 'PV'
PRICE = 'PRICE'
class Unit(StrEnum):
mw = 'mw'
yuan_per_mwh = 'yuan_per_mwh'
class Value(RootModel[constr(pattern=r'^-?\d+(\.\d+)?$')]):
root: constr(pattern=r'^-?\d+(\.\d+)?$')
class P10(BaseModel):
model_config = ConfigDict(
extra='forbid',
)
interval_minutes: Literal[15]
date: constr(pattern=r'^\d{4}-\d{2}-\d{2}$')
values: list[Value] = Field(..., max_length=96, min_length=96)
class P50(BaseModel):
model_config = ConfigDict(
extra='forbid',
)
interval_minutes: Literal[15]
date: constr(pattern=r'^\d{4}-\d{2}-\d{2}$')
values: list[Value] = Field(..., max_length=96, min_length=96)
class P90(BaseModel):
model_config = ConfigDict(
extra='forbid',
)
interval_minutes: Literal[15]
date: constr(pattern=r'^\d{4}-\d{2}-\d{2}$')
values: list[Value] = Field(..., max_length=96, min_length=96)
class Quantiles(BaseModel):
model_config = ConfigDict(
extra='forbid',
)
p10: P10
p50: P50
p90: P90
class Model(BaseModel):
model_config = ConfigDict(
extra='forbid',
)
name: constr(min_length=1)
version: constr(min_length=1)
class PriceForecast(BaseModel):
model_config = ConfigDict(
extra='forbid',
)
id: constr(min_length=1)
kind: Kind
market_date: constr(pattern=r'^\d{4}-\d{2}-\d{2}$')
unit: Unit
quantiles: Quantiles
model: Model
features_snapshot_ref: constr(pattern=r'^[0-9a-f]{64}$')
generated_at: AwareDatetime
class AdjustableCapacityMw(BaseModel):
model_config = ConfigDict(
extra='forbid',
)
interval_minutes: Literal[15]
date: constr(pattern=r'^\d{4}-\d{2}-\d{2}$')
values: list[Value] = Field(..., max_length=96, min_length=96)
class PositionBounds(BaseModel):
model_config = ConfigDict(
extra='forbid',
)
ledger_version: conint(ge=0, le=9007199254740991)
daily_energy_min_mwh: constr(pattern=r'^-?\d+(\.\d+)?$')
daily_energy_max_mwh: constr(pattern=r'^-?\d+(\.\d+)?$')
class Risk(BaseModel):
model_config = ConfigDict(
extra='forbid',
)
risk_aversion: constr(pattern=r'^-?\d+(\.\d+)?$')
commitment_buffer_k: constr(pattern=r'^-?\d+(\.\d+)?$')
min_block_mwh: constr(pattern=r'^-?\d+(\.\d+)?$')
marginal_cost_yuan_per_mwh: constr(pattern=r'^-?\d+(\.\d+)?$')
class BidOptimizationRequest(BaseModel):
model_config = ConfigDict(
extra='forbid',
)
market_date: constr(pattern=r'^\d{4}-\d{2}-\d{2}$')
price_forecast: PriceForecast
adjustable_capacity_mw: AdjustableCapacityMw
position_bounds: PositionBounds
risk: Risk