Queue Intel OS

The first job was making different ISO exports behave like one product model.

FIELD_ALIASES = {
    "queue_id": ["Queue ID", "Queue Number", "project_number"],
    "sponsor": ["Interconnecting Entity", "Interconnecting Customer", "developer"],
    "mw": ["Capacity (MW)", "Project Size (MW)", "Requested MW", "Queue MW"],
    "poi_name": ["POI", "Point of Interconnection", "Interconnection Location"],
}

def normalize_row(iso: IsoCode, row: dict[str, Any]) -> QueueProject:
    normalized = {field: _first(row, aliases) for field, aliases in FIELD_ALIASES.items()}
    queue_id = str(normalized.get("queue_id") or _hash(row)[:12])

    return QueueProject(
        project_id=f"{iso.value}:{queue_id}",
        iso=iso,
        queue_id=queue_id,
        sponsor=_clean(normalized.get("sponsor")),
        mw=_float(normalized.get("mw")),
        poi_name=_clean(normalized.get("poi_name")),
        raw_row_hash=_hash(row),
    )

A static queue is useful. A moving queue is where the signal lives: new projects, withdrawals, and capacity changes.

def detect_events(previous: list[QueueProject], current: list[QueueProject]) -> list[QueueEvent]:
    previous_by_id = {project.project_id: project for project in previous}
    current_by_id = {project.project_id: project for project in current}
    events: list[QueueEvent] = []

    for project_id, project in current_by_id.items():
        old = previous_by_id.get(project_id)
        if old is None:
            events.append(_event(EventType.NEW_PROJECT, project, "Not present", project.status, "..."))
            continue

        if (old.status or "").lower() != (project.status or "").lower():
            event_type = EventType.WITHDRAWAL if "withdraw" in (project.status or "").lower() else EventType.STATUS_CHANGE
            events.append(_event(event_type, project, old.status, project.status, "..."))

        if old.mw != project.mw:
            events.append(_event(EventType.MW_CHANGE, project, f"{old.mw} MW", f"{project.mw} MW", "..."))

    return _dedupe_events(events)

The UI ranks crowded POIs, sponsor concentration, churn, and queue-ahead pressure.

return applyPressureRanks(rows.map((row) => computeClusterRisk(mapRiskInput(row))))
  .filter((risk) => isMeaningfulText(risk.clusterName))
  .sort(
    (a, b) =>
      b.riskScore - a.riskScore ||
      (a.pressureRank ?? 100) - (b.pressureRank ?? 100) ||
      (b.queueAheadMw ?? 0) - (a.queueAheadMw ?? 0)
  )
  .slice(0, 50);

function pressureMetric(risk: ReturnType<typeof computeClusterRisk>) {
  if (risk.queueAheadMw && risk.queueAheadMw > 0) {
    return risk.queueAheadMw * 10 + risk.activeProjectCount;
  }
  return risk.activeProjectCount;
}