Build the application

## Build
Parse energy telemetry nodes from OPC UA servers via asyncua against dynamic utility tariff rates. Formulate optimal production run schedules that shift high-draw manufacturing operations out of peak pricing windows.

## User
Plant Energy Manager

## Workflow
1. Extract power draw profiles from normalized OPC UA variable telemetry logs via asyncua.
2. Load multi-tier electricity tariff schedules and factory production order deadlines.
3. Evaluate load shift scenarios against equipment setup constraints and shift hours using Optuna.
4. Produce an energy-optimized shift production schedule with projected cost savings.

## Interface
Comparative timetable visualization showing baseline vs rescheduled batch power curves.

## Data
Generate synthetic JSON fixtures containing simplified synthetic app records for machine kW draw and simulated hourly utility tariffs.
Starter examples below are synthetic. They are not downloaded records.

## Source
[open62541 OPC UA](https://raw.githubusercontent.com/open62541/open62541/master/README.md)
Leverages OPC UA information modeling concepts and telemetry variable nodes referenced in Source 0.

## Tools
optuna, pandas, asyncua.
Optuna handles multi-constraint optimization for scheduling batch operations against tariff windows.
Local lightweight model or hosted API for natural language schedule rationale explanation.

## Deliverables
Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.

## Acceptance
- Reduces peak window energy consumption by at least 15% in test runs.
- Preserves all committed customer order batch deadlines without tardiness.
- Generates a structured schedule export for production supervisors.

## Starter Examples
```json
[
  {
    "input": {
      "batch_id": "HEAT-TREAT-88",
      "power_draw_kw": 250,
      "duration_hours": 3,
      "deadline_hour": 18,
      "base_cost_per_kwh": 0.12,
      "tariff_windows": [
        {
          "start": 13,
          "end": 17,
          "cost_per_kwh": 0.42
        }
      ]
    },
    "expected_output": {
      "batch_id": "HEAT-TREAT-88",
      "scheduled_start_hour": 10,
      "scheduled_end_hour": 13,
      "projected_energy_cost": 90,
      "avoided_peak_tariff": true
    }
  },
  {
    "input": {
      "batch_id": "MELT-02",
      "power_draw_kw": 400,
      "duration_hours": 2,
      "deadline_hour": 15,
      "base_cost_per_kwh": 0.12,
      "tariff_windows": [
        {
          "start": 13,
          "end": 17,
          "cost_per_kwh": 0.45
        }
      ]
    },
    "expected_output": {
      "batch_id": "MELT-02",
      "scheduled_start_hour": 11,
      "scheduled_end_hour": 13,
      "projected_energy_cost": 96,
      "avoided_peak_tariff": true
    }
  }
]
```

## Safety
Read-only advisory scheduling; requires plant planner manual sign-off before committing runs to MES.
Use mock external writes. Require human review before any real deployment.