Build a Solar Soiling Loss and Cleaning Route Dispatcher

Calculate dust accumulation and thermal degradation across utility-scale solar arrays using plant pyranometer telemetry. Optimize automated cleaning vehicle routing schedules to maximize net energy yield.

Solar Farm Asset Manager

Ingest module temperature, plane-of-array irradiance, and daily string inverter power outputs.

Calculate baseline expected DC power output under clean conditions using pvlib performance models.

Quantify soiling loss percentages across individual tracker blocks and inverter zones.

Formulate robotic dry-brush cleaning vehicle route assignments prioritized by financial recovery rate.

Interactive plant block heatmap indicating soiling severity, economic break-even lines, and cleaning robot dispatch buttons.

Create synthetic string telemetry files including irradiance, module temperature, and measured power output across 20 inverter blocks. Starter examples below are synthetic. They are not downloaded records.

PVLib solar modeling Utilizes pvlib PVWatts or single-diode model functions to calculate clean reference power outputs under measured irradiance.

mastra-ai, pvlib, pandas. Mastra AI orchestrates deterministic step execution connecting analytical soiling models with cleaning robot task dispatchers. Local Python runtime with API-accessible LLM for generating shift handover notices.

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.

Calculates soiling loss ratio for each inverter block relative to pvlib clean reference.

Suppresses cleaning dispatch when estimated energy recovery value is less than cleaning operational cost.

Outputs a sequenced cleaning schedule for field operations teams.

```json [ { "input": { "block_id": "BLK-07", "irradiance_wm2": 850, "cell_temp_c": 52, "measured_power_kw": 620, "clean_reference_power_kw": 740, "cleaning_cost_usd": 45, "power_price_usd_kwh": 0.04 }, "expected_output": { "soiling_ratio": 0.838, "soiling_loss_pct": 16.2, "daily_revenue_loss_usd": 57.6, "dispatch_cleaning": true, "priority": "HIGH" } }, { "input": { "block_id": "BLK-12", "irradiance_wm2": 850, "cell_temp_c": 50, "measured_power_kw": 715, "clean_reference_power_kw": 735, "cleaning_cost_usd": 45, "power_price_usd_kwh": 0.04 }, "expected_output": { "soiling_ratio": 0.973, "soiling_loss_pct": 2.7, "daily_revenue_loss_usd": 9.6, "dispatch_cleaning": false, "priority": "DEFERRED" } } ] ```

Automated cleaning dispatches are mock orders; field robot operations require physical zone clearances and supervisor confirmation. Use mock external writes. Require human review before any real deployment.