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Linked challenge: Build a Seawater RO Desalination Energy Procurement Allocator
Format
Code-aware
Lines
88
Sections
11
Linked challenge
Build a Seawater RO Desalination Energy Procurement Allocator
Prompt source
Original prompt text with formatting preserved for inspection.
88 lines
11 sections
No variables
1 code block
## Build
Align reverse osmosis high-pressure pump power consumption with solar generation curves and time-of-day tariffs. Formulate hourly desalination production setpoints to minimize grid energy costs.
## User
Desalination Plant Operations Dispatcher
## Workflow
1. Ingest seawater reverse osmosis membrane flux models, recovery ratios, and specific energy consumption metrics.
2. Model co-located photovoltaic solar production curves using pvlib irradiance and temperature functions.
3. Incorporate WaterTAP membrane unit performance equations for pressure versus permeate flux.
4. Synthesize an hourly high-pressure pump scheduling plan balancing potable water reservoir levels and tariff windows.
## Interface
Dashboard showing solar forecast overlays, power tariff bands, simulated permeate production curves, and pump setpoint controls.
## Data
Synthesize 24-hour time-series datasets containing hourly solar irradiance, water demand profiles, and membrane operating coefficients.
Starter examples below are synthetic. They are not downloaded records.
## Source
[WaterTAP treatment modeling](https://raw.githubusercontent.com/watertap-org/watertap/main/README.md)
Applies WaterTAP membrane treatment model specifications for calculating reverse osmosis specific energy consumption under variable flux.
## Tools
ray-serve, pvlib, numpy.
Ray Serve provides scalable model serving to run concurrent hydrodynamic and energy simulation tasks.
Local Python execution for mathematical optimization and hosted Claude API for operational summary generation.
## 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
- Maintains water reservoir storage between minimum reserve (20%) and maximum buffer (95%) across 24 hours.
- Shifts high-pressure pump load by at least 25% into peak solar production hours.
- Outputs an hourly pumping schedule with estimated power purchase costs.
## Starter Examples
```json
[
{
"input": {
"plant_id": "SWRO-01",
"storage_initial_m3": 15000,
"storage_max_m3": 50000,
"target_daily_output_m3": 30000,
"peak_solar_hours": [
10,
11,
12,
13,
14
],
"peak_grid_tariff_hours": [
17,
18,
19,
20
]
},
"expected_output": {
"solar_hour_pump_load_pct": 100,
"grid_peak_pump_load_pct": 40,
"projected_final_storage_m3": 18200,
"energy_cost_status": "OPTIMIZED",
"curtailment_avoided_mwh": 8.4
}
},
{
"input": {
"plant_id": "SWRO-02",
"storage_initial_m3": 5000,
"storage_max_m3": 50000,
"target_daily_output_m3": 35000,
"peak_solar_hours": [
11,
12,
13
],
"peak_grid_tariff_hours": [
18,
19,
20
]
},
"expected_output": {
"solar_hour_pump_load_pct": 100,
"grid_peak_pump_load_pct": 75,
"projected_final_storage_m3": 11500,
"energy_cost_status": "CONSTRAINED_BY_MINIMUM_STORAGE",
"curtailment_avoided_mwh": 3.1
}
}
]
```
## Safety
Pump setpoints are recommendations; minimum system pressures must remain within physical membrane manufacturer limits to prevent collapse.
Use mock external writes. Require human review before any real deployment.Adaptation plan
Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.
Keep stable
Hold the task contract and output shape stable so generated implementations remain comparable.
Tune next
Update libraries, interfaces, and environment assumptions to match the stack you actually run.
Verify after
Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.