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Demand vs Weather Simulator

This uses the accelerator's feature logic (ported from lib/demand_features.py): heating/cooling degree-days from temperature plus a daily seasonality profile. Move the sliders to see how weather and time-of-day drive a 48-hour demand curve.

1. Conditions

Avg outdoor temp -2°C

Weather sensitivity 1.0

Base load (MW) 200

2. Predicted demand (48h)

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Peak MW

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Average MW

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Degree-days/day

Predicted demandBase load

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Included with Demand Forecasting Accelerator

The complete Demand Forecasting Accelerator package includes:

Databricks Asset Bundle
Training + inference notebooks
Accuracy + data-quality SQL
A dependency-free feature library

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