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Heating Cost Optimizer

This runs the same Model-Predictive-Control algorithm shipped in the accelerator (ported to JavaScript). Adjust the price curve and comfort band, then optimize: the controller pre-heats when energy is cheap and coasts when it's expensive — never leaving the comfort band. This is a marketing demo; the product ships the unit-tested NumPy solver, thermal-model training, and savings SQL.

1. Set the scenario

Peak price multiplier 5×

Comfort band width 3.0°C

Building thermal inertia 0.80

2. Result

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Baseline cost

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Optimized cost

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Energy cost saved

Price signal Baseline setpoint Optimized setpoint Indoor temp (optimized)

Get the full accelerator — $2990

Included with Predictive Heating Optimization Accelerator

The complete Predictive Heating Optimization Accelerator package includes:

Bundle definition (all variables)
3 scheduled jobs
Per-site Ridge thermal model
The NumPy MPC solver (unit-tested)
MPC notebook (uses the solver)
Verified energy savings

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