Chiller Simulation Documentation

Simulate how data center chillers affect each other and find the most efficient way to run them.

Contents:

• Getting Started
  • Installation
  • Basic Concepts
  • Package Structure
  • Minimal Working Example
  • Understanding Results
  • Next Steps
• User Guide
  • Architecture
  • SimulatorBuilder Reference
  • Running Simulations
  • Results Reference
  • Physics Plugins
  • Warm Start with InitialState
• Examples
  • Example 1 – Your First Optimization
  • Example 2 – Thermal Interference
  • Example 3 – Capacity, Aging, and the Feasibility Gate
  • Example 4 – Streaming a 24-Hour Load Profile
  • Example 5 – Time-Varying Wind
• API Reference
  • Layout
  • Physics
  • Simulation

Overview

When chillers sit close together, hot exhaust from one can blow into another’s intake. That heats the air and makes the second chiller work harder – using more electricity for the same cooling.

This package models that effect and helps you choose which chillers to run.

• Thermal interference: Physics-based Gaussian plume model of exhaust affecting neighbors

• Optimization: Greedy selection of the best subset of chillers to run

• Aging: Models capacity loss as chillers get older

• Startup ramp: Freshly started chillers come online at reduced capacity

• Dynamic simulation: Time-varying load, wind, and ambient temperature

• Modular design: Swap physics plugins via the fluent builder API

Quick Start

from chiller_sim import Simulator

sim = (
    Simulator()
    .with_grid(rows=2, cols=2, spacing_m=10.0, base_cop=4.0, max_cooling_kw=500.0)
    .with_wind(speed_m_per_s=5.0, angle_deg=0.0)
    .with_ambient_temp(temp_k=298.15)
    .with_load_fn(lambda t: 800.0)
    .build()
)

result = sim.optimize(time_hours=0.0)
print(f"Work: {result.total_work_kw:.2f} kW")

Indices and tables

• Index

• Module Index

• Search Page