BETTER-LBNL-OS Documentation
Welcome to BETTER-LBNL-OS, an open-source Python library for building energy analytics extracted from the Building Efficiency Targeting Tool for Energy Retrofits (BETTER). BETTER is a software toolkit that enables building operators to quickly, easily identify the most cost-saving energy efficiency measures in buildings and portfolios. BETTER is made possible by support from the U.S. Department of Energy (DOE) Building Technologies Office (BTO).
Features
Change-point Model Fitting: Automated fitting of 1-, 3-, 5-parameter (1P/3P/5P) models
Building Benchmarking: Statistical performance comparison of building energy performance against peer groups
Energy Savings Estimation: Weather-normalized energy savings calculations with uncertainty quantification
Energy Efficiency Recommendations: Rule-based recommendations for energy efficiency improvements
Portfolio Analytics: Aggregate analysis across multiple buildings
Quick Start
Installation:
pip install better-lbnl-os
Basic usage:
from better_lbnl_os import BuildingData, fit_changepoint_model
import numpy as np
# Create a building
building = BuildingData(
name="Office Building",
floor_area=50000,
space_type="Office",
location="Berkeley, CA"
)
# Fit change-point model
temperatures = np.array([45, 50, 55, 60, 65, 70, 75, 80])
energy_use = np.array([120, 110, 95, 85, 80, 82, 95, 115])
model = fit_changepoint_model(temperatures, energy_use)
print(f"R-squared: {model.r_squared:.3f}")
Contents: