BICEP Examples

This section provides hands-on examples demonstrating how to use BICEP for electrical infrastructure analysis.

Interactive Jupyter Notebooks

We provide several Jupyter notebooks that demonstrate different aspects of BICEP:

1. basic-analysis.ipynb - Basic analysis workflow
   • View on GitHub (main branch)
   • Setting up BICEP analysis
   • Loading pre-computed scenario results
   • Calculating and visualizing costs
   • Key cost drivers
2. data-requirements.ipynb - Understanding input data
   • View on GitHub (main branch)
   • Input data structure and requirements
   • Available technologies and projections
   • Technology forecasts across scenarios
   • Custom forecast integration
3. scenario-comparison.ipynb - Comparing scenarios
   • View on GitHub (main branch)
   • BAU vs High load growth scenarios
   • Scenario comparison plots and analysis
   • Cost differences and implications
4. custom-distributions.ipynb - Advanced customization
   • View on GitHub (main branch)
   • Using custom cost distributions
   • Distribution classes and parameters
   • Sensitivity analysis

Running the Notebooks

Prerequisites

1. Conda Environment: Set up the BICEP conda environment (see Getting Started)
2. Data Files: Notebooks use the local SQLite database at data/bicep.x-stock.db
3. Jupyter Kernel: Select the bicep-env kernel in VS Code or JupyterLab

Launch Instructions

Option 1: VS Code (Recommended)

• Open the notebook file in VS Code
• Select the bicep-env kernel when prompted
• Run cells using Shift+Enter

Option 2: JupyterLab

jupyter lab examples/notebooks/basic-analysis.ipynb

Option 3: Jupyter Notebook

jupyter notebook examples/notebooks/basic-analysis.ipynb

Using BICEP Methods

For detailed API documentation and method references, see the API Reference.

Quick Start

The simplest way to use BICEP:

from bicep.analysis import BicepResults

# Create results for a scenario
results = BicepResults(scenario='bau')  # or 'high'

# View total costs
print(f"Total infrastructure cost: ${results.total_cost:,.0f}")

# Plot capacity requirements by technology
results.plot_drivers(residential=1)

Next Steps

• Data Requirements Example - Understanding input data
• Scenario Comparison - Comparing BAU vs High scenarios
• Custom Distributions - Advanced customization
• API Reference - Complete technical documentation

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Table of contents

• Data Requirements
• Scenario Comparison
• Custom Distributions