PJM ECHO: A Visual Analytics App for Analyzing Electricity Market Prices

The interface allows users to visualize congestion deltas, filter historical data, retrieve summary information, and replay market days hour-by-hour.

Quick Start Guide

Prerequisites: Node.js, npm, Conda and Git installed.

Clone, Install and Run the App:

# Clone the repo
git clone https://github.com/nudataviz/project-fall25-darbyatNE
cd project-fall25-darbyatNE
# Create and activate the Conda environment
conda env create -f environment.yml
conda activate lmp-env
# Run the app
npm install
npm run dev

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Documentation

1. User Guide & Domain Logic 👈 Start Here for Context

• Key Terms: What are PJM, LMP, DA/RT, and Congestion?
• How to Read the Map: Interpreting color scales and timelines.
• Workflow: How to use the Query Tool to find "Like Days."

2. Technical Setup & Data Ingestion 👈 Start Here for Building the Infrastructure

• Database: AWS RDS configuration and Schema.
• Hydration: Running the Python scripts to ingest PJM data.
• Environment: Setting up .env keys (PJM API, MapTiler, MYSQL credentials).

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Project Goal

To help energy traders forecast financial risk.

This tool allows users to select custom historical time periods enabling them to visualize prices across PJM's dual-settlement system, specifically focusing on the volatile price difference ("Congestion") between zones.

By comparing interregional zonal pricing using Day-Ahead settlement (The Plan) against Real-Time actuals (The Reality), users can identify costly bottlenecks and make data-driven decisions to identify financial opportunities.

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Feedback & Contact

Feedback and suggestions are welcome. Please send your thoughts to:

Ben Darby: darby.b@northeastern.edu
Ben Henshaw: henshaw.b@northeastern.edu