GENXUI

Overview

GENXUI is designed to make GenX.jl easier to use by removing the need to manually edit or inspect CSV files. It provides a simple browser interface to launch Julia runs, manage case inputs, and view results in a simple workflow.

Features

• Runner page for selecting a GenX case, launching Julia, and streaming terminal output live.

• Input browser for resources, system, policies, and settings files with inline editing and save support.

• Interactive results dashboard with LCOE tables, capacity charts, supply-to-load mix, cost breakdowns, and storage metrics.

• Reads GenX output CSVs directly so results can be inspected without rerunning Julia.

Prerequisites

• Julia ≥ 1.9 installed and available on your system PATH.

• GenX.jl repository placed alongside the GENXUI folder, not inside it.

• Python ≥ 3.10 installed.

• Python dependencies installed from requirements.txt.

Running the App

From the GENXUI directory, start the interface with Streamlit:

python -m streamlit run app.py

Then open http://localhost:8501 in your browser.

Case Setup

Each GenX case should follow the standard GenX input structure and include:

• Run.jl

• resources/ files such as Thermal.csv, Vre.csv, Storage.csv, and Vre_stor.csv

• system/ files such as Demand_data.csv, Generators_variability.csv, and Fuels_data.csv

• policies/

• settings/genx_settings.yml

Results

After a successful run, GENXUI reads output from the GenX case results directory and displays:

• LCOE per resource, including annual cost, generation, supply-to-load mix, and curtailment.

• Capacity built in MW and MWh by resource.

• Supply-to-load mix visualization.

• Cost breakdown by investment, fixed O&M, variable O&M, fuel, and startup costs.

• Storage metrics including power, energy, and duration.

Limitations

GENXUI mostly solved my problem, but maybe not yours.

• One case at a time — no side-by-side case comparison.

• Multi-zone / transmission runs are supported for viewing and analysis; the network-flow attribution in Supply to Load Mix is a documented approximation (local generation assumed to serve local load first).

• No multi-stage (MultiStage) investment support.

• Julia startup latency (~30–90 s) before the first solver output appears.

Author

Developed by Alex Panchula.

Project repository: https://github.com/apanchula/GENXUI