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POMATO review

Free#33 of 63 in Energy Analytics Software

A specialized, open-source model for electricity-market clearing and grid analysis.

5.6/10Editor score
POMATO5.6 Visit POMATO

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

POMATO (Power Market Tool) is an open-source Python and Julia application for modeling and analyzing electricity markets. It is aimed at researchers and practitioners studying market clearing, dispatch, and grid constraints. Users supply input data and choose a grid representation to calculate economic dispatch, then process and visualize the results. Its local installation and modeling focus suit technical work more than a general-purpose energy analytics workflow.

Its analytical scope covers several linked market and grid questions. POMATO supports zonal market clearing, flow-based market coupling, redispatch, and nodal or zonal power-flow representations, including N-0 and N-1. Renewable generation availability and curtailment can be modeled alongside electricity and heat storage. Chance-constrained optimization addresses renewable uncertainty and reserves. The tool also includes data input, processing, validation, and result analysis, making it relevant for studies that need to examine how market outcomes relate to network constraints and generation assumptions.

The project is free and open source, with self-hosted deployment on Windows and Linux. Its integrations include Python, Julia, JuMP, Clp.jl, ECOS, and Gurobi.jl. Those options fit users working in computational power-systems research, but the requirement to install Python and Julia means it is not a turnkey analytics service. A significant consideration is project status: the repository says POMATO is no longer actively developed, although its maintainer still keeps an eye on it. Researchers who need its specific market-clearing and grid-modeling capabilities may find the scope appropriate; teams seeking active development or broader, ready-to-use energy analytics should consider alternatives.

POMATO pros and cons

  • Where it wins
    • Models zonal market clearing, flow-based coupling, and redispatch
    • Includes nodal and zonal power-flow analysis, including N-0 and N-1
    • Supports renewable curtailment, storage, and uncertainty modeling
  • Where it doesn't
    • Requires local installation of Python and Julia
    • Focused on electricity-market and grid studies rather than broad energy analytics
    • The project is no longer actively developed

POMATO fact sheet, pricing and score →

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