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PLEXOS›
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PLEXOS

Energy Exemplar› offers PLEXOS

ProductOperating Status: Currently Offered

PLEXOS is power-system modeling software for energy-market and resource-planning analysis.

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Overview
Analysis

PLEXOS - Research Notes

  • PLEXOS models several energy commodities in one co-optimized framework, while many competing tools simulate electricity markets on their own. Its mathematical formulation can be inspected, which supports audit and calibration work by modelers.

    Competing offerings include EnCompass from Yes Energy, SERVM from PowerGEM, GE Vernova's PlanOS capacity expansion product, and REint's GridBricks modeling suite. PLEXOS differentiates on commodity breadth and an installed base accumulated across international markets since the early 2000s.

  • PLEXOS originated in the doctoral research of Glenn Drayton at the University of Canterbury, where early optimization tools for electricity scheduling were developed. Drayton Analytics was founded in 1999 in New Zealand, and the first version of PLEXOS was released in mid-2000.

    The business was renamed Energy Exemplar in 2006, and the platform was applied to renewable integration studies from 2008 onward. Its thousandth installation was reached in 2015, and PLEXOS today operates as a co-optimized energy market simulation platform spanning power, gas, water, and hydrogen.

  • Decarbonization is widening the study workload carried by market simulation platforms, as storage, hydrogen, and emissions policy add scenario types to resource and market plans.

    Vendors in the category are pairing engines with AI-assisted analysis; Energy Exemplar introduced the PLEXOS Pulse agent-style interface for traders in July 2026. Rival platforms are investing in automation and cloud delivery in response.

  • PLEXOS is Energy Exemplar's simulation platform for co-optimized modeling of power, gas, water, and hydrogen systems. Studies run at zonal or nodal resolution across capacity expansion, production cost, and resource adequacy questions.

    Planning, market, and trading teams build scenario sets from their own network and asset data and compare outcomes across planning horizons. Cloud execution, simulation-ready market datasets, and template libraries extend the core engine within the same product family.