Commercial Demand Module - NEMS Documentation
July 2025
Introduction
Purpose of the report
This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Commercial Demand Module (CDM, or module). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and outputs generated through the use of the module.
This document serves three purposes. First, it is a reference document providing a detailed description for model analysts, users, and the public. Second, this report meets the legal requirement of the U.S. Energy Information Administration (EIA) to provide adequate documentation in support of its models (Public Law 93-275, section 57.b.1). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.
Model summary
The NEMS CDM is a simulation tool based on economic and engineering relationships that models commercial sector energy demands at the census division level of detail for 11 distinct categories of commercial buildings (Table 1). The CDM is used in developing long-term projections and energy policy analysis over the projection period beginning with our most recent Commercial Buildings Energy Consumption Survey (CBECS) (the module’s base year) through 2050 (the current projection period). Commercial equipment selections are performed for the major fuels (electricity, natural gas, and distillate fuel oil) and for the major end-use services (space heating, space cooling, water heating, ventilation, cooking, lighting, and refrigeration). The market segment level of detail is modeled using a constrained life-cycle cost minimization algorithm that considers commercial sector consumer behavior and risk-adjusted time preference premiums. The algorithm also models demand for minor fuels (residual fuel oil, propane, steam coal, motor gasoline, and kerosene), renewable fuel sources (hydroelectric, solar energy, and wind, including biomass sources such as wood and municipal solid waste), and the minor services of computing, office equipment, and other or miscellaneous electric loads (MELs) in less detail than the major fuels and services. Commercial decisions regarding the use of distributed generation (DG) and combined-heat-and-power (CHP) technologies are performed using an endogenous cash-flow algorithm. Numerous specialized considerations are incorporated, including the effects of changing building shell efficiencies and consumption to provide district energy services.
As a component of the NEMS integrated projection tool, the Commercial Demand Module generates projections of commercial sector energy demand. The module facilitates policy analysis of energy markets, technological development, environmental issues, and regulatory development as they affect commercial sector energy demand.
Documentation
U.S. Energy Information Administration, Commercial Demand Module of the National Energy Modeling System: Model Documentation, DOE/EIA-M066 (2025) (Washington, DC, August 2025).
Archive media and installation manuals
The module, as part of the NEMSNEMS, has been archived for the Reference case published in the Annual Energy Outlook 2025 (AEO2025), DOE/EIA-0383 (2025).
Model archival citation
This documentation refers to the NEMS Commercial Demand Module as archived for the Annual Energy Outlook 2025 (AEO2025).
The latest open-source NEMS code and input files are available at https://github.com/EIAgov/NEMS
Model contact
Buildings Energy Consumption and Efficiency Modeling
EIAInfoConsumption&EfficiencyOutlooks@eia.gov
Report organization
Chapter 2 of this report discusses the purpose of the model, detailing its objectives, primary input and output quantities, and its relationship to the other modules of the NEMSNEMS. Chapter 3 of the report describes the rationale behind the model design, providing insights into further assumptions used in the model development process to this point. Chapter 4 details the model structure, using graphics and text to illustrate model flows and key computations.
The appendixes to this report provide supporting documentation for the input data and parameter files. Appendix A lists and defines the input data used to generate parameter estimates and endogenous projections, along with the parameter estimates and the outputs of most relevance to the NEMSNEMS and the model evaluation process. A table referencing the equations in which each variable appears is also provided in Appendix A. Appendix B contains a mathematical description of the computational algorithms, including the complete set of model equations and variable transformations. Appendix C is a bibliography of reference materials used in the development process. Appendix D provides the model abstract, and Appendix E discusses data quality and estimation methods. Other analyses discussing alternative assumptions, sensitivities, and uncertainties in projections developed using the NEMS CDM are available at our website.