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National Energy Modeling System (NEMS) Documentation Archive

Commercial Demand Module - NEMS Documentation

October 24, 2018


Purpose of the report

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Commercial Demand Module (CDM, Commercial Module, 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 Commercial Demand Module is a simulation tool based upon economic and engineering relationships that models commercial sector energy demands at the census division level of detail for eleven distinct categories of commercial buildings, as seen in Table 1 in the next section of this document. The CDM is used in developing long-term projections and energy policy analysis over the time horizon beginning with EIA’s most recent Commercial Building Energy Consumption Survey (CBECS) (the module’s base year) through 2050 (the current projection horizon). Commercial equipment selections are performed for the major fuels of electricity, natural gas, and distillate fuel oil, for the major end-use services of 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, liquefied petroleum gas, steam coal, motor gasoline, and kerosene), renewable fuel sources (wood, municipal solid waste, hydroelectric, solar energy, and wind), and the minor services of personal computers, other 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 Module generates projections of commercial sector energy demand. The model facilitates policy analysis of energy markets, technological development, environmental issues, and regulatory development as they impact commercial sector energy demand.

Model archival citation

This documentation refers to the NEMS Commercial Demand Module as archived for the Annual Energy Outlook 2018 (AEO2018).

Organization of this report

Chapter 2 of this report discusses the purpose of the model, detailing its objectives, primary input and output quantities, and the relationship of the Commercial Module to the other modules of the NEMS system. Chapter 3 of the report describes the rationale behind the model design, providing insights into further assumptions utilized 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 Appendices 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 NEMS system and the model evaluation process. A table referencing the equation(s) 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 alternate assumptions, sensitivities, and uncertainties in projections developed using the NEMS Commercial Demand Module are available at EIA’s website.

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