skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Model documentation: Electricity Market Module. Modifications to the electricity capacity planning submodule

Technical Report ·
OSTI ID:46682

The Electricity Market Module (EMM) is the electricity supply component of the National Energy Modeling System (NEMS). The EMM represents the generation, transmission, and pricing of electricity. It consists of four main submodules: Electricity Capacity Planning (ECP), Electricity Fuel Dispatching (EFD), Electricity Finance and Pricing (EFP), and Load and Demand-Side Management (LDSM). The ECP evaluates changes in the mix of generating capacity that are necessary to meet future demands for electricity and comply with environmental regulations. The EFD represents operating decisions and determines how to allocate available capacity to meet the current demand for electricity. Using investment expenditures from the ECP and operating costs from the EFD, the EFP calculates the price of electricity, accounting for state-level regulations involving the allocation of costs. The LDSM translates annual demands for electricity into distributions that describe hourly, seasonal, and time-of-day variations. These distributions are used by the EFD and the ECP to determine the quantity and types of generating capacity that are required to ensure reliable and economical supplies of electricity. The EMM also represents non-utility suppliers and interregional and international transmission and trade. The ECP uses a linear programming (LP) model to consider planning decisions involving changes in capital stock that occur over several years and require a substantial capital investment. It projects how the electric power industry will change its generating capability in response to changes in environmental regulations and increases in demand. The ECP has been modified for the Annual Energy Outlook 1995. Enhancements to the ECP include an endogenous representation of maintenance scheduling, the incorporation of technological optimism and learning factors, and a market-sharing algorithm.

Research Organization:
USDOE Energy Information Administration, Washington, DC (United States). Energy Supply and Conversion Div.
Sponsoring Organization:
USDOE, Washington, DC (United States)
OSTI ID:
46682
Report Number(s):
DOE/EIA-M068-B/1; ON: DE95010355; NC: NONE; TRN: AHC29513%%97
Resource Relation:
Other Information: PBD: Apr 1995
Country of Publication:
United States
Language:
English