Industrial Demand Module
The NEMS Industrial Demand Module estimates energy consumption by energy
source (fuels and feedstocks) for 15 manufacturing and 6 nonmanufacturing
industries. The manufacturing industries are further subdivided into the
energy-intensive manufacturing industries and nonenergy-intensive manufacturing
industries (Table 6.1). The manufacturing industries are modeled through
the use of a detailed process-flow or end-use accounting procedure, whereas
the nonmanufacturing industries are modeled with substantially less detail.
The petroleum refining industry is not included in the industrial module,
as it is simulated separately in the Petroleum Market Module of NEMS. The
Industrial Demand Module calculates energy consumption for the four Census
Regions (see Figure 5) and disaggregates the energy consumption to the
nine Census Divisions based on fixed shares from the State Energy Data
System [1].
The energy-intensive industries (food products, paper and allied products,
bulk chemicals, glass and glass products, cement, iron and steel, and aluminum)
are modeled in considerable detail. Each industry is modeled as three separate
but interrelated components consisting of the Process Assembly (PA) Component,
the Buildings (BLD) Component, and the Boiler/Steam/Cogeneration (BSC)
Component. The BSC Component satisfies the steam demand from the PA and
BLD Components. In some industries, the PA Component produces byproducts
that are consumed in the BSC Component. For the manufacturing industries,
the PA Component is separated into the major production processes or end
uses.
Petroleum refining (NAICS 32411) is modeled in detail in the Petroleum
Market Module of NEMS, and the projected energy consumption is included
in the manufacturing total. Projections of refining energy use, lease and
plant fuel, and fuels consumed in cogeneration in the oil and gas extraction
industry (NAICS 211) are exogenous to the Industrial Demand Module, but
endogenous to the NEMS modeling system.
Key Assumptions
The NEMS Industrial Demand Module primarily uses a bottom-up process modeling
approach. An energy accounting framework traces energy flows from fuels
to the industry’s output. An important assumption in the development
of this system is the use of 2002 baseline Unit Energy Consumption (UEC)
estimates based on analysis of the Manufacturing Energy Consumption Survey
(MECS) 2002. [2] The UECs represent the energy required to produce one
unit of the industry’s output. The output may be defined in terms of
physical units (e.g., tons of steel) or in terms of the dollar value of
shipments.
The industrial module depicts the manufacturing industries (apart from
petroleum refining) with a detailed process flow or end use approach.
The dominant process technologies are characterized by a combination of
unit energy consumption estimates and “technology possibility curves.”
The technology possibility curve is an exponential growth trend corresponding
to a given average annual growth rate, or technology possibility coefficient
(TPC). The TPC defines the assumed average annual growth rate of the energy
intensity of a process step or an energy end use. The TPCs for new and
existing plants vary by industry vintages and process. These assumed rates
were developed using professional engineering judgments regarding the energy
characteristics, year of availability, and rate of market adoption of new
process technologies.
Process/Assembly Component
The PA Component models each major manufacturing production step or end
use for the manufacturing industries. The throughput production for each
process step is computed, as well as the energy required to produce it.
The amount of energy to produce a unit of output is defined as the unit
energy coefficient (UEC), another term for the energy intensity of the
process. The PA component for the bulk chemical industry was revised for
the AEO2010 and is discussed separately. This section describes the PA
component for the rest of the industries.
The module distinguishes the UECs by three vintages of capital stock.
The amount of energy consumption reflects the assumption that new vintage
stock will consist of state-of-the-art technologies that are more energy
efficient than the average efficiency of the existing capital stock. Consequently,
the amount of energy required to produce a unit of output using new capital
stock is less than that required by the existing capital stock. Capital
stock is grouped into three vintages: old, middle, and new. The old vintage
consists of capital existing in 2002 and surviving after adjusting for
assumed retirements each year (Table 6.2). New production capacity is
assumed to be added in a given projection year such that sufficient surviving
and new capacity is available to meet the level of an industry’s output
as determined in the NEMS Regional Macroeconomic Module. Middle vintage
capital is that which is added after 2002 up through the year prior to
the current projection year.
To simulate technological progress and adoption of more efficient energy
technologies, the UECs are adjusted each projection year based on the assumed
TPC for each step. The TPCs are derived from assumptions about the relative
energy intensity (REI) of productive capacity by vintage (new capacity
relative to existing stock in a given year) or over time (new or surviving
capacity in 2035 relative to the 2002 stock) (Table 6.3). For example,
state-of-the-art additions to mechanical pulping capacity in 2002 are assumed
to require only 93.1 percent as much energy as does the average existing
plant, so the REI for new capacity in 2002 is 0.931 (see Table 6.3). Over
time, the UECs for new capacity are assumed to improve, and the rate of
improvement is given by the TPC. The UECs of the surviving 2002 capital
stock are also assumed to decrease over time, but not as rapidly as for
new capital stock. For example, with mechanical pulping, the TPC for new
facilities is -0.012, while the TPC for existing facilities is -0.007.
Also provided in Table 6.3 are alternative assumptions used to reflect
a more optimistic, “high tech” case.
The concepts of REI and TPCs are a means of embodying assumptions regarding
new technology adoption in the manufacturing industry and the associated
increased energy efficiency of capital without characterizing individual
technologies in detail. The approach reflects the assumption that industrial
plants will increase in energy efficiency as owners replace old equipment
with new, more efficient equipment, add new capacity, or upgrade their
energy management practices. The reasons for the increased efficiency
are not likely to be directly attributable to technology choice decisions,
changing energy prices, or other factors readily subject to modeling. Instead,
the module uses the REI and TPC concepts to characterize efficiency trends
for bundles of technologies available for major process steps or end use.
There are two exceptions to the general approach in the PA component.
The first is for electric motor technology choice implemented for 8 industries
to simulate their electric machine drive energy end use. Machine drive
electricity consumption in the food industry, the five metal-based durables
industries, and the three non-intensive manufacturing industries is calculated
by a motor stock model. The beginning stock of motors is modified over
the projection horizon as motors are added to accommodate growth in shipments
for each sector, as motors are retired and replaced, and as failed motors
are rewound. When an old motor fails, an economic choice is made on whether
to repair or replace the motor. When a new motor is added, either to accommodate
growth or as a replacement, the motor must meet the efficiency standard
minimum or a premium efficiency motor. Table 6.4 provides the beginning
stock efficiency for seven motor size groups in each of the three industry
groups, as well as efficiencies for EPACT minimum and premium motors. [3]
As the motor stock changes over the projection horizon, the overall efficiency
of the motor population changes as well.
The second exception in the PA component is the Bulk chemicals Sub-model.
The methodology is described below.
Bulk Chemical Industry
For the AEO2010, a new PA Component module for the bulk chemical industry
was implemented. The need to analyze the impacts of high energy prices
on feedstock use and also to track some of the chemical products that are
highly dependent on energy resources, such as ammonia and ethylene, compelled
this change. It is important to note that this model only replaces the
PA Component of the bulk chemical energy consumption projections. The BSC
and BLD components remain the same for this industry.
Table 6.5 shows the list of the chemical products represented in the model.
There are 16 organic, 5 inorganic, 5 resins, and 2 agricultural chemicals,
plus four aggregate groups (rest of organic, rest of inorganic, rest of
resins, and rest of agricultural chemicals).
The choice of chemicals included in the model is driven by several factors,
including relatively large production volumes, high energy intensity, expected
high production growth, and/or high energy and feedstock consumption.
The bulk chemical model has several components and these are briefly discussed
below.
2002 Base Year Data
This component provides a picture of the bulk chemical industry’s production,
processes, and energy requirements for 2002. Data are provided for each
chemical in Table 6.5.
Chemical Production Component
This component forecasts chemical production for each chemical in Table
6.5. In the bulk chemical industry, there is significant interplay among
basic chemicals, intermediate chemicals, and final chemical products. A
good understanding of the relationships among these chemicals helped in
the development of the methodology used to forecast the production levels
of each chemical. To develop the models or equations that forecast chemical
production, the relationships between the chemicals were considered. In
addition, the relationships between the production levels of the chemicals
and dollar value of output (or shipments) of the chemical industry and
other industries that use the chemicals, and other drivers such as gross
domestic product (GDP), energy prices, and U.S population were also considered.
Chemical Process Component
This component forecasts processes for each chemical in Table 6.5. Besides
the level of chemical production, a major driver of energy consumption
in the bulk chemical industry is the process used to produce a chemical
product. Table 6.6 shows the industrial processes used to produce each
chemical represented in the model.
The unit energy requirements of steam, electricity, and fuel for each process
listed in Table 6.6 are provided for 14 categories of energy services:
Process water cooling, pumping, compression, motive force, direct clean
heat, indirect heat, indirect drying, concentration, distillation, electrolysis,
feedstocks, reforming, fuel from feed [4], and byproduct adjustment [5].
Because the choice of processes is not generally driven just by energy
prices, the shares of processes used to produce a chemical is mostly exogenous
to the model. The exceptions are those chemicals and their processes that
use significant amounts of energy feedstocks, such as ethylene, propylene
and butadiene. These three basic chemicals are sensitive to energy prices,
and as such, the model captures the feedstock switching response to changing
energy prices. There are other chemicals in which only one process is used
for its production (at an industrial-scale). For these chemicals, the process
is assigned 100 percent.
As indicated above, three chemicals, ethylene, propylene, and butadiene
are modeled with more detail than the other chemicals in the model. More
detailed descriptions of the representations of process or feedstock choices
among these chemicals are discussed below.
Ethylene/Propylene/Butadiene Feedstocks Component
This component forecasts ethylene/propylene/butadiene feedstocks consumption.
The primary feedstocks used to produce ethylene, propylene, and butadiene,
are natural gas liquids (NGLs) (ethane, propane, butane) and petrochemical
feedstocks (gas oil, naphtha) [6]. Biomass can be a potential raw material
source, although it is assumed that there will be no-biomass-based capacity
over the projection period because of economic barriers. The type of feedstock
not only determines the feedstocks usage but also the energy for heat and
power requirements to produce the chemicals. The main approach used to
forecast the shares of ethylene, propylene and butadiene feedstocks is
the use of linear regression equations relating the feedstock shares with
oil prices and gas prices. Naphthas and gas oils are oil products and ethane,
propane and butane are natural gas liquids. Thus, the relative values of
natural gas and oil prices are key drivers for the choice between using
oil-based feedstocks and gas-based ones.
Energy Consumption Component
This component calculates the energy requirements (machine drive, non-machine
drive electricity, direct process heat, feedstocks, steam) for each chemical/chemical
group in Table 6.5. Unit energy (steam, fuel, electricity) requirements
for each of the 14 energy services listed above are assumed to change as
energy prices change. The calculated total steam consumption is passed
to the BSC Component.
Buildings Component
The total buildings energy demand by industry for each region is a function
of regional industrial employment and output. Building energy consumption
was estimated for building lighting, HVAC (heating,ventilation, and air
conditioning), facility support, and onsite transportation. Space heating
was further divided to estimate the amount provided by direct combustion
of fossil fuels and that provided by steam (Table 6.7). Energy consumption
in the BLD Component for an industry is estimated based on regional employment
and output
growth for that industry using the 2002 MECS as a basis.
Boiler/Steam/Combined Heat and Power Component
The steam demand and byproducts from the PA and BLD Components are passed
to the BSC Component, which applies a heat rate and a fuel share equation
(Table 6.8) to the boiler steam requirements to compute the required energy
consumption.
The boiler fuel shares apply only to the fuels that are used in boilers
for steam-only applications. Fuel shares for the portion of the steam demand
associated with combined heat and power (CHP) is assumed fixed. Some fuel
switching for the remainder of the boiler fuel use is assumed and is calculated
with a logit sharing equation where fuels shares are a function of fuel
prices. The equation is calibrated to 2002 so that the 2002 fuel shares
are produced for the relative prices that prevailed in 2002.
The byproduct fuels, production of which are estimated in the PA Component,
are assumed to be consumed without regard to price, independent of purchased
fuels. The boiler fuel share equations and calculations are based on
the 2002 MECS.
Combined Heat and Power
CHP plants, which are designed to produce both electricity and useful heat,
have been used in the industrial sector for many years. The CHP estimates
in the module are based on the assumption that the historical relationship
between industrial steam demand and CHP will continue in the future, and
that the rate of additional CHP penetration will depend on the economics
of retrofitting CHP plants to replace steam generated from existing non-CHP
boilers. The technical potential for CHP is primarily based on supplying
thermal requirements. Capacity additions are then determined by the interaction
of payback periods CHP retrofit investment, and market penetration rates
for investments with given payback periods. Assumed installed costs for
the CHP systems are given in Table 6.9.
Legislation and Regulations
Energy Improvement and Extension Act of 2008
Under EIEA2008 Title I, “Energy Production Incentives,” Section 103 provides
an Investment Tax Credit (ITC) for qualifying Combined Heat and Power (CHP)
systems placed in service before January 1, 2017. Systems with up to 15
megawatts of electrical capacity qualify for an ITC up to 10 percent of
the installed cost. For systems between 15 and 50 megawatts, the percentage
tax credit declines linearly with the capacity, from 10 percent to 3 percent.
To qualify, systems must exceed 60-percent fuel efficiency, with a minimum
of 20 percent each for useful thermal and electrical energy produced. The
provision was modeled in AEO2010 by adjusting the assumed capital cost
of industrial CHP systems to reflect the applicable credit.
The Energy Independence and Security Act of 2007
Under EISA2007, the motor efficiency standards established under the Energy
Policy Act of 1992 (EPACT) are superseded for purchases made after 2011.
Section 313 of EISA2007 increases or creates minimum efficiency standards
for newly manufactured, general purpose electric motors. The efficiency
standards are raised for general purpose, integral-horsepower induction
motors with the exception of fire pump motors. Minimum standards were
created for seven types of poly-phase, integral-horsepower induction motors
and NEMA design “B” motors (201-500 horsepower) that were not previously
covered by EPACT standards. The industrial module’s motor efficiency assumptions
reflect the EISA2007 efficiency standards for new motors added after 2011.
Energy Policy Act of 1992 (EPACT)
EPACT contains several implications for the industrial module. These implications
concern efficiency standards for boilers, furnaces, and electric motors.
The industrial module uses heat rates of 1.25 (80 percent efficiency) and
1.22 (82 percent efficiency) for gas and oil burners, respectively. These
efficiencies meet the EPACT standards. EPACT mandates minimum efficiencies
for all motors up to 200 horsepower purchased after 1998. The choices
offered in the motor efficiency assumptions are all at least as efficient
as the EPACT minimums.
Clean Air Act Amendments of 1990 (CAAA90)
The CAAA90 contains numerous provisions that affect industrial facilities.
Three major categories of such provisions are as follows: process emissions,
emissions related to hazardous or toxic substances, and SO2
emissions.
Process emissions requirements were specified for numerous industries and/or
activities (40 CFR 60). Similarly, 40 CFR 63 requires limitations on almost
200 specific hazardous or toxic substances. These specific requirements
are not explicitly represented in the NEMS industrial model because they
are not directly related to energy consumption projections.
Section 406 of the CAAA90 requires the Environmental Protection Agency
(EPA) to regulate industrial SO2 emissions at such time that total industrial
SO2 emissions exceed 5.6 million tons per year (42 USC 7651). Since industrial
coal use, the main source of SO2 emissions, has been declining, EPA does
not anticipate that specific industrial SO2 regulations will be required
(Environmental Protection Agency, National Air Pollutant Emission Trends:
1990-1998, EPA-454/R-00-002, March 2000, Chapter 4). Further, since industrial
coal use is not projected to increase, the industrial cap is not expected
be a factor in industrial energy consumption projections. (Emissions due
to coal-to-liquids CHP plants are included with the electric power sector
because they are subject to the separate emission limits of large electricity
generating plants.)
Industrial Alternative Cases
Technology Cases
The high technology case assumes earlier availability, lower costs, and
higher efficiency by more advanced equipment, based on engineering judgments
and research compiled by Focis Associates in a 2005 study for EIA (Tables
6.3 and 6.9). [7] The high technology case also assumes that the rate
at which biomass byproducts will be recovered from industrial processes
increases from 0.1 percent per year to 0.7 percent per year. The availability
of additional biomass leads to an increase in biomass-based cogeneration.
Changes in aggregate energy intensity can result both from changing equipment
and production efficiency and from changes in the composition of industrial
output. Since the composition of industrial output remains the same as
in the reference case, delivered energy intensity declines by 1.4 percent
annually compared with the reference case, in which delivered energy intensity
is projected to decline 1.2 percent annually.
The 2010 technology case holds the energy efficiency of plant and equipment
constant at the 2010 level over the projection. Both technology cases
were run with only the Industrial Demand Module rather than as a fully
integrated NEMS run, (i.e., the other demand models and the supply
models of NEMS were not executed). Consequently, no potential feedback
effects from energy market interactions were captured.
AEO2010 also includes an integrated high technology case, which
combines the high technology case of the four end-use demand sectors, the
electricity low fossil technology case, the low nuclear cost case, and
the low renewable technology case.
The low renewable technology case assumes that the rate at which biomass
byproducts will be recovered from industrial processes increases from 0.1 percent per year to 1.4 percent per year. The availability of additional biomass leads to an increase in biomass-based CHP.
Industrial Tables 
Industrial Demand Module Notes |