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Short-Term Energy Outlook

Natural Gas Model Description


Contents

Related Natural Gas Model Documentation


Introduction

The Energy Information Administration (EIA) of the U.S. Energy Department (DOE) developed the Short-Term Integrated Forecasting (STIFS) model to generate short-term (up to 24 months), monthly forecasts of U.S. supplies, demands, imports, stocks, and prices of various forms of energy. The purpose of this report is to define the natural gas model in STIFS and describe its basic properties. This report documents the May 1999 version of the natural gas model equations in STIFS.

This report is written for persons who want to know how short-term energy markets forecasts are produced by EIA. The report is intended as a reference document for model analysts, users, and the public.


Overview


Natural Gas Demand

In STIFS, natural gas demand is calculated for six sectors, including four major consumption or end-use categories as well as estimated consumption of natural gas by pipelines and natural gas consumption by gas field and natural gas plant operations. In addition, a small amount of gas exports is accounted for. Weather (particularly in the residential and commercial sectors), household formation (residential sector), commercial employment (commercial sector), natural gas prices relative to competing fuel prices, and industrial output (industrial sector) are all important factors in the short-term determination of natural gas demand. In the electric utility sector, gas demand is affected by the level of overall electricity output, which is determined primarily by various factors affecting electricity demand, as well as the availability of hydroelectric and nuclear power, and the price of gas relative to other fuels. Some longer term factors, such as gradually improving energy efficiency of residential and commercial buildings and of industrial processes, ongoing penetration of high-efficiency gas appliances, and demographic trends, may marginally influence the aggregate gas intensity (that is consumption per customer or per unit of output) and thus aggregate gas consumption in the short term. These longer term factors, if apparent, are generally captured by the inclusion of time trends in the equations for gas demand. All gas demand relationships are estimated based on monthly data, with demand data being expressed in terms of consumption per day, to correct for varying days in months.

For some of the natural gas demand categories used in STIFS (as is also true for similar categories in the electricity model), reported monthly sales are not strictly the same as demand in the month that they are reported. This is because reported sales are on a billing-cycle basis, which generally records monthly electricity actually used by customers in part of the current month and part of the previous month. The current version of STIFS models natural gas demand on an 'as-reported' basis, but includes lagged as well as current values for some key determinants (particularly weather) to compensate for the billing lag problem.

Because of quantity constraints on certain natural gas supply variables (described below), temporary variables (usually identified with either an "X" or "Z" as the last character in the variable name) are calculated for some of the natural gas demand quantities until STIFS checks for whether or not initially calculated demand is within assumed deliverability limits. If initially calculated demand exceeds the supply constraints, demand cutbacks may automatically be enforced (in the electric utility and industrial sectors only), unless accommodating changes in inventory patterns or higher price trajectories (or both) are instituted. The STIFS model automatically calculates final demand and supply quantities that may be equal to or less than quantities initially calculated.

Residential sector natural gas demand per household per day (NGRCPUSX) is modeled as a function of general seasonal factors (using monthly dummy variables) and weather, as measured by gas customer-weighted heating degree-days (ZGHDPUS), expressed as deviations from "normal." Normal gas-weighted heating degree-days for any month (ZGHNPUS) are defined by the National Oceanographic and Atmospheric Administration (NOAA) as the average of the thirty observations on heating degree-days recorded for that month between 1961 and 1990. Current and (one-period) lagged degree-days are included in the equation to account for the billing lag problem (i.e. that some of the current-period reported sales relate to consumption generated last period). The heating degree-days variable is restricted to have non-zero effects only during the heating season (October to April).

Residential natural gas demand per customer per day:

NGRCPUSX = NGRC_01
+ NGRC_HD * [(ZGHDPUS-ZGHNPUS)/ZSAJQUS] * (OCT+NOV+DEC+JAN+FEB+MAR+APR)
+ NGRC_HD1 * LAG[((ZGHDPUS-ZGHNPUS)/ZSAJQUS) * (OCT+NOV+DEC+JAN+FEB+MAR+APR)]
+ monthly dummy variables

[Click here for Regression Results]

As-reported residential gas consumption per day:

NGRCPUS = NGRCPUSX * KQHMPUS

Where,
KQHMPUS = Housing stocks, millions
NGRCPUSX = Residential natural gas demand per household per day
NGRCPUS = As-reported total residential natural gas demand per day
ZGHDPUS = Gas-weighted heating degree-days
ZGHNPUS = Normal gas-weighted heating degree-days
 
 
A similar structure is used for commercial demand. Whereas it would be preferable to use commercial demand per unit of output in the commercial sector as the dependent variable, the unavailability of consistent estimates of commercial output has led to the adoption of commercial employment as a normalizing factor for the equation. Also, population-weighted degree-days are used in the commercial sector equation since the gas-weighted variable relates specifically to house heating.
 

Commercial natural gas demand per commercial employee per day:

NGCCPUSX = NGCC_01
+ NGCC_HD * [(ZWHDPUS-ZWHNPUS)/ZSAJQUS] * (OCT+NOV+DEC+JAN+FEB+MAR+APR)
+ NGCC_HD1 * LAG[((ZWHDPUS-ZWHNPUS)/ZSAJQUS) * (OCT+NOV+DEC+JAN+FEB+MAR+APR)]
+ NGCC_D2 * D8912
+ monthly dummy variables

[Click here for Regression Results]

As-reported commercial gas consumption per day:

NGCCPUS = NGCCPUSX * EMCMPUS

Where,
D8912 = Dummy intercept variable for December 1989
EMCMPUS = commercial employment (millions)
NGCCPUSX = Commercial natural gas consumption per customer per day
NGCCPUS = As-reported total commercial natural gas demand per day
ZWHDPUS = Population weighted heating degree-days
ZWHNPUS = Normal population weighted heating degree-days

The demand for natural gas in the industrial sector (NGINPUS) is modeled as a function of gas-oriented industrial production, relative fuel prices and general seasonal factors. Due to the lack of a consistent measure of the industrial gas price, the gas price used in the industrial equation is the electric utility price. An estimate of gas consumption for electricity generation by non-utilities is also used a factor in the equation since much of the growth in measured industrial gas demand since the late 1980's has been from this source.

NGINPUSX = NGIN_01
+ NGIN_HDD * [(ZWHDPUS-ZWHNPUS)/ZSAJQUS] * (OCT+NOV+DEC+JAN+FEB+MAR+APR)
+ NGIN_P * [(NGEUDUS) / (RFEUDUS)]
+ NGIN_NU*NGNUPUS + NGIN_Q*QSIC
+ monthly dummy variables

[Click here for Regression Results]

Where,
NGINPUSX = Initial estimate for industrial gas consumption per day (billion cubic feet per day)
NGEUDUS = Natural gas price to electric utilities ($ per million Btu)
RFEUDUS = Residual fuel price to electric utilities ($ per million Btu)
NGNUPUS = Gas consumption for power generation by nonutilities
QSIC = Gas-weighted industrial production (Index)

The method for determining natural gas demand in the electric utility sector is shown in the description of the electricity model, but the balancing of total gas demand and supply quantities is described in the supply section below.

Two relatively minor categories of gas demand are gas used in oil and gas well field and lease operations (NGLPPUS) and pipeline fuel (NGACPUS). For lease and plant fuel, it is assumed that demand is a function of production and seasonal factors.

NGLPPUSX = NGLP_01
+ NGLP_D2 * D90ON
+ NGLP_LE * NGPRPUSX
+ monthly dummy variables

[Click here for Regression Results]

For pipeline fuel, it is assumed that fuel consumption is linearly related to pipeline throughput.

NGACPUSX = NGAC_01
+ NGAC_DM * (NGRCPUS + NGCCPUS + NGEUPUSX + NGINPUSX - BALITX)
+ monthly dummy variables

[Click here for Regression Results]

A small amount of natural gas exports (NGEXPUS) is expected, in amounts that have averaged between about 200 million and 500 million cubic feet per day since 1989.

NGEXPUS = NGEX_01
+ monthly dummy variables for APR and MAY

[Click here for Regression Results]

Initial calculations for total natural gas demand (NGTCPUSX) are made by adding up individual sectoral components:

NGICPUS = NGINPUS + NGLPPUS;

NGTCPUSX = NGACPUSX + NGLPPUSX + NGRCPUS + NGCCPUS + NGINPUSX + NGEUPUSX;


Natural Gas Supply

Domestic natural gas supply in STIFS encompasses aggregate production (including conventional dry natural gas (NGPRPUS) as well as supplemental gaseous fuels (NGSFPUS), imports (NGIMPUS) and inventory change. Inventories in this case refer to gas in underground storage (NGUSPUS).

In STIFS, the volume of natural gas supplied at any time is subject to certain constraints on the capacity of the domestic supply system to produce and deliver gas to markets. In particular, exogenous constraints on total domestic productive capacity and on total import capability are imposed so as to prevent production and imports from exceeding maximums calculated from detailed analysis outside of the STIFS system.(1) STIFS allows for excess demand to feed through automatically to price changes that will move the system toward an equilibrium, but a combination of involuntary cutbacks and significantly higher spot natural gas price trajectories may be required to prevent solutions in which demand exceeds available supply.

An initial estimate of gas storage (NGUSPUSX) is taken to be the normal level (NGUSPNM - a multi-year moving average) less a portion of the last period deviation from normal.

NGUSPUSX = NGUSPNM
+ NGUS_R1 * LAG(NGUSPUS - NGUSPNM)

[Click here for Regression Results]

A secondary estimate of gas storage (NGUSPUSY) is calculated as a residual, given demand, production, net imports, other supply and balancing item. The final gas storage estimate (NGUSPUS) splits the difference between NGUSPUSX and NGUSPUSY.

NGUSPUSY = LAG(NGUSPUS) - (NGTCPUSX - BALITX - NGPRPUSX - NGIMPUSX + NGEXPUS - NGSFPUS) * ZSAJQUS

NGUSPUS = NGUSPUSY + 0.5 * (NGUSPUSX - NGUSPUSY)

Net gas withdrawal (billion cubic feet per day) is given as:

NGNWPUS = [LAG(NGUSPUS) - NGUSPUS] / ZSAJQUS

A preliminary estimate of the balancing item (BALITX - usually a negative number on an annual basis) between as-reported demand and supply is:

BALITX = NGBL_01
+ monthly dummy variables

[Click here for Regression Results]

Currently, the final estimate for the balancing item is taken to be the difference between the demand levels and supply:

BALIT = NGTCPUS - NGPRPUS - NGNIPUS - NGNWPUS - NGSFPUS

Supplemental fuels natural gas supply (which includes supply from coal gasification plants) is assumed to be constant at average seasonal values.

NGSFPUS = NGSF_01
+ monthly dummy variables

[Click here for Regression Results]

Initial values of net imports are modeled as a function of time and seasonal factors

NGIMPUSX = NGIM_01
+ NGIM_T * TIME
+ monthly dummy variables

[Click here for Regression Results]

The following step calculates final gas net imports as the minimum of import capacity (NGIMMX) and notional gas imports share of residual supply requirements.

NGIMPUS = MIN(NGIMMX, NGIMPUSX);

NGNIPUS = NGIMPUS - NGEXPUS

Currently, dry gas (and wet gas) production is taken as exogenous from analysis done outside the STIFS model by EIA's Reserves and Natural Gas Division, Dallas Field Office.

The following steps calculate final demand levels for non-core gas sectors. Any reduction in demand due to binding productive capacity or import constraints, is distributed to the industrial, utility, transportation, and L&P sectors proportionately. The utility calculation is done in electricity module.

NGINPUS = NGINPUSX * [1 - (NGTCPUSX - NGTCPUS) /(NGINPUSX+NGEUPUSX+NGACPUSX+NGLPPUSX)]

NGACPUS = NGACPUSX * [1 - (NGTCPUSX - NGTCPUS) / (NGINPUSX+NGEUPUSX+NGACPUSX+NGLPPUSX)]

NGLPPUS = NGLPPUSX * [1 - (NGTCPUSX - NGTCPUS) / (NGINPUSX+NGEUPUSX+NGACPUSX+NGLPPUSX)]


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