Regression based process energy analysis system
The results of an investigation are presented to determine which weather, production, and time-related parameters exert significant influence on installation energy consumption for the U.S. Army Armament, Munitions and Chemical Command (AMCCOM) using regression analysis methods. Based on data gathered at AMCCOM HQ, potentially significant weather and production/mission parameters are identified, and Process Energy Analysis Systems are developed for each installation using regression analysis methods on a monthly data base for the period FY75 through FY82 (October 1974 through September 1982). The regression model for AMCCOM shows that aggregate energy consumption in general depends on heating degree-days, production level, and labor force strength. At individual installations, additional important parameters include cooling degree-days and facility changes over time. The model was applied to actual FY84 data and predicted total energy consumption to within 3% to 6% of actual consumption. Results of this effort will be used to forecast energy consumption and establish energy guidelines throughout AMCCOM.
- Research Organization:
- GARD, Niles, IL
- OSTI ID:
- 6999975
- Report Number(s):
- CONF-860106-
- Journal Information:
- ASHRAE Trans.; (United States), Journal Name: ASHRAE Trans.; (United States) Vol. 92:1A; ISSN ASHTA
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
290100 -- Energy Planning & Policy-- Energy Analysis & Modeling
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
320100* -- Energy Conservation
Consumption
& Utilization-- Buildings
COOLING LOAD
DATA BASE MANAGEMENT
EFFICIENCY
ENERGY ANALYSIS
FORECASTING
HEATING LOAD
MANAGEMENT
MATHEMATICS
MILITARY FACILITIES
MONTHLY VARIATIONS
NATIONAL ORGANIZATIONS
RECOMMENDATIONS
REGRESSION ANALYSIS
STATISTICS
THERMAL EFFICIENCY
TIME DEPENDENCE
US DOD
US ORGANIZATIONS
VARIATIONS
WEATHER