Modeling Energy Consumption in the Defense Logistics Agency

Abstract

The Defense Logistics Agency (DLA) Office of Installation Services and Environmental Protection was tasked with developing goals for energy consumption at each of the DLA-managed facilities. These goals could be based on factors which are beyond the control of the organization and can vary from month to month, such as weather conditions and workload. This report presents the results of an analysis that mathematically modeled energy consumption and then attempted to use these models to assist in setting consumption goals for the agency. The DLA facilities identified the factors which they considered to be predictors of energy consumption. Three years of monthly data were submitted for each factor. The data were screened to identify possible problems and to determine which factors had some relationship with energy consumption. Regression models were developed to predict total consumption, electric consumption, and non-electric consumption at each location. These models showed a definite relationship between weather and workload factors and energy consumption. However, the models were not accurate enough to be used to set consumption goals in DLA due to the impact of extraneous factors that were not quantifiable. Goals for energy consumption should be flexible to allow changes when unusual weather or workload conditions exist. However, these goals cannot be derived through a precise mathematical formula given the existing detail of available data.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1988
Accession Number
ADA196434

Entities

People

  • Jeffrey J. Hobson

Organizations

  • Defense Logistics Agency

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Classification
  • Correlation Analysis
  • Economic Analysis
  • Electric Energy Consumption
  • Energy Conservation
  • Energy Consumption
  • Energy Management
  • Environmental Protection
  • Inclusions
  • Logistics
  • Operations Research
  • Organizational Structure
  • Regression Analysis
  • Security
  • Test And Evaluation
  • Workload

Readers

  • Computational Modeling and Simulation
  • Energy Conservation and Renewable Energy Engineering.
  • Logistics and Supply Chain Management.