STOFEAS: A Personal Computer Program for Estimating the Economic Feasibility of Storage Cooling Systems

Abstract

Utility companies often increase electric rates for hours associated with high demand. For Army installations, this high demand charge can increase electrical utility bills from 30 to 60 percent. Storage cooling systems (SCSs) have become an important tool in reducing on-peak electric demand by shifting electric power use to off-peak periods. Before implementing an SCS, an economic feasibility study must he done. This study developed STOFEAS, a personal computer (PC) program that helps estimate the economic feasibility of SCSs. STOFEAS offers the following advantages: (1) STOFEAS will run on any IBM PC or compatible with 640K RAM. (2) Most required economic parameters are built into STOFEAS as default input. However, users can incorporate local information into an input data file. (3) The program does an initial economic feasibility analysis of SCSs, and outputs payback periods, differential system first costs, and rough sizes of SCSs sized to shift 1 to 25 percent of the total peak electric demand. (4) STOFEAS does a preliminary feasibility analysis for new construction, replacement, or retrofit with SCSs. This analysis must be followed by a separate, detailed design of the selected SCS before beginning actual construction of an SCS. Storage cooling systems, Economic analysis, STOFEAS, Cost effectiveness

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1992
Accession Number
ADA266270

Entities

People

  • Chang W. Sohn
  • Jeong‐Han Kim

Organizations

  • Construction Engineering Research Laboratory

Tags

DTIC Thesaurus Topics

  • Application Software
  • Army Facilities
  • Computer Programs
  • Computers
  • Cost Models
  • Economic Analysis
  • Electric Power
  • Electricity
  • Energy Consumption
  • Energy Storage
  • Engineering
  • Feasibility Studies
  • Load Monitoring
  • Maintenance Costs
  • Peak Power
  • Personal Computers
  • Power

Readers

  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Energy Conservation and Renewable Energy Engineering.
  • Life Cycle Cost Analysis