New and Underutilized Refrigeration, Computer Power Management, and Vending Machine Technologies
The following refrigeration, computer power management, and vending machine technologies are underutilized within the Federal sector. These technologies have been identified by FEMP as the most promising for Federal agency deployment. Review each technology for potential facility energy savings.
Additional information is available by clicking on the individual technology, including technology application, key factors and considerations for deployment, and points of contact.
|Refrigeration Management Systems||Refrigeration management systems control temperatures within walk-in coolers and freezers.||Applicable in hospital, school, prison, housing, service, and other buildings with large kitchen facilities.||38|
|Computer Power Management||Network-based software that manages computer power consumption by automatically putting them in standby, hibernation, or other low energy consuming state without interfering with user productivity or IT functions.||Applicable in most building categories with high computer counts.||58|
|Vending Machine Occupancy Sensors||Device that detects when no people are in the vicinity and powers down beverage vending machines. Does not completely turn off compressor, but reduces run times.||Applicable in most building categories where vending machines are present.||51|
Ranking hinges on three major attributes derived from specific capabilities and qualities of that technology in the Federal marketplace. Each attribute is weighted and scored individually. The ultimate ranking score is a summation of scores and weightings of each attribute, such as:
Federal Impact (50% weighting): Combination of energy savings potential and applicability in the Federal market.
Cost Effectiveness (30% weighting): Relative cost of the implementation and average expected return typically reported in case studies as simple payback period.
Probability of Success (20% weighting): Combination of the qualitative characteristics scored separately and averaged to determine probability of success. Criteria include strength of supply chain, knowledge base, implementation difficulty, and customer acceptance.