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Daylighting Strategies for U.S. Air Force Office Facilities: Economic Analysis of Building Energy Performance and Life-Cycle Cost Modeling With Monte

by Sang M. Lee
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Current price ₹1,579.00
Original price ₹1,765.00
Original price ₹1,765.00
Original price ₹1,765.00
(-11%)
₹1,579.00
Current price ₹1,579.00

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Book cover type: Paperback
  • ISBN13: 9781286862292
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Biblioscholar
  • Publisher Imprint: Biblioscholar
  • Publication Date:
  • Pages: 160
  • Original Price: GBP 13.95
  • Language: English
  • Edition: N/A
  • Item Weight: 232 grams
  • BISAC Subject(s): General

The U.S. federal government maintains more than 500,000 facilities in the United States and around the world, most of which are heavily dependent on fossil fuels to produce electricity. Within the federal government, the Department of Defense (DOD) spends over $2.5 billion per year on facility energy consumption which makes them the largest single energy consumer in the United States. Therefore, federal energy conservation goals focus on aggressively reducing energy consumption by reducing the energy demand at the facility level within the next 20 years. Daylighting is a passive solar energy strategy at the facility level that leverages load avoidance by relying on windows and skylights to reduce building electrical lighting load; which accounts for approximately $15-23 billion annually in energy consumption. Our research findings show that electrochromic windows have the lowest energy consumption compared with other daylighting strategies appropriate for building retrofit. However, the prohibitive initial investment cost of electrochomic windows do not make them economically viable; therefore, the only daylighting strategy currently viable for Air Force facilities, based on our simulations, is the advanced daylighting control system. We found that economic incentive policies currently available for other passive solar technology could make emerging daylighitng technology, such as electrochromic windows, viable. Finally, we demonstrate the robustness of probabilistic life-cycle cost model using Monte Carlo simulation that could provide significantly more information compared to the current deterministic tool, BLCC 5, used for federal energy projects.

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