Manual Vs. Automated Window Blinds: Analysis of Energy Use Based on Climate Scenarios
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Niknia, Sepideh
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Abstract
Windows in buildings impact energy usage for temperature control through solar heat gain and enable natural light to reduce reliance on artificial lighting. Balancing solar heat gain and daylight utilization is a challenge, which can be addressed by employing automated or manual blind systems to manage daylight and enhance user comfort and energy efficiency. Additionally, accurate weather forecasts are essential for predicting energy-efficient strategies through individual building energy simulations, as weather conditions synergistically interact with occupant behavior to influence energy consumption patterns. This research aims to assess the energy consumption associated with manual and automated internal window blinds in medium-sized office buildings situated within two distinct and significant climate zones in the United States, considering both present and future climate change scenarios based on the IPCC report (RCP 4.5 - 8.5). Employing a simulation-based methodology, the study unveiled varying effectiveness levels of diverse window blind configurations contingent on the specific climate zones (e.g., 4A Mixed-Humid, 2B Hot-Dry). In different climate zones, on-site energy consumption alterations for heating and cooling become evident as temperatures escalate in the forthcoming years. Using simulation as the method and comparing RCP 4.5 and 8.5 scenarios reveals that automated blinds—a more efficient choice than manual blinds—significantly reduces cooling energy consumption, particularly under RCP 8.5 in a 4A Mixed-Humid zone. Rising temperatures in Climate Zone 2B Hot-Dry are a factor in increased energy requirements for cooling and decreased energy requirements for heating due to climate change. This study provides enlightening insights into the potential benefits of diverse window-covering strategies concerning energy conservation within varied climatic contexts for the future.
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2025-03
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