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Showing posts with the label EnergyPlus

Comparative Thermal Performance of Advanced Insulation Materials and Hybrid Wall Systems in Cold-Climate Buildings

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Improving building envelope performance is a critical strategy for reducing heating energy demand and enhancing indoor thermal comfort in cold climates. This study evaluates the thermal effectiveness of four advanced insulation materials—phase change materials (PCM), aerogel, vacuum insulated panels (VIP), and autoclaved aerated concrete (AAC)—through dynamic energy simulations. Using 24 years of hourly climate data, five wall configurations were analyzed, including an uninsulated reference case. The research focuses on annual heating demand, surface temperature stability, thermal time lag, and comfort hours to determine how different material properties contribute to energy efficiency and occupant comfort. Methodological Framework and Simulation Approach The investigation employed dynamic building energy modeling using EnergyPlus, incorporating long-term hourly climate data to ensure robust performance assessment. PCM behavior was simulated through an enthalpy–temperature phase ch...

Imputing Missing U-Values for Reliable Building Energy Modelling and Retrofit Planning

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Accurate thermal transmittance (U-value) information for building envelopes is fundamental to energy performance modelling, retrofit prioritization, and large-scale decarbonization strategies. However, incomplete datasets particularly missing U-values in existing building stock records—pose a major obstacle to evidence-based decision-making. This study addresses this challenge by systematically evaluating data imputation methods to enhance the reliability and usability of large building energy datasets. Challenges of Missing Envelope Performance Data In many national and municipal building databases, U-values are frequently absent due to inconsistent data collection, legacy construction records, or reporting gaps. Such missing values undermine the accuracy of energy simulations and retrofit impact assessments, leading to uncertainty in policy planning and investment decisions. Addressing these gaps requires imputation methods that balance accuracy, robustness, and computational effi...