Due to the high contribution of buildings system design decisions to both long term energy consumption and associated greenhouse gas emissions, reducing building energy use is a key path to decrease buildings’ environmental footprint. The purpose of this study is to use an optimization approach to alternative design options, seeking designs that reduce the energy consumption, reduce the environmental impact from material selection, as well as decrease the construction and maintenance costs as early as possible in the design process.
In the current study, a multi-objective optimization model, using the Harmony Search (HS) algorithm, is in development to identify how to best combine design variables, to create a solution that will improve building energy efficiency while also decreasing the life cycle costs. This model considers multiple building envelope materials as design input variables to identify optimum design scenarios with the lowest environmental emissions and life cycle costs.
For more information on this research, please reach out to Ehsan Mostavi (email@example.com) or Dr. Somayeh Asadi (firstname.lastname@example.org).
Indoor environments should meet the needs of the occupants and enhance their comfort, health and productivity. Efforts to reduce energy consumption often lead to decreased satisfaction for building occupants. These modifications to the environment often cause occupants to change their behavior to improve their personal comfort, often resulting in additional energy use and often cancelling any intended energy improvements.
This study examines how occupant behavior can be more accurately predicted based upon demographics and comfort profiles. Surveys and continuous energy monitoring results provide an in-depth understanding of the indoor environment preferences of the occupants and their energy consumption habits. The data are collected for two case study buildings in Pennsylvania, and two in Doha, Qatar and will be modeled into a machine learning algorithm to forecast occupant comfort desires ad behaviors in a space. A simulation platform is being developed that can accept occupant behavior and preferences as inputs and produce corresponding energy consumption behavior data to help better forecast the user impacts for different design decisions.
For more information on this research please reach out to Yewande Abraham (YSA104@psu.edu) or Dr. Somayeh Asadi (email@example.com) and Dr. Chimay Anumba (Anumba@engr.psu.edu).