Optimized passive heating for multi-family dwellings

Abstract

A significant contributing factor to the high amount of electricity consumption are the heating, ventilation, and air conditioning (HVAC) systems used to maintain buildings at comfortable temperatures. Although many advancements have been made in the HVAC industry to decrease the electricity consumed by these systems, these advancements have focused primarily on increasing the efficiency of the active, mechanical heating systems to include space heaters, baseboard heaters, or electric boiler systems. Non-mechanical, passive methods of increasing energy efficiency, such as the creation of highly insulated walls and roofs, have been used but often involve implementation during the construction phase of a building and are difficult to implement in pre-existing infrastructure. Additionally, studies on the utilization of natural heating and cooling resource elements, such as solar heating, night cooling, seasonal weather patterns and other passive solutions have had little research, despite the possibility of being effective at providing the desired internal conditions with minimal electricity expenditure.

In 2019, approximately 4 trillion kilowatt-hours of electricity was generated in the United States alone, with over half of this electricity generated from the burning of fossil fuels. In addition to being a finite resource, the burning of fossil fuels contributes to the addition of harmful amounts of greenhouse gas (GHG) emissions in the atmosphere. Unfortunately, the demand for energy is continually increasing and consequently the demand for electricity. This increase in electricty production leads to an ever increasing amount of GHG emissions. Although it is difficult to eliminate the demand for energy entirely, in an effort to decrease the total GHG emissions, researchers have conducted studies to help reduce the world's energy consumption.

The goal of this thesis is to introduce a method of decreasing heating load of HVAC systems in a single-dwelling model of a multi-family building, by controlling movable insulation through the optimization of flux, time, surface incident solar radiation, and temperature thresholds. This thesis contributes to the current state of the art by 1) demonstrating that optimization of the threshold control parameters of flux, time, surface incident solar radiation and temperature can lead to a significant decrease in total heating energy expenditure and 2) introducing a co-simulation method to use MATLAB, in conjunction with EnergyPlus, as an optimization tool to find optimal control thresholds.