Skip to main content

Introduction

  • In total, 3.9% of global greenhouse gas emissions and 10% of global electricity usage overall originate from air conditioning systems
  • According to a report by the International Energy Agency (IEA), targeting specific inefficiencies of air conditioning systems is paramount to reducing the total energy consumption of buildings, since air conditioning contributes to 20% of office building electricity use.
  • Woods et al. discusses the impact of humidity on the energy wasted and emissions produced by air conditioning systems
    • Managing humidity in the building environment is as important as controlling temperature
    • Appropriate control of both is necessary to minimize excess use of energy and refrigerant materials for air conditioning and reduce costs of HVAC systems to improve accessibility

The demand1 on these HVAC systems is decided by electrical controllers2 for commercial buildings.

We aim to implement methods to optimize HVAC Controllers to work in a way which maximizes energy savings and maintains occupant comfort.

Research Question​

What are the energy and cost savings associated with alternative methods of preprocessing demand handling3 in the controller for HVAC systems?

Objective​

Our goal is to create a comparative tool to analyze the costs associated with demand preprocessing in the controllers for HVAC systems. We plan on using EWMA-based4 filtering of the setpoint curve and frequency-based filtering to account for the response time and reduce energy wastes regarding unrealistic setpoint expectations.

Hypothesis​

We hypothesize that using a lower frequency of demand curve signal {i.e. one with a dead time5 of 2*typical} and a midway value for EWMA filtration (0.9 weighting of the previous value) will lead to the scenario that optimizes for occupancy comfort while also consuming less energy than the standard values {EWMA=1, demand curve has been filtered to have the period be equivalent to that of our dead time}.

Footnotes​

  1. Demand: The values that the building manager sets the setpoints at for certain times
  2. Controllers: The specific equipment in a HVAC system that activates different functions of a HVAC system based on inputs.
  3. Preprocessing Demand Handling: Filtering that occurs on the demand signal in order to minimize energy consumption for the controller to meet the setpoints.
  4. EWMA: Exponential Weighted Moving Average.
  5. Dead Time: The amount of time between setting a specific function, and the response given by the HVAC system.