It has been estimated that the buildings contribute close to 20-30% of energy use in the United States at an annual cost of over $100B. Additionally, buildings also contribute an estimated 35-40% of all US CO2 emissions. There can be a substantial environmental and economic impact if there are efforts to decrease building energy consumption. The complexity of building energy consumption is not to be taken for granted.
Efforts to improve energy conservation and efficiency in buildings often involve simulating or analyzing specific physical systems. For example, designers may study the potential savings of using light-colored paint on a building’s roof, switching to high-efficiency fluorescent lights, or applying light-colored paint to the roof. The complex interaction between the environment and building systems makes it difficult to do accurate estimations.
When occupant behavior is included, the complexity of this problem also increases dramatically. Let’s understand this with a hypothetical example: a building consumes $1M per year in electricity for lighting. Analysis might show that, given current use patterns, installing high-efficiency lighting would cost $1M and result in 50% electricity savings which are $500,000 per year.
It would lead to break-even in two years. However, imagine that the building owner invests in a campaign to increase awareness, leading to a 25% reduction in the amount of electricity used by the occupants, or an annual electricity cost of $750,000. The same high-efficiency lighting would now only save $375,000 per year. It would now take nearly three years to reach break-even.
Even more complex interactions take place when you start considering all building systems-like appliances, data networks, usage patterns, and other aspects of occupant behavior that impact usage and demand patterns.
For example, improving climate control might encourage occupants to spend more time inside the building which will further lead to an increase in energy consumption. This phenomenon is also defined as the rebound effect.
This kind of emergent behavior is a sign of complex systems. The overall behaviour of such complex systems is determined in sometimes unpredictable ways by the elements of the system interacting with one another and with the environment.
There are numerous examples of human-made complex systems all around you, like stock market fluctuations, traffic jams, etc.
What is ABS?
Traditional analytical techniques are not well-equipped to manage complex systems as the behavior of such systems often exhibits sharp nonlinearities such as tipping points. In recent years, commercial entities such as Icosystem, as well as researchers at academic centres such as the Santa Fe Institute, have successfully studied as well as managed complex systems using Agent-Based Simulation (ABS).
How Does It Capture the Behavior of Systems?
It is a simulation technique that captures the behavior of systems from the bottom up. Initially, ABS was studied primarily in academic settings, whereas recently it has been used to solve a variety of complex business technology and business problems in many problem areas and industry sectors. The work of ABS also explains the complexity of building energy consumption.