Optimizing complex heating sequences in mixed heating source campus buildings
A large post-secondary educational institution in Canada has a variety of heating and cooling systems on campus. The choice between their district heating and cooling plants and local systems on each building is complex and has to take into account several variables. Controls sequences need to efficiently decide when one heating or cooling source should be used vs. another, and when a mix of more than one energy source is justified.
These energy source decisions are typically made with complex sequences of operation in the Building Automation System (BAS). Inputs such as weather conditions, heating and cooling loads from buildings, and occupancy schedules all play a part in determining how the campus’ systems should be operated. CopperTree’s Kaizen software was used to analyze how the systems were performing given all these disparate inputs and recommend new, more efficient sequences of operations that will drastically reduce the amount of natural gas required to heat the campus’ 2 largest buildings. As part of the project, algorithms were added to Kaizen to calculate the efficiency and costs of both central and local building energy systems as they relate to outdoor air temperatures and buildings heating/cooling loads, determining the optimal mix of energy sources at any given time. Once armed with these calculations, CopperTree was able to work with the client to fine-tune the programming of their systems to harness the identified efficiencies.
CopperTree’s recommendations will help the campus reduce its energy consumption by approximately 2,400,000 kWh per year. The optimizations in energy consumption translate into large financial savings, but also a yearly reduction of over 1,700 metric tons of Carbon Dioxide (CO2) equivalent emissions, which is the amount of carbon that would be sequestered by growing 28,124 trees for 10 years from seedlings.
