Before buying a new machine, find where the energy goes
Mira, a fictional building manager, sees a high energy bill and wants new equipment. Instead of choosing a machine from one number, she asks for the building assets and operations to be assessed.
Original fictional animation with synthetic English narration and English captions. The narration is not Ahmadreza Samadi’s recorded voice. The building and characters are illustrative; this film is not an engineering inspection or an energy audit.
Read the English film transcript
Mira manages a fictional apartment building. A winter energy bill arrives, much higher than usual. Her first thought is to replace the old heating unit. A bill can show cost and consumption. It cannot explain the cause by itself. A higher bill might reflect a
tariff change, not more energy. If use did rise, the cause could be the equipment, settings, schedules, air leaks, how the building is used, or the weather. That’s what an energy audit is for. It looks at the building’s equipment and how it’s operated, ideally
with a qualified assessor, before ranking what to do. The U.S. Department of Energy offers tools for this work. Its Audit Template is a web tool for collecting building and audit information, following an industry standard for energy audits. Its BuildingSync format gives audit data
a consistent structure, because data without a standard is harder to use and compare. In Mira’s building, the energy ribbons are traced room by room. One ribbon keeps running at night, when nobody is there. Consistent data comes first: the bills, the equipment list, and
an operations diary. Then inspection. Then a ranked list of possible measures. An audit identifies opportunities. It doesn’t make the changes, and it doesn’t guarantee savings. Weather, occupancy and operation can all change the results. Doing the work, and measuring what happened afterwards, are separate
steps. These are U.S. educational resources, not the rules where you live. Check what applies to your building. Before buying a new machine, follow four steps: data, diagnosis, decision, and then verification. Ahmadreza Samadi. More at a-samadi.com