EDF, the European energy giant, has released a “real-time energy dashboard” for the 2012 Olympic Park that displays energy interval data and other relevant inputs, such as weather and competition hours. This sort of data provides a terrific lens on building operations, so we decided to engage in a little Olympic competition of our own: how much savings can we spot on the main meter of London’s shiny new (and ostensibly energy-efficient) sporting venues?
Interval data from the Basketball Arena shows a change in midnight to 6am load starting July 19th
The accompanying graph is from the Basketball Arena. The bold line on the graph shows the energy use every 30 minutes over the course of several days. Tuesday, July 17 follows a typical pattern: demand begins to build at 6am, climbs steadily until the late afternoon, drops sharply at 5pm, and then hovers at a lower but elevated level until midnight. Finally, at midnight, the building drops to baseload, its lowest level of energy use, and remains there until the cycle repeats the next day.
At Gridium, we look carefully at baseload, because a building’s off-hours behavior often reveals opportunities for big savings. This is a bit counterintuitive – you might expect to go hunting for savings during periods of peak demand. But typical buildings are only occupied for about 50 hours per week. During the other other 118 hours, energy use adds up.
For the Basketball Arena, check out the night beginning on Thursday, July 19. Demand drops at 5pm as usual, but it remains elevated all night long, never touching baseload. In fact, it never reaches baseload again, remaining elevated through the next several days.
The costs are significant. Each night of elevated use represents an extra 1,000 kWh. At standard retail rates, this translates to over $72,232 per year. That’s 105 tons of carbon emissions added to the tally for an event that aspires to lighten its environmental impact.
Of course, the off-hours use might be occurring for a reason. Perhaps athletes are practicing into the wee hours. Perhaps final construction is on a 24-hour schedule. Perhaps preparations are being made for a special event. Or maybe this is just an all-too-familiar lapse and potential savings opportunity.
Interval data can’t tell you everything about how a building is run, but as this example shows, it can usefully highlight areas that bear further investigation. We don’t know yet what happened on Thursday night, but at least we now have the data to ask the question.
