We all know that not everyone uses energy the same way. Some of us shut off all the lights when we leave in the morning until we get home at 6 p.m., others crank up the AC in the mid-afternoon. But, how does a utility go about uncovering these kinds of patterns for hundreds of thousands or millions of customers?
It starts with data of course. By combining detailed energy data along multiple dimensions — such as time, geography, and weather — you can then tease out key similarities and differences among types of energy users.