Power Laws: Detecting Anomalies in Usage

Commercial buildings waste an estimated 15% to 30% of energy used due to poorly maintained, degraded, and improperly controlled equipment. Competitors built quick-response algorithms to find anomalies in energy use and elevate them for human attention and intervention. #energy

€26,000 in prizes
mar 2018
649 joined

Good news! Schneider Electric has made the training data for this competition available on their Data Exchange for ongoing use, practice and learning.

In order to access the data, you’ll first need to create an account on the Schneider Exchange. Then follow the link below to add the competition dataset to your Digital Library, where you’ll be able to freely access the data. These datasets are maintained by Schneider Electric and released at their discretion.


Dataset: Detecting anomalies in building energy usage


Please note that we won't be able to field questions about the data, but we wanted to share it here for the benefit of the community. If you have a question, feel free to post it to the forum.

For more details on the results and winners of the competition, including links to open source solutions, check out the results blog post.