eptk: energy prediction toolkit

Building energy use prediction plays a crucial role in whole building energy management. In recent years, with the advent of advanced metering infrastructures that generate sub-hourly energy meter readings, data-driven energy prediction models have been implemented by leveraging advanced machine learning algorithms. However, the lack of standardization of model development and evaluation tools hinders the advancement and proliferation of data-driven energy prediction techniques on a large scale. This paper presents eptk, an open-source toolkit that enables the seamless development of data-driven energy prediction models. The proposed toolkit helps researchers and practitioners to easily benchmark the existing and new data-driven models on various open-source datasets containing time-series of multiple energy meter data along with relevant metadata. Using the toolkit, we develop and compare the performance of 34 models on two large datasets containing more than 3,000 smart meter readings. eptk will be released in open-source for community use.