petolau / clusterforecast

Clustering-based Forecasting Method for Individual End-consumer Electricity Consumption Using Smart Grid Data

ClusterForecast

The source code for the papers:

• "New Clustering-based Forecasting Method for Disaggregated End-consumer Electricity Load Using Smart Grid Data";

• "Clustering-based forecasting method for individual consumers electricity load using time series representations".

Citations:

• P. Laurinec and M. Lucká, "New clustering-based forecasting method for disaggregated end-consumer electricity load using smart grid data," 2017 IEEE 14th International Scientific Conference on Informatics, Poprad, Slovakia, 2017, pp. 210-215. doi: 10.1109/INFORMATICS.2017.8327248. Link for .pdf here.

• P. Laurinec and M. Lucká, "Clustering-based forecasting method for individual consumers electricity load using time series representations" Open Computer Science, 8(1), (2018): pp. 38-50. Retrieved 31 Jul. 2018, from doi: 10.1515/comp-2018-0006. Link for .pdf here.

The implementation of time series representation methods used in experiments is in the R package TSrepr.

You can read more about my research here: petolau.github.io/research/.