Published April 21, 2021 | Version v1
Dataset Open

Supplementary Material for "Probabilistic Day-ahead Inertia Forecasting"

  • 1. Imperial College London
  • 2. University of Strathclyde

Description

This data set is supplementary material for the paper 'Probabilistic Day-ahead Inertia Forecasting' by Evelyn Heylen, Jethro Browell and Fei Teng. Future releases are subject to change following revisions of this article.

This dataset contains data of the Great Britain power system of 2016 - 2018. More specifically, data are included related to demand (day-ahead forecast and out-turn), generation by different generator types, interconnection flows, day-ahead electricity price, wind and solar generation (day-ahead forecasts and out-turn) and estimated inertial energy from transmission-connected synchronous generator units. The resolution of the data is 30 minutes.

 

Notes

The research of Evelyn Heylen and Fei Teng has received funding from Network Innovation Allowance under reference NIA_NGSO0020.

Files

GB_data_2016_2018.csv

Files (32.6 MB)

Name Size Download all
md5:eaad9887deedb6ebe7931a83ea719af5
32.6 MB Preview Download
md5:39446c15f99f144bea95a1028b8173e6
8.3 kB Preview Download

Additional details

Funding

UK Research and Innovation
System-wide Probabilistic Energy Forecasting EP/R023484/1