### Abstract

Language | English |
---|---|

Title of host publication | Proceedings of European Control Conference (ECC), Aalborg, Denmark, Jun. 2016 |

Publisher | Institute of Electrical and Electronics Engineers |

Pages | 1123-1128 |

Number of pages | 6 |

ISBN (Electronic) | 978-1-5090-2591-6 |

DOIs | |

State | Published - Jun 2016 |

Event | 15th European Control Conference (ECC 2016) - Aalborg, Denmark Duration: 29 Jun 2016 → 1 Jul 2016 Conference number: 15 http://www.ecc16.eu/index.shtml http://www.ecc16.eu/index.shtml |

### Conference

Conference | 15th European Control Conference (ECC 2016) |
---|---|

Abbreviated title | ECC 2016 |

Country | Denmark |

City | Aalborg |

Period | 29/06/16 → 1/07/16 |

Internet address |

### Fingerprint

### Cite this

*Proceedings of European Control Conference (ECC), Aalborg, Denmark, Jun. 2016*(pp. 1123-1128). [Paper ThA8.1] Institute of Electrical and Electronics Engineers. DOI: 10.1109/ECC.2016.7810440

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*Proceedings of European Control Conference (ECC), Aalborg, Denmark, Jun. 2016.*, Paper ThA8.1, Institute of Electrical and Electronics Engineers, pp. 1123-1128, 15th European Control Conference (ECC 2016), Aalborg, Denmark, 29/06/16. DOI: 10.1109/ECC.2016.7810440

**Probabilistic short-term load forecasting with conditional mean-variance and quantile regression models.** / Bikcora, C.; Verheijen, L.; Weiland, S.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Probabilistic short-term load forecasting with conditional mean-variance and quantile regression models

AU - Bikcora,C.

AU - Verheijen,L.

AU - Weiland,S.

PY - 2016/6

Y1 - 2016/6

N2 - For the day-ahead density forecasting of electricity load, this paper proposes the combination of the autoregressive moving average (ARMA) model and the generalized autoregressive conditional heteroskedasticity (GARCH) model, with both of them admitting exogenous inputs. This composite structure on the conditional mean and variance is referred to as the ARMAX-GARCHX model. As an alternative to its estimation by means of log-likelihood maximization, approaches based on iterative least-squares (ILS) and nonlinear least-squares (NLS) are considered. Apart from the ARMAX-GARCHX model, quantile regression models (QRMs) are also tested in forecasting where a wide range of quantiles are separately modeled to approximate a density. Phase currents of several low voltage transformer cables from the Netherlands are forecasted to compare the performances, and as the probabilistic evaluation criterion, the continuous ranked probability score is used. As an outline of the results, the ARMAX-GARCHX model outperformed QRMs and among its estimation techniques, the likelihood-based approach had the best performance, though the differences in the errors are often minor. Thus, owing to its computational simplicity, the ILS solution can be a valuable option when processing large batches of data in practice.

AB - For the day-ahead density forecasting of electricity load, this paper proposes the combination of the autoregressive moving average (ARMA) model and the generalized autoregressive conditional heteroskedasticity (GARCH) model, with both of them admitting exogenous inputs. This composite structure on the conditional mean and variance is referred to as the ARMAX-GARCHX model. As an alternative to its estimation by means of log-likelihood maximization, approaches based on iterative least-squares (ILS) and nonlinear least-squares (NLS) are considered. Apart from the ARMAX-GARCHX model, quantile regression models (QRMs) are also tested in forecasting where a wide range of quantiles are separately modeled to approximate a density. Phase currents of several low voltage transformer cables from the Netherlands are forecasted to compare the performances, and as the probabilistic evaluation criterion, the continuous ranked probability score is used. As an outline of the results, the ARMAX-GARCHX model outperformed QRMs and among its estimation techniques, the likelihood-based approach had the best performance, though the differences in the errors are often minor. Thus, owing to its computational simplicity, the ILS solution can be a valuable option when processing large batches of data in practice.

U2 - 10.1109/ECC.2016.7810440

DO - 10.1109/ECC.2016.7810440

M3 - Conference contribution

SP - 1123

EP - 1128

BT - Proceedings of European Control Conference (ECC), Aalborg, Denmark, Jun. 2016

PB - Institute of Electrical and Electronics Engineers

ER -