Araştırma Makalesi

Electricity load forecasting plays a key role for

utility companies. Short-term and medium-term electricity load forecasting

processes allow the utility companies to retain reliable operation and high

energy efficiency. On the other hand, long-term electricity load forecasting

allows the utility companies to minimize the risks. Long-term forecasting also

helps the utility companies to plan and make feasible decisions in regard to

generation and transmission investments. Since there are commercial and technical

implications of electricity load forecasting, the accuracy of the electricity

forecasting is important not only to the utility companies but also to the

consumers. In this paper, we carry out a performance evaluation study to

evaluate the accuracy of different classification approaches for electricity

load forecasting. As shown with the results of the performance evaluation

study, some of the investigated approaches can successfully achieve high

accuracy rates and therefore can be used for short-, mid-, or long-term

electricity load forecasting.

Load-Forecasting plan Artificial neural networks Regression analysis Support vector machine Prediction techniques

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Yıl 2018,
Sayı: 2, 233 - 238, 19.08.2018
### Öz

### Kaynakça

Toplam 1 adet kaynakça vardır.

Birincil Dil | İngilizce |
---|---|

Konular | Mühendislik |

Bölüm | Makaleler |

Yazarlar | |

Yayımlanma Tarihi | 19 Ağustos 2018 |

Yayımlandığı Sayı | Yıl 2018Sayı: 2 |