NBEATS*: Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting

We presents an enhanced N-BEATS model, N-BEATS*, for improved mid-term electricity load forecasting (MTLF). Building on the strengths of the original N-BEATS architecture, which excels in handling complex time series data without requiring preprocessing or domain-specific knowledge, N-BEATS* introduces two key modifications. A novel loss function combining pinball loss based on MAPE with normalized MSE, the new loss function allows for a more balanced approach by capturing both L1 and L2 loss terms. A modified block architecture– the internal structure of the N-BEATS blocks is adjusted by introducing a destandardization component to harmonize the processing of different time series, leading to more efficient and less complex forecasting tasks. Evaluated on real-world monthly electric ity consumption data from 35 European countries, N-BEATS* demonstrates superior performance compared to its predecessor and other established fore casting methods, including statistical, machine learning, and hybrid models. N-BEATS* achieves the lowest MAPE and RMSE, while also exhibiting the lowest dispersion in forecast errors.

This repository provides an implementation of the NBEATS* algorithm introduced in [https://arxiv.org/pdf/2412.02722].

Model	MAPE/MedAPE/IQRAPE	SMAPE/MedSAPE/IQRSAPE	RMSE	MAE	MPE
ARIMA	5.65/3.32/5.24	5.19/3.27/5.17	463±875	409±890	-2.35±13.62
ETS	5.05/3.50/4.80	4.93/3.53/4.80	375±605	325±626	-1.04±7.97
k-NNw+ETS	4.47/2.71/3.52	4.27/2.72/3.53	328±535	270±560	-1.25±9.00
FNM+ETS	4.40/2.64/3.46	4.20/2.67/3.41	322±522	268±545	-1.26±8.80
N-WE+ETS	4.37/2.68/3.36	4.17/2.68/3.31	321±523	266±546	-1.26±8.68
GRNN+ETS	4.38/2.64/3.51	4.19/2.66/3.48	325±524	268±548	-1.26±8.61
MLP	5.27/2.97/3.84	4.98/2.99/3.75	379±668	307±695	-1.37±13.49
ANFIS	6.18/3.56/4.87	5.81/3.58/4.72	489±765	384±813	-2.51±12.63
LSTM	6.11/3.73/4.50	5.73/3.75/4.43	432±645	341±688	-3.12±11.79
ETS+RD-LSTM	4.48/2.74/3.55	4.23/2.71/3.54	347±624	287±646	-1.11±10.07
TFT	5.34/3.21/4.14	4.96/3.19/4.06	388±663	324±702	-3.09±10.72
iTransformer	5.17/3.09/4.09	4.85/3.08/4.02	416±735	335±769	-2.32±10.07
TCN	5.61/4.06/4.22	5.39/4.02/4.11	467±728	382±788	-2.61±8.57
BiTCN	4.54/2.88/3.59	4.29/2.86/3.54	334±578	283±597	-2.35±8.92
RMoK	4.95/2.96/3.70	4.58/2.94/3.62	371±626	301±655	-2.81±10.89
N-HiTS	4.63/2.97/3.72	4.42/2.95/3.66	355±581	298±605	-2.27±8.40
N-BEATS	3.78/2.55/3.30	3.74/2.55/3.27	310±506	256±528	-0.34±6.43
N-BEATS*	3.44/2.20/3.41	3.52/2.20/3.38	304±544	255±561	0.57±5.43

Citation

If you use this code in any context, please cite the following paper:

@misc{kasprzyk2024enhancednbeatsmidtermelectricity,
      title={Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting}, 
      author={Mateusz Kasprzyk and Paweł Pełka and Boris N. Oreshkin and Grzegorz Dudek},
      year={2024},
      eprint={2412.02722},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2412.02722}, 
}