A comparative assessment of SARIMA, LSTM RNN and Fb Prophet models to forecast total and peak monthly energy demand for India
A comparative assessment of SARIMA, LSTM RNN and Fb Prophet models to forecast total and peak monthly energy demand for India
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DOI：
10.1016/j.enpol.2022.113097
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发表时间：
2022-09-01
期刊：
影响因子：
9
通讯作者：
McCullen, Nick
中科院分区：
文献类型：
--
作者：
Chaturvedi, Shobhit;Rajasekar, Elangovan;McCullen, Nick
由于长期趋势、短期季节性和不确定性的复杂相互作用，选择合适的能源需求预测方法具有挑战性。本文比较了四种时间序列模型对印度月能源需求总量和峰值的预测性能。印度中央能源局(CEA)现有的基于趋势的模型被用作(I)季节性自回归综合移动平均(SARIMA)、(Ii)长期短期记忆递归神经网络(LSTM RNN)和(Iii)Facebook(FB)Prophet模型的基线。使用108个月的训练数据对24个月的未知数据进行预测，CEA模型对月总能源需求的预测效果较好，均方根误差(RMSE 4.23GWh)和平均绝对百分比误差(MAPE，3.4%)较低，但显著低于对月峰值能源需求的预测(RMSE 13.31GW，MAPE 7.2%)。相比之下，FB Prophet在月度总需求(RMSE 4.23GWh，MAPE 3.3%)和高峰需求(RMSE 6.51GW，MAPE 3.01%)方面表现良好。SARIMA和LSTM RNN的预测误差高于CEA和FB Prophet。因此，FB Prophet被选中来制定2019年至2024年的未来能源预测，这表明印度的年度总能源需求和峰值能源需求可能分别以3.9%和4.5%的年增长率增长。
Selecting a suitable energy demand forecasting method is challenging due to the complex interplay of long-term trends, short-term seasonalities, and uncertainties. This paper compares four time-series models performance to predict total and peak monthly energy demand in India. Indian's Central Energy Authority's (CEA) existing trend-based model is used as a baseline against (i) Seasonal Auto-Regressive Integrated Moving Average (SARIMA), (ii) Long Short Term Memory Recurrent Neural Network (LSTM RNN) and (iii) Facebook (Fb) Prophet models. Using 108 months of training data to predict 24 months of unseen data, the CEA model performs well in predicting monthly total energy demand with low root-mean square error (RMSE 4.23 GWh) and mean absolute percentage error (MAPE, 3.4%), but significantly under predicts monthly peak energy demand (RMSE 13.31 GW, MAPE 7.2%). In contrast, Fb Prophet performs well for monthly total (RMSE 4.23 GWh, MAPE 3.3%) and peak demand (RMSE 6.51 GW, MAPE 3.01%). SARIMA and LSTM RNN have higher prediction errors than CEA and Fb Prophet. Thus, Fb Prophet is selected to develop future energy forecasts from 2019 to 2024, suggesting that India's annual total and peak energy demand will likely increase at an annual growth rate of 3.9% and 4.5%, respectively.