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A systematic review of statistical and machine learning methods for electrical power forecasting with reported mape score
Electric power forecasting plays a substantial role in the administration and balance of
current power systems. For this reason, accurate predictions of service demands are needed …
current power systems. For this reason, accurate predictions of service demands are needed …
[HTML][HTML] Modeling energy demand—a systematic literature review
PA Verwiebe, S Seim, S Burges, L Schulz… - Energies, 2021 - mdpi.com
In this article, a systematic literature review of 419 articles on energy demand modeling,
published between 2015 and 2020, is presented. This provides researchers with an …
published between 2015 and 2020, is presented. This provides researchers with an …
Effective energy consumption forecasting using empirical wavelet transform and long short-term memory
L Peng, L Wang, D ** region. To properly formulate policies, it is necessary to have reliable forecasts …
Mid-term electricity demand forecasting using improved variational mode decomposition and extreme learning machine optimized by sparrow search algorithm
T Gao, D Niu, Z Ji, L Sun - Energy, 2022 - Elsevier
Mid-term electricity demand forecasting plays an important role in ensuring the operational
safety of the power system and the economic efficiency of grid companies. Most studies …
safety of the power system and the economic efficiency of grid companies. Most studies …
Combination of manifold learning and deep learning algorithms for mid-term electrical load forecasting
Mid-term load forecasting (MTLF) is of great significance for power system planning,
operation, and power trading. However, the mid-term electrical load is affected by the …
operation, and power trading. However, the mid-term electrical load is affected by the …
A review on short‐term load forecasting models for micro‐grid application
VY Kondaiah, B Saravanan… - The Journal of …, 2022 - Wiley Online Library
Load forecasting (LF), particularly short‐term load forecasting (STLF), plays a vital role
throughout the operation of the conventional power system. The precise modelling and …
throughout the operation of the conventional power system. The precise modelling and …
Predictive analysis of quarterly electricity consumption via a novel seasonal fractional nonhomogeneous discrete grey model: A case of Hubei in China
WZ Wu, H Pang, C Zheng, W **e, C Liu - Energy, 2021 - Elsevier
Accurate electricity consumption forecasting plays a crucial role in electric power systems
and is a challenging task due to its complicated mechanism induced by multiple influential …
and is a challenging task due to its complicated mechanism induced by multiple influential …
NDVI forecasting model based on the combination of time series decomposition and CNN–LSTM
P Gao, W Du, Q Lei, J Li, S Zhang, N Li - Water Resources Management, 2023 - Springer
Normalized difference vegetation index (NDVI) is the most widely used factor in the growth
status of vegetation, and improving the prediction of NDVI is crucial to the advancement of …
status of vegetation, and improving the prediction of NDVI is crucial to the advancement of …
Regression modeling for enterprise electricity consumption: A comparison of recurrent neural network and its variants
Effective electricity consumption forecasting is extremely significant for enterprises' electricity
planning which can provide data support for production decision, thus improving the level of …
planning which can provide data support for production decision, thus improving the level of …