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 …
A review on machine learning forecasting growth trends and their real-time applications in different energy systems
T Ahmad, H Chen - Sustainable Cities and Society, 2020 - Elsevier
Energy forecasting and planning play an important role in energy sector development and
policy formulation. The forecasting model selection mostly based on the availability of the …
policy formulation. The forecasting model selection mostly based on the availability of the …
NSDAR: A neural network-based model for similar day screening and electric load forecasting
Z Jiang, L Zhang, T Ji - Applied Energy, 2023 - Elsevier
The load forecasting methods based on similar days has been widely studied in decades,
where similar days were mostly used as an auxiliary means to improve model performance …
where similar days were mostly used as an auxiliary means to improve model performance …
Short-term load forecast using ensemble neuro-fuzzy model
Abstract In this paper, Takagi-Sugeno-Kang neuro-fuzzy model is trained using locally linear
model tree (LOLIMOT) method to forecast day-ahead hourly load profile. The proposed …
model tree (LOLIMOT) method to forecast day-ahead hourly load profile. The proposed …
Energy consumption prediction of air-conditioning systems in buildings by selecting similar days based on combined weights
Z Ma, J Song, J Zhang - Energy and Buildings, 2017 - Elsevier
Accurate modelling and prediction of energy consumption of the air conditioning system is
crucial for improving decision making. A method for predicting the energy consumption of air …
crucial for improving decision making. A method for predicting the energy consumption of air …
Priority index considering temperature and date proximity for selection of similar days in knowledge-based short term load forecasting method
Short term load forecasting (STLF) is one of the important issues in the energy management
of power systems. Increasing the accuracy of STLF results leads to improving the energy …
of power systems. Increasing the accuracy of STLF results leads to improving the energy …
Holidays short‐term load forecasting using fuzzy improved similar day method
Holidays load forecasting is one of the most challenging topics in the short‐term load
forecasting area. This is mainly due to different load behaviors and insufficient samples of …
forecasting area. This is mainly due to different load behaviors and insufficient samples of …
Combining forecasts in short term load forecasting: empirical analysis and identification of robust forecaster
We present an empirical analysis to show that combination of short term load forecasts leads
to better accuracy. We also discuss other aspects of combination, ie, distribution of weights …
to better accuracy. We also discuss other aspects of combination, ie, distribution of weights …
An adaptive and parallel forecasting strategy for short-term power load based on second learning of error trend
MF Elahe, M **, P Zeng - IEEE Access, 2020 - ieeexplore.ieee.org
Modeling an accurate forecasting model for short-term load is still challenging due to the
diverse causes of load changing and lack of information on many of these causes. In this …
diverse causes of load changing and lack of information on many of these causes. In this …
Combination approaches for short term load forecasting
Short term load forecasting for day ahead operations is an important task of an electric
distribution company. Forecasting errors directly impact the economics of the distribution …
distribution company. Forecasting errors directly impact the economics of the distribution …