[HTML][HTML] Short-term load forecasting models: A review of challenges, progress, and the road ahead

S Akhtar, S Shahzad, A Zaheer, HS Ullah, H Kilic… - Energies, 2023 - mdpi.com
Short-term load forecasting (STLF) is critical for the energy industry. Accurate predictions of
future electricity demand are necessary to ensure power systems' reliable and efficient …

An efficient hour-ahead electrical load forecasting method based on innovative features

A Rafati, M Joorabian, E Mashhour - Energy, 2020 - Elsevier
Deregulation of electric power market and aggregation of renewable resources raise the
need for new hour-ahead load forecasting models. This paper proposes a new hybrid data …

Systematic development of short-term load forecasting models for the electric power utilities: The case of Pakistan

AA Mir, ZA Khan, A Altmimi, M Badar, K Ullah… - IEEE …, 2021 - ieeexplore.ieee.org
Load forecasts are fundamental inputs for the reliable and resilient operation of a power
system. Globally, researchers endeavor to improve the accuracy of their forecast models …

[HTML][HTML] Short-term electricity load forecasting with machine learning

E Aguilar Madrid, N Antonio - Information, 2021 - mdpi.com
An accurate short-term load forecasting (STLF) is one of the most critical inputs for power
plant units' planning commitment. STLF reduces the overall planning uncertainty added by …

Artificial intelligence and statistical techniques in short-term load forecasting: a review

AB Nassif, B Soudan, M Azzeh, I Attilli… - arXiv preprint arXiv …, 2021 - arxiv.org
Electrical utilities depend on short-term demand forecasting to proactively adjust production
and distribution in anticipation of major variations. This systematic review analyzes 240 …

[HTML][HTML] Clustering informed MLP models for fast and accurate short-term load forecasting

AI Arvanitidis, D Bargiotas, A Daskalopulu… - Energies, 2022 - mdpi.com
The stable and efficient operation of power systems requires them to be optimized, which,
given the growing availability of load data, relies on load forecasting methods. Fast and …

A comparative assessment of deep learning models for day-ahead load forecasting: Investigating key accuracy drivers

S Pelekis, IK Seisopoulos, E Spiliotis… - … Energy, Grids and …, 2023 - Elsevier
Short-term load forecasting (STLF) is vital for the effective and economic operation of power
grids and energy markets. However, the non-linearity and non-stationarity of electricity …

[HTML][HTML] Advanced ml-based ensemble and deep learning models for short-term load forecasting: Comparative analysis using feature engineering

PP Phyo, C Jeenanunta - Applied Sciences, 2022 - mdpi.com
Short-term load forecasting (STLF) plays a pivotal role in the electricity industry because it
helps reduce, generate, and operate costs by balancing supply and demand. Recently, the …

EGA-STLF: A hybrid short-term load forecasting model

P Lv, S Liu, W Yu, S Zheng, J Lv - IEEE Access, 2020 - ieeexplore.ieee.org
As the development of smart grids and electricity markets around the world, short-term load
forecasting (STLF) plays an increasingly important role in safe and economical operations of …

A deep bi-directional long-short term memory neural network-based methodology to enhance short-term electricity load forecasting for residential applications

S Atef, K Nakata, AB Eltawil - Computers & Industrial Engineering, 2022 - Elsevier
Unexpected fluctuations associated with electricity load consumption patterns pose a
significant threat to the stability, efficiency, and sustainability of modernized energy systems …