Load forecasting techniques for power system: Research challenges and survey

N Ahmad, Y Ghadi, M Adnan, M Ali - IEEE Access, 2022‏ - ieeexplore.ieee.org
The main and pivot part of electric companies is the load forecasting. Decision-makers and
think tank of power sectors should forecast the future need of electricity with large accuracy …

[HTML][HTML] Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark

J Lago, G Marcjasz, B De Schutter, R Weron - Applied Energy, 2021‏ - Elsevier
While the field of electricity price forecasting has benefited from plenty of contributions in the
last two decades, it arguably lacks a rigorous approach to evaluating new predictive …

Model identification of proton-exchange membrane fuel cells based on a hybrid convolutional neural network and extreme learning machine optimized by improved …

E Han, N Ghadimi - Sustainable Energy Technologies and Assessments, 2022‏ - Elsevier
In this research, a new optimized deep learning-based methodology is proposed for optimal
and efficient modeling of the Proton-exchange membrane fuel cells. Here, a hybrid method …

Model parameters identification of the PEMFCs using an improved design of Crow Search Algorithm

F Duan, F Song, S Chen, M Khayatnezhad… - International Journal of …, 2022‏ - Elsevier
There is an increasing trend for fuel cell systems applications in electricity generation
systems instead of traditional power generation systems because of their advantages such …

Short-term wind power forecasting based on support vector machine with improved dragonfly algorithm

LL Li, X Zhao, ML Tseng, RR Tan - Journal of Cleaner Production, 2020‏ - Elsevier
It is hard to predict wind power with high-precision due to its non-stationary and stochastic
nature. The wind power has developed rapidly around the world as a promising renewable …

Optimal modeling of combined cooling, heating, and power systems using developed African Vulture Optimization: a case study in watersport complex

L Chen, H Huang, P Tang, D Yao, H Yang… - Energy Sources, Part …, 2022‏ - Taylor & Francis
The present study proposes an optimal design of combined cooling, heating, and power
systems (CCHP) for a watersport complex. The main purpose is to reduce the energy losses …

A comprehensive review of the load forecasting techniques using single and hybrid predictive models

A Al Mamun, M Sohel, N Mohammad… - IEEE …, 2020‏ - ieeexplore.ieee.org
Load forecasting is a pivotal part of the power utility companies. To provide load-shedding
free and uninterrupted power to the consumer, decision-makers in the utility sector must …

Skin cancer diagnosis based on optimized convolutional neural network

N Zhang, YX Cai, YY Wang, YT Tian, XL Wang… - Artificial intelligence in …, 2020‏ - Elsevier
Early detection of skin cancer is very important and can prevent some skin cancers, such as
focal cell carcinoma and melanoma. Although there are several reasons that have bad …

Improving time series forecasting using LSTM and attention models

H Abbasimehr, R Paki - Journal of Ambient Intelligence and Humanized …, 2022‏ - Springer
Accurate time series forecasting has been recognized as an essential task in many
application domains. Real-world time series data often consist of non-linear patterns with …

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 …