Forecasting electricity prices from the state-of-the-art modeling technology and the price determinant perspectives

S Chai, Q Li, MZ Abedin, BM Lucey - Research in International Business …, 2024 - Elsevier
Accurate electricity price forecasting (EPF) is crucial to participants and decision-makers
within the electricity market. This paper reviews 62 screened literature works on EPF during …

Predicting of Daily PM2.5 Concentration Employing Wavelet Artificial Neural Networks Based on Meteorological Elements in Shanghai, China

Q Guo, Z He, Z Wang - Toxics, 2023 - mdpi.com
Anthropogenic sources of fine particulate matter (PM2. 5) threaten ecosystem security,
human health and sustainable development. The accuracy prediction of daily PM2. 5 …

[HTML][HTML] Understanding electricity prices beyond the merit order principle using explainable AI

J Trebbien, LR Gorjão, A Praktiknjo, B Schäfer… - Energy and AI, 2023 - Elsevier
Electricity prices in liberalized markets are determined by the supply and demand for electric
power, which are in turn driven by various external influences that vary strongly in time. In …

Spillover effects among electricity prices, traditional energy prices and carbon market under climate risk

D Liu, X Liu, K Guo, Q Ji, Y Chang - International Journal of …, 2023 - mdpi.com
With the increase in global geopolitical risks and the frequent occurrence of extreme climate
in recent years, the electricity prices in Europe have shown large fluctuations. Electricity …

Bitcoin Price Forecasting: An Integrated Approach Using Hybrid LSTM‐ELM Models

C Luo, L Pan, B Chen, H Xu - Mathematical Problems in …, 2022 - Wiley Online Library
In recent years, digital currencies have flourished on a considerable scale, and the markets
of digital currencies have generated a nonnegligible impact on the whole financial system …

A combined system based on data preprocessing and optimization algorithm for electricity load forecasting

L Gu, J Wang, J Liu - Computers & Industrial Engineering, 2024 - Elsevier
Creating steady models for predicting electricity load can enhance the equilibrium between
power supply and demand, a critical factor in advancing precise distribution management …

Improving long-term multivariate time series forecasting with a seasonal-trend decomposition-based 2-dimensional temporal convolution dense network

J Hao, F Liu - Scientific Reports, 2024 - nature.com
Improving the accuracy of long-term multivariate time series forecasting is important for
practical applications. Various Transformer-based solutions emerging for time series …

A novel ensemble electricity load forecasting system based on a decomposition-selection-optimization strategy

Y Wang, H Li, A Jahanger, Q Li, B Wang… - Energy, 2024 - Elsevier
Electricity load forecasting exhibits an irreplaceable role in enhancing the dispatching and
management efficiency of power systems. However, the majority of existing research …

Application of extreme learning machine-autoencoder to medium term electricity price forecasting

A Najafi, O Homaee, M Golshan… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Electricity market prices are highly volatile, highly frequent, non-linear, and non-stationary
which makes forecasting very complicated. Although accurate forecasting plays a crucial …

[HTML][HTML] Short-term performance degradation prediction of proton exchange membrane fuel cell based on discrete wavelet transform and Gaussian process regression

F Zhang, B Wang, Z Gong, Z Qin, Y Yin, T Guo, F Wang… - Next Energy, 2023 - Elsevier
Proton exchange membrane fuel cell (PEMFC) is regarded as one of the most promising
energy conversion devices, but cost and durability are two challenges that hinder its large …