Energy forecasting: A review and outlook

T Hong, P Pinson, Y Wang, R Weron… - IEEE Open Access …, 2020‏ - ieeexplore.ieee.org
Forecasting has been an essential part of the power and energy industry. Researchers and
practitioners have contributed thousands of papers on forecasting electricity demand and …

Taxonomy research of artificial intelligence for deterministic solar power forecasting

H Wang, Y Liu, B Zhou, C Li, G Cao, N Voropai… - Energy Conversion and …, 2020‏ - Elsevier
With the world-wide deployment of solar energy for a sustainable and renewable future, the
stochastic and volatile nature of solar power pose significant challenges to the reliable …

Key technologies for smart energy systems: Recent developments, challenges, and research opportunities in the context of carbon neutrality

H Zhu, HH Goh, D Zhang, T Ahmad, H Liu… - Journal of Cleaner …, 2022‏ - Elsevier
Energy crisis and environmental pollution have expedited the transition of the energy
system. Global use of low-carbon energy has increased from 1: 6.16 to 1: 5.37. Smart energy …

A review on the integration of probabilistic solar forecasting in power systems

B Li, J Zhang - Solar Energy, 2020‏ - Elsevier
As one of the fastest growing renewable energy sources, the integration of solar power
poses great challenges to power systems due to its variable and uncertain nature. As an …

Hybrid Bayesian-Copula-based risk assessment for tall buildings subject to wind loads considering various uncertainties

XW Zheng, HN Li, P Gardoni - Reliability Engineering & System Safety, 2023‏ - Elsevier
The aleatory and epistemic uncertainties coming from various sources have significant
impacts on the accuracy of risk estimates for structures under dynamic excitations. This …

A holistic review on energy forecasting using big data and deep learning models

J Devaraj, R Madurai Elavarasan… - … journal of energy …, 2021‏ - Wiley Online Library
With the growth of forecasting models, energy forecasting is used for better planning,
operation, and management in the electric grid. It is important to improve the accuracy of …

A cross-sectional survey of deterministic PV power forecasting: Progress and limitations in current approaches

A Sabadus, R Blaga, SM Hategan, D Calinoiu… - Renewable Energy, 2024‏ - Elsevier
This review reports a quantitative analysis across the deterministic photovoltaic (PV) power
forecasting approaches. Model accuracy tests from papers passing a set of selection criteria …

Solar irradiance forecasting based on direct explainable neural network

H Wang, R Cai, B Zhou, S Aziz, B Qin, N Voropai… - Energy Conversion and …, 2020‏ - Elsevier
As the penetration of solar energy into electrical power and energy system expands in
recent years over the world, accurate solar irradiance forecasting is becoming highly …

Convergence of photovoltaic power forecasting and deep learning: State-of-art review

M Massaoudi, I Chihi, H Abu-Rub, SS Refaat… - Ieee …, 2021‏ - ieeexplore.ieee.org
Deep learning (DL)-based PV Power Forecasting (PVPF) emerged nowadays as a
promising research direction to intelligentize energy systems. With the massive smart meter …

Probabilistic solar power forecasting based on weather scenario generation

M Sun, C Feng, J Zhang - Applied Energy, 2020‏ - Elsevier
Probabilistic solar power forecasting plays an important role in solar power grid integration
and power system operations. One of the most popular probabilistic solar forecasting …