A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization

R Ahmed, V Sreeram, Y Mishra, MD Arif - Renewable and Sustainable …, 2020 - Elsevier
Integration of photovoltaics into power grids is difficult as solar energy is highly dependent
on climate and geography; often fluctuating erratically. This causes penetrations and voltage …

Solar photovoltaic power forecasting: A review

KJ Iheanetu - Sustainability, 2022 - mdpi.com
The recent global warming effect has brought into focus different solutions for combating
climate change. The generation of climate-friendly renewable energy alternatives has been …

Solar photovoltaic generation forecasting methods: A review

S Sobri, S Koohi-Kamali, NA Rahim - Energy conversion and management, 2018 - Elsevier
Solar photovoltaic plants are widely integrated into most countries worldwide. Due to the
ever-growing utilization of solar photovoltaic plants, either via grid-connection or stand …

Review of photovoltaic power forecasting

J Antonanzas, N Osorio, R Escobar, R Urraca… - Solar energy, 2016 - Elsevier
Variability of solar resource poses difficulties in grid management as solar penetration rates
rise continuously. Thus, the task of solar power forecasting becomes crucial to ensure grid …

Intermittent and stochastic character of renewable energy sources: Consequences, cost of intermittence and benefit of forecasting

G Notton, ML Nivet, C Voyant, C Paoli, C Darras… - … and sustainable energy …, 2018 - Elsevier
Solar and wind energy are inherently time-varying sources of energy on scales from minutes
to seasons. Thus, the incorporation of such intermittent and stochastic renewable energy …

Advanced methods for photovoltaic output power forecasting: A review

A Mellit, A Massi Pavan, E Ogliari, S Leva, V Lughi - Applied Sciences, 2020 - mdpi.com
Forecasting is a crucial task for successfully integrating photovoltaic (PV) output power into
the grid. The design of accurate photovoltaic output forecasters remains a challenging issue …

Deep learning and statistical methods for short-and long-term solar irradiance forecasting for Islamabad

SA Haider, M Sajid, H Sajid, E Uddin, Y Ayaz - Renewable Energy, 2022 - Elsevier
The growing threat of global climate change stemming from the huge carbon footprint left
behind by fossil fuels has prompted interest in exploring and utilizing renewable energy …

[HTML][HTML] Using artificial intelligence to improve real-time decision-making for high-impact weather

A McGovern, KL Elmore, DJ Gagne… - Bulletin of the …, 2017 - journals.ametsoc.org
Using Artificial Intelligence to Improve Real-Time Decision-Making for High-Impact Weather
in: Bulletin of the American Meteorological Society Volume 98 Issue 10 (2017) Jump to …

[HTML][HTML] Artificial intelligence for electricity supply chain automation

L Richter, M Lehna, S Marchand, C Scholz… - … and Sustainable Energy …, 2022 - Elsevier
Abstract The Electricity Supply Chain is a system of enabling procedures to optimize
processes ranging from production to transportation and consumption of electricity. The …

The value of solar forecasts and the cost of their errors: A review

O Gandhi, W Zhang, DS Kumar… - … and Sustainable Energy …, 2024 - Elsevier
Despite the advances in solar forecasting methods, and their ever-increasing accuracy, little
is known about their value for real applications, eg, bidding in the electricity market, power …