A hybrid forecasting method considering the long-term dependence of day-ahead electricity price series
Y Guo, Y Du, P Wang, X Tian, Z Xu, F Yang… - Electric Power Systems …, 2024 - Elsevier
Day-ahead electricity market is crucial for ensuring the balance of electricity supply and
demand. Its electricity price serves as a key guide for market participants and power …
demand. Its electricity price serves as a key guide for market participants and power …
[HTML][HTML] Forecasting solar energy generation in the Mediterranean region up to 2030–2050 using convolutional neural networks (CNN)
This study investigates the significant rise in solar energy production across the
Mediterranean region from 2010 to 2022, attributing this growth to technological …
Mediterranean region from 2010 to 2022, attributing this growth to technological …
Development of prescriptive maintenance methodology for maintenance cost minimization of photovoltaic systems
The number of Photovoltaic (PV) plants is expected to increase exponentially, due to
policies favoring climate neutrality. This could add additional burden to companies that are …
policies favoring climate neutrality. This could add additional burden to companies that are …
[HTML][HTML] Time-dependent photovoltaic performance assessment on a global scale using artificial neural networks
Abstract The integration of Renewable Energy Sources (RESs), particularly solar
PhotoVoltaics (PVs) has become an imperative aspect of sustainable energy systems. In this …
PhotoVoltaics (PVs) has become an imperative aspect of sustainable energy systems. In this …
Robust day-ahead solar forecasting with endogenous data and sliding windows
Renewable energy forecasting services comprise various modules for intra-day and day-
ahead forecasts. This work specifically addresses day-ahead forecasts, utilizing …
ahead forecasts. This work specifically addresses day-ahead forecasts, utilizing …