Advanced Forecasting Methods for Sustainable Power Systems

Topic Information

Dear Colleagues,

The increasing penetration of renewable energy sources (RES), particularly wind and photovoltaic (PV) systems, is transforming modern power systems and is introducing significant variability and uncertainty in both generation and demand. Unlike conventional dispatchable units, RES are inherently dependent on meteorological conditions, making accurate forecasting a key enabler for ensuring system reliability, flexibility, and efficient operation.

In this context, advanced forecasting methods play a crucial role in supporting power system planning, operation, and control. The integration of data-driven approaches, such as machine learning and deep learning techniques, with physical and hybrid models, offers new opportunities to improve the accuracy and robustness of short-term and long-term predictions. 

This Topic aims to gather contributions from academia and industry focusing on innovative forecasting methodologies for sustainable power systems. Topics of interest include, but are not limited to, renewable generation forecasting, demand prediction, uncertainty quantification, probabilistic approaches, and their applications to enhance resilience, stability, and energy management in future low-carbon power systems.

Dr. Cristina Ventura
Dr. Santi Agatino Rizzo
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Applied Sciences applsci	2.9	6.1	2011	16 Days	CHF 2400	Submit
Electronics electronics	2.9	7.0	2012	16.4 Days	CHF 2400	Submit
Energies energies	3.9	8.3	2008	16.8 Days	CHF 2600	Submit
Forecasting forecasting	4.2	7.1	2019	26.3 Days	CHF 1800	Submit
Processes processes	3.4	5.7	2013	14.9 Days	CHF 2400	Submit
Sci sci	4.1	5.4	2019	26.7 Days	CHF 1400	Submit
Sustainability sustainability	4.1	8.9	2009	17.9 Days	CHF 2400	Submit
Wind wind	2.7	4.5	2021	25 Days	CHF 1200	Submit

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