Advanced Methods for Renewable Energy Forecasting
Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 1473
Prediction is a crucial procedure applied in many fields for the optimal management of assets and resources. Energy commodities are a vital element of human activities. They are optimally planned and managed by policymakers through a prediction process that includes the availability of natural resources and other relevant socio-economic parameters and indices.
The environmental problems related to coal, oil, and natural gas exploitation for power generation motivate policymakers to modify the energy mix to increase the portion of the energy produced from clean sources. The transition to an environmentally-friendly power system also relies on a forecasting process applied on different ranges from hours to years.
This special issue aims to collect state-of-the-art prediction techniques and studies mainly based on deep learning and artificial intelligence and assess their implementation for planning and managing renewable power systems, energy portfolios, energy stocks and markets, and natural resource assessment. In addition to deep learning algorithms, other methodologies based on statistical analysis and physical methods supported by weather information are also welcomed.
Dr. Juan M. Lujano-Rojas
Manuscript Submission Information
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.