Application of Information Measures for Analysis and Predictability of Renewable Energy Time Series
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".
Deadline for manuscript submissions: closed (31 May 2019) | Viewed by 16988
Special Issue Editors
Interests: complex systems; information theory; climate modeling; UV radiation; water resources; chaos theory; modeling of environmental interfaces; environmental physics; psychophysics
Interests: solar radiation mapping and prediction; fractal theory; climate change; tropical meteorology; atmospheric physics
Special Issue Information
Dear Colleagues,
Renewable energy is energy that is collected from carbon-free resources, which are naturally provided on a human time scale, such as solar radiation, wind, rain, tides, biomass, waves and geothermal heat. This energy often provides energy in four important areas: Electricity generation, air and water heating/cooling, transportation and energy for off-grid services, which can be either stand-alone power systems or mini-grids typically supplying a smaller community or small islands with electricity. In the past few decades, the renewable energy has become one of the attractors for policy makers and for the worldwide scientific community, both on a theoretical and practical level.
The work on Renewable Energy includes three equally-important parts: (i) reliability of the measuring procedure, (ii) analysis of measured time series often carrying hidden physical information that cannot be established by traditional methods from different mathematical fields and (iii) predictability of the behavior of those time series, which are essentially connected. In this Special Issue in the focus will be research that addresses Renewable Energy problems using Information Theory approaches, by introducing a novel development of Information Theory for specific applications, and/or by solving a new Renewable Energy problem using the tools of Information Theory. Submissions at the edge of Information Theory, Renewable Energy, and other disciplines are also welcome.
Prof. Dr. Dragutin T. Mihailović
Prof. Dr. Miloud Bessafi
Guest Editors
Manuscript Submission Information
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Keywords
- renewable energy
- physics
- complex systems
- predictability
- Shannon entropy
- Kolmogorov complexity measures
- Kolmogorov time
- information theory
- nonlinearity
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