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Atmosphere
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Climate Modeling for Renewable Energy Resource Assessment
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Climate Modeling for Renewable Energy Resource Assessment

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Climatology".

Deadline for manuscript submissions: closed (30 June 2020) | Viewed by 11123

Special Issue Editors

Dr. Sonia Jerez

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Guest Editor
Department of Physics, University of Murcia, Murcia, Spain
Interests: climate change; climate variability; regional climate models
Special Issues, Collections and Topics in MDPI journals
Dr. Marco Turco

E-Mail Website
Guest Editor
Department of Earth Sciences, Barcelona Supercomputing Center, 08034 Barcelona, Spain
Interests: climate prediction; seasonal forecast; climate services; climate change impacts; regional downscaling

Special Issue Information

Dear Colleagues,

This Special Issue of Atmosphere aims to gather high-quality, original research articles, reviews, and technical notes on how climate modeling serves and helps to perform renewable energy assessments (abundance, variability, predictability, vulnerability, feasibility, and the optimization of development projects), as well as on how currently available climate modeling tools and techniques could, or would need to, be improved for such a purpose.

A good understanding and characterization of the behavior of variable renewable energy resources, such as wind, water, and solar radiation, is key to making advances in the design and implementation of smart climate change mitigation strategies. Renewable energies are also needed to achieve clean atmospheres, to favor the development of poor regions worldwide, and to ensure energy supply and security beyond political conflicts. The meteorological and climatic dependence of these resources implies intermittence in their availability, which poses a major flaw compromising the societal and economical commitment to them, and a grade of vulnerability to changes in climate. However, such dependence also confers causal behavior, which is predictable up to a point, which could be positively argued and exploited.

Constraints in the observational records hamper a proper characterization of these aspects, making climate modeling a powerful way to advance current knowledge frontiers on the topic, in spite of its limitations (resolution, performance, and missed and parametrized processes of potential relevance). What can we learn about renewables using climate models? What are their main constraints for such a purpose?

Research works addressing these questions, giving answers or unveiling new related issues on this trending topic, are expected to compose a snapshot of the overarching field. Multidisciplinary collaborations are particularly encouraged, and may including perspectives from the energy, economical, health, social, political, and environmental sectors.

Sincerely,

Dr. Sonia Jerez
Dr. Marco Turco
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 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.

Keywords

  • climate modeling
  • renewable energy
  • solar power
  • wind power
  • hydropower
  • climate change
  • climate variability
  • climate prediction

Published Papers (3 papers)

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Research

17 pages, 6005 KiB  
Article
High-Resolution Solar Climate Atlas for Greece under Climate Change Using the Weather Research and Forecasting (WRF) Model
by Theodoros Katopodis, Iason Markantonis, Nadia Politi, Diamando Vlachogiannis and Athanasios Sfetsos
Atmosphere 2020, 11(7), 761; https://doi.org/10.3390/atmos11070761 - 18 Jul 2020
Cited by 15 | Viewed by 4044
Abstract
In the context of climate change and growing energy demand, solar technologies are considered promising solutions to mitigate Greenhouse Gas (GHG) emissions and support sustainable adaptation. In Greece, solar power is the second major renewable energy, constituting an increasingly important component of the [...] Read more.
In the context of climate change and growing energy demand, solar technologies are considered promising solutions to mitigate Greenhouse Gas (GHG) emissions and support sustainable adaptation. In Greece, solar power is the second major renewable energy, constituting an increasingly important component of the future low-carbon energy portfolio. In this work, we propose the use of a high-resolution regional climate model (Weather Research and Forecasting model, WRF) to generate a solar climate atlas for the near-term climatological future under the Representative Concentration Pathway (RCPs) 4.5 and 8.5 scenarios. The model is set up with a 5 × 5 km2 spatial resolution, forced by the ERA-INTERIM for the historic (1980–2004) period and by the EC-EARTH General Circulation Models (GCM) for the future (2020–2044). Results reaffirm the high quality of solar energy potential in Greece and highlight the ability of the WRF model to produce a highly reliable future climate solar atlas. Projected changes between the annual historic and future RCPs scenarios indicate changes of the annual Global Horizontal Irradiance (GHI) in the range of ±5.0%. Seasonal analysis of the GHI values indicates percentage changes in the range of ±12% for both scenarios, with winter exhibiting the highest seasonal increases in the order of 10%, and autumn the largest decreases. Clear-sky fraction fclear projects increases in the range of ±4.0% in eastern and north continental Greece in the future, while most of the Greek marine areas might expect above 220 clear-sky days per year. Full article
(This article belongs to the Special Issue Climate Modeling for Renewable Energy Resource Assessment)
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24 pages, 9621 KiB  
Article
A Four Dimensional Variational Data Assimilation Framework for Wind Energy Potential Estimation
by Elias D. Nino-Ruiz, Juan C. Calabria-Sarmiento, Luis G. Guzman-Reyes and Alvin Henao
Atmosphere 2020, 11(2), 167; https://doi.org/10.3390/atmos11020167 - 05 Feb 2020
Cited by 4 | Viewed by 2164
Abstract
In this paper, we propose a Four-Dimensional Variational (4D-Var) data assimilation framework for wind energy potential estimation. The framework is defined as follows: we choose a numerical model which can provide forecasts of wind speeds then, an ensemble of model realizations is employed [...] Read more.
In this paper, we propose a Four-Dimensional Variational (4D-Var) data assimilation framework for wind energy potential estimation. The framework is defined as follows: we choose a numerical model which can provide forecasts of wind speeds then, an ensemble of model realizations is employed to build control spaces at observation steps via a modified Cholesky decomposition. These control spaces are utilized to estimate initial analysis increments and to avoid the intrinsic use of adjoint models in the 4D-Var context. The initial analysis increments are mapped back onto the model domain from which we obtain an estimate of the initial analysis ensemble. This ensemble is propagated in time to approximate the optimal analysis trajectory. Wind components are post-processed to get wind speeds and to estimate wind energy capacities. A matrix-free analysis step is derived from avoiding the direct inversion of covariance matrices during assimilation cycles. Numerical simulations are employed to illustrate how our proposed framework can be employed in operational scenarios. A catalogue of twelve Wind Turbine Generators (WTGs) is utilized during the experiments. The results reveal that our proposed framework can properly estimate wind energy potential capacities for all wind turbines within reasonable accuracies (in terms of Root-Mean-Square-Error) and even more, these estimations are better than those of traditional 4D-Var ensemble-based methods. Moreover, large variability (variance of standard deviations) of errors are evidenced in forecasts of wind turbines with the largest rate-capacity while homogeneous variability can be seen in wind turbines with the lowest rate-capacity. Full article
(This article belongs to the Special Issue Climate Modeling for Renewable Energy Resource Assessment)
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14 pages, 6771 KiB  
Article
The Significance of Wind Turbines Layout Optimization on the Predicted Farm Energy Yield
by Mohammad Al-Addous, Mustafa Jaradat, Aiman Albatayneh, Johannes Wellmann and Sahil Al Hmidan
Atmosphere 2020, 11(1), 117; https://doi.org/10.3390/atmos11010117 - 20 Jan 2020
Cited by 19 | Viewed by 4490
Abstract
Securing energy supply and diversifying the energy sources is one of the main goals of energy strategy for most countries. Due to climate change, wind energy is becoming increasingly important as a method of CO2-free energy generation. In this paper, a [...] Read more.
Securing energy supply and diversifying the energy sources is one of the main goals of energy strategy for most countries. Due to climate change, wind energy is becoming increasingly important as a method of CO2-free energy generation. In this paper, a wind farm with five turbines located in Jerash, a city in northern Jordan, has been designed and analyzed. Optimization of wind farms is an important factor in the design stage to minimize the cost of wind energy to become more competitive and economically attractive. The analyses have been carried out using the WindFarm software to examine the significance of wind turbines’ layouts (M, straight and arch shapes) and spacing on the final energy yield. In this research, arranging the turbines facing the main wind direction with five times rotor diameter distance between each turbine has been simulated, and has resulted in 22.75, 22.87 and 21.997 GWh/year for the M shape, Straight line and Arch shape, respectively. Whereas, reducing the distance between turbines to 2.5 times of the rotor diameter (D) resulted in a reduction of the wind farm energy yield to 22.68, 21.498 and 21.5463 GWh/year for the M shape, Straight line and Arch shape, respectively. The energetic efficiency gain for the optimized wind turbines compared to the modeled layouts regarding the distances between the wind turbines. The energetic efficiency gain has been in the range between 8.9% for 5D (rotor diameter) straight layout to 15.9% for 2.5D straight layout. Full article
(This article belongs to the Special Issue Climate Modeling for Renewable Energy Resource Assessment)
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