By a News Reporter-Staff News Editor at Computer Weekly News -- A new study on Information Technology - Information and Data Mining is now available. According to news reporting originating in Shandong, People’s Republic of China, by VerticalNews journalists, research stated, “Considering the volatility and synergies of renewable energy sources, sufficient resource assessment is of great significance for investors and planners to reduce power fluctuations, increase integration capacity, and improve economic and social benefits. This paper proposes a tri-level framework to evaluate and visualize the spatio-temporal characteristics of regional wind and solar energy resources from the perspective of data mining.”
Financial supporters for this research include National Key Research and Development Program of China, Scientific Instruments of the National Natural Science Foundation of China.
The news reporters obtained a quote from the research from Shandong University, “Furthermore, a free, open-source software package named Quantitative Synergy Assessment Toolbox for renewable energy sources (QSAT V1.0) has been developed with Python and hosted on GitHub, which is a useful tool for the resources assessment and preliminary regional synergetic planning. In the first level, the long-term reanalysis meteorological data of wind speed, solar irradiation and ambient temperature are acquired from MERRA, processed via virtual generation systems, and corrected by in-situ measured data. For the progressive two levels of single-site and wide-area data assessments, the data mining methods incorporating attribute construction, principal components analysis and k-means clustering are used to reduce the dimensionality and capture the temporal and spatial synergy patterns. According to the extracted patterns, the rational combinations of sub-regions can be selected as candidates to make full use of the synergies. Shandong province in China is taken as a demonstration to quantify and analyze the complementarities of solar and wind resources.”
According to the news reporters, the research concluded: “The proposed method and tools can help enhance the planning of renewable energy sources.”
For more information on this research see: Quantitative synergy assessment of regional wind-solar energy resources based on MERRA reanalysis data. Applied Energy , 2018;216():172-182. Applied Energy can be contacted at: Elsevier Sci Ltd, The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, Oxon, England. (Elsevier - www.elsevier.com; Applied Energy - http://www.journals.elsevier.com/applied-energy/)
Our news correspondents report that additional information may be obtained by contacting H.X. Zhang, Shandong University, Minist Educ, Key Lab Power Syst Intelligent Dispatch & Control, Jinan 250061, Shandong, People’s Republic of China. Additional authors for this research include Y.J. Cao, Y. Zhang and V. Terzija.
The direct object identifier (DOI) for that additional information is: https://doi.org/10.1016/j.apenergy.2018.02.094. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.
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CITATION: (2018-05-09), New Information and Data Mining Findings Has Been Reported by Investigators at Shandong University (Quantitative synergy assessment of regional wind-solar energy resources based on MERRA reanalysis data), Computer Weekly News, 553, ISSN: 1944-1606, BUTTER® ID: 015632243
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