Applications Of Modeling By Artificial Intelligence Of A Forecast System For The Production Of Alternative Energies

Abstract

The present investigation consists of a bibliometric review related to the prediction systems for the production of renewable energies through artificial intelligence. In this regard, a systematic bibliographic search of the topic was carried out in the Scopus database in November 2022 using the search equation: ( TITLE-ABS-KEY ( "artificial intelligence") OR TITLE-ABS-KEY ( " machine learning" ) OR TITLE-ABS-KEY ( "Deep learning") AND TITLE-ABS-KEY ( "renewable energies " ) OR TITLE-ABS-KEY ( "alternative energies" ) OR TITLE-ABS-KEY ( "clean energies" " ) AND TITLE-ABS-KEY ( "predictive model*" ) OR TITLE-ABS-KEY ( "forecast* systems" ) OR TITLE-ABS-KEY ( "predictive method" ) OR TITLE-ABS-KEY ( "predictive analytics " ) ). The results obtained show that between the years 2021 and 2022, 58% of all the investigations carried out are concentrated. In the geographical section, China (36) turned out to be the country that contributed the most papers to the subject studied, closely followed by the United States (34). In turn, the four journals that publish the most on the subject were ENERGIES (14), IEEE ACCESS (11), JOURNAL OF CLEANER PRODUCTION (6) and APPLIED ENERGY (5), while the 3 authors with the most published articles were Deo RC (12), Ghimire S (6) and Raj N (4). Finally, the three publications with the highest number of citations were Hu Q, 2016, Renew Energy (301), Ahmad MW, 2018, J Clean Prod (151) and Ahmad T, 2020, Sustainable Cities SOC (149).