Clustering Analysis of the Energy Mix in Romania Using K-Means Algorithm

Cristina (Antohi) Barbu, Stefan-Mihai Petrea, Corina Sbughea and Cristina Gabriela Zamfir
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Cristina (Antohi) Barbu: Dunarea de Jos University of Galati, Romania
Stefan-Mihai Petrea: Dunarea de Jos University of Galati, Romania
Cristina Gabriela Zamfir: Dunarea de Jos University of Galati, Romania

Risk in Contemporary Economy, 2023, 253-262

Abstract: In the context of the challenges generated by the changes on the energy market, Romania is aligning with the European norms regarding the increase of the electricity production capacity from renewable sources. The objective of the work is to analyze the electricity production capacity in Romania and to highlight, through grouping techniques specific to machine learning, the vulnerabilities of electricity production from renewable sources. The research methods used are based on the analysis of the power generated by the electricity production capacities during February 2021 – February 2023. The K-means clustering technique is used for the following types of electricity: wind, photovoltaic, biomass, coal and hydrocarbons. Elbow and Silhouette methods are used to determine the optimal number of clusters. The results of the study outline the idea that Romania has an energy potential from renewable sources insufficiently capitalized. Maximizing the production potential from renewable sources is possible through the implementation of appropriate policies and measures to increase the integration of renewable energy sources (RES) into the National Energy System (SEN).

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:ddj:fserec:y:2023:p:253-262

DOI: 10.35219/rce20670532167

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