Microgrid Infrastructure Compendium Analysis with a Model Creation Tool and Guideline Based on Machine Learning Techniques

Miguel Carpintero-Rentería, David Santos-Martín, Mónica Chinchilla and David Rebollal
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Miguel Carpintero-Rentería: Department of Electrical Engineering, University Carlos III of Madrid (UC3M), Avda. De la Universidad 30, Leganés, 28911 Madrid, Spain
David Santos-Martín: Department of Electrical Engineering, University Carlos III of Madrid (UC3M), Avda. De la Universidad 30, Leganés, 28911 Madrid, Spain
Mónica Chinchilla: Department of Electrical Engineering, University Carlos III of Madrid (UC3M), Avda. De la Universidad 30, Leganés, 28911 Madrid, Spain
David Rebollal: Department of Electrical Engineering, University Carlos III of Madrid (UC3M), Avda. De la Universidad 30, Leganés, 28911 Madrid, Spain

Energies, 2019, vol. 12, issue 23, 1-18

Abstract: A microgrid (MG) is an electric power distribution system that may provide a suitable ecosystem for distributed generation. Detailed information about the infrastructure layer in MG projects is available, so this study aimed to propose a compendium and a model creation guideline for MGs. The aggregated information based on 1618 MGs was summarized into different tables and analyzed based on various parameters. Two MG infrastructure model creation tools were developed. First, a simple guideline was created based on the information in the tables, and then a machine learning tool based on decision trees was proposed that generates more accurate MG models using two main inputs: latitude and the segment in which they operate.

Keywords: microgrids; distributed generation; smart grids; machine learning (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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