Microgrid Infrastructure Compendium Analysis with a Model Creation Tool and Guideline Based on Machine Learning Techniques
| Autor: | David Santos-Martin, Miguel Carpintero-Rentería, David Rebollal, Monica Chinchilla |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Control and Optimization
Computer science 020209 energy microgrids Energy Engineering and Power Technology 02 engineering and technology Machine learning computer.software_genre Ingeniería Industrial 020401 chemical engineering 0202 electrical engineering electronic engineering information engineering smart grids 0204 chemical engineering Electrical and Electronic Engineering Layer (object-oriented design) Microgrids Engineering (miscellaneous) Electric power distribution distributed generation SIMPLE (military communications protocol) Renewable Energy Sustainability and the Environment business.industry Smart grids Compendium Smart grid machine learning Distributed generation Artificial intelligence Microgrid business computer Energy (miscellaneous) |
| Zdroj: | Energies Volume 12 Issue 23 e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid instname e-Archivo: Repositorio Institucional de la Universidad Carlos III de Madrid Universidad Carlos III de Madrid (UC3M) |
| ISSN: | 1996-1073 |
| DOI: | 10.3390/en12234509 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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