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2021 | OriginalPaper | Chapter

A Methodology for the Conversion of a Network Section with Generation Sources, Storage and Loads into an Electrical Microgrid Based on Raspberry Pi and Home Assistant

Authors : Oscar Izquierdo-Monge, Paula Peña-Carro, Luis Hernández-Callejo, Oscar Duque-Perez, Angel Zorita-Lamadrid, Roberto Villafafila-Robles

Published in: Smart Cities

Publisher: Springer International Publishing

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Abstract

This paper presents a methodology to convert a network section with generation sources, storage, and loads into an electrical microgrid. This conversion will allow greater autonomy and efficiency in its management. Besides, after the analysis of the recorded data, a reduction in the consumption of the distribution network can be achieved, and therefore, a reduction in the costs of the electricity bill. To achieve this transformation it is necessary to provide the network with intelligence, proposing a methodology based on four steps: identification and description of the elements that form it, choice of hardware and software for monitoring and controlling the system, establishment of communication between the different elements and creation of a control network framework for visualization. As a case study, the microgrid of the Renewable Energy Development Centre (CEDER) located in the province of Soria (Spain) is shown, formed by different sources of generation, storage systems, and consumption. All the elements of this microgrid are integrated with single free software, Home Assistant, installed in a Raspberry Pi 4 to provide the network with basic intelligence, control and monitoring in real-time through different communication protocols.

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Metadata
Title
A Methodology for the Conversion of a Network Section with Generation Sources, Storage and Loads into an Electrical Microgrid Based on Raspberry Pi and Home Assistant
Authors
Oscar Izquierdo-Monge
Paula Peña-Carro
Luis Hernández-Callejo
Oscar Duque-Perez
Angel Zorita-Lamadrid
Roberto Villafafila-Robles
Copyright Year
2021
DOI
https://doi.org/10.1007/978-3-030-69136-3_17

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