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DEVELOPMENT OF A TOOL TO OPTIMIZE ELECTRICAL CONSUMPTION IN BUILDINGS WITH SOLAR GENERATION

JANUARY-DECEMBER 2024   -  Volume: 13 -  Pages: [8P.]

DOI:

https://doi.org/10.6036/ES11030

Authors:

NEKANE SAINZ BEDOYA
-
JULEN IGLESIAS TEJEDOR
-
IGNACIO GARCIA QUINTANILLA
-
VERONICA CANIVELL CASTILLO
-
ANA MARIA MACARULLA ARENAZA

Disciplines:

  • Electrical technology and engineering (OTRAS (ESPECIFICAR) )

Downloads:   17

How to cite this paper:  

Received Date :   28 July 2023

Reviewing Date :   15 September 2023

Accepted Date :   8 March 2024

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Key words:
Eficiencia energética, generación energía solar, modelos consumo, Big data, aplicación de gestión, Energy efficiency, solar power generation, consumption models, Big data, management application
Article type:
ARTICULO DE INVESTIGACION / RESEARCH ARTICLE
Section:
COLLABORATIONS

ABSTRACT:
The project focuses on the field of energy and sustainability within the framework of the sustainable development goals, specifically number seven, affordable and clean energy, and number eleven, sustainable cities and communities. Based on the energy generation and consumption data of two residential facilities, one at the Comillas University in Madrid and the other at the Deusto University in Bilbao, solar energy generation has been modeled. And the design and development of a web application to analyze energy consumption and view different summaries of the data, thus facilitating their analysis and interpretation has been programmed.
To achieve this objective, it has been necessary to carry out an exhaustive collection, transformation and cleaning of the data of the solar installation inverters, as well as to store them to be able to represent them later. The application allows a clear and accessible visual presentation of the data through different graphs, allowing users to quickly and easily understand the patterns and trends related to energy consumption that help them make decisions that optimize the energy consumption.
Keywords: Energy efficiency, solar power generation, consumption models, Big data, management application

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