From big data to smart energy services: An application for intelligent energy management

Vangelis Marinakis, Haris Doukas, John Tsapelas, Spyros Mouzakitis, Álvaro Sicilia, Leandro Madrazo, Sgouris Sgouridis

Research output: Indexed journal article Articlepeer-review

106 Citations (Scopus)

Abstract

Big data is an ascendant technological concepts and includes smart energy services, such as intelligent energy management, energy consumption prediction and exploitation of Internet of Things (IoT) solutions. As a result, big data technologies will have a significant impact in the energy sector. This paper proposes a high level architecture of a big data platform that can support the creation, development, maintenance and exploitation of smart energy services through the utilisation of cross-domain data. The proposed platform enables the simplification of the procedure followed for the information gathering by multiple sources, turning into actionable recommendations and meaningful operational insights for city authorities and local administrations, energy managers and consultants, energy service companies, utilities and energy providers. A web-based Decision Support System (DSS) has been developed according to the proposed architecture, exploiting multi-sourced data within a smart city context towards the creation of energy management action plans. The pilot application of the developed DSS in three European cities is presented and discussed. This “data-driven” DSS can support energy managers and city authorities for managing their building facilities’ energy performance.

Original languageEnglish
Pages (from-to)572-586
Number of pages15
JournalFuture Generation Computer Systems
Volume110
DOIs
Publication statusPublished - Sept 2020

Keywords

  • Big data
  • Decision support system
  • Energy services
  • Intelligent management
  • Smart Cities

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