Data-driven framework for energy-efficient smart cities

Energy management is one of the greatest challenges in smart cities. Moreover, the presence of autonomous vehicles makes this task even more complex. In this paper, we propose a data-driven smart grid framework which aims to make smart cities energy-efficient focusing on two aspects: energy trading...

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Bibliographic Details
Published inSerbian journal of electrical engineering Vol. 17; no. 1; pp. 41 - 63
Main Authors Petrovic, Nenad, Kocic, Djordje
Format Journal Article
LanguageEnglish
Published Faculty of Technical Sciences in Cacak 2020
Subjects
blockchain
deep learning
linear programming
relay protection
smart city
smart contract
smart grid
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ISSN1451-4869
2217-7183
2217-7183
DOI10.2298/SJEE2001041P

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Summary:Energy management is one of the greatest challenges in smart cities. Moreover, the presence of autonomous vehicles makes this task even more complex. In this paper, we propose a data-driven smart grid framework which aims to make smart cities energy-efficient focusing on two aspects: energy trading and autonomous vehicle charging. The framework leverages deep learning, linear optimization, semantic technology, domain-specific modelling notation, simulation and elements of relay protection. The evaluation of deep learning module together with code generation time and energy distribution cost reduction performed within the simulation environment also presented in this paper are given. According to the results, the achieved energy distribution cost reduction varies and depends from case to case.
ISSN:1451-4869
2217-7183
2217-7183
DOI:10.2298/SJEE2001041P