SCE

Smart City Energy Analytics

Objectifs

Le projet SCE (Smart City Energy Analytics) a été lancé en 2014 avec l’objectif frdévelopper une plateforme ouverte d’analyse de données associant les fournisseurs de technologies, les intégrateurs de systèmes, les services énergétiques et de transport, les opérateurs et les entités de recherche universitaires.  Cette plateforme a permisde tester différentes stratégies de gestion énergétique et de voir apparaître de nouveaux business models.

Résultats

Publications du projet SCE

A New Crypto-Classifier Service for Energy Efficiency in Smart Cities.

Oana Stan, Mohamed-Haykel Zayani, Renaud Sirdey, Amira Ben Hamida, Alessandro Ferreira Leite, Mallek Sallami-Mziou

Conférence SmartGreens 2018

A novel model and tool for energy renovation planning in French Residential buildings and districts.

Kahina Amokrane-Ferka and Amira Ben Hamida

International Conference on Smart Data and Smart Cities (SDSC) 2018

Train speed profiles optimization using a genetic algorithm based on a random-forest model to estimate energy consumption.

Ahmed Amrani, Amira Ben Hamida, Tao Liu, Olivier Langlois

Transport Research Arena 2018

A SaaS implementation of a New Generic Crypto-Classifier Service for Secure Energy Efficiency in Smart Cities.

Oana Stan, Mohamed-Haykel Zayani, Renaud Sirdey, Amira Ben Hamida, Mallek Sallami-Mziou, Alessandro Ferreira Leite

Springer CCIS Series Book 2018

Privacy-preserving Tax Calculations in Smart Cities by Means of Inner-Product Functional Encryption.

Oana Stan, Renaud Sirdey, Cédric Gouy-Pailler, Pierre Blanchart, Amira Ben Hamida, Mohamed-Haykel Zayani.

Cyber Security In Networking Conference (CSNET) 2018

Probabilistic load flow method for estimation of electrical network reliability indices

Fallilou Diop, Martin Hennebel

Powertech Manchester 2017

A dedicated mixture clustering-based model applied on smart meters data: Identification and analysis of electricity consumption behaviors.

Fateh Nassim Melzi, Allou Samé, Mohamed Haykel Zayani, and Latifa Oukhellou

Revue Energies 2017

Stratégies de planification de recharge de véhicules électriques pour minimiser le coût financier.

Fallilou Diop, Martin Hennebel

Symposium du Génie électrique 2016

Hourly solar irradiance forecasting based on machine learning models.

Nassim Fateh Melzi, Latifa Oukhellou and co.

International Conference on Machine Learning and Application (ICMLA) 2016

Towards Smart City Energy Analytics: Identification of Electric Consumption Patterns Based on Clustering Approaches.

Nassim Fateh Melzi, Latifa Oukhellou and co.

Complex System Design and Management (CSD&M) 2015

Identifying Daily Electric Consumption Patterns from Smart Meter Data by Means of Clustering Algorithms.

Nassim Fateh Melzi, Latifa Oukhellou and co.

International Conference on Machine Learning and Application (ICMLA) 2015

Rétrospective

Médiathèque

 

Terminé
Environnement et développement durable
Partenaires industriels
Alstom Artelys Cosmo Tech Engie GE Grid solutions NovEner Reuniwatt Ecogélec Sherpa Engineering Solunergie
Partenaires académiques
CEA CentraleSupélec IFSTTAR
Chef de projet
Amira Ben Hamida
amira.benhamida [at] irt-systemx.fr