Objectives

Design a decision-support tool allowing cities’s intelligence energy management.

SCE (Smart City Energy Analytics) project was launched in 2014 with the aim of developing solutions for better energy management. The main goal was to take benefit from Artificial Intelligence techniques at different scales of the city of tomorrow. Various granularities and end-users are targeted. Scenarios simulating buildings, districts and factories and mobility of the future are envisioned.

Results

Publications

SCE publications

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

Project timeline

Badge Environment and Sustainable Development
IMPROVE
Environment and Sustainable Development
Project Status:État du projet : Completed
Industrial partners:Partenaires industriels :
Alstom Artelys Cosmo Tech Engie GE Grid solutions NovEner Reuniwatt Ecogélec Sherpa Engineering Solunergie
Academic PartnersPartenaires académiques
CEA CentraleSupélec IFSTTAR
Project ManagerChef de projet
Amira Ben Hamida
amira.benhamida [at] irt-systemx.fr

Videos to see




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