Projet Lyon Smart Community Community Management System

Transcription

1 Projet Lyon Smart Community Community Management System Janvier 2014 Toshiba Corporation, Toshiba Solutions Corporation 2014 Toshiba Corporation / Toshiba Solutions Corporation

2 Projet Lyon Smart Community (4) 4 SEQUENCES (1) (2) (3) 2

3 Projet Lyon Smart Community (1) HIKARI Bâtiments intelligents à énergie positive / Novembre 2012 : Obtention du permis de construire / Juin 2013 : Pose de la première pierre / Printemps 2015 : Livraison des bâtiments / Juin 2016 : Fin de la période de démonstration m² 3 bâtiments conçus par Kengo Kuma 34 Appartements neufs Bureaux et commerces LED Equipements sobres en consommation PV EnR en façade et toiture et Stockage Cogénération biomasse Batteries Intelligentes Lithium et plomb 3

4 HIKARI Bâtiments intelligents à énergie positive Systèmes de gestion d énergie Système de gestion de l énergie du bâtiment Système de gestion de l énergie domestique (BEMS) (HEMS) Systèmes de production d énergie Panneaux photovoltaiques Centrale de cogénération à l huile végétale Systèmes de stockage d énergie Batteries intelligentes Matériau à changement de phase (MCP) Systèmes d économies d énergie Groupe froid à absorption Système d éclairage LED 4

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12 Bilan Energetique Prévisionnel de l Ilot Hikari INFORMATION CONFIDENTIELLE NON DIFFUSABLE 12

13 2 Projet Lyon Smart Community (2) SUNMOOV Système d autopartage zéro émission / Mai 2013 : Installation des stations de recharge / Octobre 2013 : Lancement du service d autopartage / Octobre 2014 : Connexion au système PV / Décembre 2015 : Fin de la période de démonstration 30 Véhicules électriques Mitsubishi, Peugeot, Citroen 6 Stations de recharge 33 Bornes de recharge Alimentée par des énergies renouvelables 3 bornes de recharge rapide 13

14 SUNMOOV - Système d autopartage zéro émission μems / Prévisions d énergie PV Le système µems de Toshiba aidera à maintenir un bon équilibre entre les besoins de recharge des véhicules électriques, la quantité d énergie renouvelable disponible et l état du réseau local de distribution. Système d optimisation de la planification de la recharge Ce système constitue la principale technologie utilisée pour optimiser la planification de la recharge des véhicules électriques avec une énergie renouvelable. Système de contrôle de la recharge Ce système contrôle à distance les bornes de recharge normale et rapide en fonction du temps de recharge optimisé et communique également avec le système d ErDF afin d obtenir des informations sur le réseau de distribution électrique. 14

15 Reservation information, EV condition Charging Schedule Schéma Technique Basing on EV reservations and forecasts of PV generation, EV car sharing will be powered by renewable energy and mainly by PV solar panels to be installed in building rooftop within La Confluence district (70% of EV energy needs to be covered). SUNMOOV car sharing service was launched on 15 th October, PV Owner PV generation information Meteo France Weather information μems Charging Schedule Optimization system ERDF Go or No Go for charging Car sharing system (reservations, billing) Charge Command Use Authorization Charging Control System Normal and rapid Chargers NO. Normal Chargers Rapid Chargers 1 5 Stands 1 Stand Stands 5 Stands 4 5 Stands 1 Stand 6 5 Stands 6 5 Stands 1 Stand 15

16 Use Case (1) Case 1 When the weather is sunny, the EV with small remaining energy will be powered in priority. PV installed in the Lyon Confluence System Power (Renewable Energy produced by local company) Charging Control System NC NC NC QC 16

17 Case (2a) Case 2a When the weather is cloudy or at night, we do not charge the EV if the reservation schedule is not full. PV installed in the Lyon Confluence System Power (Renewable Energy produced by local company) Charging Control System NC NC NC QC Reservation Reservation Reservation 17

18 Use Case (2b) Case 2b When the weather is cloudy or at night, we charge the EV by using renewable energy produced by local company (grid) if the reservation schedule is full. PV installed in the Lyon Confluence System Power (Renewable Energy produced by local company) Charging Control System NC NC NC QC Reservation Reservation Reservation 18

19 Use Case (3a) Case 3a When returning the EV to the station, the user will return the EV to normal charger if there is no reservation after. PV installed in the Lyon Confluence System Power (Renewable Energy produced by local company) Charging Control System NC NC NC QC 19

20 Use Case (3b) Case 3b When returning the EV to the station, the user will return the EV to rapid charger if there is a reservation after. PV installed in the Lyon Confluence System Power (Renewable Energy produced by local company) Charging Control System NC NC NC QC Next Reservation 20

21 Demonstration system screens Demonstration Indexes 1 Multi vendor for car sharing System, EV, and charging stands 2 Forecast of PV energy production 3 Impact on the local distribution network 4 Forecast of necessary charging time 5 Efficient use of renewable energy 6 Car sharing turnover 7 Rapid charger efficiency 8 Introduction of renewable energy 9 Business model validation 21

22 Projet Lyon Smart Community (3) ConsoTab Rénovation et système de visualisation énergétique / Septembre 2013 : Installation des premiers systèmes de monitoring / Juin 2014 : Début du projet de rénovation de la Cité de Perrache / Décembre 2015 : Fin de la période de démonstration 275 Appartements existants Compteurs intelligents multi-fluides Electricité, gaz, chaleur, eau Système d alertes Et/ou de conseils de consommation en temps réel, par équipement Système de suivi Historique, affichage des économies budgétaires pour les locataires Evaluation Des consommations énergétiques pré et post rénovation 22

23 CONSOTAB Ecran du Système de Visualisation 23

24 CONSOTAB Ecran du Système de Visualisation 24

25 CONSOTAB Ecran du Système de Visualisation 25

26 4 Lyon Smart Community (4) Community Management System / Mars 2013 : Ouverture du Data Center à Lyon / Septembre 2014 : Connexion des bâtiments au CMS / Juin 2016 : Fin de la période de démonstration SMART CITIZENS 1 Datacenter à Lyon Spécialement dédié au projet Système de suivi en temps réel Des différents bâtiments et du système d autopartage de véhicules électriques CMS Contrôle des production et consommation d énergie A l échelle d un quartier en connexion avec les fournisseurs d énergie 26

27 Le Concept du CMS / Perfomance grâce à la collecte et analyse des données ; / Nouveaux services ; / Communication intéractive et ludique avec les citoyens. Government Leadership Leadership Planning Information Behavior change Data Collection Lifelog Smarter citizen Citizens satisfaction Information Big Data Synthesis Weather Open data Buildings CMS Mobility SNS Medical info Public Service Operators 27

28 Schema Technique du CMS INFORMATION CONFIDENTIELLE NON DIFFUSABLE Analysis DB Web Server Get map data City Inf. Grand Lyon GIS Information Browsing 5 scenarios of CMS Energy Consumption in buildings Effect of refurbishment Effect of providing data Power supply/energy demand Status of usage of EV car sharing WS Crawler JMS Adapter Internet Web Input/output? Data ERDF GRDF Communication Interface Cloud HEMS Cloud BEMS Other buildings PV information Weather Stations μems Charging Optmization Schedule System Visualization server n n P-Plot Building HEMS 36 apartments P-Plot BEMS G/W Other Buildings in Confluence G/W PV information Other Buildings in Confluence Weather Station Information Car sharing system Charging Stand Energy Box Gas, water devices 3~5 buidlings (Future buildings to be constructed) 28

29 Ecran du CMS (prototype) Ecran Principal Description: Real-time and (7-day) Historical Overview of the Community Status The screens are being developed. Details of the design may change in the future. 29

30 Les Différents Scénarios du CMS / Exemples d utilisation du CMS / 5 scénarios basés sur des données bien distinctes / Futurs scénarios No Principes des Scénarios 1 Suivi de la consommation énergétique des bâtiments 2 Suivi de l impact de la rénovation sur les bâtiments 3 Suivi de l impact des informations transmises aux habitants 4 5 Suivi de l équilibre entre l offre et la demande énergétique à l échelle d un quartier Suivi de la situation de l utilisation du système de véhicules électriques en autopartage 30

31 Offline analysis Scenario1 (Confirmation of the energy consumption of the buildings) Analyze periodic trends and long-term trends of energy consumption of the buildings Extract the correlation between meteorological data and energy consumption of buildings INFORMATION CONFIDENTIELLE NON DIFFUSABLE For example, we can see that the trend and the peak weekly or daily of energy consumption is different depending on the usage of the building For example, we can see that there is the difference of the correlation between temperature and energy consumption of the peak by the usage of the building. Action We can identify the building likely to exceed the guideline and investigate the detailed status of that building. Comparison of guidelines and the measured value at the time of operation can be help to set the guidelines for buildings in the future. It can be help for policy consideration of peak cut of energy consumption. 31

32 Subgraph Main graph Scenario2 (Confirmation of the effect of refurbishment) Compare energy consumption before and after refurbishment We can see whether energy consumption reduce by refurbishment. Action It can be help for setting refurbishment policy in the future. It can be used to estimate the effect of refurbishment measures of other buildings. Visualization/Analysis knowledge and information gained INFORMATION CONFIDENTIELLE NON DIFFUSABLE Compare energy consumption by each housing type before and after refurbishmen Compare energy consumption by each number of household before and after refurbishment Compare energy consumption on a yearly basis efore and after refurbishment We can see whether there are differences in the reduction of energy consumption by the housing type. We can see whether there are differences in the reduction of energy consumption by number of household. We can see whether there are differences in the reduction of energy consumption by season or year. 32

33 Subgraph Main graph Scenario3 (Confirmation of the effect of providing information) Compare energy consumption of the group that will carry out the visualization with the group that will not in Task3 We can see energy consumption reduction effect of visualization of Task3. Action It can be help for considering how much HEMS are introduced in the region. Visualization/Analysis knowledge and information gained 8000 Average of Power consumption per unit area of housing type Average of Power consumption per unit area of housing type Average of Power consumption per unit area of housing type3 INFORMATION CONFIDENTIELLE NON DIFFUSABLE Kwh 5000 Average of Power consumption per unit area of housing type4 Average of Power consumption per unit area of housing type5 Average of Power consumption per unit area of housing type6 Average of Gas consumption per unit area of housing type1 Average of Gas consumption per unit area of housing type2 Average of Gas consumption per unit area of housing type3 Average of Gas consumption per unit area of housing type4 Average of Gas consumption per unit area of housing type Average of Gas consumption per unit area of housing type6 Compare gas consumption of the group that will carry out the visualization with the group that will not in Task3 Compare water consumption of the group that will carry out the visualization with the group that will not in Task3 Compare the effect of visualization by housing type We can see gas consumption reduction effect of visualization of Task3. We can see water consumption reduction effect of visualization of Task3. We can see the effect of visualization of Task3 by housing type. 33

34 Subgraph Main graph Scenario4 (Confirmation of the power supply and demand situation in the region) Confirm the condition of local energy consumption and production. We can see the selfsufficiency status by renewable energy. Action It can be help for considering how much PV are introduced in the region in order to reduce CO2 emissions. The progress of the action plan can be reflected in the action plan for the future. Visualization/Analysis knowledge and information gained INFORMATION CONFIDENTIELLE NON DIFFUSABLE Confirm the breakdown of local energy consumption by usage Confirm the breakdown of local energy consumption by equipment Compare amount of CO2, population to comparable target value of base year on a yearly basis We can see which usage consumes a lot of energy by season. We can see which equipment consumes a lot of energy by season. We can see the progress of the action plan to reduce CO2 emissions and increase of population. 34

35 Subgraph Main graph Scenario5 (Confirmation of the status of usage of EV car sharing) % EV car share occupancy rate (%) Renewable energy supply rate for EV (%) Confirm changes in the time series of EV car share occupancy rate and renewable energy supply rate for EV Action Visualization/Analysis knowledge and information gained We can see whether EV supply from renewable energy are being carried out without reducing the car sharing operation rate. It can be help for considering measures of EV car sharing. INFORMATION CONFIDENTIELLE NON DIFFUSABLE Confirm available periods, lending periods and EV charging periods Confirm amount of EV charge and amount of energy produced by PV on a hourly basis Compare amount of EV charge to amount of energy produced by PV For examples, we can find that the proportion of available period rate is high and EV is not effectively used For examples, we can see how much it is possible for the PV power generation to charge EV. For examples, we can see how much PV power generation afford the EV charging each day or month. 35

36 Merci pour votre attention! 36