• Share
  • Email
  • Embed
  • Like
  • Save
  • Private Content
Building Optimisation using Scenario Modeling and Linked Data
 

Building Optimisation using Scenario Modeling and Linked Data

on

  • 1,947 views

As buildings become more complex, it becomes more difficult to manage and operate them effectively. The holistic management and maintenance of facilities is a multi-domain problem encompassing ...

As buildings become more complex, it becomes more difficult to manage and operate them effectively. The holistic management and maintenance of facilities is a multi-domain problem encompassing financial accounting, building maintenance, human resources, asset management and code compliance, affecting different stakeholders in different ways. One technique, called scenario modelling, customises data-driven decision support for building managers during building operation. However, current implementations of scenario modeling have been limited to data from Building Management Systems with little interaction with other relevant data sources due to interoperability issues. Linked data helps to overcome interoperability challenges to enable data from multiple domains to be merged into holistic scenario models for different stakeholders of the building. The approach is demonstrated using an owner-occupied office building.

Statistics

Views

Total Views
1,947
Views on SlideShare
1,409
Embed Views
538

Actions

Likes
0
Downloads
13
Comments
0

5 Embeds 538

http://edwardcurry.org 466
http://flavors.me 60
http://edcurry.flavors.me 9
http://www.linkedin.com 2
http://prlog.ru 1

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment
  • {PA)s can relate to one objectGranularityObserved in contextContextualised information for end user
  • Need to pull information from across the enterprise, so you can understand energy use in context
  • Technology Stack uses tool from across the DERI house
  • Platform allows us to build very detailed energy management applications

Building Optimisation using Scenario Modeling and Linked Data Building Optimisation using Scenario Modeling and Linked Data Presentation Transcript

  • Building Optimisation using Scenario Modeling and Linked Data Edward Curry, James O’Donnell, Edward Corry 1st Workshop Linked Data in Architecture and Construction (LDAC2012) Ghent 28/29 March 2012
  • OverviewDigital Enterprise Research Institute www.deri.ie  Introduction  IRUSE (Built Environment)  DERI (Semantic Web/Linked Data)  LBNL (Built Environment)  Cross-domain Data for Building Management  Enhanced Decision Support with Scenario Modelling  Challenges  Linked Building Data  DERI Building Use Case Enabling Networked Knowledge
  • Who are IRUSE?Based at National University of Ireland, GalwayResearch Group of Civil/Mechanical Engineers5 post-docs & 7 PhDs 3
  • IRUSE interested in Building Optimisation during Operational Phase HVAC systems integration and Optimisation Information driven building operation Stakeholders specific performance dataEnergy SimulationBuilding Information ModelsCalibration of simulation models 4
  • About DERIDigital Enterprise Research Institute www.deri.ie  Founded June 2003 as a CSET (Centre for Science, Engineering and Technology).  Link scientists and engineers / academia and industry  Fundamental research  Development of Irish-based technology companies  Attract industry  Education & outreach  DERI Institute  CSET  Commercialization, DAI  EU, EI, direct industry, IRCSET  DERI strategic plan responds to priorities  Local: University focus on Informatics, Physical & Computational Sciences  National: SMART Economy, Program for Government  International: EU Digital Agenda Enabling Networked Knowledge
  • About DERIDigital Enterprise Research Institute www.deri.ie  Number one in its core space  Research Publications > 950  Participate in 17 standardisation groups (W3C, OASIS)  Approx 140 members from 30 nations  57 PhD’s /Masters  42 completed PhDs/Masters  Core Industrial Partners:  MNC’s: Cisco, Avaya, Bel-Labs, Ericsson…  SME’s: Storm, Celtrak, OpenLink……  Research: FBK  Total Research Grants: >€60 million  SFI, EU Framework, Enterprise Ireland, Industry Enabling Networked Knowledge
  • The 2012 DERI HouseDigital Enterprise Research Institute www.deri.ie DERI Applied Research Commercialisation eBusiness Green & eLearning Financial Services Sustainable IT Health Care Cyber Data eGovernment Life Sciences Security Linked Cloud Analyt Data ics Information Security, Cloud Data Sensor Social Software Mining Privacy Management Middleware and Retrieval & Trust Data Natural Service Reasoning and Knowledge Visualisation Language Oriented Querying Discovery and Interaction Processing Architecture DERI is designed to provide an integrated solution Enabling Networked Knowledge
  • Lawrence Berkeley National LaboratoryFounded in 1931 Awarded 13 Nobel Prizes ~ $850 Million annual budget 4200 Employees including: 1685 Scientists, Engineers and faculty 475 Postdoctoral fellows 560 Undergraduate and graduate student employees 8
  • My position and research activities at LBNL Energy and Environmental Sciences Environmental Energy Technologies Division Building Technology and Urban Systems DepartmentCreate whole building energysimulation models of buildings Create interoperable processes toDevelop software for whole building support whole building energy simulationenergy simulation Create stakeholder driven information display methods, based on automated data processing, for performance evaluation of buildings 9
  • IRUSE, LBNL, and DERI have Complementary Research Interests Main focus of interest at Decision IRUSE/LBNL Support Holistic Performance View Resource Performance Fault Stakeholder Financial Analysis Metrics Detection Analysis Management Analytic Layer Main focus of interest at DERI Operational Stakeholder Data Data Aggregation Layer RDF BMS BIM Utilities Weather FM Financial Other Data Raw Data Silos 10
  • Organisations incur substantial costs as a result of data mismanagement Confusion No Interoperability Cost Overruns Higher Costs Inefficiencies Building Manager 11
  • Research Motivation - a concrete example CO2 levels Time Monday Tuesday Wednesday Thursday FridayASHRAE 08:00-09:0062.1-2010 09:00-10:00 237 237 200 237 10:00-11:00 237 237 237 200 11:00-12:00 237 180 180 145 237 12:00-13:00 237 200 237 200 149 13:00-14:00 145 14:00-15:00 221 237 145 140 15:00-16:00 221 120 160 140 16:00-17:00 149 250 160 17:00-18:00 200 160 12
  • These are the types of data that we wish to leverageUtility Bills BMS Sensor & Weather Data Meter Data HR Occupancy Security FireSimulation Models Building Models Other DataOutput 13
  • Scenario Modelling provides a holistic interpretation of building performance 14
  • Define information required by stakeholder and related data Scenario DescriptionPerformance Building Performance Performance Formulae Datum Sources Aspects Objects Objectives Metrics A B C 15
  • A building manager would like to analyse comfort and energy consumption Scenario: Compare Comfort & Energy ConsumptionPerformance Building Performance Performance Formulae Datum Sources Aspects Objects Objectives Metrics Measured Datum 1: Zone Temperature ( C) Building Gymnasium Maintain Zone Zone Zone Temperature Temperature = (Datum1) Function Datum 1: Zone Temperature ( C) Simulated Measured Datum 1: Water Flow Rate (kg/s) Datum 2: Water Supply Temperature ( C) Datum 3: Water Return Temperature ( C) Energy Optimise Chiller Chiller Energy =(Datum 1*Constant ChillerConsumption Operation Output *(Datum3-Datum2)) Datum 1: Water Flow Rate (kg/s) Datum 2: Water Supply Temperature ( C)Constant = Specific Heat Capacity of Datum 3: Water Return Temperature ( C)output fluid measured in J/kgK Simulated 16
  • Cross-Domain PerspectiveDigital Enterprise Research Institute www.deri.ie ENERGY FINANCE ERP CARBON BMS Enabling Networked Knowledge
  • Key ChallengesDigital Enterprise Research Institute www.deri.ie  Initially developed a Performance Framework Tool  IFC based  Encountered significant roadblocks with BIM  Originally felt BIM was central pillar of performance assessment  Recognise an as-built BIM is one of many pillars  Technology and Data Interoperability  Data scattered among different information systems  Multiple incompatible technologies make it difficult to use  Dynamic data, sensors, ERP, BMS, assets databases, … Enabling Networked Knowledge 18
  • Linked Building DataDigital Enterprise Research Institute www.deri.ie  Linking building data builds context between systems  Relevant information can linked together to build holistic views of the building  Broader context can be used in decision making  Maintains loose coupling between systems  Allows domain systems to focus on their expertise  Allows systems to develop independently Enabling Networked Knowledge 19
  • IRUSE, LBNL, and DERI have Complementary Research Interests Main focus of interest at Decision IRUSE/LBNL Support Holistic Performance View Resource Performance Fault Stakeholder Financial Analysis Metrics Detection Analysis Management Analytic Layer Main focus of interest at DERI Operational Stakeholder Data Data Aggregation Layer RDF BMS BIM Utilities Weather FM Financial Other Data Raw Data Silos 20
  • Case Study: DERI BuildingDigital Enterprise Research Institute www.deri.ie  DERI Building  No BMS or BEMS  160 person Office space  Café  Data centre  3 Kitchens  80 person Conference room  4 Meeting rooms  Computing museum  Sensor Lab Enabling Networked Knowledge 21
  • DERI DataspaceDigital Enterprise Research Institute www.deri.ie Applications Decision Support Energy Analysis Energy and Situation Awareness Systems Model Sustainability Dashboards Apps Complex Events Services Support Entity Complex Event Data Provenance Search & Management Processing Catalog Query Engine Service Linked Data Adapter Adapter Adapter Adapter Adapter Sources Enabling Networked Knowledge
  • Building EnergyDigital Enterprise Research Institute www.deri.ie 1. Data from Enterprise Linked Data Cloud 2. Sensor Data 3. Building Energy Situation Awareness Enabling Networked Knowledge 23 of 26
  • DERI Energy ObservatoryDigital Enterprise Research Institute www.deri.ie Enterprise Energy Observatory Organisation Business Process Personal Linked dataspace for Energy Intelligence (Linked Data, Semantic Web, Semantic Sensor Networks) Enabling Networked Knowledge 24
  • Selected ReferencesDigital Enterprise Research Institute www.deri.ie  Curry, E., et al . (2011). An Entity-Centric Approach To Green Information Systems. 19th European Conference on Information Systems (ECIS 2011).  Hasan, S. et al. (2011). Toward Situation Awareness for the Semantic Sensor Web: Complex Event Processing with Dynamic Linked Data Enrichment. 4th International Workshop on Semantic Sensor Networks  Curry, E., & Donnellan, B. (2012). Green and Sustainable Informatics. In, Harnessing Green IT: Principles and Practices (in press). John Wiley & Sons  Curry, E. et al, Using Multi-Domain Data to Optimize Building Operational Performance: A Linked Data Approach to Interoperability. Advanced Engineering Informatics. (Under Review)  White, M. et al. An Energy Efficiency Metric to Report the Cost of Data Centre Services to Consumers in Real-Time. DCEE 2012, (Under Review)  Curry, E. et al. Towards an Open Platform for Holistic Real-time Enterprise Energy Intelligence: A Linked Data Approach, e-Energy 2012, (Under Review)  Curry. E. et al. Intel and IT Sustainability, MISQE, (Under Review) Enabling Networked Knowledge