Building Optimisation using Scenario Modeling and Linked Data

Edward Curry
Edward CurryResearch Unit Leader at Digital Enterprise Research Institute (DERI)
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
Overview
Digital 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, Galway

Research Group of Civil/Mechanical Engineers

5 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 data



Energy Simulation

Building Information Models

Calibration of simulation models

                                                                           4
About DERI
Digital 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 DERI
Digital 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 House
Digital 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 Laboratory

Founded 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 Department




Create whole building energy
simulation models of buildings                     Create interoperable processes to
Develop software for whole building                support whole building energy simulation
energy 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 Friday
ASHRAE
                                          08:00-09:00
62.1-2010                                 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 leverage




Utility Bills       BMS                      Sensor &
                                                          Weather Data
                                             Meter Data




                                                                  HR
                                                               Occupancy
                                                                Security
                                                                  Fire

Simulation Models          Building Models                      Other Data
Output

                                                                             13
Scenario Modelling provides a holistic interpretation of
                building performance




                                                       14
Define information required by stakeholder and related
                            data
                                Scenario Description
Performance   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 Consumption
Performance            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
                        Chiller
Consumption                              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 Perspective
Digital Enterprise Research Institute                                             www.deri.ie



                                                 ENERGY




                              FINANCE                            ERP




                                        CARBON            BMS




                                                            Enabling Networked Knowledge
Key Challenges
Digital 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 Data
Digital 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 Building
Digital 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 Dataspace
Digital 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 Energy
Digital 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 Observatory
Digital 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 References
Digital 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
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Building Optimisation using Scenario Modeling and Linked Data

  • 1. 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
  • 2. Overview Digital 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
  • 3. Who are IRUSE? Based at National University of Ireland, Galway Research Group of Civil/Mechanical Engineers 5 post-docs & 7 PhDs 3
  • 4. IRUSE interested in Building Optimisation during Operational Phase HVAC systems integration and Optimisation Information driven building operation Stakeholders specific performance data Energy Simulation Building Information Models Calibration of simulation models 4
  • 5. About DERI Digital 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
  • 6. About DERI Digital 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
  • 7. The 2012 DERI House Digital 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
  • 8. Lawrence Berkeley National Laboratory Founded 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
  • 9. My position and research activities at LBNL Energy and Environmental Sciences Environmental Energy Technologies Division Building Technology and Urban Systems Department Create whole building energy simulation models of buildings Create interoperable processes to Develop software for whole building support whole building energy simulation energy simulation Create stakeholder driven information display methods, based on automated data processing, for performance evaluation of buildings 9
  • 10. 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
  • 11. Organisations incur substantial costs as a result of data mismanagement Confusion No Interoperability Cost Overruns Higher Costs Inefficiencies Building Manager 11
  • 12. Research Motivation - a concrete example CO2 levels Time Monday Tuesday Wednesday Thursday Friday ASHRAE 08:00-09:00 62.1-2010 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
  • 13. These are the types of data that we wish to leverage Utility Bills BMS Sensor & Weather Data Meter Data HR Occupancy Security Fire Simulation Models Building Models Other Data Output 13
  • 14. Scenario Modelling provides a holistic interpretation of building performance 14
  • 15. Define information required by stakeholder and related data Scenario Description Performance Building Performance Performance Formulae Datum Sources Aspects Objects Objectives Metrics A B C 15
  • 16. A building manager would like to analyse comfort and energy consumption Scenario: Compare Comfort & Energy Consumption Performance 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 Chiller Consumption 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
  • 17. Cross-Domain Perspective Digital Enterprise Research Institute www.deri.ie ENERGY FINANCE ERP CARBON BMS Enabling Networked Knowledge
  • 18. Key Challenges Digital 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
  • 19. Linked Building Data Digital 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
  • 20. 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
  • 21. Case Study: DERI Building Digital 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
  • 22. DERI Dataspace Digital 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
  • 23. Building Energy Digital 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
  • 24. DERI Energy Observatory Digital 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
  • 25. Selected References Digital 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

Editor's Notes

  1. {PA)s can relate to one objectGranularityObserved in contextContextualised information for end user
  2. Need to pull information from across the enterprise, so you can understand energy use in context
  3. Technology Stack uses tool from across the DERI house
  4. Platform allows us to build very detailed energy management applications