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Cyber-physical System Modeling using Modelica for Smart and Sustainable Communities Jing Wang 1 , Sen Huang 2 , Wangda Zuo 1 1 Sustainable Buildings and Societies Laboratory, University of Colorado Boulder 2 Pacific Northwest National Laboratory


  1. Cyber-physical System Modeling using Modelica for Smart and Sustainable Communities Jing Wang 1 , Sen Huang 2 , Wangda Zuo 1 1 Sustainable Buildings and Societies Laboratory, University of Colorado Boulder 2 Pacific Northwest National Laboratory 9/18/2020 1

  2. Introduce the Speakers Jing Wang, Ph.D. Candidate Jing is a PhD Candidate in Architectural Engineering at University of Colorado Boulder. Her research interests are resilient energy systems, building energy system modeling and control, building-to-grid integration. She is an ASHRAE Student Member. Sen Huang, Ph.D. Sen Huang joined the Pacific Northwest National Laboratory as a scientist in May 2016. Before joining PNNL, he worked as a building services engineer at Arup (2011- 2012), a teaching assistant (2013) and a research assistant (2014-2016) both at the University of Miami. 2

  3. Acknowledgement • This presentation is supported by the following projects: • U.S. Department of Energy, Energy Efficiency and Renewable Energy, Building Technologies Office, under Contract No. DE- AC05-76RL01830. • National Science Foundation under Award IIS-1802017. • Special thanks to Dassault Systèmes and Barcroft Technology for providing free Dymola licenses during the workshop! 3

  4. Background Vision of future smart cities Communication System Transportation network Communication Flux Energy Flow Wireless Signal Solar Panel Thermal Energy Storage Energy System Charging Station Air Conditioning Centralized HVAC Household Appliances Residential Commercial Buildings Buildings Electric heating Lighting system Autonomous electrical vehicle Transportation System Hydro Communication Tower Wind Park 4

  5. Goals and Challenges Modeling for smart and sustainable communities Interdependency Modeling Optimal Operation Built Environment Improving Dynamic System Controls 5

  6. Who are we? Principal Investigator: Prof. Wangda Zuo • 9 PhD Students • 1 Visiting PhD Student • 3 Graduate/Undergraduate Research Assistants Major Research Projects • Modelica library development • Modelica Buildings Library • Data Center package • District Heating & Cooling • Modelica supported research • Occupancy-centric flexibility quantification • Building-to-grid integration Homepage: https://www.colorado.edu/lab/sbs/ 6

  7. NSF Funded Development BIGDATA: Collaborative Research: IA: Big Data Analytics for Optimized Planning of Smart, Sustainable, and Connected Communities (9/16-8/21), National Science Foundation, collaboration with Virginia Tech. Smart and Connected Community Library Net-Zero Energy Community Library CU Boulder Virginia Tech • Kathryn Hinkelman • • Dr. Wangda Zuo Dr. Walid Saad • Jessica Stershic • • Xing Lu Dr. Harpreet Dhillon • Jing Wang 7

  8. DoE Funded Application C3PO: Comprehensive Pliant Permissive Priority Optimization (10/18-9/20), Department of Energy, collaboration with PNNL and ORNL. Stochastic occupancy module Occupancy- based control Occupant- centric optimization CU Boulder PNNL ORNL • • • Dr. Wangda Zuo Dr. Draguna Vrabie Dr. Piljae Im • • • Jing Wang Dr. Sen Huang Dr. Yeonjin Bae • Dr. Jian Sun 8

  9. SCC Library - Proposed Framework Transmission Block A Block B City Layer Com munication Communicative Roads Energy Transportation Power Lines Block C Communication Center Road Network Grid Network Com munication ... ... Energy Transportation Multi Layer Multi-layer Block B Block A Block C Multi-block Community Block Layer Multi Block Communication Packets for Packets for Transportation Energy control navigation Control Routing events events Charging Control/ demand Price signal Control / Price signal Multi-agent System Agent Layer Multi Agent Charging demand 9 Renewable enengy Charging Distribution Storage Consumption Road/Vehicles generation infrastructure

  10. SCC Library - Models Energy + Comm. Transport + Comm. Energy + Transport weaDat weaDat qRes resBlo T+C powRes powRes resBlo numPacRes E+C resBlo E+T nevRes qRes numPac1 comBlo E+T powCom comBlo comBlo E+C powCom T+C numPacCom nevCom qBlo numPac2 qCom Distribution System Communication System Transportation System numPac1 comBlo ter1 RL8 RL13 pow8 pow13 RL8 RL13 numPac2 RL4 pow4 RL4 roa1 lin7 lin7 lin15 lin15 lin11 lin11 ter2 RL9 RL10 RL14 RL9 pow9 RL10 pow10 RL14 pow14 lin2 lin2 lin14 lin14 lin8 lin8 res com tra1 roa2 RL5 RL11 RL12 pow5 pow11 pow12 RL5 RL11 RL12 resBlo lin4 lin4 lin16 lin16 lin13 lin13 RL6 RL7 RL16 RL15 pow6 pow7 pow16 pow15 RL6 RL7 RL16 RL15 ter3 tra2 EV Charging Road Battery PSta term_p int2 k=0 batMod1 I batCon.y == 1 traCos batMod2 k=1 numVeh int1 Delay batCon.y == 2 abs((int1.y - int2.y)/3600) swi1 numEV PowerCha I loaEV PEV loaEV add.y - batCon.thrCha k=1 numEV*PChar qIn swi2 varDel qOut PowerDis batBan SOC term_p P add.y - batCon.thrDis P delayMax=100000000 s add PSup +1 10 + batCon roaTyp +1 PDem

  11. Coupled Infrastructure Networks Residential District Residential District Communication Resistance Energy Roads System Power Cable Commercial District 11

  12. Energy Model Energy Simple Load System Model Detailed Model Communication Tower Load 12

  13. ሶ Transportation Model Road Model 𝛽 1 𝑉 𝑡 U = Charging Station Model 𝛾 1 + 𝑊 𝐷 𝑙 𝑗𝑜 𝑙 𝑝𝑣𝑢 3 𝛾 = 𝛽 2 + 𝛽 3 𝑊 𝑂 = ෍ 𝑟 𝑗𝑜 − ෍ 𝑟 𝑝𝑣𝑢 𝐷 𝑗=1 𝑗=1 U · ׬ 𝑟 𝑝𝑣𝑢 − 𝑟 𝑗𝑜 𝑒𝑢 V = 𝑀 13

  14. Validation 24.0 Original Data Power Distribution 23.5 Simulation Results Literature Comparison: Bus Voltage (kV) 23.0 Civanlar, S., Grainger, J. J., Yin, H., 22.5 & Lee, S. S. H. (1988). Distribution feeder reconfiguration for loss 22.0 reduction, in IEEE Transactions on Relative errors are within 21.5 Power Delivery, 3, 3, 1217-1223. 2% for all locations 21.0 3 5 7 9 11 13 15 17 Bus Number Road Model Literature Comparison: Ang, K. C. & Neo, K. S. (2005). Real-life application of a simple continuum traffic flow model,’ International Journal of Mathematical Education in Science and Technology, 36, 8, 913 – 922. 14

  15. Case Study • At high traffic hours (around 8:00 and 18:00), the communication system deteriorates the traffic condition due to poor packet arrival rates. (a) • The deviation of power draw prediction increases during the peak commuting times (circled). The largest deviation ratio of 7% occurs around 8:00. (b) 15

  16. Workshop Tutorials Tutorial 1: Residential Tutorial 2: Coupling Energy District and Transportation Systems 16

  17. Summary • We developed a multi-domain modeling framework, which integrates the energy, transportation, and communication systems. • An open source Modelica Smart and Connected Community (SCC) library utilizing our 3M approach has been released. • The workshop cases demonstrate the application of the modeling framework for studying the operation of future connected communities. 17

  18. Net Zero Energy Community (NZEC) Library • What? • An open source library for the NZECs • This library consists of • components for subsystem of NZECs • A system model for a real-world NZEC in Florida • Who should use it? • Building owners who seek for economically sound design • Building operators who seek for optimal and resilient operation • Researchers who develop advanced control strategies Historical Green Village Subsystems 18

  19. Major components • Containing both physics-based (Modelica) and data-driven (ANN) models • Standard interfaces for considering the interactions between subsystems Performance Weather bus Zone Dataset Controller Renewable Energy Subsystem Grid Subsystem Internal PV Wind heat gain Grid GSHP Panel Turbine Bus Bus Condenser water loop Buildings Bus Domestic Hot Water Subsystem Subsystem Heat recovery loop Bus Bus Physics-based Solar Building Heater Bus Bus Bus Bus Bus Heat Pump Electricity Domestic Hot Water Heating /Cooling Air Heating /Cooling Water Data-driven Ground-coupled Heat Pump Subsystem Heat Exchanger Borehole 19 Recovered Heat

  20. Components - Validations • Unit tests were performed to validate the accuracy of the components Heat Pump PV 20

  21. Historical Green Village A community consisting of both residential buildings and commercial buildings Location Anna Maria Island, FL Floor area Building Type HVAC system (kW) DHW system (m 2 ) F Bakery 410 HP (19.5) Gas heater G1 Office 95 HP (8.22) Gas heater G2 Residential 95 HP (8.22) Solar thermal water heater A1-W Gift shop 88 HP (8.22) Electric heater A1-E Gift shop 56 HP (11.07) A2 Residential 94 HP (11.07) Solar thermal water heater D Gift shop 95 HP (15.07) Electric heater C1 General store kitchen 120 HP (15.07) Solar thermal water heater C2 Ice cream shop 40 HP (15.07) Achieved the net zero energy goal in 2014 150,485 119,448 118,096 116,582 105,133 102,828 [kWh] 43,141 37,301 2011 2012 2013 2014 21 Annual Electricity Generation Annual Electricity Demand

  22. System Model - Model Diagram Weather bus Irradiation PV information Power Grid Information bus GSHP Building DHW 22

  23. System Model - Validation 23

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