Presentation on theme: "ME 4343 HVAC Design Real-Time Building Energy Modeling and Fault Detection and Diagnostics for a DoD Building Bing Dong 1, Zheng O’Neill 2 1 University."— Presentation transcript:
ME 4343 HVAC Design Real-Time Building Energy Modeling and Fault Detection and Diagnostics for a DoD Building Bing Dong 1, Zheng O’Neill 2 1 University of Texas, San Antonio, TX, USA 2 University of Alabama, AL, USA The work was done at the United Technologies Research Center
Introduction Motivation Source: NBI report 2008 Energy Performance of LEED For New Construction Buildings
Introduction HVAC systems consume >20% more energy than design intent – Equipment performance degradation, and interact with other systems. – Existing control and information systems do not make visible system level energy consumption. Need for a scalable building energy management system that includes whole building energy diagnostics and visualization – Better HVAC operational controls and energy diagnostics – Raises the visibility of energy performance to help decision making
Building Facts Each 150K sf 2 Barrack – Compartments, classrooms and cafeteria/galley Cooling – Two absorption chiller: 450 ton – Chilled water loop with fixed-speed primary pump Heating – Steam from the base wide central heating plant – steam to water heat exchanger 5 AHUs for each building More than 200 VAV boxes with reheat coil A distributed Direct Digital Control System (DDC)
Technology Approaches 5 Core Layer: BIM-based Database BIM to BEM Real-time Data Acquisition Application Layer: Real-time energy simulation, visualization and diagnostics Overview of the Integrated Infrastructure
Technology Approaches Integrated Energy Modeling Approach
Technology Approaches 7 BIM to BEM automatic code generation Traditional Approach Building 7114 Architectural Model Building 7114 Mechanical Model BEM (Thermal Network Model) One Week
Technology Approaches 8 BIM to BEM automatic code generation Automatic data extract IFC BIM Database Automatic data extract BEM Input files Building 7114 Architectural Model BEM (Thermal Network Model) Building 7114 Mechanical Model Our Approach Traditional Approach Building 7114 Architectural Model Building 7114 Mechanical Model BEM (Thermal Network Model) One Week < 5 minutes!! gbXML
Technology Approaches 9 Real-time Data Acquisition Simens EMS Our DAQ sleeping area cafeteriaclassroom Outside view Naval Station Great Lakes (Bldg 7114) Extend BCVTB BACnet actors: 1) BACnet reader utility: Automatically generate a.xml configuration file and a.csv point description file based on the file created by Simens EMS 2) StoreBACnetDatatoBIMDatabase: Based on the.csv file, automatically create SQL statements based on the raw data received from EMS 3) DatabaseManager Establish the connection between BCVTB and BIM- based database Building Control Virtual Test Bed (BCVTB)
10 Results Real-time Energy Performance Visualization Building Hierarchy Interface Time-Series Energy Flows Interface Energy Statistics Pie Chart Interface
Results 11 Real-time Energy Simulation Building 7114 AHU3 secondary and primary system diagram Building 7114 Real-Time Simulation Results from 07/06/2011 to 07/11/2011.
Results OAT AHU energy OAD Airflow Damper Valve AHU network Reference ROM Building Operation data Train Inference Energy Impact Operation data OA damper 100% DAT setpoint cannot be maintained Building 7114 Building 7114 Energy Diagnostics: Economizer fault identified and corrected Economizer faults: Enthalpy calculation in control sequences is wrong Faults was corrected on Aug 3 rd, Measured chilled water energy consumption shows 18% savings were achieved
Conclusion This study has demonstrated an integrated infrastructure which integrates design information, database and real- time data acquisition in a real building to support energy modeling, visualization and FDD. 13 Observations and Lessons learned: Manually mapping BMS points of each HVAC component. The designed control logic in the HVAC control system is usually different from what is actually implemented locally. Communication with field people is necessary to get an accurate baseline model.
Acknowledgements: – DoD ESTCP program manager: Dr. Jim Galvin – UTRC: Dong Luo, Madhusudana, Shashanka,Sunil Ahuja, Trevor Bailey – Naval Station Great Lakes Energy manager: Peter Behrens Mechanical Engineer: Kirk Brandys Facility team Questions? 14 Thank you!