Measurement Science Roadmap for Net-Zero Energy Buildings

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information to “spotlight” or identify poor performing buildings. Another keylimitation is the lack of data on fault frequency and its impact on energy use.Control systems are an essential enabling technology in intelligent buildings.Advancement of control system technology is impeded by a lack of dynamicsimulation models and robust optimization techniques that work in discontinuoussystems.Non-Technical ChallengesOwnership of building energy use is an overarching challenge. One of the mostcritical barriers to adoption of intelligent building technology is the disconnectionbetween who makes the initial decision to invest, or not, in the energy-efficientsystem and who actually pays the cost or reaps the benefits over time. The centralissue comes down to determining who actually has ownership of the energy use ina building (e.g., the owner, manager, and occupant).Privacy concerns and human behavior are an impediment. Utilities, for example,are currently reluctant to share existing data due to privacy issues and areconcerned that data could be used to penalize customers. Fundamentalunderstanding about how occupants and buildings interface ⎯which has manycomplexities based on human behavior⎯is needed and will most likely requireinput and study by psychologists or social scientists. To use intelligent systems,consumers may need incentives other than just cost, such as “cool” gadgetry oraesthetics.D. Measurement BarriersA number of measurement barriers and challenges were identified that arecritical to the development and implementation of intelligent buildingtechnologies. These are summarized in Table IV-2 by topical area, with therelative priorities indicated.Some of the most critical measurement challenges include:• Data and methods for assessing the performance of buildings,• Tests and test beds for the evaluation of controls technology and faultdetection approaches,• Best practices guidelines for intelligent design and operation of buildings,• Measurements to support automation of commissioning processes, and• Low-cost, reliable energy metering systems.Table IV‐2. Intelligent Buildings – Measurement Barriers and Challenges(● = one vote)Data Sharing and ProtocolsHighPriority• Lack of standards for collecting and sharing data ●●●●●●– Standard data format that enables easy sharing of data– Data protocols for all facets of data collection– Lack of standard format for transferring data from systems to analysis tools– Protocols for integrating large quantities of sensor data– Clear data ownership⎯defined standards and methodologies to control flow ofdata so building owner can select which data are sent “upstream”26 Measurement Science for Net-Zero Energy Buildings
Table IV‐2. Intelligent Buildings – Measurement Barriers and Challenges(● = one vote)Data Sharing and Protocols (continued)MediumPriorityLowerPriority• Lack of protocols to measure equipment performance in situ ●●• Data sharing ⎯a universal database for actual energy performance data is notavailable, and many are unwilling to share data ●●• Inability to measure privacy impacts on data, alone or in combination with otherdata, or in models or predictive tools ●• Lack of buy‐in from providers to feed data into database ●Data Collection and InterpretationHighPriorityMediumPriorityLowerPriority• Challenging data requirements and analysis for assessing building performance,including ●●●●●●●●●●●– Identifying the critical parameters for building design, the accuracy needed, andways to measure these in real buildings– Gathering a minimal set of data to assess building energy consumption (to withina known accuracy)– Metrics to measure performance (vs. models that use those measures)– Lack of clear definition of how data will be used– Inability to fix what is not understood, i.e., lack of ways to identify the worstperforming buildings– Accuracy of sensors to measure inaccurate mechanical systems (e.g., dampers)• Lack of analysis tools to mine and interpret data ●●●• Lack of effective methods for binning data (e.g., building type, vintage)Sensors and Control SystemsHighPriorityMediumPriorityLowerPriorityModels and SimulationHighPriority• High cost of sensors/systems for measuring local consumption of electric power andother energy sources⎯precludes broad application to systems, equipment, and endusers ●●●●●●• Difficult to evaluate control strategies due to in situ system interactions ●●●• Lack of systems integration focus and a centralized control grid/network ●• Difficulty making sensors unobtrusive and integrated into structure or appliances ●• Lack of a comfort sensor and algorithm to capture comfort and calibrate it todifferent preferences• Difficulty deploying efficient, comprehensive sensor networks and lack of methods forplacing sensors to achieve best results• Understanding inputs from fusion of mobile data sources before deploying fixedsensing sources• Limited ability to extract effective model inputs by mining standardized data,including ●●●●●– Data on behavior/use of energy‐consuming appliances and demand load on grid– Energy models (linking measurable output to behavior/weather)– Field data to reduce the uncertainty in energy savings (compared toimplementation costs) for energy efficiency strategiesMeasurement Science for Net-Zero Energy Buildings 27
Page 1: NIST Technical Note 1660Measurement
Page 4 and 5: Certain commercial entities, equipm
Page 7 and 8: PREFACEThis report summarizes the r
Page 9 and 10: EXECUTIVE SUMMARYBuildings account
Page 11 and 12: I. INTRODUCTIONA. Background and Im
Page 13 and 14: • Building Envelope Energy Reduct
Page 15 and 16: advances in technology and knowledg
Page 17 and 18: Table III‐1. Onsite Energy Produc
Page 19 and 20: needs to be resolved for urban buil
Page 21 and 22: Table III‐2. Onsite Energy Genera
Page 23 and 24: Exhibit III.1. On-Site Energy Produ
Page 33 and 34: IV. INTELLIGENT BUILDINGSIntelligen
Page 35: Near Term: Systems that provide inf
Page 39 and 40: E. Priorities for Measurement Scien
Page 41 and 42: Exhibit IV.2. Intelligent Buildings
Page 47 and 48: B. Critical TechnologiesA wide vari
Page 49 and 50: difficult to efficiently integrate
Page 51 and 52: Sensors (continued)LowerPriorityBui
Page 53 and 54: Exhibit V.1. Whole Buildings Measur
Page 59 and 60: VI. BUILDING ENVELOPEBuilding energ
Page 61 and 62: Long Term: Energy efficiency rating
Page 63 and 64: Sensors (continued)LowerPriorityBui
Page 65 and 66: Exhibit VI.1. Building Envelope Mea
Page 71 and 72: B. Critical TechnologiesMore energy
Page 73 and 74: optimize and recalibrate when neces
Page 75 and 76: Table VII‐2. Building Equipment -
Page 77 and 78: Exhibit VII.1. Building Equipment M
Page 79 and 80: Exhibit VII.3. Building Equipment M
Page 81 and 82: APPENDICESMeasurement Science for N
Page 83 and 84: Whole BuildingsBill Bahnfleth Penns
Page 85 and 86: APPENDIX C: ACRONYMSANSI:ASHRAE:AST

Measurement Science Roadmap for Net-Zero Energy Buildings

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