MasterofScienceinBuildingPerformance&Diagnostics(MSBPD)

FinalThesisProjectPresentations

FacultyAzizan Aziz :EricaCochranHameen :VivianLoftness

10:00– 10:20 Aakash Goliyan “DynamicExternalShadingDevicestoMaximizeOccupantComfortandEnergySavingsinOfficeBuildings"

10:20– 10:40 ChenZhou“IdentifyingPotentialBenefitsofIntegrated Passive Strategies with MixedModeVentilationinCommercialBuildings”

10:40– 11:00 Xiaowen Gu “EvaluationofThermalComfortinNaturallyVentilatedOfficeBuildingswithDoubleSkinFaçade”

11:00– 11:10 BREAK

11:10– 11:30 KevinBoyd“SmartMeterAnalytics”11:40– 11:50 Yuzhe Liu“EvaluationofaFaultDetectionandDiagnosticsAlgorithmforVAVBoxes”11:50– 12:10 HanLi“IdentifySignificantAlarmsfromBASAlarmsPackagesandEvaluateTheirImpact”

12:10– 12:40 LUNCH

12:40– 1:00 Siliang Lu“DynamicHVACOperationsbasedonOccupancyPatternswithReal-timeVision-basedSystem”

1:00– 1:20 Nilesh Bansal“UtilizingMachineLearningTechniquestoPredictEnergyConservationMeasuresinBuildings”

1:20– 1:40 Yuqi Pan“Multi-criteriaEvaluationofBuildingRetrofit/Re-tuningStrategies”

SCHEDULE

AakashGoliyan

This study aims to develop framework for the selected dynamic external shading devices to achieve maximumoccupant comfort and energy savings inside an office building. The framework integrates daylightperformance metric, dynamic occupancy schedules and multi-criteria optimization algorithm to achieveoccupant comfort (as primary objective) and energy savings (as secondary objective).

Fig. 1 External louvers installed at AGC Headquarters, Belgium The figure shows how the installed external louvres adapt automatically to different climate conditions.

Image reference: https://www.glassonweb.com/article/evaluation-adaptive-facades-case-study-agc-headquarter-belgium

DynamicExternalShadingDevicestoMaximizeOccupantComfortandEnergySavingsinOfficeBuildings

Fig. 1 External automated shading uses intelligent controlsystems to automatically track the sun and position bladeelements to block direct glare, while still allowingpenetration of natural daylight

IdentifyingPotentialBenefitsofIntegrated Passive Strategies with MixedModeVentilationinCommercialBuildings

ChenZhou

Images: http://www.cbe.berkeley.edu/mixedmode/, http://terrawisehomes.com/, http://mimg.org.my/

MixedModeVentilation buildings which combines themechanicalventilationwithnaturalventilation hasbeenproved to improve thermal comfort as well as save energy in severalregionsofEurope,NorthAmericaandAsia.Thisthesisprojectaims to use simulation tools to identifyand compare thepotential benefitsofintegratedpassive strategies with mixedmodeventilationinhigh-rise officebuildingsunder three differentclimates interms of energyefficiency andthermalcomfort levels.

Buildings in mixedmodeventilation integrated with passive strategies.(http://www.szibr.com/, DaveBurk,2016)

EvaluationofThermalComfortinNaturallyVentilatedOfficeBuildingswithDoubleSkinFaçade

XiaowenGu

(Barbosa&Ip,2016)

This thesis project investigates the influence of double skin façade (DSF) onthermal comfort in naturally ventilated office buildings in hot climate. It isintended to provide architects and engineers with some insights into theconceptual design of office buildings with DSF.

http://www.paladinoandco.com/wp-content/uploads/2015/12/Gensler_PNC_03.jpg

http://intercongreen.com/2010/05/04/green-buildings-the-cambridge-public-library/

Newelectric,gas,andwatermetersthatareabletoprovideusagedatawithresolutionsof15minutesorlessarebeingwidelydeployedbyutilitycompaniesinresponsetodemandsfrompolicymakersandshareholders.

Myresearchaimstoprovideasetofmethodstoidentifyfacility- andportfolio-scaleopportunitiesforbenchmarking,instantaneousaudits,andbehavioralimpactobservation.

SmartMeterAnalyticsKevinBoyd

Image:userKristoferb,WikimediaCommons (CreativeCommonsLicense)

EvaluationofaFaultDetectionandDiagnosticsAlgorithmforVAVBoxes

Faultdetectionanddiagnosticsincross-levelbuildingsystemsimprovesFacilityManagertasksbyautomatingtheongoingcommissioningprocess.Thisprojectaimstoevaluateadataminingalgorithm(Model,ClusterandCompare)forfaultdetectionofvariableairvolume(VAV)boxestoimproveaccuracyandenergyefficiency.

Reference:Najafi,M.(2010).FaultDetectionandDiagnosisinBuildingHVACSystems.UCBerkeley.Retrievedfromhttp://escholarship.org/uc/item/6w02z2hmKatipamula,S.,&Brambley,M.(2005b).ReviewArticle:MethodsforFaultDetection,Diagnostics,andPrognosticsforBuildingSystems—AReview,PartII.HVAC&RResearch,11(2),169–187.

HVACFDDhierarchy(Najafi,2010) ClassificationofFDDmethods(Katipamula&Brambley,2005b)

YuzheLiu

VAVbox

IdentifySignificantAlarmsfromBASAlarmsPackagesandEvaluateTheirImpact

HanLi

Thisstudyinvestigatesthepossibilityofusingstatisticalmethodstofilter,cluster,andrankBuildingAutomationSystem(BAS)alarmsfrommulti-objectiveperspectives.TheoutcomesofthisstudywillhelpfacilitymanagerstooptimizebuildingsystemOperationandMaintenance(O&M)perdifferentusepurposessuchassavingenergy,improvingthermalcomfort,andreducingrepairingefforts.

Figure 2. Framework of Alarm Management Tool for BAS Figure 1. Modern BAS

Image: https://www.linkedin.com/pulse/understanding-building-automation-control-systems-francois-marcil?articleId=8399161764881533039#comments-8399161764881533039&trk=sushi_topic_posts

HVAC is one of the most important components to determining energyconsumption and comfort level in a building. Currently, most of existing HVACsystems are being operated without the ability to adjust in response todynamic occupancy profiles. Due to this inefficiency, much of energy is wasted.To solve this problem, the project proposes a real-time vision-based occupantpattern recognition system by realizing occupancy counting and activity levelclassification. The results showed accuracy for counting and activity levelclassification could be over 90% without many occlusions and the energymodel showed dynamic schedules indeed can bring about energy savings andincrease comfort level.

Videorecording

Videostream

Videoprocessing

Occupancycounting

Activitylevelclassification

Clothingrecognition,etc.Energy-based

HVACcontrolPMV-basedHVACcontrol

DynamicHVACOperationsbasedonOccupancyPatternRecognitionwithReal-timeVision-basedSystem SiliangLu

F’(x)Impact1. Identifyoutlierswithoutauditingall

buildings2. SuitableECMsprediction3. Saveauditcost$3000-$150004. Save3monthsofaudittime5. Scaletocitylevel(predictingECMs)6. UsefulforPolicymakers,Large

buildingportfolioowners,Utilitycompanies,Facilitymanagers,Buildingowners

NileshBansalUtilizingMachineLearningTechniquestoPredictEnergyConservationMeasuresinBuildings

Multi-criteriaEvaluationofBuildingRetrofit/Re-tuningStrategies

This study aims to develop a comprehensive multi-objective optimization framework for building retuning decisionmaking. The framework integrates building performance model and multi-objective algorithm to providequantitative assessment and trade-offs of solutions regarding different objectives The results from multi-objectiveoptimization model is refined to address the specific project goal.

Fig.2Commonretuningstrategies[1]Fig.1Structureofco-simulationplatform

[1]Fernandez,N.,Taasevigen,D.,Underhill,R.M.,2016.SuccessofCommercialBuildingRetuninginFederalBuildings :ResultsandCaseStudies.J.Archit.Eng.1–10.doi:10.1061/(ASCE)AE.1943-5568.0000216.

YuqiPan