Building Energy Actuarial TablesFalcon EngineeringEdward H. Brzezowski
Course – IE7113, Fall 2013
Professor Robert Albano
Di YangRahul Rao
Onkar SawantAllay DesaiYash Shah
Oinam R Singh
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Energy Benchmarking
� Goal: Goal: Goal: Goal: To create a central repository of building related Energy Data and form an Energy Benchmarking System
� The system offers:
• Risk Assessment
• Cost and savings for improvements in operations and maintenance
• Opportunities for implementing energy measures in various building types.
� Information gathered was analyzed, curated and tabulated in the building energy actuarial tables that are easy to use and allow direct comparison of building metrics.
� Performed in-depth analysis of energy conservation measures to study their benefits and short comings.
� Analysis was performed in the form of Scenario A and Scenario B, each focusing on particular aspect of building specifications.
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Project Approach
Business Understanding
Data Preparation Data Modelling
Data Evaluation
Analysis & Deployment
Data Understanding
StepStepStepStep 1111: Develop thorough business understanding
StepStepStepStep 2222: Perform continuous iterations to model thedata base
StepStepStepStep 3333:::: Once model approved, determine methodsto verify and validate authenticity of the collecteddata
StepStepStepStep 4444: Develop an analysis and prepare data forfinal presentation
Accomplishments
� Tabulated energy database structure
� Harvested data manually and entered the ECM data in thedatabase
� Identified and categorized required ECM parameters
� Created a data validation process using:� Google forms
� Excel in-built validations
� Manual Validation
� Designed easy reference Scenario based on ECM parametersand building parameters to provide user an overview of appliedECM’s
� Designed an interactive Scenario table structure to provideuser a filtered graphical representation of the ECM’s
� Analyzed data to plot Frequency distribution charts based onfilters for ease of understanding
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Database Design
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E-R Diagram
ECM Summary (Scenario A)
� ECM summary is modeled based on the following parameters:
� ECM parameters
� ECM related information
� ECM type
� A dynamic table, which adjusts the values depending on the change in the database
� An overview of the type of building and its parameters, namely ECM savings percentage, ECM cost, ECM payback years etc.
� Provide ECM breakdown for the chosen building type, namely Heating, Ventilation, lighting etc.
� Calculated weighted average of ECM parameters
� Standard deviation column to show range of the payback years
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ECM Summary
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ECM Calculator (Scenario B)7
� ECM calculator is modeled based on the building parameters:� Building type� Building sub-type� Building square/feet
� A visual graphical representation that gives the user the option to choose specificBuilding type, Building sub-type, ECM category and Building square feet
� Provide weighted average of with ECM cost, Savings , Payback years for the chosencriteria
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ECM Calculator- Heating Analysis8
Payback years
Fre
qu
en
cy
� Frequency distribution is shown in an interactive graphical plot for given payback year ranges
� Normal distribution with a mean of 14.1 years and median between 15 to 18 years
� Graphs shows majority of the payback years between 12-18 years for heating
Demonstration
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Project Details
� Obstacles tackled:
� Interactive-VB script in excel
� Accuracy of data
� Categorization of ECM parameters
� Courses applied during the project work:
� Power systems
� Engineering Economics
� Quality Control and Improvement
� Project Management
� What did not work:
� Google form could not handle intricate details of the database
� Automatic data extraction tool
� Automatic data validation tool
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Lessons Learned
� Significance and types of Energy audit reports
� Key energy conservation parameters which affects thebuilding energy efficiency
� Processes involved in data mining activity viz., dataextraction, system modeling and validation, data analysis
� Application of MS Excel for extensive data warehousing andanalysis
� Brief understanding about automated data extractionprocesses
� Project scheduling and management skills
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Future Development
� Procure more data to improve accuracy of the analysis
� Broaden scope of project to all building types
� Extend building energy benchmarking to other parts of theU.S.A
� Migrate the current excel sheets to a database and develop aninterface on cloud for ease of data entry and quicker response
� Continue categorizing new ECM data into respective categoriesfor uniformity of the database
� Identify effective methods and tools to automate data validationand data extraction processes
� Equal weightage to be given to both data extraction as well asdata analysis (50-50) to utilize the procured data efficiently
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Summary
� The objective of the this project was to study the ECM’sand verify its effectiveness by structuring of datacollection and validation process and by analyzing theharvested data.
� The goal for the current period of the project was toconfirm if development of such a system was possible andif the data results will be useful.
� The initial results have been promising and show largescope for further analysis
� With further development of this system, moreinstitutions are bound to be attracted to support andcontribute to this cause leading towards a large centralrepository of building related energy data
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Course Review
� Identifying SMART objectives
� Maintaining a well oiled process to meet the deadlines and deliverables
� Emphasis on continuous optimization of the process implemented
� Quality is to be given preference in all circumstances
� It is essential to have the ability to deal with ambiguity
� Willingness to learn new skills to explore new areas of study which could effectively refine the project
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