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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