# Presentation: 737902

## Analysis of Utility Project Data

*Bill Sandusky*
*Pacific Northwest National Laboratory*

## Why I’m I talking today?

- Kate and I have received data from agencies and utilities for years, so now it is time to give you some analytical results back!
- Also, we need a reality check!
- Show the value of data!

## Provide credit where it’s due!

- Information you will see is contained in the article “*Analysis of Energy Savings in the Federal sector through Utilities Service Programs”*
*Contributors to that article include:*
*Kate McMordie Stoughton*
*Amy Solana*
*Rick Bates*
*Bill Sandusky*

## Analysis Objectives

- Provide a baseline of information regarding UESC projects to support  FEMP Utility Program
- Better estimate Btus saved per dollar invested
- Conduct a limited quality check on individual project data

## Data Base Characteristics – Utility Projects

- Data obtained from utilities, sites, or agency data bases
- Covers period of January 1, 1994 through July 31, 2004
- Data for more than 1,200 projects
- Complete data for 528 projects
- Covers 80 utilities

## Investment of Awarded Projects

## Types of Energy Conservation Measures (ECMs)

- Analysis
- Boiler/Chiller
- Central Plants
- Comprehensive Upgrades
- Controls/Upgrades/Repairs
- Distributed Energy
- HVAC/Motors/Pumps
- Insulation/Envelope
- Lighting Only

## Types of ECMs - Continued

- Lighting and Mechanical Systems
- Renewable
- Water
- Other (e.g., demand control and transformer replacement)
- Unknown

## Analysis Sub-Data Set Characteristics

- Eliminate ECM projects for:
- Insulation/Envelope
- Analysis
- Water
- Other
- Unknown
- Include projects with sufficient data n=528
- Create typical range of values (plots)
- Eliminate projects with following:
- Inaccurate reported data
- Anomaly in project cost or savings calculation
- Ambiguous project description

## Number of Projects by ECM Category – Analysis Sub-Set

## Capital Investment by ECM Category – Analysis Sub-Dataset

## Relating Capital Investment to Btu Saved

- Gain better understanding of the value of utility projects toward meeting energy goals
- Determine variance in savings among ECMs
- Identify better implementation strategy (if it exists)
- Estimate savings for projects with missing data

## Curve Fitting Analysis Approach Models

- Simple Linear Model
- Y = ao + a1X
- Simple Non-linear Model
- Y = aXb
- Taking logarithm of both sides
- LogY=Loga+bLogX

## Data Plot – All ECMs

## Data Plot – Controls/Upgrades/Repairs

## Data Plot - Lighting

## Data Plot - Renewables

## Simple Liner Model – Slopes and Confidence Intervals

## Observations – Utility Programs

- Capital investment is not uniform across all regions of the country.
- DOD has made the largest use of utility alternative financing programs.
- Lighting and mechanical systems are the utility projects of choice, based on past data.
- Energy savings varies markedly across ECM categories.
- Controls/upgrades/repairs yield largest return.

## Next Steps – Analysis Activities

- Re-evaluate some project data.
- Compare to ESPC project results on an ECM by ECM basis.
- Incorporate additional data collected or provided for projects after July 2004.
- Provide results in time-series format.