PRISM

PRISM logo.

Transforms run-of-the-mill billing data into statistically sound savings estimates. With PRISM (PRInceton Scorekeeping Method), utilities and energy analysts can systematically estimate total savings from a conservation or demand-side management program, for large samples of houses or buildings participating in the program, and for comparison groups as well. Enhanced model tuning and data pruning produce reliable savings estimates and statistics.

Keywords

utility billing data, demand-side management, statistical energy savings

Validation/Testing

N/A

Expertise Required

The package includes a Users' Guide to PRISM (Advanced Version 1.0) in two parts: 1) Getting Started, with tutorials to help those who have never used PRISM and to teach beginning and experienced PRISM users about the new features; and 2) Reference Manual, with a full description of the available options, including how to access them in the software and how to interpret the results. A complete bibliography listing PRISM reports available from Princeton University is also provided.

Users

More than 500 organizations.

Audience

Utilities, private firms, government agencies, and universities.

Input

Average daily outdoor temperatures, available free from NOAA and downloadable from their web site and monthly meter readings from Utility billing data.

Output

Weather-adjusted Normalized Annual Consumption (NAC) index, along with other physically meaningful parameters and extensive reliability statistics. A key feature of the method is its estimation of best reference temperature to which heating and cooling degree-days in the model are computed. PRISM is generally run on the pre- and post-weatherization periods for all buildings in a sample to produce distributions of savings across the sample. Participant and control groups are easily compared, in graphical and tabular forms.

Computer Platform

IBM PCs and compatibles (386 or higher) with Microsoft Windows 3.1 or 3.11, Windows 95 or Windows NT. At least 4 MB of RAM is recommended, with more RAM required for large data sets.

Programming Language

Fortran compiled in Visual Basic.

Strengths

Generally run on the pre- and post-weatherization periods for all buildings in a sample to produce distributions of savings across the sample. Participant and control groups are easily compared, in graphical and tabular forms. Handy for analyzing individual building energy signatures. Additional features include: - Input data translators (including procedure for treating estimated readings) - Statistical summaries of temperature data - Automated model selection (to match the consumption data to appropriate model) - Automated identification and correction of undesignated estimated readings - Identification of cases with anomalous data, and automated application to these cases - Aggregate versions for weather adjustment of utility aggregate sales data - Interactive ("point-and-click") graphics for individual-building analysis - User-specified reliability criteria - Standardized summary of savings results for control vs. participant groups.

Weaknesses

None.

Contact

Company:

Princeton University

Address:

Program on Science & Global Security
Princeton, New Jersey 08542
United States

Telephone:

(847) 733-1469

Facsimile:

(847) 733-1473

E-mail:

marean@princeton.edu

Website:

http://www.princeton.edu/~marean

Availability

See the web site for more information and ordering instructions.