|Title||Commercial Building Energy Baseline Modeling Software: Performance Metrics and Method Testing with Open Source Models and Implications for Proprietary Software Testing|
|Year of Publication||2013|
|Authors||Phillip N Price, Jessica Granderson, Michael D Sohn, Nathan J Addy, David A Jump|
|Institution||Lawrence Berkeley National Laboratory|
The overarching goal of this work is to advance the capabilities of technology evaluators in evaluating the building-level baseline modeling capabilities of Energy Management and Information System (EMIS) software. Through their customer engagement platforms and products, EMIS software products have the potential to produce whole-building energy savings through multiple strategies: building system operation improvements, equipment efficiency upgrades and replacements, and inducement of behavioral change among the occupants and operations personnel. Some offerings may also automate the quantification of whole-building energy savings, relative to a baseline period, using empirical models that relate energy consumption to key influencing parameters, such as ambient weather conditions and building operation schedule. These automated baseline models can be used to streamline the whole-building measurement and verification (M&V) process, and therefore are of critical importance in the context of multi-measure whole-building focused utility efficiency programs.
This report documents the findings of a study that was conducted to begin answering critical questions regarding quantification of savings at the whole-building level, and the use of automated and commercial software tools. To evaluate the modeling capabilities of EMIS software particular to the use case of whole-building savings estimation, four research questions were addressed:
Additional project objectives that were addressed as part of this study include: (1) clarification of the use cases and conditions for baseline modeling performance metrics, benchmarks and evaluation criteria, (2) providing guidance for determining customer suitability for baseline modeling, (3) describing the portfolio level effects of baseline model estimation errors, (4) informing PG&E's development of EMIS technology product specifications, and (5) providing the analytical foundation for future studies about baseline modeling and saving effects of EMIS technologies.
A final objective of this project was to demonstrate the application of the methodology, performance metrics, and test protocols with participating EMIS product vendors. The test protocols and demonstration, which will take place at a later date, will be reported separately.
The target audiences for this work are the energy efficiency program administrators, regulatory authorities, EMIS technology vendors, building science researchers, and national standards organizations.
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