Automated measurement and verification: Performance of public domain whole-building electric baseline models

Granderson, Jessica; Price, Phillip N.; Jump, David; Addy, Nathan; Sohn, Michael D.

doi:10.1016/j.apenergy.2015.01.026

Cited by 45 publications

(38 citation statements)

References 8 publications

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“…Prior work established a 4-step statistical procedure that can be used to evaluate the predictive accuracy, of a given baseline model [12,3]. The test dataset comprised interval meter data and independent variable data, such as outside air temperature, for dozens to hundreds of buildings.…”

Section: General Baseline Model Performance Assessmentmentioning

confidence: 99%

“…In addition to enabling operational savings, EMIS and related analytics tools have begun to automate the quantification of whole-building energy savings, relative to a baseline period, using empirical baseline models that relate energy consumption to key influencing parameters, such as ambient weather conditions and building operation schedule [3,4,5,6,7]. The term "M&V 2.0" is being used to describe the use of large data sets (either high frequency interval data, or large volumes across many buildings) combined with computational automation to streamline and scale the M&V process.…”

Section: Introductionmentioning

confidence: 99%

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Application of automated measurement and verification to utility energy efficiency program data

Granderson

Touzani

Fernandes

et al. 2017

Energy and Buildings

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Trustworthy savings calculations are critical to convincing regulators of both the costeffectiveness of energy efficiency program investments and their ability to defer supply-side capital investments. Today's methods for measurement and verification (M&V) of energy savings constitute a significant portion of the total costs of energy efficiency programs. They also require time-consuming data acquisition. A spectrum of savings calculation approaches is used, with some relying more heavily on measured data and others relying more heavily on estimated, modeled, or stipulated data.The increasing availability of "smart" meters and devices that report near-real time data, combined with new analytical approaches to quantify savings, offers the potential to conduct M&V more quickly and at lower cost, with comparable or improved accuracy. Commercial energy management and information systems (EMIS) technologies are beginning to offer these 'M&V 2.0' capabilities, and program administrators want to understand how they might assist programs in quickly and accurately measuring energy savings. This paper presents the results of recent testing of the ability to use automation to streamline the M&V process.In this paper, we apply an automated whole-building M&V tool to historic data sets from energy efficiency programs to begin to explore the accuracy, cost, and time trade-offs between more traditional M&V, and these emerging streamlined methods that use high-resolution energy data and automated computational intelligence. For the data sets studied we evaluate the fraction of buildings that are well suited to automated baseline characterization, the uncertainty in gross savings that is due to M&V 2.0 tools' model error, and indications of labor time savings, and how the automated savings results compare to prior, traditionally determined savings results. The results show that 70% of the buildings were well suited to the automated approach. In a majority of the cases (80%) savings and uncertainties for each individual building were quantified to levels above the criteria in ASHRAE Guideline 14. In addition the findings suggest that M&V 2.0 methods may also offer time-savings relative to traditional approaches. Finally we discuss the implications of these findings relative to the potential evolution of M&V, and pilots currently being launched to test how M&V automation can be integrated into ratepayer-funded programs and professional implementation and evaluation practice.

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Section: General Baseline Model Performance Assessmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Application of automated measurement and verification to utility energy efficiency program data

Granderson

Touzani

Fernandes

et al. 2017

Energy and Buildings

Self Cite

View full text Add to dashboard Cite

show abstract

“…Researchers have developed, applied, and published a test procedure to determine the overall predictive accuracy of M & V 2.0 approaches for commercial buildings that are based on IPMVP Option C or Option B (Granderson and Price, 2014;Granderson et al, 2015). This procedure is based on large test data sets of meter data and statistical cross-validation, and provides the ability to evaluate and compare and contrast both open and proprietary M & V 2.0 tools.…”

Section: And V 20 Tool Testing and Standardizationmentioning

confidence: 99%

“…For example, recent publications have articulated the potential advantages of advanced M & V and intersections with evaluation (DNV-GL, 2015;, as well as the development of new data analysis and modeling techniques (Ahmad et al, 2017;Araya et al, 2017;Burkhart et al, 2014;Heo and Zavala, 2012). Testing and validation of advanced M & V has been highlighted in case studies and technical articles (Franconi and Jump, 2017;Granderson and Price, 2014;Granderson et al, 2015Kupser et al, 2016). And finally, technology attributes have also been documented over a period of years (Crowe et al, 2014;Kramer et al, 2013;Kupser et al, 2016;NEEP, 2016).…”

Section: Introductionmentioning

confidence: 99%

The state of advanced measurement and verification technology and industry application

Granderson

Fernandes

2017

The Electricity Journal

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“…This paper expands recent analyses Granderson and Price 2014; J. Granderson et al 2015] of public-domain whole-building M&V methods, focusing on more novel baseline modeling approaches that leverage interval meter data using a larger set of buildings.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Automated Measurement and Verification (M&V) Methods

Granderson

Touzani

Custodio

et al. 2015

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Automated measurement and verification: Performance of public domain whole-building electric baseline models

Cited by 45 publications

References 8 publications

Application of automated measurement and verification to utility energy efficiency program data

Application of automated measurement and verification to utility energy efficiency program data

The state of advanced measurement and verification technology and industry application

Assessment of Automated Measurement and Verification (M&V) Methods

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