PROBLEM
Measuring Demand-Side Impacts Net of Outside Events
Settlement-quality measurement of demand flexibility programs and virtual power plants requires management of external factors like Flex Alerts on the radio, new utility rates, economic booms and busts, and natural disasters. GRIDmeter provides a robust open-source method to implement comparison groups to manage exogenous events and ensure payments and forecasts represent the resource being delivered.
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SOLUTIONThe GRIDmeter™ methods apply advanced machine learning algorithms, including clustering, to identify non-participant comparison groups that can remove model error on account of both external and internal factors.
The GRIDmeter methods have proven accurate and superior to traditional comparison group approaches through empirical testing for both residential and commercial applications. |
IMPLEMENTATIONOpen-Source Recurve has published an open-source code base that can be used to run the GRIDmeter methods.
This code repository is available to all parties without restriction under an open-source license. |
PROJECTOpen-source methods developed in a public data-driven process.
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METHODSStratified comparison groups that deliver settlement-quality results.
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CODEOpen-source Python code available to all parties without restriction.
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Stay at home orders due to COVID, economic changes, and the electrification of buildings, all change patterns of energy use, overwhelm traditional measurement techniques for demand flexibility and energy efficiency.
To generate a settlement-quality, revenue-grade calculation for demand flexibility and energy efficiency, M&V must adjust for these outside events.
To generate a settlement-quality, revenue-grade calculation for demand flexibility and energy efficiency, M&V must adjust for these outside events.
To solve this problem, Recurve received funding from the DOE to convene a public working group to develop methods and code to generating standardized, automated comparison groups capable of isolating the effects of exogenous changes on portfolios.
Through this process, the GRIDmeter was proven capable of enabling accurate measurement of behind the meter distributed energy resources impacts, net even of the extreme effects of COVID on energy use, for commercial and residential buildings. The GRIDmeter methods and open-source GRIDmeter code repo are the outcomes of this process. They are available for use by any party, without restriction, to enable settlement-quality measurement and verification during this time of COVID, and as we accelerate the decarbonization of buildings going forward. |
How the GRIDmeter works
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Why Open Source?
Transparent
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Replicable
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Available
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Stakeholder
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Acknowledgments
These methods and open-source code were developed with funding from the U.S. Department of Energy, through the National Renewable Energy Laboratory. Recurve would also like to thank MCE for supporting this project by providing secure access to data. Finally, Recurve thanks the members of the Comparison Groups Working Group, who devoted their time and effort to listening, reviewing, and providing feedback throughout the research and development of the methods and recommendations in this report. |