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From M&V to M&T: An artificial intelligence-based framework for real-time performance verification of demand-side energy savings
- Source :
- 2018 International Conference on Smart Energy Systems and Technologies (SEST).
- Publication Year :
- 2018
- Publisher :
- IEEE, 2018.
-
Abstract
- The European Union's Energy Efficiency Directive is placing an increased focus on the measurement and verification (M&V) of demand side energy savings. The objective of M&V is to quantify energy savings with minimum uncertainty. M&V is currently undergoing a transition to practices, known as M&V 2.0, that employ automated advanced analytics to verify performance. This offers the opportunity to effectively manage the transition from short-term M&V to long-term monitoring and targeting (M&T) in industrial facilities. The original contribution of this paper consists of a novel, robust and technology agnostic framework that not only satisfies the requirements of M&V 2.0, but also bridges the gap between M&V and M&T by ensuring persistence of savings. The approach features a unique machine learning-based energy modelling methodology, model deployment and an exception reporting system that ensures early identification of performance degradation. A case study demonstrates the effectiveness of the approach. Savings from a real-world project are found to be 177,962 +/- 12,334 kWh with a 90% confidence interval. The uncertainty associated with the savings is 8.6% of the allowable uncertainty, thus highlighting the viability of the framework as a reliable and effective tool.
- Subjects :
- Learning (artificial intelligence)
Long-term monitoring
Computer science
Demand side management
Energy savings
Energy modelling
Energy conservation
Data modeling
Energy measurement
Measurement and verification
Mathematical model
Machine learning
Technology agnostic framework
media_common.cataloged_instance
Real-time performance verification
Buildings
European union
Artificial intelligence-based framework
Energy 12334.0 kWh
M&V 2.0
media_common
Monitoring and targeting
business.industry
European Union Energy Efficiency Directive
Uncertainty
Data models
Computational modeling
Automated advanced analytics
Machine learning-based energy modelling methodology
Reliability engineering
M&V
Performance verification
Identification (information)
Energy efficiency
Analytics
Software deployment
M&T
Production facilities
Demand-side energy savings
Industrial facilities
Measurement and Verification
business
Efficient energy use
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2018 International Conference on Smart Energy Systems and Technologies (SEST)
- Accession number :
- edsair.doi.dedup.....1c2bc6a47d1b131eb5a12dba7a4aec87