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Data-driven key performance indicators and datasets for building energy flexibility: A review and perspectives

Authors: Li, Han; Johra, Hicham; de Andrade Pereira, Flavia; Hong, Tianzhen; Le Dréau, Jérôme; Maturo, Anthony; Wei, Mingjun; +11 Authors

Data-driven key performance indicators and datasets for building energy flexibility: A review and perspectives

Abstract

Energy flexibility, through short-term demand-side management (DSM) and energy storage technologies, is now seen as a major key to balancing the fluctuating supply in different energy grids with the energy demand of buildings. This is especially important when considering the intermittent nature of ever-growing renewable energy production, as well as the increasing dynamics of electricity demand in buildings. This paper provides a holistic review of (1) data-driven energy flexibility key performance indicators (KPIs) for buildings in the operational phase and (2) open datasets that can be used for testing energy flexibility KPIs. The review identifies a total of 81 data-driven KPIs from 91 recent publications. These KPIs were categorized and analyzed according to their type, complexity, scope, key stakeholders, data requirement, baseline requirement, resolution, and popularity. Moreover, 330 building datasets were collected and evaluated. Of those, 16 were deemed adequate to feature building performing demand response or building-to-grid (B2G) services. The DSM strategy, building scope, grid type, control strategy, needed data features, and usability of these selected 16 datasets were analyzed. This review reveals future opportunities to address limitations in the existing literature: (1) developing new data-driven methodologies to specifically evaluate different energy flexibility strategies and B2G services of existing buildings; (2) developing baseline-free KPIs that could be calculated from easily accessible building sensors and meter data; (3) devoting non-engineering efforts to promote building energy flexibility, such as designing utility programs, standardizing energy flexibility quantification and verification processes; and (4) curating datasets with proper description for energy flexibility assessments.

30 pages, 14 figures, 4 tables

Countries
Denmark, United Kingdom, Denmark, Ireland, Denmark, United States, Denmark
Keywords

690, Building energy flexibility, Economics, Systems and Control (eess.SY), /dk/atira/pure/sustainabledevelopmentgoals/industry_innovation_and_infrastructure; name=SDG 9 - Industry, Innovation, and Infrastructure, /dk/atira/pure/sustainabledevelopmentgoals/responsible_consumption_and_production; name=SDG 12 - Responsible Consumption and Production, Building-to-grid service, Electrical Engineering and Systems Science - Systems and Control, Engineering, /dk/atira/pure/sustainabledevelopmentgoals/affordable_and_clean_energy; name=SDG 7 - Affordable and Clean Energy, Affordable and Clean Energy, Demand response datasets, FOS: Electrical engineering, electronic engineering, information engineering, Building, demand-side management, /dk/atira/pure/sustainabledevelopmentgoals/climate_action; name=SDG 13 - Climate Action, grid-interactive buildings, Demand-side management, Built environment and design, demand response datasets, Demand response, Energy, Building -to -grid service, Key performance indicator, 620, Climate Action, key performance indicator, Built Environment and Design, demand response, Demand -side management, demand flexibility, physics.app-ph, /dk/atira/pure/sustainabledevelopmentgoals/sustainable_cities_and_communities; name=SDG 11 - Sustainable Cities and Communities, building-to-grid service

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    60
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
60
Top 10%
Top 10%
Top 1%
Green
hybrid