Enabling portable demand flexibility control applications in virtual and real buildings

Author:

de Andrade Pereira FlaviaORCID,Paul Lazlo,Pritoni MarcoORCID,Casillas ArmandoORCID,Prakash AnandORCID,Huang WeipingORCID,Shaw Conor,Martin-Toral Susana,Finn Donal,Donnell James O’

Funder

US Department of Energy

European Union's Research and Innovation

Publisher

Elsevier BV

Reference68 articles.

1. Demand response;International Energy Agency,2023

2. Defining and applying an electricity demand flexibility benchmarking metrics framework for grid-interactive efficient commercial buildings;Liu;Adv. Appl. Energy,2022

3. Control Strategies and Algorithms for Obtaining Energy Flexibility in Buildings;Santos,2019

4. Data-driven key performance indicators and datasets for building energy flexibility: A review and perspectives;Li;Appl. Energy,2023

5. A new framework integrating reinforcement learning, a rule-based expert system, and decision tree analysis to improve building energy flexibility;Zhou;J. Build. Eng.,2023

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