Demand response in the workplace: A field experiment

Llerena, Daniel; Roussillon, Béatrice; Teyssier, Sabrina; Fadhuile, Adélaïde; Buckley, Penelope; Delinchant, Benoît; Ferrari, Jérôme; Laranjeira, Tiansi; Würtz, Fréderic

doi:10.1016/j.jenvman.2023.117992

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Context and Requirment Specifications1

) Correction Term Learning Added To Physical Model1

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2023

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(2 citation statements)

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“…They can interact directly with flexible assets or via end users, but must in any case receive their consent and can encounter many barriers [1]. In order to optimize this management, the aggregator must have knowledge of the distributed production, but also of consumer behavior, which is an active research field [2] and subject to many uncertainties. More and more individual Renewable Energy Sources (RES) generation are being implemented at the scale of buildings, or at the scale of energy communities.…”

Section: Context and Requirment Specificationsmentioning

confidence: 99%

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Lightweight hybrid local PV short term forecasting using both physics and data

Delinchant,

Imard,

Bermudez

et al. 2023

2023 IEEE PES 15th Asia-Pacific Power and Energy Engineering Conference (APPEEC)

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Section: Context and Requirment Specificationsmentioning

confidence: 99%

“…In order to apply the hybrid methodology detailed earlier, we defined a correction term as in equation (2) to model the gap between clear sky model and PV generation measures.…”

Section: ) Correction Term Learning Added To Physical Modelmentioning

confidence: 99%