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Field data-driven discrete-event simulation of residential PV/energy storage systems in cold climate regions

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DOITrouver le DOI : https://doi.org/10.1109/EESAT62935.2025.10891235
AuteurRechercher : 1Identifiant ORCID : https://orcid.org/0000-0002-6452-3973; Rechercher : 1Identifiant ORCID : https://orcid.org/0000-0001-7200-6450; Rechercher : 1Identifiant ORCID : https://orcid.org/0000-0003-3183-4537; Rechercher : 2
Affiliation
  1. Conseil national de recherches Canada. Construction
  2. NB Power, Fredericton, Canada
FormatTexte, Article
ConférenceThe 13th IEEE Electrical Energy Storage Applications and Technologies Conference (EESAT) January 20-21, 2025, Charlotte, North Carolina, United States
Sujetbattery energy storage; decarbonization; distributed energy resources; peak management; simulation
Résumé
This paper presents a field data-driven simulation model for PV and battery systems in residential buildings. The increased electricity demand in buildings, particularly in morning and evening peak periods, has increased the need for optimized on-site renewable energy utilization. A battery system’s output depends on various parameters, including occupant energy use behavior, load profile, operation mode, state of charge, battery management system programming, and weather conditions. This paper addresses the gap by proposing a discrete-event simulation model based on field data collected from 75 homes in Atlantic Canada. The model replicates the performance of PV and battery systems under time-based control mode. Validation of the model demonstrates promising results. The evidence-based model can inform utility companies, ratepayers, and stakeholders about the costs and benefits of implementing battery energy storage systems and provides insights for developing decarbonization plans.
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Maison d’éditionIEEE
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Langueanglais
Publications évaluées par des pairsOui
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Identificateur de l’enregistrement3fe0da15-28c9-419c-9804-22d7155029d9
Enregistrement créé2025-11-18
Enregistrement modifié2026-02-19

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