Multi-time scale energy management framework for smart PV systems mixing fast and slow dynamics

Watari, Daichi; Taniguchi, Ittetsu; Goverde, Hans; Manganiello, Patrizio; Shirazi, Elham; Catthoor, Francky; Onoye, Takao

doi:https://doi.org/10.1016/j.apenergy.2021.116671

Multi-time scale energy management framework for smart PV systems mixing fast and slow dynamics

Watari, Daichi; Taniguchi, Ittetsu; Goverde, Hans et al.

Applied Energy, 2021, 289, 116671

Number of Access:383（2025-09-03 05:13 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/92479

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Title	Multi-time scale energy management framework for smart PV systems mixing fast and slow dynamics
Creator	CreatorName Watari, Daichi
	NRID 1000040551453 1000040551453 ORCID 0000-0002-7843-5907 0000-0002-7843-5907 researchmap permalink ittetsu ittetsu Scopus Author ID 23013657500 23013657500 CreatorName Taniguchi, Ittetsu
	CreatorName Goverde, Hans
	CreatorName Manganiello, Patrizio
	CreatorName Shirazi, Elham
	CreatorName Catthoor, Francky
	NRID 1000060252590 1000060252590 researchmap permalink read0096872 read0096872 CreatorName Onoye, Takao
Subject	Battery
	Energy management system
	Multi-time scale
	PV forecasting
	Shiftable appliance
Description	Watari D., Taniguchi I., Goverde H., et al. Multi-time scale energy management framework for smart PV systems mixing fast and slow dynamics. Applied Energy 289, 116671 (2021); https://doi.org/10.1016/j.apenergy.2021.116671.
Abstract	We propose a multi-time scale energy management framework for a smart photovoltaic (PV) system that can calculate optimized schedules for battery operation, power purchases, and appliance usage. A smart PV system is a local energy community that includes several buildings and households equipped with PV panels and batteries. However, due to the unpredictability and fast variation of PV generation, maintaining energy balance and reducing electricity costs in the system is challenging. Our proposed framework employs a model predictive control approach with a physics-based PV forecasting model and an accurately parameterized battery model. We also introduce a multi-time scale structure composed of two-time scales: a longer coarse-grained time scale for daily horizon with 15-minutes resolution and a shorter fine-grained time scale for 15-minutes horizon with 1-second resolution. In contrast to the current single-time scale approaches, this alternative structure enables the management of a necessary mix of fast and slow system dynamics with reasonable computational times while maintaining high accuracy. Simulation results show that the proposed framework reduces electricity costs up 48.1% compared with baseline methods. The necessity of a multi-time scale and the impact on accurate system modeling in terms of PV forecasting and batteries are also demonstrated.
Publisher	Elsevier Ltd
Source Title	Applied Energy
Volume (Issue)	289
Page	116671
Date of Issued	2021-05-01
Language	English
Handle URL	https://hdl.handle.net/11094/92479
PISSN	03062619
NCID	AA00543227
Relation.isIdenticalTo	DOI (Publisher Version) https://doi.org/10.1016/j.apenergy.2021.116671
Access Rights	open access
CopyRight	This article is licensed under a Creative Commons Attribution 4.0 International License.
oaire:version	Version of Record
Category	学術雑誌論文 Journal Article

Resource Type	journal article
Local Type	Journal Article
DCMI Type	Text
DCTERMS.bibliographicCitation	Applied Energy. 2021, 289, p. 116671
DC.title	Multi-time scale energy management framework for smart PV systems mixing fast and slow dynamics
DC.creator	Watari, Daichi
	Taniguchi, Ittetsu
	Goverde, Hans
	Manganiello, Patrizio
	Shirazi, Elham
	Catthoor, Francky
	Onoye, Takao
DC.publisher	Elsevier Ltd
DC.language' scheme='DCTERMS.RFC1766	English
DC.type' scheme='DCTERMS.DCMIType	Text
DCTERMS.issued' scheme='DCTERMS.W3CDTF	2021-05-01
DC.identifier	https://doi.org/10.1016/j.apenergy.2021.116671
DC.subject	Battery
	Energy management system
	Multi-time scale
	PV forecasting
	Shiftable appliance
DC.description	Watari D., Taniguchi I., Goverde H., et al. Multi-time scale energy management framework for smart PV systems mixing fast and slow dynamics. Applied Energy 289, 116671 (2021); https://doi.org/10.1016/j.apenergy.2021.116671.
DCTERMS.abstract	We propose a multi-time scale energy management framework for a smart photovoltaic (PV) system that can calculate optimized schedules for battery operation, power purchases, and appliance usage. A smart PV system is a local energy community that includes several buildings and households equipped with PV panels and batteries. However, due to the unpredictability and fast variation of PV generation, maintaining energy balance and reducing electricity costs in the system is challenging. Our proposed framework employs a model predictive control approach with a physics-based PV forecasting model and an accurately parameterized battery model. We also introduce a multi-time scale structure composed of two-time scales: a longer coarse-grained time scale for daily horizon with 15-minutes resolution and a shorter fine-grained time scale for 15-minutes horizon with 1-second resolution. In contrast to the current single-time scale approaches, this alternative structure enables the management of a necessary mix of fast and slow system dynamics with reasonable computational times while maintaining high accuracy. Simulation results show that the proposed framework reduces electricity costs up 48.1% compared with baseline methods. The necessity of a multi-time scale and the impact on accurate system modeling in terms of PV forecasting and batteries are also demonstrated.
DC.rights	This article is licensed under a Creative Commons Attribution 4.0 International License.
DC.format	92479
citation_title	Multi-time scale energy management framework for smart PV systems mixing fast and slow dynamics
citation_author	Watari, Daichi
	Taniguchi, Ittetsu
	Goverde, Hans
	Manganiello, Patrizio
	Shirazi, Elham
	Catthoor, Francky
	Onoye, Takao
citation_publisher	Elsevier Ltd
citation_language	English
citation_date	2021-05-01
citation_journal_title	Applied Energy
citation_volume	289
citation_firstpage	116671
citation_doi	https://doi.org/10.1016/j.apenergy.2021.116671
citation_public_url	https://hdl.handle.net/11094/92479

Multi-time scale energy management framework for smart PV systems mixing fast and slow dynamics

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