Energy Storage Scheduling in Distribution Systems Considering Wind and Photovoltaic Generation Uncertainties

Flexible distributed energy resources, such as energy storage systems (ESSs), are increasingly considered as means for mitigating challenges introduced by the integration of stochastic, variable distributed generation (DG). The optimal operation of a distribution system with ESS can be formulated as...
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Gespeichert in:

Autor*in:	Iver Bakken Sperstad [verfasserIn] Magnus Korpås [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	multi-period optimal power flow dynamic optimal power flow battery storage distribution network distribution grid operational planning

Übergeordnetes Werk:	In: Energies - MDPI AG, 2008, 12(2019), 7, p 1231
Übergeordnetes Werk:	volume:12 ; year:2019 ; number:7, p 1231

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/en12071231

Katalog-ID:	DOAJ025195395

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language	English
source	In Energies 12(2019), 7, p 1231 volume:12 year:2019 number:7, p 1231
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author	Iver Bakken Sperstad
spellingShingle	Iver Bakken Sperstad misc multi-period optimal power flow misc dynamic optimal power flow misc battery storage misc distribution network misc distribution grid misc operational planning misc Technology misc T Energy Storage Scheduling in Distribution Systems Considering Wind and Photovoltaic Generation Uncertainties
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topic_title	Energy Storage Scheduling in Distribution Systems Considering Wind and Photovoltaic Generation Uncertainties multi-period optimal power flow dynamic optimal power flow battery storage distribution network distribution grid operational planning
topic	misc multi-period optimal power flow misc dynamic optimal power flow misc battery storage misc distribution network misc distribution grid misc operational planning misc Technology misc T
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title	Energy Storage Scheduling in Distribution Systems Considering Wind and Photovoltaic Generation Uncertainties
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title_sort	energy storage scheduling in distribution systems considering wind and photovoltaic generation uncertainties
title_auth	Energy Storage Scheduling in Distribution Systems Considering Wind and Photovoltaic Generation Uncertainties
abstract	Flexible distributed energy resources, such as energy storage systems (ESSs), are increasingly considered as means for mitigating challenges introduced by the integration of stochastic, variable distributed generation (DG). The optimal operation of a distribution system with ESS can be formulated as a multi-period optimal power flow (MPOPF) problem which involves scheduling of the charging/discharging of the ESS over an extended planning horizon, e.g., for day-ahead operational planning. Although such problems have been the subject of many works in recent years, these works very rarely consider uncertainties in DG, and almost never explicitly consider uncertainties beyond the current operational planning horizon. This article presents a framework of methods and models for accounting for uncertainties due to distributed wind and solar photovoltaic power generation beyond the planning horizon in an AC MPOPF model for distribution systems with ESS. The expected future value of energy stored at the end of the planning horizon is determined as a function of the stochastic DG resource variables and is explicitly included in the objective function. Results for a case study based on a real distribution system in Norway demonstrate the effectiveness of an operational strategy for ESS scheduling accounting for DG uncertainties. The case study compares the application of the framework to wind and solar power generation. Thus, this work also gives insight into how different approaches are appropriate for modeling DG uncertainty for these two forms of variable DG, due to their inherent differences in terms of variability and stochasticity.
abstractGer	Flexible distributed energy resources, such as energy storage systems (ESSs), are increasingly considered as means for mitigating challenges introduced by the integration of stochastic, variable distributed generation (DG). The optimal operation of a distribution system with ESS can be formulated as a multi-period optimal power flow (MPOPF) problem which involves scheduling of the charging/discharging of the ESS over an extended planning horizon, e.g., for day-ahead operational planning. Although such problems have been the subject of many works in recent years, these works very rarely consider uncertainties in DG, and almost never explicitly consider uncertainties beyond the current operational planning horizon. This article presents a framework of methods and models for accounting for uncertainties due to distributed wind and solar photovoltaic power generation beyond the planning horizon in an AC MPOPF model for distribution systems with ESS. The expected future value of energy stored at the end of the planning horizon is determined as a function of the stochastic DG resource variables and is explicitly included in the objective function. Results for a case study based on a real distribution system in Norway demonstrate the effectiveness of an operational strategy for ESS scheduling accounting for DG uncertainties. The case study compares the application of the framework to wind and solar power generation. Thus, this work also gives insight into how different approaches are appropriate for modeling DG uncertainty for these two forms of variable DG, due to their inherent differences in terms of variability and stochasticity.
abstract_unstemmed	Flexible distributed energy resources, such as energy storage systems (ESSs), are increasingly considered as means for mitigating challenges introduced by the integration of stochastic, variable distributed generation (DG). The optimal operation of a distribution system with ESS can be formulated as a multi-period optimal power flow (MPOPF) problem which involves scheduling of the charging/discharging of the ESS over an extended planning horizon, e.g., for day-ahead operational planning. Although such problems have been the subject of many works in recent years, these works very rarely consider uncertainties in DG, and almost never explicitly consider uncertainties beyond the current operational planning horizon. This article presents a framework of methods and models for accounting for uncertainties due to distributed wind and solar photovoltaic power generation beyond the planning horizon in an AC MPOPF model for distribution systems with ESS. The expected future value of energy stored at the end of the planning horizon is determined as a function of the stochastic DG resource variables and is explicitly included in the objective function. Results for a case study based on a real distribution system in Norway demonstrate the effectiveness of an operational strategy for ESS scheduling accounting for DG uncertainties. The case study compares the application of the framework to wind and solar power generation. Thus, this work also gives insight into how different approaches are appropriate for modeling DG uncertainty for these two forms of variable DG, due to their inherent differences in terms of variability and stochasticity.
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