Probabilistic day-ahead simultaneous active/reactive power management in active distribution systems

Distributed generations (DGs) are main components for active distribution networks (ADNs). Owing to the large number of DGs integrated into distribution levels, it will be essential to schedule active and reactive power resources in ADNs. Generally, energy and reactive power scheduling problems are...

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Main Author: Abouzar Samimi
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:Journal of Modern Power Systems and Clean Energy
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8964535/
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spelling doaj-dedb2be56c5b482e9acc52880bbfcae92021-04-23T16:14:01ZengIEEEJournal of Modern Power Systems and Clean Energy2196-54202019-01-01761596160710.1007/s40565-019-0535-48964535Probabilistic day-ahead simultaneous active/reactive power management in active distribution systemsAbouzar Samimi0Arak University of Technology,Department of Electrical Engineering,Arak,IranDistributed generations (DGs) are main components for active distribution networks (ADNs). Owing to the large number of DGs integrated into distribution levels, it will be essential to schedule active and reactive power resources in ADNs. Generally, energy and reactive power scheduling problems are separately managed in ADNs. However, the separate scheduling cannot attain a global optimum scheme in the operation of ADNs. In this paper, a probabilistic simultaneous active/reactive scheduling framework is presented for ADNs. In order to handle the uncertainties of power generations of renewable-based DGs and upstream grid prices in an efficient framework, a stochastic programming technique is proposed. The stochastic programming can help distribution system operators (DSOs) to make operation decisions in front of existing uncertainties. The proposed coordinated model considers the minimization of the energy and reactive power costs of all distributed resources along with the upstream grid. Meanwhile, a new payment index as loss profit value for DG units is introduced and embedded in the model. Numerical results based on the 22-bus and IEEE 33-bus ADNs validate the effectiveness of the proposed method. The obtained results verify that through the proposed stochastic-based power management system, the DSO can effectively schedule all DGs along with its economic targets while considering severe uncertainties.https://ieeexplore.ieee.org/document/8964535/Simultaneous active/reactive power schedulingStochastic programmingUncertaintyLoss profit valueDistributed generations
collection DOAJ
language English
format Article
sources DOAJ
author Abouzar Samimi
spellingShingle Abouzar Samimi
Probabilistic day-ahead simultaneous active/reactive power management in active distribution systems
Journal of Modern Power Systems and Clean Energy
Simultaneous active/reactive power scheduling
Stochastic programming
Uncertainty
Loss profit value
Distributed generations
author_facet Abouzar Samimi
author_sort Abouzar Samimi
title Probabilistic day-ahead simultaneous active/reactive power management in active distribution systems
title_short Probabilistic day-ahead simultaneous active/reactive power management in active distribution systems
title_full Probabilistic day-ahead simultaneous active/reactive power management in active distribution systems
title_fullStr Probabilistic day-ahead simultaneous active/reactive power management in active distribution systems
title_full_unstemmed Probabilistic day-ahead simultaneous active/reactive power management in active distribution systems
title_sort probabilistic day-ahead simultaneous active/reactive power management in active distribution systems
publisher IEEE
series Journal of Modern Power Systems and Clean Energy
issn 2196-5420
publishDate 2019-01-01
description Distributed generations (DGs) are main components for active distribution networks (ADNs). Owing to the large number of DGs integrated into distribution levels, it will be essential to schedule active and reactive power resources in ADNs. Generally, energy and reactive power scheduling problems are separately managed in ADNs. However, the separate scheduling cannot attain a global optimum scheme in the operation of ADNs. In this paper, a probabilistic simultaneous active/reactive scheduling framework is presented for ADNs. In order to handle the uncertainties of power generations of renewable-based DGs and upstream grid prices in an efficient framework, a stochastic programming technique is proposed. The stochastic programming can help distribution system operators (DSOs) to make operation decisions in front of existing uncertainties. The proposed coordinated model considers the minimization of the energy and reactive power costs of all distributed resources along with the upstream grid. Meanwhile, a new payment index as loss profit value for DG units is introduced and embedded in the model. Numerical results based on the 22-bus and IEEE 33-bus ADNs validate the effectiveness of the proposed method. The obtained results verify that through the proposed stochastic-based power management system, the DSO can effectively schedule all DGs along with its economic targets while considering severe uncertainties.
topic Simultaneous active/reactive power scheduling
Stochastic programming
Uncertainty
Loss profit value
Distributed generations
url https://ieeexplore.ieee.org/document/8964535/
work_keys_str_mv AT abouzarsamimi probabilisticdayaheadsimultaneousactivereactivepowermanagementinactivedistributionsystems
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