A robust optimization framework for the day-ahead scheduling of active distribution networks including energy storage systems

Nick, Mostafa (EPFL, Lausanne, Switzerland) ; Bozorg, Mokhtar (EPFL, Lausanne, Switzerland) ; Cherkaoui, Rachid (EPFL, Lausanne, Switzerland) ; Paolone, Mario (EPFL, Lausanne, Switzerland)

In this paper we present an adaptive robust optimization framework for the day-ahead scheduling of Active Distribution Networks (ADNs) where the controlled devices are distributed Energy Storage Systems (ESSs). First, the targeted problem is formulated using a two-stage optimization approach. The first-stage decisions determine the amount of import/export energy from the external grid at each hour, as well as energy exchanges for each ESS. The second stage deals with the intra-day control, given the first stage decisions. In order to effectively consider the impacts of uncertainties, the problem is transformed into a ‘min-max-min’ formulation. Here, we minimize the first (day-ahead scheduling) and second stage (intra-day operation) costs while uncertainties are maximally affecting the cost function of the second stage. The Benders dual cut algorithm is employed for the solution of the optimization problem. IEEE 34 bus standard network is the benchmark grid for assessing the performances and effectiveness of the developed robust optimization process.


Note: BOZORG, Mokhtar est chercheur à la HES-SO, HEIG-VD, depuis 2017.


Keywords:
Conference Type:
published full paper
Faculty:
Ingénierie et Architecture
School:
HEIG-VD
Institute:
IESE - Institut d'Energie et Systèmes Electriques
Subject(s):
Ingénierie
Publisher:
Milan, Italy, 23-27 June 2019
Date:
2019-06
Milan, Italy
23-27 June 2019
Pagination:
6 p.
Published in:
Proceedings of the 13th IEEE PowerTech (POWERTECH) 2019
DOI:
ISBN:
978-1-5386-4722-6
Appears in Collection:

Note: The status of this file is: restricted


 Record created 2021-07-12, last modified 2021-07-16

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