Browse by author
Lookup NU author(s): Dr Vahid VahidinasabORCiD, Professor Damian Giaouris, Professor Phil Taylor
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
© 2010-2012 IEEE.This paper proposes an optimization framework to deal with the uncertainty in a day-ahead scheduling of smart active distribution networks (ADNs). The optimal scheduling for a power grid is obtained such that the operation costs of distributed generations (DGs) and the main grid are minimized. Unpredictable demand and photovoltaics (PVs) impose some challenges such as uncertainty. So, the uncertainty of demand and PVs forecasting errors are modeled using a hybrid stochastic/robust (HSR) optimization method. The proposed model is used for the optimal day-ahead scheduling of ADNs in a way to benefit from the advantages of both methods. Also, in this paper, the ac load flow constraints are linearized to moderate the complexity of the formulation. Accordingly, a mixed-integer linear programming (MILP) formulation is presented to solve the proposed day-ahead scheduling problem of ADNs. To evaluate the performance of the proposed linearized HSR (LHSR) method, the IEEE 33-bus distribution test system is used as a case study.
Author(s): Baharvandi A, Aghaei J, Nikoobakht A, Niknam T, Vahidinasab V, Giaouris D, Taylor P
Publication type: Article
Publication status: Published
Journal: IEEE Transactions on Smart Grid
Year: 2020
Volume: 11
Issue: 1
Pages: 357-367
Print publication date: 01/01/2020
Online publication date: 19/06/2019
Acceptance date: 02/04/2019
ISSN (print): 1949-3053
ISSN (electronic): 1949-3061
Publisher: Institute of Electrical and Electronics Engineers Inc.
URL: https://doi.org/10.1109/TSG.2019.2922355
DOI: 10.1109/TSG.2019.2922355
Altmetrics provided by Altmetric