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Baharvandi, A., Aghaei, J., Nikoobakht, A., Niknam, T., Vahidinasab, V. 
ORCID: 0000-0002-0779-8727, Giaouris, D. and Taylor, P.,
2020.
Linearized hybrid stochastic/robust scheduling of active distribution networks encompassing PVs.
IEEE Transactions on Smart Grid, 11 (1), pp. 357-367.
ISSN 1949-3053
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Abstract
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.
| Item Type: | Journal article | ||||||
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| Publication Title: | IEEE Transactions on Smart Grid | ||||||
| Creators: | Baharvandi, A., Aghaei, J., Nikoobakht, A., Niknam, T., Vahidinasab, V., Giaouris, D. and Taylor, P. | ||||||
| Publisher: | Institute of Electrical and Electronics Engineers (IEEE) | ||||||
| Date: | January 2020 | ||||||
| Volume: | 11 | ||||||
| Number: | 1 | ||||||
| ISSN: | 1949-3053 | ||||||
| Identifiers: |
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| Rights: | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||||||
| Divisions: | Schools > School of Science and Technology | ||||||
| Record created by: | Laura Ward | ||||||
| Date Added: | 09 Feb 2023 09:28 | ||||||
| Last Modified: | 09 Feb 2023 09:28 | ||||||
| URI: | https://irep.ntu.ac.uk/id/eprint/48205 |
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