Modelling smart grid technologies in optimisation problems for electricity grids
File(s)energies-16-05249.pdf (1.52 MB)
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Author(s)
Type
Journal Article
Abstract
The decarbonisation of the electricity grid is expected to create new electricity flows. As a result, it may require that network planners make a significant amount of investments in the electricity grids over the coming decades so as to allow the accommodation of these new flows in a way that both the thermal and voltage network constraints are respected. These investments may include a portfolio of infrastructure assets consisting of traditional technologies and smart grid technologies. One associated key challenge is the presence of uncertainty around the location, the timing, and the amount of new demand or generation connections. This uncertainty unavoidably introduces risk into the investment decision-making process as it may lead to inefficient investments and inevitably give rise to excessive investment costs. Smart grid technologies have properties that enable them to be regarded as investment options, which can allow network planners to hedge against the aforementioned uncertainty. This paper focuses on key smart technologies by providing a critical literature review and presenting the latest mathematical modelling that describes their operation.
Date Issued
2023-06-30
Date Acceptance
2023-06-29
Citation
Energies, 2023, 16 (13), pp.1-15
ISSN
1996-1073
Publisher
MDPI AG
Start Page
1
End Page
15
Journal / Book Title
Energies
Volume
16
Issue
13
Copyright Statement
Copyright: © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
License URL
Identifier
http://dx.doi.org/10.3390/en16135088
Publication Status
Published
Date Publish Online
2023-06-30