Transition to Digitalized Paradigms for Security Control and Decentralized Electricity Market

Journal Article (2022)
Author(s)

Federica Bellizio (Imperial College London)

Wangkun Xu (Imperial College London)

Dawei Qiu (Imperial College London)

Yujian Ye (Southeast University)

Dimitrios Papadaskalopoulos (Imperial College London)

Jochen L. Cremer (TU Delft - Electrical Engineering, Mathematics and Computer Science, TU Delft - Electrical Engineering, Mathematics and Computer Science)

Fei Teng (Imperial College London)

Goran Strbac (Imperial College London)

Research Group
Intelligent Electrical Power Grids
DOI related publication
https://doi.org/10.1109/JPROC.2022.3161053 Final published version
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Publication Year
2022
Language
English
Research Group
Intelligent Electrical Power Grids
Issue number
7
Volume number
111
Pages (from-to)
744-761
Downloads counter
494
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Abstract

Digitalization is one of the key drivers for energy system transformation. The advances in communication technologies and measurement devices render available a large amount of operational data and enable the centralization of such data storage and processing. The greater access to data opens up new opportunities for a more efficient and decentralized management of the energy system. At the distribution level of the energy system, local electricity markets (LEMs) provide new degrees of flexibility by trading and balancing the energy locally and offering ancillary services to the wider transmission and distribution system operators. Maximizing the grid impact from this flexibility calls for novel data analytics and artificial intelligence techniques to enhance the system's security and reduce the energy costs of local prosumers. At the same time, however, relying on data-based approaches increases the risk of cyberattacks, and robust countermeasures are, therefore, needed as an integral aspect of digitalization efforts. This article discusses the key role of centralized data analytics to fully benefit from the advantages of LEMs in terms of system's security enhancement and energy costs' reduction. Data-driven paradigms are investigated that allow for flexibility from decentralized markets, mitigate the physical security risks, and devise defensive strategies shielding the system from cyber threats.

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