Foundation models for the electric power grid

Hamann, Hendrik F.; Gjorgiev, Blazhe; Brunschwiler, Thomas; Martins, Leonardo S.A.; Puech, Alban; Varbella, Anna; Weiss, Jonas; Bernabe-Moreno, Juan; Massé, Alexandre Blondin; Choi, Seong Lok; Foster, Ian; Hodge, Bri-Mathias; Jain, Rishabh; Kim, Kibaek; Mai, Vincent; Mirallès, François; De Montigny, Martin; Ramos-Leaños, Octavio; Suprême, Hussein; Xie, Le; Youssef, El-Nasser S.; Zinflou, Arnaud; Belyi, Alexander; Bessa, Ricardo J.; Bhattarai, Bishnu Prasad; Schmude, Johannes; Sobolevsky, Stanislav

doi:10.1016/j.joule.2024.11.002

Joule

2024

DOI: 10.1016/j.joule.2024.11.002

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Foundation models for the electric power grid

Hendrik F. Hamann,

Blazhe Gjorgiev,

Thomas Brunschwiler

et al.

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Cited by 2 publications

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Accelerating quasi-static time series simulations with foundation models

Puech,

Mirallès,

Weiss

et al. 2024

Elektrotech. Inftech.

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Accelerating quasi-static time series simulations with foundation models

Puech,

Mirallès,

Weiss

et al. 2024

Elektrotech. Inftech.

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Stochastic Approaches to Energy Markets: From Stochastic Differential Equations to Mean Field Games and Neural Network Modeling

Di Persio,

Alruqimi,

Garbelli

2024

Energies

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This review paper examines the current landscape of electricity market modelling, specifically focusing on stochastic approaches, transitioning from Mean Field Games (MFGs) to Neural Network (NN) modelling. The central objective is to scrutinize and synthesize evolving modelling strategies within power systems, facilitating technological advancements in the contemporary electricity market. This paper emphasizes the assessment of model efficacy, particularly in the context of MFG and NN applications. Our findings shed light on the diversity of models, offering practical insights into their strengths and limitations, thereby providing a valuable resource for researchers, policy makers, and industry practitioners. The review guides navigating and leveraging the latest stochastic modelling techniques for enhanced decision making and improved market operations.

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Foundation models for the electric power grid

Cited by 2 publications

References 42 publications

Accelerating quasi-static time series simulations with foundation models

Accelerating quasi-static time series simulations with foundation models

Stochastic Approaches to Energy Markets: From Stochastic Differential Equations to Mean Field Games and Neural Network Modeling

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