A Comprehensive Review of Artificial Intelligence (AI) Companies in the Power Sector

Vladimir Franki (), Darin Majnarić and Alfredo Višković
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Vladimir Franki: Faculty of Engineering Rijeka, University of Rijeka, Vukovarska 58, 51000 Rijeka, Croatia
Darin Majnarić: Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Ul. Ivana Lučića 5, 10000 Zagreb, Croatia
Alfredo Višković: Faculty of Engineering Rijeka, University of Rijeka, Vukovarska 58, 51000 Rijeka, Croatia

Energies, 2023, vol. 16, issue 3, 1-35

Abstract: There is an ongoing, revolutionary transformation occurring across the globe. This transformation is altering established processes, disrupting traditional business models and changing how people live their lives. The power sector is no exception and is going through a radical transformation of its own. Renewable energy, distributed energy sources, electric vehicles, advanced metering and communication infrastructure, management algorithms, energy efficiency programs and new digital solutions drive change in the power sector. These changes are fundamentally altering energy supply chains, shifting geopolitical powers and revising energy landscapes. Underlying infrastructural components are expected to generate enormous amounts of data to support these applications. Facilitating a flow of information coming from the system′s components is a prerequisite for applying Artificial Intelligence (AI) solutions in the power sector. New components, data flows and AI techniques will play a key role in demand forecasting, system optimisation, fault detection, predictive maintenance and a whole string of other areas. In this context, digitalisation is becoming one of the most important factors in the power sector′s transformation process. Digital solutions possess significant potential in resolving multiple issues across the power supply chain. Considering the growing importance of AI, this paper explores the current status of the technology’s adoption rate in the power sector. The review is conducted by analysing academic literature but also by analysing several hundred companies around the world that are developing and implementing AI solutions on the grid’s edge.

Keywords: artificial intelligence; power sector; adoption rate; application; AI companies; AI start-ups (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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