Artificial Intelligence for Electricity Supply Chain automation

Lucas Richter, Malte Lehna, Sophie Marchand, Christoph Scholz, Alexander Dreher, Stefan Klaiber and Steve Lenk

Renewable and Sustainable Energy Reviews, 2022, vol. 163, issue C

Abstract: The Electricity Supply Chain is a system of enabling procedures to optimize processes ranging from production to transportation and consumption of electricity. The proportion of distributed energy sources within the electricity system increases steadily, which necessitates an improved monitoring capability to ensure the overall reliability and quality of the Electricity Supply Chain. Automation is strongly required to process the growing amount of data. Thus, it is inevitable to handle large amounts of heterogeneous data and process the information using forecasting and optimization techniques. Artificial Intelligence techniques are crucial for extending human cognitive abilities in these tasks. In our work, we synthesize the main impacts of the Artificial Intelligence paradigm on the automation of the Electricity Supply Chain. We describe the emerging automation through Artificial Intelligence in every layer of the Smart Grid Architecture Model and highlight state-of-the-art approaches. In the review, we focus on the following Electricity Supply Chain functionalities: generation, maintenance, pre-processing, analysis, forecasting, optimization, and trading within energy systems. After investigating the individual perspectives, we examine the potential implementation of a fully automated Electricity Supply Chain. Lastly, we discuss perspectives and limitations for the transformation from conventional to automated Electricity Supply Chains, specifically in terms of human interaction, Artificial Intelligence adaptation, energy transition, and sustainability.

Keywords: Electricity supply chain; Energy management; Energy transition; Artificial intelligence automation data processing forecasting optimization autonomous trading.interaction (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.rser.2022.112459

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