Electricity Market Empowered by Artificial Intelligence: A Platform Approach

Abstract

Artificial intelligence (AI) techniques and algorithms are increasingly being utilized in energy and renewable research to tackle various engineering problems. However, a majority of the AI studies in the energy domain have been focusing on solving specific technical issues. There is limited discussion on how AI can be utilized to enhance the energy system operations, particularly the electricity market, with a holistic view. The purpose of the study is to introduce the platform architectural logic that encompasses both technical and economic perspectives to the development of AI-enabled energy platforms for the future electricity market with massive and distributed renewables. A constructive and inductive approach for theory building is employed for the concept proposition of the AI energy platform by using the aggregated data from a European Union (EU) Horizon 2020 project and a Finnish national innovation project. Our results are presented as a systemic framework and high-level representation of the AI-enabled energy platform design with four integrative layers that could enable not only value provisioning but also value utilization for a distributed energy system and electricity market as the new knowledge and contribution to the extant research. Finally, the study discusses the potential use cases of the AI-enabled energy platform.

A Learning-Based Bidding Approach for PV-Attached BESS Power Plants

“…This research implies that, in the electricity market, it is possible to train agents with AI algorithms to better solve the optimization of bidding problems. The common core techniques for AI are classified as the artificial neural network, reinforcement learning, genetic algorithms, and multiagent systems (Xu et al, 2019).…”

Governing AI in Electricity Systems: Reflections on the EU Artificial Intelligence Bill

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