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Coupling AI in Electricity Markets

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "C: Energy Economics and Policy".

Deadline for manuscript submissions: 25 July 2025 | Viewed by 1632

Special Issue Editors


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Guest Editor
School of Automation, Central South University, Changsha 410083, China
Interests: electricity market and integration of renewable energy; artificial intelligence technology and its application in energy systems

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Guest Editor
Department of Electrical Engineering, University of Leuven, 3001 Leuven, Belgium
Interests: robust distributed coordination and control; specifically in the context of smart electric distribution networks; smart grids; user-centric energy systems; smart metering; distributed control; robust system design; sustainability; multi-energy systems; infrastructure interdependencies and dependability modelling; all in a context of energy and data infrastructures
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Special Issue Information

Dear Colleagues,

Electricity markets are key areas for achieving the energy transition and low-carbon development of smart grids, as well as being important application areas for artificial intelligence (AI) technologies. With the widespread integration of renewable energy, distributed generation, participation of users in demand response programs, electric vehicles, energy storage systems and other new power devices, the complexity and uncertainty of power systems are increasing, posing higher requirements for the operation mechanisms of electricity markets.

AI is widely considered to be a powerful technology that can effectively process the massive data in electricity markets, improve the efficiency and reliability of electricity markets, and foster the innovation and transformation of electricity markets. Work has shown that advanced AI technologies, such as federated learning, reinforcement learning, deep learning, deep reinforcement learning, graph neural networks, attention mechanisms, etc., provide workable solutions in various market scenarios and obtain promising results. How to explore and exploit the power of AI further to improve the performance and resilience of electricity markets remains an important and exciting research direction.

This Special Issue welcomes various papers related to “AI + electricity markets”, including but not limited to the following topics:

  • AI applications in electricity market forecasting, scheduling, optimization, and control;
  • AI applications in electricity market security, stability, and fault diagnosis;
  • AI applications in electricity market demand response, distributed energy, and energy storage;
  • AI applications in electricity market trading, pricing, and market design;
  • AI applications in electricity market regulation, policy, and social impact;
  • AI applications in the electricity market: new modes, new formats, and new technologies;

Dr. Zhifeng Qiu
Prof. Dr. Geert Deconinck
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • electricity market
  • artificial intelligence
  • AI applications

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Published Papers (1 paper)

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Review

41 pages, 592 KiB  
Review
Review of Power Market Optimization Strategies Based on Industrial Load Flexibility
by Caixin Yan and Zhifeng Qiu
Energies 2025, 18(7), 1569; https://doi.org/10.3390/en18071569 - 21 Mar 2025
Viewed by 545
Abstract
New power systems, predominantly based on renewable energy, necessitate active load-side management to effectively alleviate the pressures associated with balancing supply-side fluctuations and demand-side energy requirements. Concurrently, as power markets continue to evolve, both the energy market and ancillary services market offer valuable [...] Read more.
New power systems, predominantly based on renewable energy, necessitate active load-side management to effectively alleviate the pressures associated with balancing supply-side fluctuations and demand-side energy requirements. Concurrently, as power markets continue to evolve, both the energy market and ancillary services market offer valuable guidance for the optimal economic dispatch of industrial loads. Although substantial energy-saving potential exists within industrial production processes, their inherent complexity, dynamic nature, and mixed continuous–discrete modal characteristics present significant challenges in achieving accurate and efficient demand-side response. Conversely, the ongoing advancement of industrial internet techniques lays a robust technical foundation for the reliable, stable, and economically efficient operation of new power systems with large-scale industrial load response. This paper starts from the industrial load, discusses the resources and advantages and disadvantages of the industry itself, and carefully distinguishes the advantages and disadvantages of participating in the power market to make decisions. This paper provides a comprehensive review of intelligent optimization and regulation of industrial load flexibility in response to new power systems. Firstly, it synthesizes the three prevalent demand response strategies (load shedding, load shifting, and load substitution), along with their associated regulatory techniques, considering the operational characteristics of various industrial sectors. It then examines the trading strategies and modeling challenges of flexible industrial loads within two power market environments: the energy market and the ancillary services market. Subsequently, using the non-ferrous industry electrolytic process as a case study, it explores the optimization of production process parameters under energy usage planning. Finally, from the perspectives of market, technical innovation, and stakeholder engagement, it highlights the unresolved issues and provides insights into future research directions concerning the intelligent, digital, and market-driven integration of flexible industrial load flexibility. Full article
(This article belongs to the Special Issue Coupling AI in Electricity Markets)
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