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Energy Markets and Energy Economy

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

Deadline for manuscript submissions: 27 March 2025 | Viewed by 2945

Special Issue Editor

Dr. Zhilun Jiao

E-Mail Website
Guest Editor
College of Economic and Social Development, Nankai University, Tianjin 300071, China
Interests: energy economics; environmental economics; transportation economics; logistics economics; technological innovation

Special Issue Information

Dear Colleagues,

Energy markets are places where the trade and distributions of energy resources happen, while energy economies study the complex interplay in those markets, including the production, consumption, and management of energy. Traditionally, the dynamics of energy production and demand, the integration and utilization of energy resources, and the evolution of energy technologies have been the key determinants of energy markets and economies. These factors have shaped the infrastructure, policies, and practices within the energy sector. However, the landscape of energy markets and energy economies is undergoing a transformation driven by new forces. The advent of artificial intelligence (AI) and other smart technologies is revolutionizing the way energy is supplied and consumed. Additionally, global events and economic/political instabilities are causing fluctuations in energy markets, with supply chains being tested and market mechanisms being challenged. The role of international and regional carbon trading systems is also becoming increasingly significant in regulating energy markets. Therefore, there is a pressing need for comprehensive and multidisciplinary research into energy markets and energy economies.

Researchers should aim to understand the complex interactions in energy markets considering traditional and emerging factors, assess the implications of technological advancements, or develop strategies to navigate energy markets’ volatility due to global events and regulatory frameworks.

Topics of interest for this Special Issue include the following:

  • Energy market structures and dynamics;
  • Energy market price prediction;
  • Economic implications of high renewable energy penetration;
  • AI and energy economies;
  • Economic impact of sustainable energy policies and regulations;
  • Behavioral economics in energy consumption;
  • Energy market volatility and risk management;
  • Carbon trading and energy economics;
  • Energy markets and the circular economy;
  • Energy efficiency and environmental economics;
  • Energy transformation and carbon emission for economic sectors;
  • Green technology and emissions.

Dr. Zhilun Jiao
Guest Editor

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

  • energy markets
  • energy price
  • AI technologies
  • energy structures
  • energy consumption
  • risk management
  • green technology
  • circular economy

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Published Papers (4 papers)

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Research

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25 pages, 2326 KiB  
Article
Directions of Price Transmission on the Diesel Oil Market in Poland
by Grzegorz Przekota and Anna Szczepańska-Przekota
Energies 2025, 18(1), 139; https://doi.org/10.3390/en18010139 - 1 Jan 2025
Viewed by 449
Abstract
The formation of crude oil prices and their impact on diesel prices represent a significant economic challenge. The economy’s dependence on energy resources means that the development and competitiveness of the economy, as well as the standard of living of society, are contingent [...] Read more.
The formation of crude oil prices and their impact on diesel prices represent a significant economic challenge. The economy’s dependence on energy resources means that the development and competitiveness of the economy, as well as the standard of living of society, are contingent upon energy prices, including those of liquid fuels. It is therefore important to recognise the process by which changes in the price of crude oil affect other commodities. The recognition of these dependencies will have implications for political and fiscal decision-making at the governmental level, investment strategies of enterprises, and patterns of consumption. The research presented in this paper concerns the transmission of crude oil prices and the wholesale and retail prices of diesel oil in Poland between 2010 and 2024. A correlation analysis, a Granger causality test, and an impulse response function calculation were conducted. The research demonstrated that crude oil prices are the cause of the formation of wholesale and retail prices of diesel oil. However, the causality between wholesale and retail prices is bilateral, with a stronger flow of impulses from retail prices to wholesale prices than vice versa. These findings have significant implications for the evolution of the retail market. While the current situation may lead to the monopolisation of the market, it also provides decision-makers with the ability to regulate the market, potentially reducing the volatility of retail prices relative to raw material quotations. Furthermore, it offers a means to safeguard the retail market against speculative activities and mitigate the impact of sudden increases in raw material prices. Full article
(This article belongs to the Special Issue Energy Markets and Energy Economy)
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23 pages, 820 KiB  
Article
Navigating and Overcoming Barriers to Digital Energy Transition for Carbon Neutrality in China
by Shuao Sun and Sheeraz Ahmed
Energies 2024, 17(23), 5888; https://doi.org/10.3390/en17235888 - 23 Nov 2024
Viewed by 880
Abstract
As China strives for carbon neutrality, the transition to digital energy systems presents both significant opportunities and formidable challenges. This study investigates the key barriers hindering this transition and the urgent need for effective strategies to address them, raising the critical research question: [...] Read more.
As China strives for carbon neutrality, the transition to digital energy systems presents both significant opportunities and formidable challenges. This study investigates the key barriers hindering this transition and the urgent need for effective strategies to address them, raising the critical research question: What are the main obstacles to digital energy adoption in China, and how can these challenges be overcome? In this study, the fuzzy AHP method has been utilized to prioritize barriers and fuzzy WASPAS to evaluate the strategies. Using fuzzy AHP, we found that stakeholder and governance barriers are the most critical, emphasizing issues like misalignment among stakeholders and governance challenges. Following this, financial constraints and technological limitations emerged as other significant barriers, highlighting the need for improved financing mechanisms and robust infrastructure. Through fuzzy WASPAS analysis, the top strategies identified are enhancing public awareness and capacity-building programs, strengthening governance and anti-corruption measures, and increasing investment in green finance. The results emphasize the importance of tackling governance and financial issues alongside technological advancements. Policy implications and recommendations are provided to guide China’s digital energy transition, with suggestions for future research focused on broader regional comparisons and the integration of emerging technologies. Full article
(This article belongs to the Special Issue Energy Markets and Energy Economy)
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19 pages, 2550 KiB  
Article
Stochastic Decision-Making Optimization Model for Large Electricity Self-Producers Using Natural Gas in Industrial Processes: An Approach Considering a Regret Cost Function
by Laís Domingues Leonel, Mateus Henrique Balan, Luiz Armando Steinle Camargo, Dorel Soares Ramos, Roberto Castro and Felipe Serachiani Clemente
Energies 2024, 17(21), 5389; https://doi.org/10.3390/en17215389 - 29 Oct 2024
Viewed by 688
Abstract
In the context of high energy costs and energy transition, the optimal use of energy resources for industrial consumption is of fundamental importance. This paper presents a decision-making structure for large consumers with flexibility to manage electricity or natural gas consumption to satisfy [...] Read more.
In the context of high energy costs and energy transition, the optimal use of energy resources for industrial consumption is of fundamental importance. This paper presents a decision-making structure for large consumers with flexibility to manage electricity or natural gas consumption to satisfy the demands of industrial processes. The proposed modelling energy system structure relates monthly medium and hourly short-term decisions to which these agents are subjected, represented by two connected optimization models. In the medium term, the decision occurs under uncertain conditions of energy and natural gas market prices, as well as hydropower generation (self-production). The monthly decision is represented by a risk-constrained optimization model. In the short term, hourly optimization considers the operational flexibility of energy and/or natural gas consumption, subject to the strategy defined in the medium term and mathematically connected by a regret cost function. The model application of a real case of a Brazilian aluminum producer indicates a measured energy cost reduction of USD 3.98 millions over a six-month analysis period. Full article
(This article belongs to the Special Issue Energy Markets and Energy Economy)
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Review

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30 pages, 10761 KiB  
Review
Artificial Intelligence in Energy Economics Research: A Bibliometric Review
by Zhilun Jiao, Chenrui Zhang and Wenwen Li
Energies 2025, 18(2), 434; https://doi.org/10.3390/en18020434 - 20 Jan 2025
Viewed by 548
Abstract
Artificial intelligence (AI) is gaining attention in energy economics due to its ability to process large-scale data as well as to make non-linear predictions and is providing new development opportunities and research subjects for energy economics research. The aim of this paper is [...] Read more.
Artificial intelligence (AI) is gaining attention in energy economics due to its ability to process large-scale data as well as to make non-linear predictions and is providing new development opportunities and research subjects for energy economics research. The aim of this paper is to explore the trends in the application of AI in energy economics over the decade spanning 2014–2024 through a systematic literature review, bibliometrics, and network analysis. The analysis of the literature shows that the prominent research themes are energy price forecasting, AI innovations in energy systems, socio-economic impacts, energy transition, and climate change. Potential future research directions include energy supply-chain resilience and security, social acceptance and public participation, economic inequality and the technology gap, automated methods for energy policy assessment, the circular economy, and the digital economy. This innovative study contributes to a systematic understanding of AI and energy economics research from the perspective of bibliometrics and inspires researchers to think comprehensively about the research challenges and hotspots. Full article
(This article belongs to the Special Issue Energy Markets and Energy Economy)
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