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

Deadline for manuscript submissions: closed (18 September 2024) | Viewed by 11294

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Special Issue Editors

Prof. Dr. Periklis Gogas

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Guest Editor

Department of Economics, Democritus University of Thrace, 69100 Komotini, Greece
Interests: banking; finance; machine learning; artificial intelligence; econometrics
Special Issues, Collections and Topics in MDPI journals

Dr. Donato Morea

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Guest Editor

Department of Mechanical, Chemical and Materials Engineering, University of Cagliari, Via Marengo, 2, 09123 Cagliari, Italy
Interests: renewable energy; investment analysis; project financing; public–private partnership; Islamic finance; agricultural economics; circular economy; corporate social responsibility; productivity analysis; organizational models; digital innovation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to announce this call for paper for a Special Issue in the journal Energies (IF 3.252).

This Special Issue entitled “Feature Papers in Energy Economics and Policy” will focus on recent developments in the area of Energy Economics and the policies that relate to the investment, production, distribution, privatization, nationalization, competition, regulation, and pricing of energy.

These fields have attracted significant research interest over the last decade, but especially over the last two years. The issues covered are extremely topical and draw the attention of academics, policy makers, and the relevant industry. The significant developments in the geopolitical sphere and the orientation toward renewable energy sources that reduce the carbon dioxide footprint, especially in the last decade, provide a rich environment for research and innovation in the area. As a result of these changes, energy economics and the associated energy policy undergo significant changes as they adopt to these new developments and requirements.

We seek the submission of empirical or theoretical work in energy economics, i.e., the production, distribution, storing, forecasting, financing, risk, taxation, trading, exchanges, networks, etc. These may refer to all sources of energy, i.e., coal, hydrocarbons and fossil fuels, renewable energy, nuclear energy, etc.

We are focusing on innovative theoretical and methodological approaches in these fields. These approaches may have a significant impact on policy makers and all relevant stakeholders such as the industry in the production, distribution, and pricing of energy or the consumption of energy by both firms and household consumers. The issues of regulating, pricing, and even the environmental and social welfare consequences of energy in terms of income and poverty are also important.

Theoretical robustness, methodological innovation, and possible applicability of the conclusions are the basic requirements for a paper to be considered for publication.

Prof. Dr. Periklis Gogas
Dr. Donato Morea
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

energy economics
energy policy
energy finance
production
risk and volatility in energy
energy as a commodity
pricing
supply and demand
forecasting energy production and prices
energy exchanges
distribution of energy
regulation
privatization
nationalization
geopolitical issues
subsidies in energy producers and consumers
renewable energy
social welfare impact
environmental impact

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Published Papers (6 papers)

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19 pages, 6414 KiB

Open AccessFeature PaperArticle

Estimating the Deterministic and Stochastic Levelized Cost of the Energy of Fence-Type Agrivoltaics

by Kyu-Won Hwang and Chul-Yong Lee

Energies 2024, 17(8), 1932; https://doi.org/10.3390/en17081932 - 18 Apr 2024

Cited by 2 | Viewed by 1036

Abstract

Agrivoltaics can be used to supply energy and produce agricultural products in order to meet the growing demand for energy and food. The amount of power generation is affected by the solar panel direction, spacing, tilt, and panel technology; however, there is insufficient empirical data-based research on the operation of agrivoltaics. This study estimates the levelized cost of energy (LCOE) for a fence-based agrivoltaics system using bifacial modules. This study installed and operated photovoltaic (PV) systems on a rice paddy and saltern in South Korea to estimate the input variables that could affect their economic efficiency and LCOE. For the research methods, this study used Monte Carlo simulation (a stochastic analysis method that reflects the uncertainty of the input variables), a deterministic LCOE analysis, and a sensitivity analysis of the input variables. In terms of space utilization, the LCOE of the paddy system (139.07~141.19 KRW/kWh) was found to be relatively lower than that of the saltern system (145.43~146.18 KRW/kWh), implying that the PV system on the paddy was economically favorable. In terms of installation direction, it was more economical to operate the southwest-facing panels (139.07~145.43 KRW/kWh) than the southeast-facing panels (141.19~146.18 KRW/kWh). This study provides foundational policy data for the adoption of fence-based agrivoltaics and contributes to the widespread and active use of agrivoltaics. Full article

(This article belongs to the Special Issue Feature Papers in Energy Economics and Policy)

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17 pages, 2770 KiB

Open AccessArticle

The Effect of Information and Communication Technology on Electricity Intensity in Korea

by Suyi Kim

Energies 2024, 17(8), 1906; https://doi.org/10.3390/en17081906 - 17 Apr 2024

Viewed by 1560

Abstract

This study investigated the impact of information and communication technology (ICT) on electricity intensity, incorporating electricity prices, financial development, and population growth in Korea from 1990 to 2020, using the ARDL (autoregressive distributed lag) model. Three cases were considered, each relating to a different ICT proxy: Internet use, mobile cellular phone use, and exports of ICT-related products. The results varied depending on the proxy used to represent ICT. An increase in mobile cellular phone use leads to an increase in electricity intensity in the long run; however, the short-run effects of this change are unclear. An increase in Internet use also leads to an increase in electricity intensity in the long run but induces a decrease in electricity intensity in the short run. Increments in the exports of ICT-related products lead to an increase in electricity intensity in the short run; however, this effect is negligible in the long run. Electricity prices do not affect electricity intensity in all cases, and financial development reduces the intensity of electricity in the cases of the use of both mobile cellular phones and the Internet as proxies for ICT, whereas population growth increases electricity intensity in all cases. Full article

(This article belongs to the Special Issue Feature Papers in Energy Economics and Policy)

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24 pages, 4197 KiB

Open AccessArticle

Investigating the Impact of Agricultural, Financial, Economic, and Political Factors on Oil Forward Prices and Volatility: A SHAP Analysis

by Hyeon-Seok Kim, Hui-Sang Kim and Sun-Yong Choi

Energies 2024, 17(5), 1001; https://doi.org/10.3390/en17051001 - 21 Feb 2024

Cited by 1 | Viewed by 1295

Abstract

Accurately forecasting crude oil prices is crucial due to its vital role in the industrial economy. In this study, we explored the multifaceted impact of various financial, economic, and political factors on the forecasting of crude oil forward prices and volatility. We used various machine learning models to forecast oil forward prices and volatility based on their superior predictive power. Furthermore, we employed the SHAP framework to analyze individual features to identify their contributions in terms of the prediction. According to our findings, factors contributing to oil forward prices and volatility can be summarized into four key focal outcomes. First, it was confirmed that soybean forward pricing overwhelmingly contributes to oil forward pricing predictions. Second, the SSEC is the second-largest contributor to oil forward pricing predictions, surpassing the contributions of the S&P 500 or oil volatility. Third, the contribution of oil forward prices is the highest in predicting oil volatility. Lastly, the contribution of the DXY significantly influences both oil forward price and volatility predictions, with a particularly notable impact on oil volatility predictions. In summary, through the SHAP framework, we identified that soybean forward prices, the SSEC, oil volatility, and the DXY are the primary contributors to oil forward price predictions, while oil forward prices, the S&P 500, and the DXY are the main contributors to oil volatility predictions. These research findings provide valuable insights into the most-influential factors for predicting oil forward prices and oil volatility, laying the foundation for informed investment decisions and robust risk-management strategies. Full article

(This article belongs to the Special Issue Feature Papers in Energy Economics and Policy)

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27 pages, 773 KiB

Open AccessFeature PaperArticle

Hedging Strategies in Carbon Emission Price Dynamics: Implications for Shipping Markets

by Theodoros Syriopoulos, Efthymios Roumpis and Michael Tsatsaronis

Energies 2023, 16(17), 6396; https://doi.org/10.3390/en16176396 - 4 Sep 2023

Cited by 1 | Viewed by 2831

Abstract

The European Union (EU) has agreed to gradually include shipping in the EU emissions trading scheme (EU ETS), which makes shipping companies vulnerable to carbon price fluctuations. The aim of this paper is to investigate the effectiveness of carbon and petroleum futures contracts in managing carbon and bunker risks. We examine the effectiveness of alternative hedging methods, including both static and dynamic approaches, to estimate optimal hedge ratios under single and composite cross-hedge settings. Our results show that carbon future contracts are important for hedging the carbon emission allowances price risk, and Brent oil futures are the most effective instrument for out-of-sample hedging of bunker prices. In addition, the hedging effectiveness indicates that conventional methods outperform the sophisticated models in terms of variance reduction. Our study offers new insights into how the carbon and bunker markets relate to a combination hedging in reducing the joint price risk, which can be used to promote risk management in the market. Full article

(This article belongs to the Special Issue Feature Papers in Energy Economics and Policy)

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16 pages, 6642 KiB

Open AccessArticle

Comparison and Enhancement of Machine Learning Algorithms for Wind Turbine Output Prediction with Insufficient Data

by Subin Im, Hojun Lee, Don Hur and Minhan Yoon

Energies 2023, 16(15), 5810; https://doi.org/10.3390/en16155810 - 4 Aug 2023

Cited by 1 | Viewed by 1474

Abstract

As the penetration of renewable energy sources into a power system increases, the significance of precise short-term forecasts for wind power generation becomes paramount. However, the erratic and non-periodic nature of wind poses challenges in accurately predicting the output. This paper presents a comprehensive investigation into forecasting wind power generation for the following day, using three machine learning models: long short-term memory (LSTM), convolutional neural network-bidirectional LSTM (CNN-biLSTM), and light gradient boosting machine (LGBM). In addition, this paper proposes a method to improve the prediction performance of LGBM by separating data according to the distribution of features, and training and testing each separated dataset with a distinct model. This study includes a comparative analysis of the performance of the proposed models in predicting wind turbine output, offering valuable insights into their respective efficiencies. The results of this investigation were analyzed for two geographically distinct wind farms (Korea and the UK). The findings of this study are expected to facilitate the selection of efficient prediction models within the forecast accuracy auxiliary service market and assist grid operators in ensuring reliable power supply for the grid. Full article

(This article belongs to the Special Issue Feature Papers in Energy Economics and Policy)

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15 pages, 839 KiB

Open AccessPerspective

A Three-Stage Psychosocial Engineering-Based Method to Support Controversy and Promote Mutual Understanding between Stakeholders: The Case of CO₂ Geological Storage

by Kévin Nadarajah, Laurent Brun, Stéphanie Bordel, Emeline Ah-Tchine, Anissa Dumesnil, Antoine Marques Mourato, Jacques Py, Laurent Jammes, Xavier Arnauld De Sartre and Alain Somat

Energies 2024, 17(5), 1014; https://doi.org/10.3390/en17051014 - 21 Feb 2024

Viewed by 1182

Abstract

Subsurface engineering projects with high socio-environmental impacts raise strong controversies among stakeholders, which often affects the projects’ implementation. These controversies originate from a loss of public confidence in the decision-making process, lack of information about new technologies, and the desire of some promoters to avoid conflict. The lack of methodologies to structure each stage of the debate can, in this context, lead to the crystallization of the stakeholders’ positions and to the failure of the project. To promote mutual understanding and constructive exchanges, this article presents a combination of methods based on psychosocial engineering principles to support debate and encourage stakeholders to participate with an openness posture. The method is based on a set of studies conducted as part of the “Social Governance for Subsurface Engineering” project and includes three stages: (1) develop stakeholders’ knowledge so that they are able to participate in the debate with an informed viewpoint; (2) commit stakeholders to participate in the debate by adopting a posture conducive to constructive exchanges; and (3) structure exchanges between stakeholders through the use of cooperative methods facilitating the adoption of an openness posture. Full article

(This article belongs to the Special Issue Feature Papers in Energy Economics and Policy)

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