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Energies
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Modeling Electricity Markets and Energy Systems: Challenges and Opportunities Ahead
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Modeling Electricity Markets and Energy Systems: Challenges and Opportunities Ahead

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 (25 November 2023) | Viewed by 8640

Special Issue Editors

Dr. Danial Esmaeili Aliabadi

E-Mail Website
Guest Editor
Department of Bioenergy, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
Interests: energy systems; agent-based modeling and simulation; electricity markets
Prof. Dr. Tiago Pinto

E-Mail Website
Guest Editor
1. Department of Engineering, University of Trás-os-Montes e Alto Douro, 5001-801 Vila Real, Portugal
2. INESCTEC, University of Trás-os-Montes e Alto Douro, 5001-801 Vila Real, Portugal
Interests: artificial intelligence; machine learning; multi-agent systems; electricity markets; smart grid
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Not long ago, electricity markets were predominantly occupied by conventional power plants that produce electricity by burning fossil fuels. As the insidious ecological consequences of global warming became evident, governments worldwide decided to reduce greenhouse gas emissions. Nowadays, renewable energy technologies are changing the outlook of the climate crisis. Policymakers all over the globe support these technologies through various instruments (e.g., levies and tariffs) to decarbonize the power sector. Energy system models also harmoniously predict a higher deployment of renewable technologies in the forthcoming decades as they increasingly become affordable.

Unfortunately, the intermittency of these renewable sources (when deployed in large quantities) can introduce instability to the power grid, thereby causing tremendous challenges for system operators to sustain the electricity supply and demand balance. The imbalance between supply and demand can incite blackouts if operators foresee no contingency plan to dampen these fluctuations. Furthermore, the variability of renewables can raise the cost of electricity, which can directly impact future capacity expansion investment decisions. Therefore, the long-term effects of the variability in the power market models should be manifested in energy system models that optimize long-term investments.  

One way to overcome this issue is to incorporate new technologies and pathways to satisfy energy service demands. We have alternative energy vectors (e.g., hydrogen, ammonia) in the arsenal that can assist us in transferring energy through spatial and temporal boundaries and introduce flexibility to a carbon-neutral power sector. Although these technologies are analyzed extensively in energy system models, their roles in the future electricity grid are being overlooked. This shortcoming is due to the fact that energy system models have lower temporal and spatial resolution than power market models; therefore, underlying models can encompass higher technological explicitness to study the interplay between other energy vectors and renewables. The borderland separating the power market and energy system models is vanishing as computing power proliferates at a considerable rate, which enables the next generation of energy system models to consider operational complexity with high temporal and spatial detail.

The demand for disseminating knowledge in the open access mode regarding the latest advancements in energy systems and power markets modeling has persuaded us to create a Special Issue in the Energies journal. Experts are invited to share their latest findings in the form of original research papers, reviews, and successful case studies. The works presented in this Special Issue should concern the latest developments in energy systems and power market modeling; the coupling of energy systems and electricity market models; improving the spatial, temporal, and technological resolution of energy system models; visualizing complex energy system models; and studying the behavior of stakeholders in energy systems and electricity markets.

Dr. Danial Esmaeili Aliabadi
Dr. Tiago Pinto
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 system model
  • power market model
  • soft-coupling
  • hard-coupling
  • power generation companies
  • players’ behavior
  • energy vectors
  • visualization
  • co-simulation
  • optimization
  • flexibility
  • intermittency
  • renewable energy sources
  • sustainable development
  • technology explicitness
  • spatial resolution
  • temporal resolution

Published Papers (5 papers)

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Research

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23 pages, 411 KiB  
Article
Strategic Behavior of Competitive Local Citizen Energy Communities in Liberalized Electricity Markets
by Hugo Algarvio, António Couto, Fernando Lopes and Ana Estanqueiro
Energies 2024, 17(8), 1863; https://doi.org/10.3390/en17081863 - 13 Apr 2024
Viewed by 297
Abstract
The liberalization of energy retail markets empowered consumers with the ability to be part of new emerging entities, such as Citizen Energy Communities. With the increasing penetration of decentralized variable generation, communities have the advantage of incentive local carbon neutrality and sustainability. Local [...] Read more.
The liberalization of energy retail markets empowered consumers with the ability to be part of new emerging entities, such as Citizen Energy Communities. With the increasing penetration of decentralized variable generation, communities have the advantage of incentive local carbon neutrality and sustainability. Local generation reduces transport grid usage and costs to consumers. Furthermore, worldwide legislation incentives energy communities by providing them discounts to other fee parts of the tariff apart from wholesale prices. This paper presents a model of strategic behavior, investment, and trading of energy communities. The model comprises the investment in local renewable generation, the design of competitive tariffs, and strategic bidding on wholesale markets. Consumers have an optimization model that selects the retail tariff that minimizes their costs with energy. These models are tested using data from Portuguese consumers and the Iberian electricity market. Results from the study indicate that inflexible consumers may reduce their costs by 29% by being part of the community. Furthermore, they have the potential to reduce their costs above 50% when using demand–response, adapting themselves to local production and wholesale prices. Full article
(This article belongs to the Special Issue Modeling Electricity Markets and Energy Systems: Challenges and Opportunities Ahead)
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14 pages, 2562 KiB  
Article
Integrating Knowledge Acquisition, Visualization, and Dissemination in Energy System Models: BENOPTex Study
by Danial Esmaeili Aliabadi, David Manske, Lena Seeger, Reinhold Lehneis and Daniela Thrän
Energies 2023, 16(13), 5113; https://doi.org/10.3390/en16135113 - 02 Jul 2023
Cited by 2 | Viewed by 1178
Abstract
While storytelling and visualization have always been recognized as invaluable techniques for imparting knowledge across generations, their importance has become even more evident in the present information age as the abundance of complex data grows exponentially. These techniques can simplify convoluted concepts and [...] Read more.
While storytelling and visualization have always been recognized as invaluable techniques for imparting knowledge across generations, their importance has become even more evident in the present information age as the abundance of complex data grows exponentially. These techniques can simplify convoluted concepts and communicate them in a way to be intelligible for diverse audiences, bringing together heterogeneous stakeholders and fostering collaboration. In the field of energy and climate research, there is an increasing demand to make sophisticated models and their outcomes explainable and comprehensible for an audience of laypersons. Unfortunately, traditional tools and methods may be inefficient to provide meaning for input and output values; therefore, in this study, we employ a storytelling tool, the so-called Academic Presenter, to digest various datasets and visualize the extended BioENergy OPTimization model (BENOPTex) outcomes in different online and offline formats. The developed tool facilitates communications among collaborators with a broad spectrum of backgrounds by transforming outcomes into visually appealing stories. Although this study focuses on designing an ideal user interface for BENOPTex, the developed features and the learned lessons can be replicated for other energy system models. Full article
(This article belongs to the Special Issue Modeling Electricity Markets and Energy Systems: Challenges and Opportunities Ahead)
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16 pages, 2480 KiB  
Article
Temporally and Spatially Resolved Simulation of the Wind Power Generation in Germany
by Reinhold Lehneis and Daniela Thrän
Energies 2023, 16(7), 3239; https://doi.org/10.3390/en16073239 - 04 Apr 2023
Cited by 2 | Viewed by 1627
Abstract
Temporally and spatially resolved data on wind power generation are very useful for studying the technical and economic aspects of this variable renewable energy at local and regional levels. Due to the lack of disaggregated electricity data from onshore and offshore turbines in [...] Read more.
Temporally and spatially resolved data on wind power generation are very useful for studying the technical and economic aspects of this variable renewable energy at local and regional levels. Due to the lack of disaggregated electricity data from onshore and offshore turbines in Germany, it is necessary to use numerical simulations to calculate the power generation for a given geographic area and time period. This study shows how such a simulation model, which uses freely available plant and weather data as input variables, can be developed with the help of basic atmospheric laws and specific power curves of wind turbines. The wind power model is then applied to ensembles of nearly 28,000 onshore and 1500 offshore turbines to simulate the wind power generation in Germany for the years 2019 and 2020. For both periods, the obtained and spatially aggregated time series are in good agreement with the measured feed-in patterns for the whole of Germany. Such disaggregated simulation results can be used to analyze the power generation at any spatial scale, as each turbine is simulated separately with its location and technical parameters. This paper also presents the daily resolved wind power generation and associated indicators at the federal state level. Full article
(This article belongs to the Special Issue Modeling Electricity Markets and Energy Systems: Challenges and Opportunities Ahead)
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13 pages, 2675 KiB  
Article
Considering Forward Electricity Prices for a Hydro Power Plant Risk Analysis in the Brazilian Electricity Market
by Arthur Lauro, Daniel Kitamura, Waleska Lima, Bruno Dias and Tiago Soares
Energies 2023, 16(3), 1173; https://doi.org/10.3390/en16031173 - 20 Jan 2023
Cited by 1 | Viewed by 1296
Abstract
The Brazilian Power System is mainly composed of renewable generation from hydroelectric and wind. Hence, spot and forward electricity prices tend to represent the inherently stochastic nature of these resources, while risk management is a measure taken by agents, especially hydro power plants [...] Read more.
The Brazilian Power System is mainly composed of renewable generation from hydroelectric and wind. Hence, spot and forward electricity prices tend to represent the inherently stochastic nature of these resources, while risk management is a measure taken by agents, especially hydro power plants (HPPs) to hedge against deep financial losses. A HPP goal is to maximize its profit considering uncertainties in forward electricity prices, spot prices, and generation scaling factor (GSF) for years ahead. Therefore, the objective of this work is to simulate the real decision-making process of a HPP, where they need to have a perspective of the forward market and future spot price assessment to negotiate forward electricity contracts. To do so, the present work models the uncertainty in electricity forward prices via two-stage stochastic programming, assessing the benefits of the stochastic solution in comparison to the deterministic one. In addition, different risk aversion levels are assessed using conditional value at risk (CVaR). An important conclusion is that the results show that the greater the HPP risk aversion is, the greater the energy selling via electricity forward contracts. Moreover, the proposed model has benefits in comparison to a deterministic approach. Full article
(This article belongs to the Special Issue Modeling Electricity Markets and Energy Systems: Challenges and Opportunities Ahead)
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Review

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28 pages, 429 KiB  
Review
Market Manipulation in Stock and Power Markets: A Study of Indicator-Based Monitoring and Regulatory Challenges
by Yuna Hao, Behrang Vand, Benjamin Manrique Delgado and Simone Baldi
Energies 2023, 16(4), 1894; https://doi.org/10.3390/en16041894 - 14 Feb 2023
Viewed by 2901
Abstract
In recent years, algorithmic-based market manipulation in stock and power markets has considerably increased, and it is difficult to identify all such manipulation cases. This causes serious challenges for market regulators. This work highlights and lists various aspects of the monitoring of stock [...] Read more.
In recent years, algorithmic-based market manipulation in stock and power markets has considerably increased, and it is difficult to identify all such manipulation cases. This causes serious challenges for market regulators. This work highlights and lists various aspects of the monitoring of stock and power markets, using as test cases the regulatory agencies and regulatory policies in diverse regions, including Hong Kong, the United Kingdom, the United States and the European Union. Reported cases of market manipulations in the regions are examined. In order to help establish a relevant digital regulatory system, this work reviews and categorizes the indicators used to monitor the stock and power markets, and provides an in-depth analysis of the relationship between the indicators and market manipulation. This study specifically compiles a set of 10 indicators for detecting manipulation in the stock market, utilizing the perspectives of return rate, liquidity, volatility, market sentiment, closing price and firm governance. Additionally, 15 indicators are identified for detecting manipulation in the power market, utilizing the perspectives of market power (also known as pricing power or market structure), market conduct and market performance. Finally, the study elaborates on the current challenges in the regulation of stock and power markets in terms of parameter performance, data availability and technical requirements. Full article
(This article belongs to the Special Issue Modeling Electricity Markets and Energy Systems: Challenges and Opportunities Ahead)
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