energies-logo

Journal Browser

Journal Browser

New Trends in the Econometric and Microeconomic Modelling of 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: closed (30 December 2021) | Viewed by 5912

Special Issue Editor


E-Mail Website
Guest Editor
School of Economics, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece
Interests: energy; finance; econometrics; computer science; operations research
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The past thirty years have seen the establishment of wholesale electricity markets on a global scale followed by an upsurge of research interest in market design and the price formation mechanism. Electricity prices have distinctive features that are dictated by the nature of power production, limitations in existing storage technologies, and insufficient network infrastructure. For instance, the absence of affordable storage facilities that could be deployed on a grid scale makes it hard for system operators to buffer imbalances between generation and load, giving rise to an endogenous level of price volatility and occasional large price disruptions (spikes). Limitations in transmission capacity and cross-market hedging activities also prevent shifting power generation over space to close temporal price gaps between adjacent bidding zones. The technological inflexibility of certain generating units to immediately adjust their output causes slow absorption of price shocks and the emergence of dependencies that extend over long time scales. Slow cycling patterns in power prices are also imposed by seasonal shifts in electricity consumption, yearly variations in renewable energy generation, and business-cycle effects.

The confluence of all these factors adds to the increasing complexity of empirical price-generation processes, which calls for advanced modelling solutions. The purpose of this Special Issue is to present state-of-the-art approaches to power price and electricity markets modelling. The issue welcomes contributions in the wider context of electricity markets research, including econometric studies, microeconomic models, and agent-based simulation paradigms.

Example topics include but are not limited to the following:

  • Panel data models, forecasting and dimensionality reduction techniques, nonlinear econometric and computational intelligence paradigms for electricity markets
  • Fundamental electricity pricing models, the merit order effect, dependencies with other energy commodity markets
  • The interplay between electricity and financial markets (e.g. markets for electricity futures)
  • Agent-based modelling and market microstructure
  • New designs and trading protocols facilitating vertical and horizontal (cross-border) market integration
  • Integration and price convergence between spatially disaggregated electricity markets

Assist. Prof. Dr. Nikolaos S. Thomaidis
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.

Published Papers (3 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

24 pages, 1361 KiB  
Article
Understanding Power Market Dynamics by Reflecting Market Interrelations and Flexibility-Oriented Bidding Strategies
by Ramiz Qussous, Nick Harder and Anke Weidlich
Energies 2022, 15(2), 494; https://0-doi-org.brum.beds.ac.uk/10.3390/en15020494 - 11 Jan 2022
Cited by 13 | Viewed by 2424
Abstract
Power markets are becoming increasingly complex as they move towards (i) integrating higher amounts of variable renewable energy, (ii) shorter trading intervals and lead times, (iii) stronger interdependencies between related markets, and (iv) increasing energy system integration. For designing them appropriately, an enhanced [...] Read more.
Power markets are becoming increasingly complex as they move towards (i) integrating higher amounts of variable renewable energy, (ii) shorter trading intervals and lead times, (iii) stronger interdependencies between related markets, and (iv) increasing energy system integration. For designing them appropriately, an enhanced understanding of the dynamics in interrelated short-term physical power and energy markets is required, which can be supported by market simulations. In this paper, we present an agent-based power market simulation model with rule-based bidding strategies that addresses the above-mentioned challenges, and represents market participants individually with a high level of technical detail. By allowing agents to participate in several interrelated markets, such as the energy-only market, a procurement platform for control reserve and a local heat market representing district heating systems, cross-market opportunity costs are well reflected. With this approach, we were able to reproduce EPEX SPOT market outcomes for the German bidding zone with a high level of accuracy (mean absolute percentage error of 8 €/MWh for the years 2016–2019). We were also able to model negative market prices at the energy-only market realistically, and observed that the occurrence of negative prices differs among data inputs used. The simulation model provides a useful tool for investigating different short-term physical power/energy market structures and designs in the future. The modular structure also enables extension to further related markets, such as fuel, CO2, or derivative markets. Full article
Show Figures

Figure 1

14 pages, 2296 KiB  
Article
Fundamental Responsiveness in European Electricity Prices
by Michail I. Seitaridis, Nikolaos S. Thomaidis and Pandelis N. Biskas
Energies 2021, 14(22), 7623; https://0-doi-org.brum.beds.ac.uk/10.3390/en14227623 - 15 Nov 2021
Viewed by 1303
Abstract
We estimate fundamental pricing relationships in selected European day-ahead electricity markets. Using a fractionally integrated panel data model with unobserved common effects, we quantify the responsiveness of hourly electricity prices to two fundamental leading indicators of day-ahead markets: the predicted load and renewable [...] Read more.
We estimate fundamental pricing relationships in selected European day-ahead electricity markets. Using a fractionally integrated panel data model with unobserved common effects, we quantify the responsiveness of hourly electricity prices to two fundamental leading indicators of day-ahead markets: the predicted load and renewable generation. The application of fractional cointegration analysis techniques gives further insight into the pricing mechanism of power delivery contracts, enabling us to measure the persistence of fundamental shocks. Full article
Show Figures

Figure 1

25 pages, 8677 KiB  
Article
Manual Frequency Restoration Reserve Activation Clearing Model
by Christos Roumkos, Pandelis N. Biskas and Ilias Marneris
Energies 2021, 14(18), 5793; https://0-doi-org.brum.beds.ac.uk/10.3390/en14185793 - 14 Sep 2021
Cited by 3 | Viewed by 1409
Abstract
The integration of the European markets has started with the successful coupling of spot markets (day-ahead and intra-day) and is expected to continue with the coupling of balancing markets. In this paper, the optimization model for the activation of manual frequency restoration reserve [...] Read more.
The integration of the European markets has started with the successful coupling of spot markets (day-ahead and intra-day) and is expected to continue with the coupling of balancing markets. In this paper, the optimization model for the activation of manual frequency restoration reserve (mFRR) is presented. The model incorporates all order types agreed among the European transmission system operators (TSOs) to be included in the Manually Activated Reserves Initiative (MARI) project. Additionally, the model incorporates the buying curve (demand) of mFRR with the possible tolerance band defined by the TSOs, order clearing constraints and the cross-zonal capacity (CZC) constraints, forming a mixed integer linear programming model. The methodology employs two distinct steps: In the first step, an order conversion process is employed for the markets applying the central-scheduling scheme, and in the second step, the mFRR activation process is executed by solving the presented model. The whole process is tested using a case, including twenty-five European control areas. The attained clearing results indicate that price convergence is achieved among the involved control areas, along with a reduction in the overall balancing costs mainly due to the imbalance netting that is implicitly performed during the joint mFRR balancing energy (BE) clearing process and due to the cross-border exchange of mFRR BE. Full article
Show Figures

Figure 1

Back to TopTop