Special Issue "Energy Transition: Decentralization, Electric Vehicles, and Local Energy Markets"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A6: Electric Vehicles".

Deadline for manuscript submissions: 10 February 2022.

Special Issue Editors

Dr. Fernando Lezama
E-Mail Website
Guest Editor
GECAD–Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Institute of Engineering, Polytechnic of Porto (ISEP/IPP), 4200-072 Porto, Portugal
Interests: computational intelligence; energy resource management; energy systems simulation; evolutionary computation; local energy markets; multi-agent systems; smart grids
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Zita Vale
E-Mail Website
Guest Editor
GECAD-Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Polytechnic of Porto (P.PORTO), P-4200-465 Porto, Portugal
Interests: artificial intelligence; demand response; electric vehicles; electricity markets; power and energy systems; renewable and sustainable energy; smart grids
Special Issues, Collections and Topics in MDPI journals
Dr. John Fredy Franco
E-Mail Website
Guest Editor
School of Energy Engineering, São Paulo State University (UNESP), Rosana, Brazil
Interests: power systems; distribution networks; smart grids; distributed energy resources

Special Issue Information

Dear Colleagues,

The power industry is on the move for a significant transformation motivated by the clean energy and zero carbon emissions acts. Moreover, the world will likely face a faster energy transition due to the COVID-19 pandemic. The proliferation of distributed energy resources (DERs) in distribution networks, namely PV panels and electric vehicles, is transforming conventional centralized management into a decentralized, bottom-up, localized control model. Local markets are emerging as a promising solution to address the problem of large amounts of energy resources at this level. Trading of energy and flexibility for local agents can be achieved with adequate coordination at the distribution grid; however, this transition is not possible without solving new technical and economic challenges. The new paradigm is calling for innovative ideas and solutions with a highly interdisciplinary research scope.

This Special Issue invites original research papers for publication focusing on topics of interest including but limited to the following:

  • Pricing, market clearing, and validation methods in local electricity markets;
  • Local market architecture, business models, cost–benefit analysis, and energy policies for the adoption of DER;
  • Coordination and interactions between markets at different levels, e.g., local, distribution, and wholesale markets;
  • Modelling and coordination of different actors interacting at the different levels of the energy chain, e.g., local, distribution, and transmission levels;
  • Flexibility services for DSO, TSO, and balancing responsible parties (i.e., grid service trading);
  • Distributed ledger technology (including blockchain) for peer-to-peer energy markets and transactive energy;
  • Classical and modern optimization methods for scalable management and control of large-scale DER;
  • Modern ICT to implement decentralized energy systems in the smart grid paradigm;
  • Decentralized electric vehicle management and scheduling models;
  • Local electricity market models for electric vehicles;
  • Smart contracts for electric vehicles.

Dr. João Soares
Dr. Fernando Lezama
Prof. Dr. Zita Vale
Dr. John Fredy Franco
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 papers will be 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 2200 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 (1 paper)

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Smart Charging of Electric Vehicles Considering SOC-Dependent Maximum Charging Powers
Energies 2021, 14(22), 7755; https://doi.org/10.3390/en14227755 - 18 Nov 2021
Cited by 1 | Viewed by 454
The aim of this work is to schedule the charging of electric vehicles (EVs) at a single charging station such that the temporal availability of each EV as well as the maximum available power at the station are considered. The total costs for [...] Read more.
The aim of this work is to schedule the charging of electric vehicles (EVs) at a single charging station such that the temporal availability of each EV as well as the maximum available power at the station are considered. The total costs for charging the vehicles should be minimized w.r.t. time-dependent electricity costs. A particular challenge investigated in this work is that the maximum power at which a vehicle can be charged is dependent on the current state of charge (SOC) of the vehicle. Such a consideration is particularly relevant in the case of fast charging. Considering this aspect for a discretized time horizon is not trivial, as the maximum charging power of an EV may also change in between time steps. To deal with this issue, we instead consider the energy by which an EV can be charged within a time step. For this purpose, we show how to derive the maximum charging energy in an exact as well as an approximate way. Moreover, we propose two methods for solving the scheduling problem. The first is a cutting plane method utilizing a convex hull of the, in general, nonconcave SOC–power curves. The second method is based on a piecewise linearization of the SOC–energy curve and is effectively solved by branch-and-cut. The proposed approaches are evaluated on benchmark instances, which are partly based on real-world data. To deal with EVs arriving at different times as well as charging costs changing over time, a model-based predictive control strategy is usually applied in such cases. Hence, we also experimentally evaluate the performance of our approaches for such a strategy. The results show that optimally solving problems with general piecewise linear maximum power functions requires high computation times. However, problems with concave, piecewise linear maximum charging power functions can efficiently be dealt with by means of linear programming. Approximating an EV’s maximum charging power with a concave function may result in practically infeasible solutions, due to vehicles potentially not reaching their specified target SOC. However, our results show that this error is negligible in practice. Full article
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