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Special Issue "Power Converters, Electric Drives and Energy Storage Systems for Electrified Transportation and Smart Grid"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "Smart Grids and Microgrids".

Deadline for manuscript submissions: 31 March 2020.

Special Issue Editors

Guest Editor
Prof. Dr. Sergio Saponara

Department of Information Engineering (DII), University of Pisa, 56122 Pisa, Italy
Website | E-Mail
Interests: electric/hybrid vehicles; autonomous and connected vehicles; smart energy systems; energy storage systems; predictive diagnostics
Guest Editor
Prof. Dr. Lucian Mihet-Popa

Faculty of Engineering, Østfold University College, Kobberslagerstredet 5, 1671 Fredrikstad, Norway
Website | E-Mail
Phone: +4792271353
Interests: modelling, simulations, control and testing of DER components (including BESS) in power distribution systems (micro-grids, smart grids); integration of DGs and renewable energy sources including PV, EV, and BESS; energy efficiency in smart buildings

Special Issue Information

Dear Colleagues,

We are inviting submissions to a Special Issue of Energies entitled “Power Converters, Electric Drives, and Energy Storage Systems for Electrified Transportation and Smart Grids”.

Research activities in the field of energy storage technologies, management, and systems, and in the field of advanced electromobility, are essential for the success of electric transportation and to foster the use of renewable energy sources. Indeed, renewable energy sources are intermittent in nature and are not directly matched with users’ requirements. Energy storage systems are the key technology to solve these issues and to increase the adoption of renewable sources in smart grids. However, major challenges have still to be solved such as the design of high-performance and cost-effective energy storage systems; power electronics for the monitoring and management of battery cells and packs (BMS); the on-line estimation of state-of-charge/state-of-health of batteries and super/ultra-capacitors; the estimation of aging effects; the design and optimization of fast chargers, including also wireless power transfer; and integration within the smart grid of the charging infrastructure for e-transportation. For both chargers and BMS, cybersecurity, digitization, and interconnectivity with the infrastructure, partly thanks to the advent of 5G, are important issues.

Power converters and electric drives also need optimization in terms of increased efficiency and the implementation of predictive diagnostic and predictive maintenance features. Advanced control techniques for power electronic converters and motors, which also exploit machine learning, artificial intelligence (AI), and deep neural networks (DNN), are emerging trends. Applications are for both full electric and hybrid vehicles. Beside the hardware parts, the role of software is also increasing and new design and verification methods have to be investigated to achieve high functional safety and security levels for accelerating clean energy innovation.

The main objective of this Special Issue is, hence, to provide timely solutions for the design and management of energy storage systems, of renewable energy sources, and of relevant power electronic converter systems and innovative electric drives.

The integration of all these systems within the smart grid for e-transportation and smart/green cities is also of interest for the Special Issue. With reference to this “internet of energy” scenario, the application of IoT (Internet of things) technologies to E-transportation and smart grids is also of interest, including opportunities and challenges due to cybersecurity and 5G.

The particular topics of interest of this SI include but are not limited to the following:

  • New emerging technologies for power converters, electric drives, and energy storage;
  • Ageing mechanisms of power converters, electric drives, and energy storage devices;
  • Electronic control units for energy storage system monitoring and management;
  • Online estimation of state-of-charge and state-of-health;
  • Power electronic converters for renewable energy sources;
  • Fast chargers and smart chargers for electric-vehicles, including wireless power transfer;
  • Integration of charging infrastructures in the smart grid for E-transportation;
  • Predictive diagnostic for renewables and energy storage systems;
  • Methods for design and verification of HW and SW for energy storage and renewables;
  • Embedded systems, machine learning, AI, DNN for energy storage, conversion, and management;
  • Integration of IoT and digitalization into E-transportation;
  • Cybersecurity and 5G connectivity challenges and opportunities for energy.

Prof. Dr. Sergio Saponara
Prof. Dr. Lucian Mihet Popa
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 1800 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

  • Emerging energy storage technologies;
  • Ageing of energy storage and power converters;
  • Fast chargers and wireless power transfer;
  • Monitoring and management of energy storage systems and BMS;
  • Embedded systems, machine learning, DNN for energy storage, conversion, and management;
  • Power electronic converters;
  • Renewable energy sources;
  • Predictive diagnostic and maintenance;
  • E-transportation chargers, including wireless power transfer, and smart-grids;
  • Internet-of-energy and cybersecurity and 5G connectivity challenges and opportunities.

Published Papers (3 papers)

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Research

Open AccessArticle
Microcontroller-Based Strategies for the Incorporation of Solar to Domestic Electricity
Energies 2019, 12(14), 2811; https://doi.org/10.3390/en12142811
Received: 4 June 2019 / Revised: 28 June 2019 / Accepted: 16 July 2019 / Published: 22 July 2019
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Abstract
Microcontrollers have been largely used in applications that include reducing power consumption. Microcontroller development tools are now readily available. Many countries are faced with energy challenges such as lack of enough power capacity and growth in energy demand. It is therefore important to [...] Read more.
Microcontrollers have been largely used in applications that include reducing power consumption. Microcontroller development tools are now readily available. Many countries are faced with energy challenges such as lack of enough power capacity and growth in energy demand. It is therefore important to introduce innovative methods to reduce reliance on national grid energy and to supplement this source of energy with alternative methods. In this study, the microcontroller is used to monitor the energy consumed by household equipment and then decide, based on the power demand and available solar energy, the type of energy source to be used. In this research, a special circuit was also designed to control geyser power and align it to the capacity of the renewable energy source. This geyser control circuit includes a Dallas temperature sensor and a triode for alternating current (TRIAC) circuit that is included to control output current drawn from a low power, renewable energy source. Alternatively, two heating elements may be used instead of the TRIAC circuit. The first heating element is powered by solar to maintain the water temperature and to save energy. The second heating element is powered by national grid power and is used for the initial heating, and therefore saves water heating time. The strategy used was by adding a programmed microcontroller-based control circuit and a low power element or one current controlled element to a geyser whereby Photovoltaic (PV) energy was used to save the energy geysers consume from the domestic electricity source when they are not in use. A microcontroller, current sensor, battery level sensor, and relay board was used to incorporate solar-based renewable energy to the commercial energy supply. Full article
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Open AccessArticle
Cogging Torque Reduction in Brushless Motors by a Nonlinear Control Technique
Energies 2019, 12(11), 2224; https://doi.org/10.3390/en12112224
Received: 1 April 2019 / Revised: 3 June 2019 / Accepted: 9 June 2019 / Published: 11 June 2019
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Abstract
This work addresses the problem of mitigating the effects of the cogging torque in permanent magnet synchronous motors, particularly brushless motors, which is a main issue in precision electric drive applications. In this work, a method for mitigating the effects of the cogging [...] Read more.
This work addresses the problem of mitigating the effects of the cogging torque in permanent magnet synchronous motors, particularly brushless motors, which is a main issue in precision electric drive applications. In this work, a method for mitigating the effects of the cogging torque is proposed, based on the use of a nonlinear automatic control technique known as feedback linearization that is ideal for underactuated dynamic systems. The aim of this work is to present an alternative to classic solutions based on the physical modification of the electrical machine to try to suppress the natural interaction between the permanent magnets and the teeth of the stator slots. Such modifications of electric machines are often expensive because they require customized procedures, while the proposed method does not require any modification of the electric drive. With respect to other algorithmic-based solutions for cogging torque reduction, the proposed control technique is scalable to different motor parameters, deterministic, and robust, and hence easy to use and verify for safety-critical applications. As an application case example, the work reports the reduction of the oscillations for the angular position control of a permanent magnet synchronous motor vs. classic PI (proportional-integrative) cascaded control. Moreover, the proposed algorithm is suitable to be implemented in low-cost embedded control units. Full article
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Open AccessArticle
Spatio-Temporal Model for Evaluating Demand Response Potential of Electric Vehicles in Power-Traffic Network
Energies 2019, 12(10), 1981; https://doi.org/10.3390/en12101981
Received: 23 April 2019 / Revised: 17 May 2019 / Accepted: 18 May 2019 / Published: 23 May 2019
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Abstract
Electric vehicles (EVs) can be regarded as a kind of demand response (DR) resource. Nevertheless, the EVs travel behavior is flexible and random, in addition, their willingness to participate in the DR event is uncertain, they are expected to be managed and utilized [...] Read more.
Electric vehicles (EVs) can be regarded as a kind of demand response (DR) resource. Nevertheless, the EVs travel behavior is flexible and random, in addition, their willingness to participate in the DR event is uncertain, they are expected to be managed and utilized by the EV aggregator (EVA). In this perspective, this paper presents a composite methodology that take into account the dynamic road network (DRN) information and fuzzy user participation (FUP) for obtaining spatio-temporal projections of demand response potential from electric vehicles and the electric vehicle aggregator. A dynamic traffic network model taking over the traffic time-varying information is developed by graph theory. The trip chain based on housing travel survey is set up, where Dijkstra algorithm is employed to plan the optimal route of EVs, in order to find the travel distance and travel time of each trip of EVs. To demonstrate the uncertainties of the EVs travel pattern, simulation analysis is conducted using Monte Carlo method. Subsequently, we suggest a fuzzy logic-based approach to uncertainty analysis that starts with investigating EV users’ subjective ability to participate in DR event, and we develop the FUP response mechanism which is constructed by three factors including the remaining dwell time, remaining SOC, and incentive electricity pricing. The FUP is used to calculate the real-time participation level of a single EV. Finally, we take advantage of a simulation example with a coupled 25-node road network and 54-node power distribution system to demonstrate the effectiveness of the proposed method. Full article
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