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Advanced Management and Control Strategies for Electrical Energy Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".

Deadline for manuscript submissions: closed (20 April 2022) | Viewed by 10029

Special Issue Editors


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Guest Editor
Electrical Engineering Laboratory, Department of Electrical Engineering, University of M’sila, M’sila 28000, Algeria
Interests: distributed power generation; invertors,power grids; power supply quality; control system synthesis; electric current control; PI control,damping; machine control; nonlinear control systems; asynchronous

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Guest Editor
IREENA Laboratory, University of Nantes, 44600 Nantes, France
Interests: control and stability of power systems

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Guest Editor
IREENA Laboratory, University of Nantes, 44600 Nantes, France
Interests: machine control; electric current control; permanent magnet generators; synchronous generators; invertors; power generation control; AC-DC power convertors

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Guest Editor
IREENA Laboratory, University of Nantes, 44602 Saint-Nazaire, France
Interests: renewable energy systems; microgrids; distributed generation; power electronics; power quality; system stability; control of power systems; energy management systems
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Institut de Recherche en Energie Electrique de Nantes Atlantique, University of Nantes, 44602 Saint-Nazaire, France
Interests: Control and stability of power systems

E-Mail Website
Guest Editor
Institut de Recherche en Energie Electrique de Nantes Atlantique, University of Nantes, 44602 Saint-Nazaire, France
Interests: power grids; invertors; load regulation; power supply quality; power system interconnection; control system synthesis; damping; distributed power generation; energy management

E-Mail Website
Guest Editor
Electrical Engineering Laboratory, Department of Electrical Engineering, University of M’sila, M’sila 28000, Algeria
Interests: control and stability of power systems

Special Issue Information

Dear Colleagues,

The development of integrated frameworks for energy management, optimization and control is urgently needed to meet the high penetration levels of renewable energy sources and the development of new generation concepts and grid paradigms. It is expected that a more substantial fraction of the total consumed demand will be produced by renewable resources. Moreover, with the rapidly evolving electric vehicle (EV) technologies and dropping battery costs, more EVs are expected on the roads within the coming few years. Both renewable energy and electric vehicles impose a set of looming challenges to operators. Renewable energy sources are intermittent by nature, adversely affecting the power grid unless they are augmented with energy storage. EVs can collectively represent a significant demand increase during charging, ultimately mandating wide-scale infrastructure upgrade. Infrastructure upgrade can be deferred, and the impact of EVs can be mitigated if they are intelligently managed and their charging/discharging process is coordinated and optimally scheduled. The solution to these challenges requires the development of a set of optimal control strategies and energy management algorithms to reliably operate power grids taking into account renewable energy sources, moving and stationary electric vehicles, and controllable loads.

We cordially invite you to submit your original contributions to this Special Issue, entitled: “Advanced Management and Control Strategies for Electrical Energy Systems.” This is a Special Issue of MDPI’s Energies, an international peer-reviewed open-access journal covered by various databases, including WoS and Scopus. The present Special Issue aims to collect innovative solutions and experimental research supported by appropriate modeling and design, but also state-of-the-art studies, on the following topics:

  • Advanced control solutions for power-electronics dominated systems;
  • Investigating power quality and stability issues in electrical energy systems;
  • Fault-tolerant control in power electronics and drive applications;
  • Energy management and optimization in hybrid energy systems;
  • Hierarchical control techniques for distributed generation systems and microgrids;
  • Renewable energy systems (wind, solar, fuel cells, hybrid renewable energy systems, etc.);
  • Application of artificial intelligence in smart grids;
  • Grid integration of electric vehicles.

Prof. Dr. Ali Djerioui 
Prof. Dr. Mourad Ait Ahmed
Prof. Dr. Mohamed Fouad Benkhoris
Prof. Dr. Azeddine Houari
Prof. Dr. Mohamed MacHmoum
Prof. Dr. Hegazy Rezk
Prof. Dr. Abdelhakim Saim
Prof. Dr. Samir Zeghlache
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

  • power quality
  • microgrids
  • power electronics
  • control theory
  • distributed generation
  • photovoltaics
  • electric vehi-cles
  • renewable energy technologies
  • smart grids
  • electric machines
  • energy storage systems
  • fuel cells
  • hydrogen
  • stability
  • nonlinear control
  • energy management systems
  • metaheuristic optimization
  • fault-tolerant control
  • arti-ficial intelligence

Published Papers (4 papers)

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Research

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11 pages, 3153 KiB  
Article
Development of a Flashover Voltage Prediction Model with the Pollution and Conductivity as Factors Using the Response Surface Methodology
by Oussama Ghermoul, Hani Benguesmia and Loutfi Benyettou
Energies 2022, 15(19), 7161; https://0-doi-org.brum.beds.ac.uk/10.3390/en15197161 - 29 Sep 2022
Cited by 4 | Viewed by 1412
Abstract
In this paper, the response surface methodology (RSM) is used to predict the flashover voltage of a cap and pin 1512L insulator used by SONELGAZ Algerian Power Company (SPE). The pollution and conductivity are studied using a two-level central composite design. MINITAB 19 [...] Read more.
In this paper, the response surface methodology (RSM) is used to predict the flashover voltage of a cap and pin 1512L insulator used by SONELGAZ Algerian Power Company (SPE). The pollution and conductivity are studied using a two-level central composite design. MINITAB 19 software is used to perform the regression analysis and analysis of variance (ANOVA) of the data, from which the full quadratic model is developed. The results show that both the pollution and conductivity have a significant effect on the response. The model validation shows the good agreement between the experiment’s obtained results and the predicted results. Therefore, the model could be used to predict the flashover voltage. Full article
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15 pages, 3785 KiB  
Article
Lithium-Ion Battery Parameter Identification for Hybrid and Electric Vehicles Using Drive Cycle Data
by Yasser Ghoulam, Tedjani Mesbahi, Peter Wilson, Sylvain Durand, Andrew Lewis, Christophe Lallement and Christopher Vagg
Energies 2022, 15(11), 4005; https://0-doi-org.brum.beds.ac.uk/10.3390/en15114005 - 29 May 2022
Cited by 6 | Viewed by 2186
Abstract
This paper proposes an approach for the accurate and efficient parameter identification of lithium-ion battery packs using only drive cycle data obtained from hybrid or electric vehicles. The approach was experimentally validated using data collected from a BMW i8 hybrid vehicle. The dual [...] Read more.
This paper proposes an approach for the accurate and efficient parameter identification of lithium-ion battery packs using only drive cycle data obtained from hybrid or electric vehicles. The approach was experimentally validated using data collected from a BMW i8 hybrid vehicle. The dual polarization model was used, and a new open circuit voltage equation was proposed based on a simplification of the combined model, with the aim of reducing the number of parameters to be identified. The parameter identification was performed using NEDC data collected on a rolling road dynamometer; the results showed that the proposed model improved the accuracy of terminal voltage estimation, reducing the peak voltage error from 2.16% using the Nernst model to 1.28%. Furthermore, the robustness of these models in maintaining accuracy when new drive cycles were used was evaluated by comparing WLTC simulations with experimental measurements. The proposed model showed improved robustness, with a reduction in RMS error of more than 50% compared to the Nernst model. These findings are significant because they will improve the accuracy of model-based battery management systems used in electric vehicles, allowing for improved performance prediction without the requirement of recharacterization for different drive cycles or individual cell characterization. Full article
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14 pages, 3473 KiB  
Article
Sliding Mode Observer for State-of-Charge Estimation Using Hysteresis-Based Li-Ion Battery Model
by Mengying Chen, Fengling Han, Long Shi, Yong Feng, Chen Xue, Weijie Gao and Jinzheng Xu
Energies 2022, 15(7), 2658; https://0-doi-org.brum.beds.ac.uk/10.3390/en15072658 - 05 Apr 2022
Cited by 11 | Viewed by 1728
Abstract
Lithium-ion battery devices are essential for energy storage and supply in distributed energy generation systems. Robust battery management systems (BMSs) must guarantee that batteries work within a safe range and avoid the damage caused by overcharge and overdischarge. The state-of-charge (SoC) of Li-ion [...] Read more.
Lithium-ion battery devices are essential for energy storage and supply in distributed energy generation systems. Robust battery management systems (BMSs) must guarantee that batteries work within a safe range and avoid the damage caused by overcharge and overdischarge. The state-of-charge (SoC) of Li-ion batteries is difficult to observe after batteries are manufactured. The hysteresis phenomenon influences the existing battery modeling and SoC estimation accuracy. This research applies a terminal sliding mode observer (TSMO) algorithm based on a hysteresis resistor-capacitor (RC) equivalent circuit model to enable accurate SoC estimation. The proposed method is evaluated using two dynamic battery tests: the dynamic street test (DST) and the federal urban driving schedule (FUDS) test. The simulation results show that the proposed method achieved high estimation accuracy and fast response speed. Additionally, real-time battery information, including battery output voltage and SoC, was acquired and displayed by an automatic monitoring system. The designed system is valuable for all battery application cases. Full article
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Review

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41 pages, 6575 KiB  
Review
A Review on Mode Transition Strategies between Grid-Connected and Standalone Operation of Voltage Source Inverters-Based Microgrids
by Jihed Hmad, Azeddine Houari, Allal El Moubarek Bouzid, Abdelhakim Saim and Hafedh Trabelsi
Energies 2023, 16(13), 5062; https://0-doi-org.brum.beds.ac.uk/10.3390/en16135062 - 29 Jun 2023
Cited by 7 | Viewed by 2830
Abstract
Microgrids technologies are seen as a cost effective and reliable solution to handle numerous challenges, mainly related to climate change and power demand increase. This is mainly due to their potential for integrating available on-site renewable energy sources and their flexibility and scalability. [...] Read more.
Microgrids technologies are seen as a cost effective and reliable solution to handle numerous challenges, mainly related to climate change and power demand increase. This is mainly due to their potential for integrating available on-site renewable energy sources and their flexibility and scalability. The particularity of microgrids is related to their capacity to operate in synchronization with the main grid or in islanded mode to secure the power supply of nearby end-users after a grid failure thanks to storage solutions and an intelligent control system. The most critical operating case occurs when a sudden transition from grid-connected (GC) to stand-alone operation (SA) happens. During the transition, the system experiences abrupt changes that can result in a malfunction of the control system and a possible failure of the power system. The transition issue attracted considerable attention from researchers. Indeed, many research works are proposed to address this issue by proposing detection and transition techniques that ensure a smooth transition at the islanding time. Although there are several approaches to dealing with this issue, a categorization of the proposed methods in the literature and their differences is useful to assist engineers and researchers working on this topic. Thus, this study proposes a comprehensive review to summarize these approaches and point out their advantages and limitations. Full article
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