Special Issue "Real-Time Simulation Advancing Power and Energy Research and Industry Practices"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "Sustainable Energy".

Deadline for manuscript submissions: 20 September 2021.

Special Issue Editors

Dr. Panos Kotsampopoulos
E-Mail Website
Guest Editor
School of Electrical and Computer Engineering, National Technical University of Athens, 15780 Zografou, Greece
Interests: real-time simulation; control of distributed generation; microgrids; smart grids; power-system dynamics; education
Special Issues and Collections in MDPI journals
Dr. Md Omar Faruque
E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering and the Center for Advanced Power Systems (CAPS), FAMU-FSU College of Engineering, Florida State University, Tallahassee, FL 32310, USA
Interests: real-time simulation; ship electric systems; application of real-time simulation in the area of bulk power system monitoring and control; smart grid and renewable energy integration
Special Issues and Collections in MDPI journals
DI. Georg Lauss
E-Mail
Guest Editor
Electric Energy Systems (EES), AIT Austrian Institute of Technology, Giefinggasse 4, 1210 Vienna, Austria
Interests: controller/power hardware-in-the-loop systems; power electronics; system and control theory; mathematical methods for optimized control systems; real-time simulation for electromagnetic power systems

Special Issue Information

Dear Colleagues,

The wide integration of distributed generation, storage and electric vehicles, adoption of ICT solutions, interconnection of different energy carriers and consumer engagement pose new challenges and create new opportunities. In the transition to a sustainable energy system, advanced testing methods are needed to efficiently validate power equipment and controls in an increasingly complex environment. Real-time hardware-in-the-loop (HIL) simulations have proven to be valuable and effective methods for validating and de-risking power system equipment in highly realistic, flexible and repeatable conditions by combining the advantages of digital simulations and hardware testing of actual equipment.

This Special Issue welcomes innovative papers dealing with recent advances in real-time HIL simulations in several areas. Of special interest are papers reporting industrial best practices of, for example, power system equipment manufacturers (HVDC/FACTS, inverters, relays, controllers, etc.), utilities (TSOs, DSOs, etc.), manufacturers of real-time simulators, amplifiers, etc.

The following topics are considered most relevant:

  • advances in HIL testing of power electronic converters;
  • advances in HIL testing of power system protection;
  • advances in HIL testing of smart grid/microgrid controllers, energy management systems, wide area protection and control;
  • apparatus modeling for real-time simulation and model validation;
  • interfacing methods of PHIL and CHIL simulations—improvement of stability and accuracy;
  • HIL cosimulation, cyber-security and cyber-physical energy systems;
  • geographically distributed HIL and real-time simulator coupling/challenges;
  • mechanical, multiphysics and multidomain HIL simulations;
  • HIL in standardized testing and standardization of HILs;
  • industrial experiences in all the above areas.
Dr. Panos Kotsampopoulos
Dr. Md Omar Faruque
DI. Georg Lauss
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 2000 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

  • real-time simulation
  • controller hardware-in-the-loop simulation (CHIL)
  • power hardware-in-the-loop simulation (PHIL)
  • power and energy systems
  • industry applications
  • TSOs and DSOs
  • manufacturers
  • testing and validation of HIL interfaces for HIL setups
  • real-time EMTP simulation and application
  • optimized control for real-time-based systems

Published Papers (1 paper)

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Research

Article
Experimental Verification of Self-Adapting Data-Driven Controllers in Active Distribution Grids
Energies 2021, 14(10), 2837; https://doi.org/10.3390/en14102837 - 14 May 2021
Viewed by 476
Abstract
Lately, data-driven algorithms have been proposed to design local controls for Distributed Generators (DGs) that can emulate the optimal behaviour without any need for communication or centralised control. The design is based on historical data, advanced off-line optimization techniques and machine learning methods, [...] Read more.
Lately, data-driven algorithms have been proposed to design local controls for Distributed Generators (DGs) that can emulate the optimal behaviour without any need for communication or centralised control. The design is based on historical data, advanced off-line optimization techniques and machine learning methods, and has shown great potential when the operating conditions are similar to the training data. However, safety issues arise when the real-time conditions start to drift away from the training set, leading to the need for online self-adapting algorithms and experimental verification of data-driven controllers. In this paper, we propose an online self-adapting algorithm that adjusts the DG controls to tackle local power quality issues. Furthermore, we provide experimental verification of the data-driven controllers through power Hardware-in-the-Loop experiments using an industrial inverter. The results presented for a low-voltage distribution network show that data-driven schemes can emulate the optimal behaviour and the online modification scheme can mitigate local power quality issues. Full article
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