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Recent Contributions and Future Prospects of Converter Control in Hybrid AC/DC Microgrids

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: closed (15 December 2021) | Viewed by 3679

Special Issue Editors

Dr. Oleksandr Husev

E-Mail Website
Guest Editor
Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia
Interests: power electronics; renewable energy technologies; electrical power engineering; distributed generation; power quality; power systems analysis; power converters; inverters; energy conversion
Special Issues, Collections and Topics in MDPI journals
Dr. Roya AhmadiAhangar

E-Mail Website
Guest Editor
Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia
Interests: application of machine learning and data science in power systems; power system flexibility and demand response; integration of variable energy resources; energy storage; decentralized solutions for active distribution networks and microgrids; smart grid

Special Issue Information

Dear Colleagues,

Microgrids have gained more attention in the past decade since they provide the facility for the exploitation of Distributed Generator to satisfy the growing rate of electricity demand. On the other hand, developments in the power semiconductor technology have opened a new door of power-electronics applications in the power system. In particular, it creates a push to development of the facilities of DC microgrid.

This special issue is devoted to the converter control in hybrid AC/DC microgrids. The state of the art of power electronics topologies as bidirectional interface converters in the AC and DC parts can be adressed. Different control structures of hybrid microgrids, their control strategies, their positive and negative aspects and applications have to be covered. The prospects, main challenges, research gaps, and the trend of the hybrid microgrid structure and control will be in the focus of this special issue.

Dr. Oleksandr Husev
Dr. Roya AhmadiAhangar
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

  • control systems
  • Bidirectional interface converters
  • distributed generation
  • hybrid microgrid
  • islanding detection
  • power quality

Published Papers (1 paper)

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Research

22 pages, 15663 KiB  
Article
Exploratory Data Analysis Based Short-Term Electrical Load Forecasting: A Comprehensive Analysis
by Umar Javed, Khalid Ijaz, Muhammad Jawad, Ejaz A. Ansari, Noman Shabbir, Lauri Kütt and Oleksandr Husev
Energies 2021, 14(17), 5510; https://0-doi-org.brum.beds.ac.uk/10.3390/en14175510 - 03 Sep 2021
Cited by 24 | Viewed by 3118
Abstract
Power system planning in numerous electric utilities merely relies on the conventional statistical methodologies, such as ARIMA for short-term electrical load forecasting, which is incapable of determining the non-linearities induced by the non-linear seasonal data, which affect the electrical load. This research work [...] Read more.
Power system planning in numerous electric utilities merely relies on the conventional statistical methodologies, such as ARIMA for short-term electrical load forecasting, which is incapable of determining the non-linearities induced by the non-linear seasonal data, which affect the electrical load. This research work presents a comprehensive overview of modern linear and non-linear parametric modeling techniques for short-term electrical load forecasting to ensure stable and reliable power system operations by mitigating non-linearities in electrical load data. Based on the findings of exploratory data analysis, the temporal and climatic factors are identified as the potential input features in these modeling techniques. The real-time electrical load and meteorological data of the city of Lahore in Pakistan are considered to analyze the reliability of different state-of-the-art linear and non-linear parametric methodologies. Based on performance indices, such as Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE), the qualitative and quantitative comparisons have been conferred among these scientific rationales. The experimental results reveal that the ANN–LM with a single hidden layer performs relatively better in terms of performance indices compared to OE, ARX, ARMAX, SVM, ANN–PSO, KNN, ANN–LM with two hidden layers and bootstrap aggregation models. Full article
(This article belongs to the Special Issue Recent Contributions and Future Prospects of Converter Control in Hybrid AC/DC Microgrids)
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