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Special Issue "Modeling and Analysis of Active Distribution Networks and Smart Grids"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A5: Smart Grids and Microgrids".

Deadline for manuscript submissions: 20 December 2022 | Viewed by 673

Special Issue Editors

Dr. Eleftherios O. Kontis
E-Mail Website
Guest Editor
School of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece
Interests: power system dynamics; modeling and analysis of active distribution networks; real-time analysis and control of power systems through field measurements; application of system identification techniques to power systems; control and optimal operation of distributed energy resources
Prof. Dr. Theofilos A. Papadopoulos
E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, Democritus University of Thrace, Xanthi, Greece
Interests: earth conduction effects in overhead lines and cable systems; modelling and analysis of electromagnetic transients; electromagnetic compatibility and transmission line modeling; power line communication; power systems load and active distribution network modeling; application of system identification techniques to power systems; integration of buildings into smart grids
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Special Issue Information

Dear Colleagues,

Renewable energy sources (RESs) will constitute the backbone of future energy systems and, due to their different characteristics and dependence on geography and climate, they will be scattered throughout the power system. In this context, a vast amount of distributed energy resources (DERs), such as large- and small-scale RES power plants, energy storage systems, electric vehicles, and smart loads will be integrated into low and medium voltage distribution networks, posing unprecedented challenges to both transmission and distribution system operators (TSOs-DSOs). These challenges include both local problems as well as system-wide ones related to the overall system stability. Local problems mainly include power quality, overvoltage and congestion issues caused due to the intermittent nature of RESs and mainly due to reverse power flow phenomena during high generation periods. System-wide issues include, among others, abnormal frequency deviations, subsynchronous oscillations, fast dynamic phenomena as well as complex interactions among transmission systems (TSs) and active distribution networks (ADNs). These are mainly caused because DERs are connected to the grid via inertialess converters.

The above-mentioned challenges therefore necessitate the development of new control methods and monitoring techniques to enhance the secure and reliable operation of future power systems. Towards this direction:

  • New control functionalities must be developed for converter-interfaced DERs, targeting to improve their dynamic behaviour. Additionally, new centralized and/or distributed architectures should be developed to tackle power quality issues in ADNs.
  • The participation of low and medium voltage level ADNs to the voltage control procedure and congestion management of TSs should also be explored. In this context, coordinated strategies, aiming to control the flexibility of several DERs in order to provide aggregated ancillary services (ASs) from ADNs to the TS are required. This way, full utilization of existing DERs will be ensured, while higher energy efficiency and resiliency will be achieved.
  • New simplified aggregated, yet accurate, equivalent models must be introduced to facilitate the quasi-static, dynamic, and electromagnetic transient (EMT) analysis of ADNs. Such models can be optimally tuned using real field measurements, acquired through smart meters, phasor measurement units or frequency disturbance recorders.
  • New monitoring architectures must be also proposed to assess close-to-real-time the dynamic performance and the stability margins of power systems. The performance of these monitoring architectures can be further improved by adopting machine learning and big-data analysis techniques.
  • Numerical methods targeting to simulate complex interactions between ADNs and TSs should also be developed. These methods can be used to facilitate the modelling, operation, and control of ADNs for the coordination of TSO-DSO interactions and for the provision of aggregated ASs from ADNs to the TS.

The main objective of this special issue is to seek quality publications that highlight recent advances in the areas of monitoring, modelling, analysis, control, optimization, and simulation of ADNs as well as quality publications targeting to quantify the impact of converter-interfaced DERs on TSO-DSO interactions, system stability margins, and dynamic performance of ADNs. The topics of interest include, but are not limited to:

  • Modeling and control functionalities of converter-interfaced DERs
  • DER control principles for local and system-wide needs
  • Flexibility in ADNs from battery storage systems, electric vehicles, and RESs
  • Coordinated provision of ASs from ADNs to the TS
  • Steady-state, quasi-static, dynamic and EMT analysis of ADNs
  • Equivalencing of ADNs
  • Centralized and distributed architectures for data-driven monitoring, analysis, and control of ADNs and smart grids
  • Applications of machine learning and big data techniques for smart grid analysis
  • Numerical techniques and models for the analysis of complex interactions between ADNs and TSs
  • Impacts of converter-interfaced DERs on power system stability and dynamics
  • Application of real-time simulation and power hardware-in-the-loop analysis of ADNs
Dr. Eleftherios O. Kontis
Prof. Theofilos A. Papadopoulos
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 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.


  • Active distribution networks
  • Smart grids
  • Distributed energy resources
  • Quasi-static analysis
  • Dynamic analysis
  • Control functionalities of converter-interfaced DERs
  • Ancillary services
  • Coordinated operation of ADNs
  • Optimization of ADNs
  • Dynamic equivalencing
  • Data-driven modeling
  • Artificial intelligence
  • TSO/DSO interactions
  • Stability analysis of converter-based power systems
  • Power hardware-in-the-loop testbeds

Published Papers

This special issue is now open for submission, see below for planned papers.

Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Renewable Energy Generation Forecasting in Aggregated Energy System Level
Authors: Ioannis Panapakidis; Georgios Gousis; Nikolaos Koltsaklis; Athanasios S. Dagoumas
Affiliation: Electrical and Computer Engineering Department, University of Thessaly, Volos 38821, Greece
Abstract: The integration of Renewable Energy Sources (RES) in the distribution grids is accompanied with various techno-economic issues. Various approaches have been proposed in order to decrease the effect on power quality of RES plants. One approach is the RES generation forecasting. The vast majority of the literature focus on specific plants. In the present paper, the RES generation forecasting in national system level is examined. An ensemble model that is built on the synergy between shallow and deep learning algorithms is proposed. Simulation results indicate the robustness of the proposed architecture.

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