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Advanced Control, Operation and Energy Management of Distribution Networks and Smart Grids

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

Deadline for manuscript submissions: 24 October 2024 | Viewed by 1774

Special Issue Editors

Dr. Jacob G. Fantidis

E-Mail Website
Guest Editor
Department of Electrical Engineering, International Hellenic University, Agios Loukas, 65404 Kavala, Greece
Interests: νon-destructive testing; radiography; thermography; simulation of energy systems; detection of illicit materials based on nuclear radiation; Monte Carlo modeling
Dr. Antonis Tsikalakis

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, Hellenic Mediterranean University, Heraklion Estavromenos, 71410 Heraklion, Greece
Interests: power systems; microgrids; renewable energy

Special Issue Information

Dear Colleagues,

Today, networks play a crucial role in energy planning. Distribution networks, in particular, comprise the core of these energy systems. Modern distribution networks and related technology must be advanced towards a new model.  This schema should not only ensure the supply of reliable and high-quality electricity, but must also be fine-tuned to meet new challenges, offer smart options for more economical and efficient use and/or the production of electrical energy, and ensure the simultaneously greater and more effective control of the systems through automation and the use of new technologies.

Progress in these areas will lead us to cleaner energy and sustainable growth. This is why next-generation networks, known as smart grids, are today at the heart of planning strategies of all forward-looking electrical energy distribution companies.

As Guest Editors, my co-editors and I are inviting submissions to a Special Issue of Energies on the subject area of “Advanced Control, Operation and Energy Management of Distribution Networks and Smart Grids”. This Issue aims to examine, present and disseminate the latest developments and research efforts on this subject. All types of research approaches are equally acceptable: experimental, theoretical, simulation, optimization and their mixtures.

Topics of interest for publication include, but are not limited to:

  • Integration of renewable energy sources;
  • Energy storage systems for grids;
  • Energy management strategies;
  • Energy supply reliability;
  • Load forecasting and scheduling;
  • Island microgrids;
  • Smart grids and microgrids;
  • Optimization techniques for energy storage systems in distribution grids;
  • Anti-island control strategies for distribution grids;
  • Cascading failure of components in smart grids;
  • Fault location in distribution networks;
  • Fault management in grids;
  • Innovative fault management and location techniques for smart grids;
  • Power system planning and energy management;
  • Novel optimization techniques for power system operations;
  • Application of cutting-edge artificial intelligence techniques;
  • Planning and development of the energy transition;
  • Smart energy production and distribution;
  • Fault monitoring technologies;
  • Reliability of power distribution networks.

Dr. Jacob G. Fantidis
Dr. Antonis Tsikalakis
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

  • smart grid
  • microgrid
  • distribution system
  • energy supply
  • energy management
  • fault location
  • reliability
  • integration of RES

Published Papers (2 papers)

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Research

35 pages, 1956 KiB  
Article
Predictive Energy Management of a Building-Integrated Microgrid: A Case Study
by Romain Mannini, Tejaswinee Darure, Julien Eynard and Stéphane Grieu
Energies 2024, 17(6), 1355; https://doi.org/10.3390/en17061355 - 12 Mar 2024
Viewed by 714
Abstract
The efficient integration of distributed energy resources (DERs) in buildings is a challenge that can be addressed through the deployment of multienergy microgrids (MGs). In this context, the Interreg SUDOE project IMPROVEMENT was launched at the end of the year 2019 with the [...] Read more.
The efficient integration of distributed energy resources (DERs) in buildings is a challenge that can be addressed through the deployment of multienergy microgrids (MGs). In this context, the Interreg SUDOE project IMPROVEMENT was launched at the end of the year 2019 with the aim of developing efficient solutions allowing public buildings with critical loads to be turned into net-zero-energy buildings (nZEBs). The work presented in this paper deals with the development of a predictive energy management system (PEMS) for the management of thermal resources and users’ thermal comfort in public buildings. Optimization-based/optimization-free model predictive control (MPC) algorithms are presented and validated in simulations using data collected in a public building equipped with a multienergy MG. Models of the thermal MG components were developed. The strategy currently used in the building relies on proportional–integral–derivative (PID) and rule-based (RB) controllers. The interconnection between the thermal part and the electrical part of the building-integrated MG is managed by taking advantage of the solar photovoltaic (PV) power generation surplus. The optimization-based MPC EMS has the best performance but is rather computationally expensive. The optimization-free MPC EMS is slightly less efficient but has a significantly reduced computational cost, making it the best solution for in situ implementation. Full article
(This article belongs to the Special Issue Advanced Control, Operation and Energy Management of Distribution Networks and Smart Grids)
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21 pages, 926 KiB  
Article
Forecast-Based Energy Management for Optimal Energy Dispatch in a Microgrid
by Francisco Durán, Wilson Pavón and Luis Ismael Minchala
Energies 2024, 17(2), 486; https://doi.org/10.3390/en17020486 - 19 Jan 2024
Viewed by 844
Abstract
This article describes the development of an optimal and predictive energy management system (EMS) for a microgrid with a high photovoltaic (PV) power contribution. The EMS utilizes a predictive long-short-term memory (LSTM) neural network trained on real PV power and consumption data. Optimal [...] Read more.
This article describes the development of an optimal and predictive energy management system (EMS) for a microgrid with a high photovoltaic (PV) power contribution. The EMS utilizes a predictive long-short-term memory (LSTM) neural network trained on real PV power and consumption data. Optimal EMS decisions focus on managing the state of charge (SoC) of the battery energy storage system (BESS) within defined limits and determining the optimal power contributions from the microgrid components. The simulation utilizes MATLAB R2023a to solve a mixed-integer optimization problem and HOMER Pro 3.14 to simulate the microgrid. The EMS solves this optimization problem for the current sampling time (t) and the immediate sampling time (t+1), which implies a prediction of one hour in advance. An upper-layer decision algorithm determines the operating state of the BESS, that is, to charge or discharge the batteries. An economic and technical impact analysis of our approach compared to two EMSs based on a pure economic optimization approach and a peak-shaving algorithm reveals superior BESS integration, achieving 59% in demand satisfaction without compromising the life of the equipment, avoiding inexpedient power delivery, and preventing significant increases in operating costs. Full article
(This article belongs to the Special Issue Advanced Control, Operation and Energy Management of Distribution Networks and Smart Grids)
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