Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.2
3.0
Journals
Energies
Special Issues
Advanced Control, Operation and Energy Management of Distribution Networks and...
energies-logo
Submit to Energies Review for Energies Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

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: closed (24 October 2024) | Viewed by 6411

Special Issue Editors

Dr. Jacob G. Fantidis

E-Mail Website
Guest Editor
Department of Physics, 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
Special Issues, Collections and Topics in MDPI journals
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 Issues, Collections and Topics in MDPI journals

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

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Related Special Issue

Published Papers (5 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

19 pages, 2092 KiB  
Article
Consensus-Based Model Predictive Control for Active Power and Voltage Regulation in Active Distribution Networks
by Gianluca Antonelli, Giuseppe Fusco and Mario Russo
Energies 2024, 17(17), 4490; https://doi.org/10.3390/en17174490 - 6 Sep 2024
Viewed by 457
Abstract
In this paper, a consensus-based model predictive control (Cb-MPC) scheme is proposed to control the active power and voltage at all nodes in grid-connected active distribution networks (ADNs) with multiple distributed energy resources (DERs). The proposed design methodology is based on a multiple-input [...] Read more.
In this paper, a consensus-based model predictive control (Cb-MPC) scheme is proposed to control the active power and voltage at all nodes in grid-connected active distribution networks (ADNs) with multiple distributed energy resources (DERs). The proposed design methodology is based on a multiple-input multiple-output (MIMO) model of an ADN which accounts for both the internal and external interactions among the control loops of the DERs. To achieve the control objective, each DER unit is equipped with a controller–observer system. In particular, the observer implements the consensus algorithm to estimate the collective system state by exchanging data only with its neighbors. The scope of the controller is to solve the MPC optimal problem based on its collective state estimate, and, due to the presence of an integral term in the control action, it is robust against any unknown scenarios of the ADN, which are represented by uncertainty in the model parameters. The results of numerical simulations validate the effectiveness of the proposed method in the presence of unknown changes in the operating conditions of the ADN and of communication using a sample and hold function. Full article
(This article belongs to the Special Issue Advanced Control, Operation and Energy Management of Distribution Networks and Smart Grids)
►▼ Show Figures

Figure 1

29 pages, 5688 KiB  
Article
Enhancing Power Supply Flexibility in Renewable Energy Systems with Optimized Energy Dispatch in Coupled CHP, Heat Pump, and Thermal Storage
by Dongwen Chen and Zheng Chu
Energies 2024, 17(12), 2861; https://doi.org/10.3390/en17122861 - 11 Jun 2024
Viewed by 641
Abstract
The use of renewable energy by converting it into heat is an important form of storing energy in a usable form and improving the energy supply flexibility; therefore, the electricity–heating system (EHS) can cope with load fluctuations. However, relevant research is lacking on [...] Read more.
The use of renewable energy by converting it into heat is an important form of storing energy in a usable form and improving the energy supply flexibility; therefore, the electricity–heating system (EHS) can cope with load fluctuations. However, relevant research is lacking on improving the energy supply limitations by the optimal dispatch of energy flow at the typical EHS, such as the coupled CHP–heat pump–thermal storage system (CCHTS). Based on the study of the energy supply characteristics of the CCHTS for extending the energy supply limitation, this study develops an optimal dispatch method using a heat pump (HP) and the thermal storage (TS) of heating networks to improve the flexibility of the CCHTS and the accommodation capacity of renewable energy. The maximum and minimum energy supply limitation model of the CCHTS and the output power characteristic model are established. Based on the piecewise power supply constraint, the energy flow of the EHS is optimized by using the quadratic programming algorithm. The CCHTS can significantly improve the energy supply flexibility; both coupled combined heat and power (CHP) + HP and coupled CHP + TS can improve the power supply flexibility, but the enhanced effect of CHP + HP is better than that of CHP + TS. An increase of 7.6% in wind power consumption is achieved. The consumption of renewable energy increases by 17.9% in the energy flow optimization results. Full article
(This article belongs to the Special Issue Advanced Control, Operation and Energy Management of Distribution Networks and Smart Grids)
►▼ Show Figures

Figure 1

24 pages, 17575 KiB  
Article
Real-Time Load Forecasting and Adaptive Control in Smart Grids Using a Hybrid Neuro-Fuzzy Approach
by Fangzong Wang and Zuhaib Nishtar
Energies 2024, 17(11), 2539; https://doi.org/10.3390/en17112539 - 24 May 2024
Cited by 1 | Viewed by 1146
Abstract
The transition to smart grids is revolutionizing the management and distribution of electrical energy. Nowadays, power systems must precisely estimate real-time loads and use adaptive regulation to operate in the era of sustainable energy. To address these issues, this paper presents a new [...] Read more.
The transition to smart grids is revolutionizing the management and distribution of electrical energy. Nowadays, power systems must precisely estimate real-time loads and use adaptive regulation to operate in the era of sustainable energy. To address these issues, this paper presents a new approach—a hybrid neuro-fuzzy system—that combines neural networks with fuzzy logic. We use neural networks’ adaptability to describe complex load patterns and fuzzy logic’s interpretability to fine-tune control techniques in our approach. Our improved load forecasting system can now respond to changes in real-time due to the combination of these two powerful methodologies. Developing, training, and implementing the forecasting and control system are detailed in this article, which also explores the theoretical underpinnings of our hybrid neuro-fuzzy approach. We demonstrate how the technology improves grid stability and the accuracy of load forecasts by using adaptive control methods. Furthermore, comprehensive simulations confirm the proposed technology, showcasing its smooth integration with smart grid infrastructure. Better energy management is just the beginning of what our method can accomplish; it also paves the way for a more sustainable energy future that is easier on the planet and its inhabitants. In conclusion, this study’s innovative approach to adaptive control and real-time load forecasting advances smart grid technology, which, in turn, improves sustainability and energy efficiency. Full article
(This article belongs to the Special Issue Advanced Control, Operation and Energy Management of Distribution Networks and Smart Grids)
►▼ Show Figures

Figure 1

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
Cited by 3 | Viewed by 2263
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)
►▼ Show Figures

Figure 1

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
Cited by 2 | Viewed by 1411
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)
►▼ Show Figures

Graphical abstract

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-5
Back to TopTop