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Innovative Advances in Monitoring, Control, and Management of Microgrids

A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: closed (30 November 2021) | Viewed by 13667

Special Issue Editors

Department of Electrical, Electronical and Automatic Engineering, School of Industrial Engineering, University of Extremadura, Avda de Elvas s/n, 06006 Badajoz, Spain
Interests: smart grids and microgrids; renewable energy; industrial control and automation; monitoring and supervision; Industry 4.0
Special Issues, Collections and Topics in MDPI journals
Department of Electrical, Electronical and Automatic Engineering, School of Industrial Engineering, University of Extremadura, Avda de Elvas s/n, 06006 Badajoz, Spain
Interests: smart grids and microgrids; renewable energy; intelligent control; industrial control and automation; monitoring and supervision; Industry 4.0
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Microgrids are a new energy paradigm derived from the digital transformation applied to small-scale energy facilities. In this novel scenario, locally-available energy sources, storage equipment, and load supply are combined in a coordinated smart manner. Microgrids can include renewable/nonconventional energy sources as well as energy carriers such as hydrogen and can operate connected to the main power grid or in stand-alone mode. Microgrids, mostly those based on renewable sources, help to reduce environmental pollutants, greenhouse emissions, and dependence on fossil fuels, contributing to sustainable development.

Large-scale deployment of microgrids requires facing a number of scientific and technical challenges, from design aspects to precise digital simulation of the facility. Among these challenges, severe research efforts are devoted to develop advanced monitoring, control, and management systems for microgrids. These systems are compulsory to deal with the uncertainties of renewable energy sources (photovoltaic, wind, etc.) and changes of the load demand in order to provide a reliable, energy-efficient, and environmentally-friendly operation. Such systems use parameters and measurements from the microgrid, relying on sensing, automation, and computation equipment seamlessly integrated over communication networks to share real-time data.

This Special Issue is primarily focused on the advancements and innovations related to monitoring, control, and management of microgrids of all sizes, types, and architectures. For instance, novel approaches involving modern control strategies, open Internet-of-Things platforms or building digital replicas (also called digital twins) constitute current trends.

We would like to invite the submission of high-quality manuscripts from researchers, engineers, and industry professionals for publication in this Special Issue. The manuscripts should be unpublished and report significant research progress. The key criterion for paper acceptance will be novelty. Manuscripts reporting experimental proofs, results, and lessons learned are strongly encouraged. Review papers on the state-of-the-art of different topics related to microgrids are also welcome. The main topics of interest include but are not limited to the following:

  • Control, management, and monitoring of microgrids;
  • Integration of renewable energy sources and hydrogen;
  • Sustainable microgrids and nanogrids;
  • Design, deployment, and operation of microgrids;
  • Distributed generation, energy conversion, and storage;
  • Hardware-in-the-loop and power electronics for microgrids;
  • Advanced modeling and digital replication of microgrids;
  • Experimental implementation of microgrids;
  • Innovative technology for microgrids;
  • Reviews on the state-of-the-art in the microgrids scope.

Dr. Isaías González Pérez
Prof. Dr. Antonio José Calderón Godoy
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. Sustainability 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 2400 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 and energy management
  • Microgrids planning, operation and assessment
  • DC, AC, and DC-AC hybrid microgrids
  • Monitoring and sensing
  • Renewable energy sources
  • Hydrogen integration
  • Load management
  • Energy conversion and storage
  • Hardware-In-the-Loop
  • Power electronics
  • Open Internet of Things platforms
  • Modelling and Digital replicas

Published Papers (4 papers)

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Research

23 pages, 7037 KiB  
Article
Monitoring System for Tracking a PV Generator in an Experimental Smart Microgrid: An Open-Source Solution
by José María Portalo, Isaías González and Antonio José Calderón
Sustainability 2021, 13(15), 8182; https://doi.org/10.3390/su13158182 - 22 Jul 2021
Cited by 29 | Viewed by 3371
Abstract
Smart grids and smart microgrids (SMGs) require proper monitoring for their operation. To this end, measuring, data acquisition, and storage, as well as remote online visualization of real-time information, must be performed using suitable equipment. An experimental SMG is being deployed that combines [...] Read more.
Smart grids and smart microgrids (SMGs) require proper monitoring for their operation. To this end, measuring, data acquisition, and storage, as well as remote online visualization of real-time information, must be performed using suitable equipment. An experimental SMG is being deployed that combines photovoltaics and the energy carrier hydrogen through the interconnection of photovoltaic panels, electrolyser, fuel cell, and load around a voltage bus powered by a lithium battery. This paper presents a monitoring system based on open-source hardware and software for tracking the temperature of the photovoltaic generator in such an SMG. In fact, the increases in temperature in PV modules lead to a decrease in their efficiency, so this parameter needs to be measured in order to monitor and evaluate the operation. Specifically, the developed monitoring system consists of a network of digital temperature sensors connected to an Arduino microcontroller, which feeds the acquired data to a Raspberry Pi microcomputer. The latter is accessed by a cloud-enabled user/operator interface implemented in Grafana. The monitoring system is expounded and experimental results are reported to validate the proposal. Full article
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24 pages, 6752 KiB  
Article
Innovative Multi-Layered Architecture for Heterogeneous Automation and Monitoring Systems: Application Case of a Photovoltaic Smart Microgrid
by Isaías González, Antonio José Calderón and José María Portalo
Sustainability 2021, 13(4), 2234; https://doi.org/10.3390/su13042234 - 19 Feb 2021
Cited by 67 | Viewed by 4058
Abstract
Intelligent energy facilities, e.g., smart grids and microgrids are the evolution of traditional energy grids through digital transformation. These modern paradigms are expected to foster the utilization of renewable energies, sustainable development, and resilience of the power grid. A barrier found when deploying [...] Read more.
Intelligent energy facilities, e.g., smart grids and microgrids are the evolution of traditional energy grids through digital transformation. These modern paradigms are expected to foster the utilization of renewable energies, sustainable development, and resilience of the power grid. A barrier found when deploying experimental smart grids and microgrids consists of handling the heterogeneity of the required hardware and software components as well as the available commercial equipment. Despite the fact that there is various architecture proposed in previous literature, it commonly lacks experimental validation, specification of involved equipment concerning industrial/proprietary or open-source nature, and concretization of communication protocols. To overcome such drawbacks, this paper proposes an innovative multi-layered architecture to deploy heterogeneous automation and monitoring systems for microgrids. The architecture is structured into six functional layers to organize the hardware and software equipment in an integrated manner. The open protocol Modbus TCP is chosen to harmonize communications, enabling the interconnection of equipment from industrial and energy scopes, indeed of open-source nature. An experimental photovoltaic-based smart microgrid is reported as the application case to demonstrate the suitability and validity of the proposal. Full article
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21 pages, 4511 KiB  
Article
Optimizing Battery Energy Storage System Data in the Presence of Wind Power Plants: A Comparative Study on Evolutionary Algorithms
by Ramin Sakipour and Hamdi Abdi
Sustainability 2020, 12(24), 10257; https://doi.org/10.3390/su122410257 - 08 Dec 2020
Cited by 8 | Viewed by 3378
Abstract
This study deals with the optimization of battery energy storage system (BESS) data in terms of significant characteristics of life and efficiency, and their positive impacts on power system efficiency in the presence of wind power plants in a microgrid. To this end, [...] Read more.
This study deals with the optimization of battery energy storage system (BESS) data in terms of significant characteristics of life and efficiency, and their positive impacts on power system efficiency in the presence of wind power plants in a microgrid. To this end, a permanent magnet synchronous generator (PMSG) is used to convert the wind energy by connecting a three-phase dynamic load to the grid. The main novelty of the proposed method is designing a smart backup battery branch to improve the efficiency of the wind farm by maintaining the operating constraints even during the occurrence of harsh faults in the generation section. Additionally, for the first time, the characteristics of the BESS are optimized using nine evolutionary algorithms, including the genetic algorithm (GA), teaching–learning-based optimization (TLBO), particle swarm optimization (PSO), gravitational search algorithm (GSA), artificial bee colony (ABC), differential evolution (DE), grey wolf optimizer (GWO), moth–flame optimization algorithm (MFO), and sine cosine algorithm (SCA), and the results are compared with each other. The simulation results of a case study confirm the robustness of the proposed control strategy for the BESS. Full article
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28 pages, 4127 KiB  
Article
Extended Model Predictive Controller to Develop Energy Management Systems in Renewable Source-Based Smart Microgrids with Hydrogen as Backup. Theoretical Foundation and Case Study
by Francisco J. Vivas Fernández, Francisca Segura Manzano, José Manuel Andújar Márquez and Antonio J. Calderón Godoy
Sustainability 2020, 12(21), 8969; https://doi.org/10.3390/su12218969 - 28 Oct 2020
Cited by 15 | Viewed by 2173
Abstract
This article presents a methodological foundation to design and experimentally test a Model Predictive Controller (MPC) to be applied in renewable source-based microgrids with hydrogen as backup. The Model Predictive Controller has been developed with the aim to guarantee the best energy distribution [...] Read more.
This article presents a methodological foundation to design and experimentally test a Model Predictive Controller (MPC) to be applied in renewable source-based microgrids with hydrogen as backup. The Model Predictive Controller has been developed with the aim to guarantee the best energy distribution while the microgrid operation is optimized considering both technical and economic parameters. As a differentiating element, this proposal provides a solution to the problem of energy management in real systems, addressing technological challenges such as charge management in topologies with direct battery connection, or loss of performance associated with equipment degradation or the required dynamics in the operation of hydrogen systems. That is, the proposed Model Predictive Controller achieves the optimization of microgrid operation both in the short and in the long-term basis. For this purpose, a generalized multi-objective function has been defined that considers the energy demand, operating costs, system performance as well as the suffered and accumulated degradation by microgrid elements throughout their lifespan. The generality in the definition of the model and cost function, allows multi-objective optimization problems to be raised depending on the application, topology or design criteria to be considered. For this purpose, a heuristic methodology based on artificial intelligence techniques is presented for the tuning of the controller parameters. The Model Predictive Controller has been validated by simulation and experimental tests in a case study, where the performance of the microgrid under energy excess and deficit situations has been tested, considering the constrains defined by the degradation of the systems that make up the microgrid. The designed controller always made it possible to guarantee both the power balance and the optimal energy distribution between systems according to the predefined priority and accumulated degradation, while guaranteeing the maximum operating voltage of the system with a margin of error less than 1%. The simulation and experimental results for the case study showed the validity of the controller and the design methodology used. Full article
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